Son Model ICT [TradingFinder] HTF DOL H1 + Sweep M15 + FVG M1🔵 Introduction
The ICT Son Model setup is a precise trading strategy based on market structure and liquidity, implemented across multiple timeframes. This setup first identifies a liquidity level in the 1-hour (1H) timeframe and then confirms a Market Structure Shift (MSS) in the 5-minute (5M) timeframe to validate the trend. After confirmation, the price forms a new swing in the 5-minute timeframe, absorbing liquidity.
Once this level is broken, traders typically drop to the 30-second (30s) timeframe and enter trades based on a Fair Value Gap (FVG). However, since access to the 30-second timeframe is not available to most traders, we take the entry signal directly from the 5-minute timeframe, using the same liquidity zones and confirmed breakouts to execute trades. This approach simplifies execution and makes the strategy accessible to all traders.
This model operates in two setups :
Bullish ICT Son Model and Bearish ICT Son Model. In the bullish setup, liquidity is first accumulated at the lows of the 1-hour timeframe, and after confirming a market structure shift, a long position is initiated. Conversely, in the bearish setup, liquidity is first drawn from higher levels, and upon confirmation of a bearish trend, a short position is executed.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The ICT Son Model setup is designed around liquidity analysis and market structure shifts and can be applied in both bullish and bearish market conditions. The strategy first identifies a liquidity level in the 1-hour (1H) timeframe and then confirms a Market Structure Shift (MSS) in the 5-minute (5M) timeframe.
After this shift, the price forms a new swing, absorbing liquidity. When this level is broken in the 5-minute timeframe, the trader enters based on a Fair Value Gap (FVG). While the ideal entry is in the 30-second (30s) timeframe, due to accessibility constraints, we take entry signals directly from the 5-minute timeframe.
🟣 Bullish Setup
In the Bullish ICT Son Model, the 1-hour timeframe first identifies liquidity at the market lows, where price sweeps this level to absorb liquidity. Then, in the 5-minute timeframe, an MSS confirms the bullish shift.
After confirmation, the price forms a new swing, absorbing liquidity at a higher level. The price then retraces into a Fair Value Gap (FVG) created in the 5-minute timeframe, where the trader enters a long position, placing the stop-loss below the FVG.
🟣 Bearish Setup
In the Bearish ICT Son Model, liquidity at higher market levels is identified in the 1-hour timeframe, where price sweeps these levels to absorb liquidity. Then, in the 5-minute timeframe, an MSS confirms the bearish trend.
After confirmation, the price forms a new swing, absorbing liquidity at a lower level. The price then retraces into a Fair Value Gap (FVG) created in the 5-minute timeframe, where the trader enters a short position, placing the stop-loss above the FVG.
🔵 Settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
FVG Length : Default is 120 Bar.
MSS Length : Default is 80 Bar.
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filters :
Very Aggressive Filter: Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter: Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter: Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filter: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
🔵 Conclusion
The ICT Son Model setup is a structured and precise method for trade execution based on liquidity analysis and market structure shifts. This strategy first identifies a liquidity level in the 1-hour timeframe and then confirms a trend shift using the 5-minute timeframe.
Trade entries are executed based on Fair Value Gaps (FVGs), which highlight optimal entry points. By applying this model, traders can leverage existing market liquidity to enter high-probability trades. The bullish setup activates when liquidity is swept from market lows and a market structure shift confirms an upward trend, whereas the bearish setup is used when liquidity is drawn from market highs, confirming a downtrend.
This approach enables traders to identify high-probability trade setups with greater precision compared to many other strategies. Additionally, since access to the 30-second timeframe is limited, the strategy remains fully functional in the 5-minute timeframe, making it more practical and accessible for a wider range of traders.
Wyszukaj w skryptach "liquidity"
ICT Concepts [LuxAlgo]The ICT Concepts indicator regroups core concepts highlighted by trader and educator "The Inner Circle Trader" (ICT) into an all-in-one toolkit. Features include Market Structure (MSS & BOS), Order Blocks, Imbalances, Buyside/Sellside Liquidity, Displacements, ICT Killzones, and New Week/Day Opening Gaps.
🔶 SETTINGS
🔹 Mode
When Present is selected, only data of the latest 500 bars are used/visualized, except for NWOG/NDOG
🔹 Market Structure
Enable/disable Market Structure.
Length: will set the lookback period/sensitivity.
In Present Mode only the latest Market Structure trend will be shown, while in Historical Mode, previous trends will be shown as well:
You can toggle MSS/BOS separately and change the colors:
🔹 Displacement
Enable/disable Displacement.
🔹 Volume Imbalance
Enable/disable Volume Imbalance.
# Visible VI's: sets the amount of visible Volume Imbalances (max 100), color setting is placed at the side.
🔹 Order Blocks
Enable/disable Order Blocks.
Swing Lookback: Lookback period used for the detection of the swing points used to create order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Color settings.
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
Change in Order Blocks style:
🔹 Liquidity
Enable/disable Liquidity.
Margin: sets the sensitivity, 2 points are fairly equal when:
'point 1' < 'point 2' + (10 bar Average True Range / (10 / margin)) and
'point 1' > 'point 2' - (10 bar Average True Range / (10 / margin))
# Visible Liq. boxes: sets the amount of visible Liquidity boxes (max 50), this amount is for Sellside and Buyside boxes separately.
Colour settings.
Change in Liquidity style:
🔹 Fair Value Gaps
Enable/disable FVG's.
Balance Price Range: this is the overlap of latest bullish and bearish Fair Value Gaps.
By disabling Balance Price Range only FVGs will be shown.
Options: Choose whether you wish to see FVG or Implied Fair Value Gaps (this will impact Balance Price Range as well)
# Visible FVG's: sets the amount of visible FVG's (max 20, in the same direction).
Color settings.
Change in FVG style:
🔹 NWOG/NDOG
Enable/disable NWOG; color settings; amount of NWOG shown (max 50).
Enable/disable NDOG ; color settings; amount of NDOG shown (max 50).
🔹 Fibonacci
This tool connects the 2 most recent bullish/bearish (if applicable) features of your choice, provided they are enabled.
3 examples (FVG, BPR, OB):
Extend lines -> Enabled (example OB):
🔹 Killzones
Enable/disable all or the ones you need.
Time settings are coded in the corresponding time zones.
🔶 USAGE
By default, the indicator displays each feature relevant to the most recent price variations in order to avoid clutter on the chart & to provide a very similar experience to how a user would contruct ICT Concepts by hand.
Users can use the historical mode in the settings to see historical market structure/imbalances. The ICT Concepts indicator has various use cases, below we outline many examples of how a trader could find usage of the features together.
In the above image we can see price took out Sellside liquidity, filled two bearish FVGs, a market structure shift, which then led to a clean retest of a bullish FVG as a clean setup to target the order block above.
Price then fills the OB which creates a breaker level as seen in yellow.
Broken OBs can be useful for a trader using the ICT Concepts indicator as it marks a level where orders have now been filled, indicating a solidified level that has proved itself as an area of liquidity. In the image above we can see a trade setup using a broken bearish OB as a potential entry level.
We can see the New Week Opening Gap (NWOG) above was an optimal level to target considering price may tend to fill / react off of these levels according to ICT.
In the next image above, we have another example of various use cases where the ICT Concepts indicator hypothetically allow traders to find key levels & find optimal entry points using market structure.
In the image above we can see a bearish Market Structure Shift (MSS) is confirmed, indicating a potential trade setup for targeting the Balanced Price Range imbalance (BPR) below with a stop loss above the buyside liquidity.
Although what we are demonstrating here is a hindsight example, it shows the potential usage this toolkit gives you for creating trading plans based on ICT Concepts.
Same chart but playing out the history further we can see directly after price came down to the Sellside liquidity & swept below it...
Then by enabling IFVGs in the settings, we can see the IFVG retests alongside the Sellside & Buyside liquidity acting in confluence.
Which allows us to see a great bullish structure in the market with various key levels for potential entries.
Here we can see a potential bullish setup as price has taken out a previous Sellside liquidity zone and is now retesting a NWOG + Volume Imbalance.
Users also have the option to display Fibonacci retracements based on market structure, order blocks, and imbalance areas, which can help place limit/stop orders more effectively as well as finding optimal points of interest beyond what the primary ICT Concepts features can generate for a trader.
In the above image we can see the Fibonacci extension was selected to be based on the NWOG giving us some upside levels above the buyside liquidity.
🔶 DETAILS
Each feature within the ICT Concepts indicator is described in the sub sections below.
🔹 Market Structure
Market structure labels are constructed from price breaking a prior swing point. This allows a user to determine the current market trend based on the price action.
There are two types of Market Structure labels included:
Market Structure Shift (MSS)
Break Of Structure (BOS)
A MSS occurs when price breaks a swing low in an uptrend or a swing high in a downtrend, highlighting a potential reversal. This is often labeled as "CHoCH", but ICT specifies it as MSS.
On the other hand, BOS labels occur when price breaks a swing high in an uptrend or a swing low in a downtrend. The occurrence of these particular swing points is caused by retracements (inducements) that highlights liquidity hunting in lower timeframes.
🔹 Order Blocks
More significant market participants (institutions) with the ability of placing large orders in the market will generally place a sequence of individual trades spread out in time. This is referred as executing what is called a "meta-order".
Order blocks highlight the area where potential meta-orders are executed. Bullish order blocks are located near local bottoms in an uptrend while bearish order blocks are located near local tops in a downtrend.
When price mitigates (breaks out) an order block, a breaker block is confirmed. We can eventually expect price to trade back to this breaker block offering a new trade opportunity.
🔹 Buyside & Sellside Liquidity
Buyside / Sellside liquidity levels highlight price levels where market participants might place limit/stop orders.
Buyside liquidity levels will regroup the stoploss orders of short traders as well as limit orders of long traders, while Sellside liquidity levels will regroup the stoploss orders of long traders as well as limit orders of short traders.
These levels can play different roles. More informed market participants might view these levels as source of liquidity, and once liquidity over a specific level is reduced it will be found in another area.
🔹 Imbalances
Imbalances highlight disparities between the bid/ask, these can also be defined as inefficiencies, which would suggest that not all available information is reflected by the price and would as such provide potential trading opportunities.
It is common for price to "rebalance" and seek to come back to a previous imbalance area.
ICT highlights multiple imbalance formations:
Fair Value Gaps: A three candle formation where the candle shadows adjacent to the central candle do not overlap, this highlights a gap area.
Implied Fair Value Gaps: Unlike the fair value gap the implied fair value gap has candle shadows adjacent to the central candle overlapping. The gap area is constructed from the average between the respective shadow and the nearest extremity of their candle body.
Balanced Price Range: Balanced price ranges occur when a fair value gap overlaps a previous fair value gap, with the overlapping area resulting in the imbalance area.
Volume Imbalance: Volume imbalances highlight gaps between the opening price and closing price with existing trading activity (the low/high overlap the previous high/low).
Opening Gap: Unlike volume imbalances opening gaps highlight areas with no trading activity. The low/high does not reach previous high/low, highlighting a "void" area.
🔹 Displacement
Displacements are scenarios where price forms successive candles of the same sentiment (bullish/bearish) with large bodies and short shadows.
These can more technically be identified by positive auto correlation (a close to open change is more likely to be followed by a change of the same sign) as well as volatility clustering (large changes are followed by large changes).
Displacements can be the cause for the formation of imbalances as well as market structure, these can be caused by the full execution of a meta order.
🔹 Kill Zones
Killzones represent different time intervals that aims at offering optimal trade entries. Killzones include:
- New York Killzone (7:9 ET)
- London Open Killzone (2:5 ET)
- London Close Killzone (10:12 ET)
- Asian Killzone (20:00 ET)
🔶 Conclusion & Supplementary Material
This script aims to emulate how a trader would draw each of the covered features on their chart in the most precise representation to how it's actually taught by ICT directly.
There are many parallels between ICT Concepts and Smart Money Concepts that we released in 2022 which has a more general & simpler usage:
ICT Concepts, however, is more specifically aligned toward the community's interpretation of how to analyze price 'based on ICT', rather than displaying features to have a more classic interpretation for a technical analyst.
Entries + FVG SignalsE+FVG: A Masterclass in Institutional Trading Concepts
Chapter 1: The Modern Trader's Dilemma—Decoding the Institutional Footprint
In the vast, often chaotic ocean of the financial markets, retail traders navigate with the tools they are given: conventional indicators like moving averages, RSI, and MACD. While useful for gauging momentum and general trends, these tools often fall short because they were not designed to interpret the primary force that moves markets: institutional order flow. The modern trader faces a critical challenge: the tools and concepts taught in mainstream trading education are often decades behind the sophisticated, algorithm-driven strategies employed by banks, hedge funds, and large financial institutions.
This leads to a frustrating cycle of seemingly inexplicable price movements. A trader might see a perfect breakout from a classic pattern, only for it to reverse viciously, stopping them out. They might identify a strong trend, yet struggle to find a logical entry point, consistently feeling "late to the party." These experiences are not random; they are often the result of institutional market manipulation designed to engineer liquidity.
The fundamental problem that E+FVG (Entries + FVG Signals) addresses is this informational asymmetry. It is a sophisticated, institutional-grade framework designed to move a trader's perspective from a retail mindset to a professional one. It does not rely on lagging, derivative indicators. Instead, it focuses on the two core elements of price action that reveal the true intentions of "Smart Money": liquidity and imbalances.
This is not merely another indicator to add to a chart; it is a complete analytical engine designed to help you see the market through a new lens. It deconstructs price action to pinpoint two critical things:
Where institutions are likely to hunt for liquidity (running stop-loss orders).
The specific price inefficiencies (Fair Value Gaps) they are likely to target.
By focusing on these core principles, E+FVG provides a logical, rules-based solution to identifying high-probability trade setups. It is built for the discerning trader who is ready to evolve beyond conventional technical analysis and learn a methodology that is aligned with how the market truly operates at an institutional level. It is, in essence, an operating system for "Smart Money" trading.
Chapter 2: The Core Philosophy—Liquidity is the Fuel, Imbalances are the Destination
To fully grasp the power of this tool, one must first understand its foundational philosophy, which is rooted in the core tenets of institutional trading, often referred to as Smart Money Concepts (SMC). This philosophy can be distilled into two simple, powerful ideas:
1. Liquidity is the Fuel that Moves the Market:
The market does not move simply because there are more buyers than sellers, or vice-versa. It moves to seek liquidity. Large institutions cannot simply click "buy" or "sell" to enter or exit their multi-million or billion-dollar positions. Doing so would cause massive slippage and alert the entire market to their intentions. Instead, they must strategically accumulate and distribute their positions in areas where there is a high concentration of orders.
Where are these orders located? They are clustered in predictable places: above recent swing highs (buy-stop orders from shorts, and breakout buy orders) and below recent swing lows (sell-stop orders from longs, and breakout sell orders). This collective pool of orders is called liquidity. Institutions will often drive price towards these liquidity pools in a "stop hunt" or "liquidity grab" to trigger those orders, creating the necessary volume for them to fill their own large positions, often in the opposite direction of the liquidity grab itself. Understanding this concept is the key to avoiding being the "fuel" and instead learning to trade alongside the institutions.
2. Imbalances (Fair Value Gaps) are the Magnets for Price:
When institutions enter the market with overwhelming force, they create an imbalance in the order book. This energetic, one-sided price movement often leaves behind a gap in the market's pricing mechanism. On a candlestick chart, this appears as a Fair Value Gap (FVG)—a three-candle formation where the wicks of the first and third candles do not fully overlap the range of the middle candle.
These are not random gaps; they represent an inefficiency in the market's price delivery. The market, in its constant quest for equilibrium, has a natural tendency to revisit these inefficiently priced areas to "rebalance" the order book. Therefore, FVGs act as powerful magnets for price. They serve as high-probability targets for a price move and, critically, as logical points of interest where price may reverse after filling the imbalance. A fresh, unfilled FVG is one of the most significant clues an institution leaves behind.
E+FVG is built entirely on this philosophy. The "Entries Simplified" engine is designed to identify the liquidity grabs, and the "FVG Signals" engine is designed to identify the imbalances. Together, they provide a complete, synergistic framework for institutional-grade analysis.
Chapter 3: The Engine, Part I—"Entries Simplified": A Framework for Precision Entry
This is the primary trade-spotting engine of the E+FVG tool. It is a multi-layered system designed to identify a very specific, high-probability entry model based on institutional behavior. It filters out market noise by focusing solely on the sequence of a liquidity sweep followed by a clear and energetic displacement.
Feature 1: The Multi-Timeframe Liquidity Engine
The first and most crucial step in the engine's logic is to identify a valid liquidity grab. The script understands that the most significant reversals are often initiated after price has swept a key high or low from a higher timeframe. A sweep of yesterday's high holds far more weight than a sweep of the last 5-minute high.
Automatic Timeframe Adaptation: The engine intelligently analyzes your current chart's timeframe and automatically selects an appropriate higher timeframe (HTF) for its core analysis. For instance, if you are on a 15-minute chart, it might reference the 4-hour or Daily chart to identify key structural points. This is done seamlessly in the background, ensuring the analysis is always anchored to a significant structural context without requiring manual input.
The "Sweep" Condition: The script is not looking for a simple touch of a high or low. It is looking for a definitive sweep (also known as a "stop hunt" or "Judas swing"). This is defined as price pushing just beyond a key prior candle's high or low and then closing back within its range. This specific price action pattern is a classic signature of a liquidity grab, indicating that the move's purpose was to trigger stops, not to start a new, sustained trend. The "Entries Simplified" engine is constantly scanning the HTF price action for these sweep events, as they are the necessary precondition for any potential setup.
Feature 2: The Upshift/Downshift Signal—Confirming the Reversal
Once a valid HTF liquidity sweep has occurred, the engine moves to its next phase: identifying the confirmation. A sweep alone is not enough; institutions must show their hand and reveal their intention to reverse the market. This confirmation comes in the form of a powerful structural breakout (for bullish reversals) or breakdown (for bearish reversals). We call these events Upshifts and Downshifts.
Defining the Upshift & Downshift: This is the critical moment of confirmation, the market "tipping its hand."
An Upshift occurs after a liquidity sweep below a key low. Following the sweep, price reverses with energy and produces a decisive breakout to the upside, closing above a recent, valid swing high. This action confirms that the prior downtrend's momentum is broken, the downward move was a trap to engineer liquidity, and institutional buyers are now in aggressive control.
A Downshift occurs after a liquidity sweep above a key high. Following the sweep, price reverses aggressively and produces a sharp breakdown to the downside, closing below a recent, valid swing low. This confirms that the prior uptrend's momentum has failed, the upward move was a liquidity grab, and institutional sellers have now taken control of the market.
Algorithmic Identification: The E+FVG engine uses a proprietary algorithm to identify these moments. It analyzes the candle sequence immediately following a sweep, looking for a specific type of market structure break characterized by high energy and displacement—often leaving imbalances (Fair Value Gaps) in its wake. This is not a simple "pivot break"; the algorithm is designed to distinguish between a weak, indecisive wiggle and a true, institutionally-backed Upshift or Downshift.
The Signal: When this precise sequence—a HTF liquidity sweep followed by a valid Upshift or Downshift on the trading timeframe—is confirmed, the indicator plots a clear arrow on the chart. A green arrow below a low signifies a Bullish setup (confirmed by an Upshift), while a red arrow above a high signifies a Bearish setup (confirmed by a Downshift). This is the core entry signal of the "Entries Simplified" engine.
Feature 3: Automated Price Projections—A Built-In Trade Management Framework
A valid entry signal is only one part of a successful trade. A trader also needs a logical framework for taking profits. The E+FVG engine completes its trade-spotting process by providing automated, mathematically-derived price projections.
Fibonacci-Based Logic: After a valid Upshift or Downshift signal is generated, the script analyzes the price leg that created the setup (i.e., the range from the liquidity sweep to the confirmation breakout/breakdown). It then uses a methodology based on standard Fibonacci extension principles to project several potential take-profit (TP) levels.
Multiple TP Levels: The indicator projects four distinct TP levels (TP1, TP2, TP3, TP4). This provides a comprehensive trade management framework. A conservative trader might aim for TP1 or TP2, while a more aggressive trader might hold a partial position for the higher targets. These levels are plotted on the chart as clear, labeled lines, removing the guesswork from profit-taking.
Dynamic and Adaptive: These projections are not static. They are calculated uniquely for each individual setup, based on the specific volatility and range of the price action that generated the signal. This ensures that the take-profit targets are always relevant to the current market conditions.
The "Entries Simplified" engine, therefore, provides a complete, end-to-end framework: it waits for a high-probability condition (HTF sweep), confirms it with a specific entry model (Upshift/Downshift), and provides a logical road map for managing the trade (automated projections).
Chapter 4: The Engine, Part II—"FVG Signals": Mapping Market Inefficiencies
This second, complementary engine of the E+FVG tool operates as a market mapping system. Its sole purpose is to identify, plot, and monitor Fair Value Gaps (FVGs)—the critical price inefficiencies that act as magnets and potential reversal points.
Feature 1: Dual Timeframe FVG Detection
The significance of an FVG is directly related to the timeframe on which it forms. A 1-hour FVG is a more powerful magnet for price than a 1-minute FVG. The FVG engine gives you the ability to monitor both simultaneously, providing a richer, multi-dimensional view of the market's inefficiencies.
Chart TF FVGs: The indicator will, by default, identify and plot the FVGs that form on your current, active chart timeframe. These are useful for short-term scalping and for fine-tuning entries.
Higher Timeframe (HTF) FVGs: With a single click, you can enable the HTF FVG detection. This allows you to overlay, for example, 1-hour FVGs onto your 5-minute chart. This is an incredibly powerful feature. Seeing a 5-minute price rally approaching a fresh, unfilled 1-hour bearish FVG gives you a high-probability context for a potential reversal. The HTF FVGs act as major points of interest that can override the short-term price action.
Feature 2: The Intelligent "Tap-In" Logic—Beyond a Simple Touch
Many FVG indicators will simply alert you when price touches an FVG. The E+FVG engine employs a more sophisticated, two-stage logic to generate its signals, which helps to filter out weak reactions and focus on confirmed reversals.
Stage 1: The Entry. The first event is when price simply enters the FVG zone. This is a "heads-up" moment, and the indicator can be configured to provide an initial alert for this event.
Stage 2: The Confirmed "Tap-In." The official signal, however, is the "Tap-In." This is a more stringent condition. For a bullish FVG, a Tap-In is only confirmed after price has touched or entered the FVG zone and then closed back above the FVG's high. For a bearish FVG, the price must touch or enter the zone and then close back below the FVG's low. This confirmation logic ensures that the FVG has not just been touched, but has been respected and rejected by the market, making the resulting arrow signal significantly more reliable than a simple touch alert.
Feature 3: Interactive and Clean Visuals
The FVG engine is designed to provide maximum information with minimum chart clutter.
Clear, Color-Coded Boxes: Bullish FVGs are plotted in one color (e.g., green or blue), and bearish FVGs in another (e.g., red or orange), with a clear distinction between Chart TF and HTF zones.
Optional Box Display: Recognizing that some traders prefer a cleaner chart, you have the option to hide the FVG boxes entirely. Even with the boxes hidden, the underlying logic remains active, and the script will still generate the crucial Tap-In arrow signals.
Automatic Fading: Once an FVG has been successfully "tapped," the script can be set to automatically fade the color of the box. This provides a clear visual cue that the zone has been tested and may have less significance going forward.
Expiration: FVGs do not remain relevant forever. The script automatically removes old FVG boxes from the chart after a user-defined number of bars, ensuring your analysis is always focused on the most recent and relevant market inefficiencies.
Chapter 5: The Power of Synergy—How the Two Engines Work Together
While both the "Entries Simplified" engine and the "FVG Signals" engine are powerful standalone tools, their true potential is unlocked when used in combination. They are designed to provide confluence—a scenario where two or more independent analytical concepts align to produce a single, high-conviction trade idea.
Scenario A: The A+ Setup (Upshift into FVG). This is the highest probability setup. Imagine the "Entries Simplified" engine detects a HTF liquidity sweep below a key low, followed by a bullish Upshift signal. You look at your chart and see that this strong upward displacement is heading directly towards a fresh, unfilled bearish HTF FVG. This provides you with both a high-probability entry signal and a logical, high-probability target for the trade.
Scenario B: The FVG Confirmation. A trader might see the "Entries Simplified" engine generate a bearish Downshift signal. They feel it is a valid setup but want one extra layer of confirmation. They wait for price to rally a little further and "tap-in" to a nearby bearish FVG that formed during the Downshift's displacement. The FVG Tap-In signal then serves as their final confirmation trigger to enter the trade.
Scenario C: The Standalone FVG Trade. The FVG engine can also be used as a primary trading tool. A trader might notice that price is in a strong uptrend. They see price pulling back towards a fresh, bullish HTF FVG. They are not waiting for a full Upshift/Downshift setup; instead, they are simply waiting for the FVG Tap-In signal to confirm that the pullback is likely over and the trend is ready to resume.
By learning to read the interplay between these two engines, a trader can elevate their analysis from a one-dimensional process to a multi-dimensional, context-aware methodology.
Chapter 6: The Workflow—A Step-by-Step Guide to Practical Application
Step 1: The Pre-Market Analysis (Mapping the Battlefield). Before your session begins, enable the HTF FVG detection. Identify the key, unfilled HTF FVGs above and below the current price. These are your major points of interest for the day—your potential targets and reversal zones.
Step 2: Await the Primary Condition (Patience for Liquidity). During your trading session, your primary focus should be on the "Entries Simplified" engine. Your job is to wait patiently for the script to identify a valid HTF liquidity sweep. Do not force trades in the middle of a price range where no significant liquidity has been taken.
Step 3: The Upshift/Downshift Alert (The Call to Action). When the red or green arrow from the "Entries Simplified" engine appears, it is your cue to focus your attention. This is a potential high-probability setup.
Step 4: The Confluence Check (Building Conviction). With the Upshift or Downshift signal on your chart, ask the key confluence questions:
Did the displacement from the Upshift/Downshift create a new FVG?
Is the projected path of the trade heading towards a pre-identified HTF FVG?
Has an FVG Tap-In signal appeared shortly after the initial signal, offering further confirmation?
Step 5: Execute and Manage. If you have sufficient confluence, execute the trade. Use the automated price projections as your guide for profit-taking. A logical stop-loss is typically placed just beyond the high or low of the liquidity sweep that initiated the entire sequence.
Chapter 7: The Trader's Mind—Mastering the Institutional Mindset
This tool is more than a set of algorithms; it is a training system for professional trading psychology.
From Chasing to Trapping: You stop chasing breakouts and instead learn to identify where others are being trapped.
From FOMO to Patience: The strict, sequential logic of the entry model (Sweep -> Upshift/Downshift) forces you to wait for the highest quality setups, curing the Fear Of Missing Out.
Probabilistic Thinking: By focusing on liquidity and imbalances, you begin to think in terms of probabilities, not certainties. You understand that you are putting on trades where the odds are statistically in your favor, which is the cornerstone of any professional trading career.
Clarity and Confidence: The clear, rules-based signals remove ambiguity and second-guessing. This builds the confidence needed to execute trades decisively when the opportunity arises.
Chapter 8: Frequently Asked Questions & Scenarios
Q: The "Entries Simplified" code looks complex. Do I need to understand all of it?
A: No. The engine is designed to perform its complex analysis in the background. Your job is to understand the principles—liquidity sweep and the resulting Upshift or Downshift—and to recognize the clear arrow signals that the script generates when those conditions are met.
Q: Can I turn one of the engines off?
A: Yes, the indicator is modular. If you only want to focus on Fair Value Gaps, for example, you can disable the plot shapes for the "Entries Simplified" signals in the settings, and vice-versa.
Q: Does this work on all assets and timeframes?
A: The principles of liquidity and imbalance are universal and apply to all markets, from cryptocurrencies to forex to indices. The fractal nature of the analysis means the concepts are valid on all timeframes. However, it is always recommended that a trader backtest and forward-test the tool on their specific instrument and timeframe of choice to understand its unique behavior.
Author's Instructions
To request access to this script, please send me a direct private message here on TradingView.
Alternatively, you can find more information and contact details via the link on my profile signature.
Please DO NOT request access in the Comments section. Comments are for questions about the script's methodology and for sharing constructive feedback.
Fractal Model [Pro+] (TTrades)Introduction:
Crafted with TTrades, the Fractal Model empowers traders with a refined approach to Algorithmic Price Delivery. Specifically designed for those aiming to capitalize on expansive moves, this model anticipates momentum shifts, swing formations, orderflow continuations, as well as helping analysts highlight key areas to anticipate price deliveries.
Description:
The Fractal Model° is rooted in the cyclical nature of price movements, where price alternates between large and small ranges. Expansion occurs when price moves consistently in one direction with momentum. By combining higher Timeframe closures with the confirmation of the change in state of delivery (CISD) on the lower Timeframe, the model reveals moments when expansion is poised to occur.
Thanks to TTrades' extensive research and years of studying these price behaviors, the Fractal Model° is a powerful, adaptive tool that seamlessly adjusts to any asset, market condition, or Timeframe, translating complex price action insights into an intuitive and responsive system.
The TTrades Fractal Model remains stable and non-repainting, offering traders reliable, unchanged levels within the given Time period. This tool is meticulously designed to support analysts focus on price action and dynamically adapt with each new Time period.
Key Features:
Custom History: Control the depth of your historical view by selecting the number of previous setups you’d like to analyze on your chart, from the current setup only (0) to a history of up to 40 setups. This feature allows you to tailor the chart to your specific charting style, whether you prefer to see past setups or the current view only.
Fractal Timeframe Pairings: This indicator enables users to observe and analyze lower Timeframe (LTF) movements within the structure of a higher Timeframe (HTF) candle. By examining LTF price action inside each HTF candle, analysts can gain insight into micro trends, structure shifts, and key entry points that may not be visible on the higher Timeframe alone. This approach provides a layered perspective, allowing analysts to closely monitoring how the LTF movements unfold within the overarching HTF context.
For a more dynamic and hands-off user experience, the Automatic feature autonomously adjusts the higher Timeframe pairing based the current chart Timeframe, ensuring accurate alignment with the Fractal Model, according to TTrades and his studies.
Bias Selection: This feature allows analysts complete control over bias and setup detection, allowing one to view bullish or bearish formations exclusively, or opt for a neutral bias to monitor both directions. Easily toggle the bias filter on Fractal Model to align with your higher Timeframe market draw.
Indicator Notice for Timeframe Pairing Limitations: This indicator supports Timeframe pairings (e.g., 5m-1H, 15m-4H). If you select a timeframe, grater than the lower Timeframe (LTF) view (e.g., viewing a 15m chart when 5m-1H is enabled), the indicator will display an warning message within the table. Although the higher Timeframe (HTF) candle plotting will remain visible, note that the LTF’s CISD and associated projections will not render in this view.
Customizable Time Filters: Further synchronize Time and price studies by selecting up to three custom Time windows, filtering model formations that fall outside these specified ranges. This provides clarity and focus on relevant price action signatures within defined Time windows, at the discretion of the analyst.
Higher Time Frame Candles (PO3): The Fractal Model° integrates the HTF Power of Three framework, enabling traders to visualize and spot critical turning points live. By incorporating this structure, traders can observe key phases of price delivery and market transitions on lower Timeframes, while monitoring higher Timeframe candle development.
Info Table: Display a customizable information table that includes key details such as timeframe pairing, Time until the next higher Timeframe candle close, analyst bias, and applied Time filter preferences. Options for size, location, and border give analysts full control over the table’s appearance on the chart.
TTrades Framework Customization :
TTFM Lables (C2/C3/C4): When a setup remains valid, the label will display in gray, signifying stable conditions for the setup.
If the setup fails—defined by price returning to the initial high or low without forming a higher Timeframes swing point—the indicator will stop plotting projections, Equilibrium (EQ), Liquidity Sweep, and the T-spot. In this case, the labels for key points (C2, C3, C4) will remain on the chart but turn red, clearly indicating the failure of the setup.
If the setup does not fail within the next higher Timeframes candle, which defines the setup’s formation, the label will turn orange. This orange color signals potential consolidation, or slowdown, suggesting that the market may enter a range or pause in trend movement within the setup.
Candle 1 Liquidity: Highlight important liquidity levels at each swing point with horizontal rays, marking sweeps of liquidity and potential reversals.
Change in State of Delivery (CISD): Mark the series of candles making up significant highs or lows. A close beyond the opening price signals a change from bullish to bearish or vice versa, confirming a trend reversal.
Candle Equilibrium: Indicates 50% levels of higher time frame ranges, displaying discount and premium zones that provide additional context for potential entries and exits.
T-Spot Identification: The T-Spot marks anticipated points of the higher Timeframe candles where price wicks are expected to form, based on TTrades’ refined analysis and methodology. This level is invaluable for identifying high-probability reversal or continuation points within lower Timeframes, remaining aligned with the higher Timeframe narrative.
Projections: Leverage projected levels based on the shifts in delivery as per TTrades’ analysis. These user-defined levels serve as future points of interest for price to redeliver, rebalance, and exhaust. Analysts can add, or remove, desired projection levels – default projections being .
Formation Liquidity: Identify previous candles' highs and lows as critical liquidity points appertaining to the current developing formation. These zones are marked to provide easy visualization of engineered liquidity pools, serving as key reference points for future price action.
Fully Automated Framework: all these components, when put together in the Fractal Model° , yield TTrades' fully automated system. Each component is customizable to the analyst's liking to match their unique visual preferences and model Timeframes.
Usage Guidance:
Add Fractal Model (TTrades) to your TradingView chart.
Select your preferred Time pairings, model history, Time filers.
Automate your analysis process with Fractal Model (TTrades) and leverage it into your existing strategies to fine-tune your view through TTrades' lens.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products. Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
Płatny skrypt
ICT Venom Trading Model [TradingFinder] SMC NY Session 2025SetupIntroduction
The ICT Venom Model is one of the most advanced strategies in the ICT framework, designed for intraday trading on major US indices such as US100, US30, and US500. This model is rooted in liquidity theory, time and price dynamics, and institutional order flow.
The Venom Model focuses on detecting Liquidity Sweeps, identifying Fair Value Gaps (FVG), and analyzing Market Structure Shifts (MSS). By combining these ICT core concepts, traders can filter false breakouts, capture sharp reversals, and align their entries with the real institutional liquidity flow during the New York Session.
Key Highlights of ICT Venom Model :
Intraday focus : Optimized for US indices (US100, US30, US500).
Time element : Critical window is 08:00–09:30 AM (Venom Box).
Liquidity sweep logic : Price grabs liquidity at 09:30 AM open.
Confirmation tools : MSS, CISD, FVG, and Order Blocks.
Dual setups : Works in both Bullish Venom and Bearish Venom conditions.
At its core, the ICT Venom Strategy is a framework that explains how institutional players manipulate liquidity pools by engineering false breakouts around the initial range of the market. Between 08:00 and 09:30 AM New York time, a range called the “Venom Box” is formed.
This range acts as a trap for retail traders, and once the 09:30 AM market open occurs, price usually sweeps either the high or the low of this box to collect stop-loss liquidity. After this liquidity grab, the market often reverses sharply, giving birth to a classic Bullish Venom Setup or Bearish Venom Setup
The Venom Model (ICT Venom Trading Strategy) is not just a pattern recognition tool but a precise institutional trading model based on time, liquidity, and market structure. By understanding the Initial Balance Range, watching for Liquidity Sweeps, and entering trades from FVG zones or Order Blocks, traders can anticipate market reversals with high accuracy. This strategy is widely respected among ICT followers because it offers both risk management discipline and clear entry/exit conditions. In short, the Venom Model transforms liquidity manipulation into actionable trading opportunities.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The ICT Venom Model is applied by observing price behavior during the early hours of the New York session. The first step is to define the Initial Range, also called the Venom Box, which is formed between 08:00 and 09:30 AM EST. This range marks the high and low points where institutional traders often create traps for retail participants. Once the official market opens at 09:30 AM, price usually sweeps either the top or bottom of this box to collect liquidity.
After this liquidity grab, the market tends to reverse in alignment with the true directional bias. To confirm the setup, traders look for signals such as a Market Structure Shift (MSS), Change in State of Delivery (CISD), or the appearance of a Fair Value Gap (FVG). These elements validate the reversal and provide precise levels for trade execution.
🟣 Bullish Setup
In a Bullish Venom Setup, the market first sweeps the low of the Venom Box after 09:30 AM, triggering sell-side liquidity collection. This downward move is often sharp and deceptive, designed to stop out retail long positions and attract new sellers. Once liquidity is taken, the market typically shifts direction, forming an MSS or CISD that signals a reversal to the upside.
Traders then wait for price to retrace into a Fair Value Gap or a demand-side Order Block created during the reversal leg. This retracement offers the ideal entry point for long positions. Stop-loss placement should be just below the liquidity sweep low, while profit targets are set at the Venom Box high and, if momentum continues, at higher session or daily highs.
🟣 Bearish Setup
In a Bearish Venom Setup, the process is similar but reversed. After the Initial Range is defined, if price breaks above the Venom Box high following the 09:30 AM open, it signals a false breakout designed to collect buy-side liquidity. This move usually traps eager buyers and clears out stop-losses above the high.
After the liquidity sweep, confirmation comes through an MSS or CISD pointing to a reversal downward. At this stage, traders anticipate a retracement into a Fair Value Gap or a supply-side Order Block formed during the reversal. Short entries are taken within this zone, with stop-loss positioned just above the liquidity sweep high. The logical profit targets include the Venom Box low and, in stronger bearish momentum, deeper session or daily lows.
🔵 Settings
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The ICT Venom Model is more than just a reversal setup; it is a complete intraday trading framework that blends liquidity theory, time precision, and market structure analysis. By focusing on the Initial Range between 08:00 and 09:30 AM New York time and observing how price reacts at the 09:30 AM open, traders can identify liquidity sweeps that reveal institutional intentions.
Whether in a Bullish Venom Setup or a Bearish Venom Setup, the model allows for precise entries through Fair Value Gaps (FVGs) and Order Blocks, while maintaining clear risk management with well-defined stop-loss and target levels.
Ultimately, the ICT Venom Model provides traders with a structured way to filter false moves and align their trades with institutional order flow. Its strength lies in transforming liquidity manipulation into actionable opportunities, giving intraday traders an edge in timing, accuracy, and consistency. For those who master its logic, the Venom Model becomes not only a strategy for entry and exit, but also a deeper framework for understanding how liquidity truly drives price in the New York session.
Per Volume Price ImpactLiquidity, Information and Market Timing
* Market Liquidity
The term liquidity can refer to many things in finance. In this article, we will limit the scope of discussion to the market’s ability to transact without incurring a significant increase in volatility.
As we know, liquidity and volatility have an inversed relationship — the more ample the liquidity, the lower the volatility (attributed to transaction cost, price movement and, so on). With this understanding, we can say large movements in the market are driven by low liquidity. This does not seem to make sense because the markets are huge, how can it possibly be illiquid? Now, this has to do with how the market operates and how exchanges occur (This topic concerns the area of market microstructure).
* Order Book & the Trading Process
So how does a transaction actually occur in the market? Let’s assume we open a position with a market order. In this case, you will get the price on your quote board if there are enough units of assets people are willing to sell at that price. If there are not enough units, you will buy from the second-best price and so on until your order is filled. Now in the second case, as the order is being filled, the change in price is recorded. Therefore, if someone wishes to move the market, theoretically, they just need to buy up or sell up but it is problematic to do so.
Here is why:
while dry up the liquidity can make huge moves, it is inefficient to do so.
it takes a lot of money to do that
your position will be exposed, someone more resourceful than you may go against you and that is a huge risk
market manipulation charges
when you open a position, the entry price of the position is essentially a VWAP (volume-weighted average price). If you attempt to move the market and open a buy position at the same time, you will have a higher VWAP, eating into your own profit.
I think these reasons are sufficient in establishing why opening a position and drying up liquidity to profit is a dumb idea. But of course, the institutions are not stupid, the alternative is to enter your position first then move the market.
To measure liquidity one of the tools people use is the order book. It can offer an overview of the sentiment (by looking at the orders and changes in volume) and how people are positioned (if the broker offers such data). In my opinion, open interest is a much better tool than order as it records the transactions that have occurred, hence less prone to manipulations (google: “Navinder Singh Sarao”, the trader who used fake orders to manipulate algorithms to crash the market).
But to quantify the order book is so much work as well (there are ways, just difficult), what we can do is to make things simpler.
* Quantify Market Impact
We know price and volume reflect information, while the past technical information has no predictive power per semi-strong form of EMH, empirical studies have often tested this theory over a longer time horizon. In our case, precisely due to the mechanism of exchange and human behavior (The lack of incentive to move the market right away) we can, in the very short term (often intraday), foresee if the market is going to move or not. Back to the very definition of liquidity being the ability to transact without moving the market significantly, we can take this definition and quantify it with this formula:
Market Impact = (High — Low) / Volume
Why specifically “high — low”, because that’s the complete information in that moment and it is corresponding to the volume. A little crude but it is the simplest form.
A few things to take note of here:
We can only know the complete picture once the candle is complete. This is fine in most markets because it takes time to gather money and orders.
We often see high liquidity during certain time of the day, for example, when the market opens and so on. As a result, we need to take some scientific approaches to transform the data.
Now, this looks much better. To interpret this graph, the lower the value, the lower the market impact, the deeper the liquidity.
* Generate Tradable Insights
To generate trade ideas isn’t a difficult task, we all know the RSI, MOM, STOC, etc. all the indicators attempt to draw boundaries, and we can do the same but we need to be a little more advanced and critical.
step 1: we first need to normalize the data. To do that we will take the log of the values to make the skewed distribution normal. The result isn’t ideal if you zoom out but I think this is decent enough to work with. Here is
This is still not a stationary time series, but it looks stable enough and it mean-reverts. So we turn to our lovely standard deviation bands for help.
Step 2: Because this is not a stationary process (visually, you can test it statistically if you wish), we cannot just take sample mean and SD and also because we want to show off our data skills, so we turn to move averages and regressions. I’m going to use moving regression here because I think it is better (mean can be distorted by large values by a larger margin and it lags)
I’m using the moving regression band on TradingView and 1.5 SD here for convenience, you can try to optimize the parameters with codes or other regression models if you wish. But I think it is more important to understand the rationale here.
This step is essentially trying to figure out the anomalies in liquidity so that we can see when there is deep liquidity. This is also why choosing the parameter is crucial because you are essentially approximating how much informed trading is taking place (This is a concept in market microstructure for brokerages to set their spreads but it is not a good tool in a liquid market). By setting the level at 1.5 we are assuming about 86% of the time the market is in what we consider a normal liquid state. (again it is arbitrary, but based on the 68–95–99.7 rule of normal distribution). The rest of the time will be either low or high liquidity, When liquidity is deep, it perhaps, signals institutional money is pouring into the market and big moves may follow.
* Conclusion
There you have it, how to enter the market with the big bucks. But do take note there are plenty of assumptions and a lot to improve on here.
XAUUSD Sniper Setup (Pre-Arrows + SL/TP)//@version=5
indicator("XAUUSD Sniper Setup (Pre-Arrows + SL/TP)", overlay=true)
// === Inputs ===
rangePeriod = input.int(20, "Lookback Bars for Zone", minval=5)
maxRangePercent = input.float(0.08, "Max Range % for Consolidation", step=0.01)
tpMultiplier = input.float(1.5, "TP Multiplier")
slMultiplier = input.float(1.0, "SL Multiplier")
// === Consolidation Detection ===
highestPrice = ta.highest(high, rangePeriod)
lowestPrice = ta.lowest(low, rangePeriod)
priceRange = highestPrice - lowestPrice
percentRange = (priceRange / close) * 100
isConsolidation = percentRange < maxRangePercent
// === Zones ===
demandZone = lowestPrice
supplyZone = highestPrice
// === Plot Consolidation Zone Background ===
bgcolor(isConsolidation ? color.new(color.gray, 85) : na)
// === Plot Potential Buy/Sell Levels ===
plot(isConsolidation ? demandZone : na, color=color.green, title="Potential Buy Level", linewidth=2)
plot(isConsolidation ? supplyZone : na, color=color.red, title="Potential Sell Level", linewidth=2)
// === Liquidity Sweep ===
liquidityTakenBelow = low < demandZone
liquidityTakenAbove = high > supplyZone
// === Engulfing Candles ===
bullishEngulfing = close > open and close < open and close > open
bearishEngulfing = close < open and close > open and close < open
// === Break of Structure ===
bosUp = high > ta.highest(high , 5)
bosDown = low < ta.lowest(low , 5)
// === Sniper Entry Conditions ===
buySignal = isConsolidation and liquidityTakenBelow and bullishEngulfing and bosUp
sellSignal = isConsolidation and liquidityTakenAbove and bearishEngulfing and bosDown
// === SL & TP Levels ===
slBuy = demandZone - (priceRange * slMultiplier)
tpBuy = close + (priceRange * tpMultiplier)
slSell = supplyZone + (priceRange * slMultiplier)
tpSell = close - (priceRange * tpMultiplier)
// === PRE-ARROWS (Show Before Breakout) ===
preBuyArrow = isConsolidation ? 1 : na
preSellArrow = isConsolidation ? -1 : na
plotarrow(preBuyArrow, colorup=color.new(color.green, 50), maxheight=20, minheight=20, title="Pre-Buy Arrow")
plotarrow(preSellArrow, colordown=color.new(color.red, 50), maxheight=20, minheight=20, title="Pre-Sell Arrow")
// === SNIPER CONFIRMATION ARROWS ===
buyArrow = buySignal ? 1 : na
sellArrow = sellSignal ? -1 : na
plotarrow(buyArrow, colorup=color.green, maxheight=60, minheight=60, title="Sniper BUY Arrow")
plotarrow(sellArrow, colordown=color.red, maxheight=60, minheight=60, title="Sniper SELL Arrow")
// === BUY SIGNAL ===
if buySignal
label.new(bar_index, low, "BUY\nSL/TP Added", style=label.style_label_up, color=color.green, textcolor=color.white)
line.new(bar_index, slBuy, bar_index + 5, slBuy, color=color.red, style=line.style_dotted)
line.new(bar_index, tpBuy, bar_index + 5, tpBuy, color=color.green, style=line.style_dotted)
label.new(bar_index, slBuy, "SL", color=color.red, style=label.style_label_down)
label.new(bar_index, tpBuy, "TP", color=color.green, style=label.style_label_up)
// === SELL SIGNAL ===
if sellSignal
label.new(bar_index, high, "SELL\nSL/TP Added", style=label.style_label_down, color=color.red, textcolor=color.white)
line.new(bar_index, slSell, bar_index + 5, slSell, color=color.red, style=line.style_dotted)
line.new(bar_index, tpSell, bar_index + 5, tpSell, color=color.green, style=line.style_dotted)
label.new(bar_index, slSell, "SL", color=color.red, style=label.style_label_up)
label.new(bar_index, tpSell, "TP", color=color.green, style=label.style_label_down)
// === Alerts ===
alertcondition(buySignal, title="Sniper BUY", message="Sniper BUY setup on XAUUSD")
alertcondition(sellSignal, title="Sniper SELL", message="Sniper SELL setup on XAUUSD")
OANDA:XAUUSD
ICT/SMC DOL Detector PRO (Final)This indicator is designed to operate only on the 1-hour timeframe.
The ICT/SMC DOL Detector PRO is an educational indicator designed to identify and visualize Draw on Liquidity (DOL) levels across multiple time-frames. It tracks unmitigated daily highs and lows, clusters them into zones, and calculates confidence scores based on multiple factors including time decay, cluster size, and time-frame alignment.
This indicator is based on ICT (Inner Circle Trader) concepts and liquidity theory, which suggests that price tends to seek out areas of concentrated unfilled orders before reversing or continuing its trend.
What is a DOL (Draw on Liquidity)?
A Draw on Liquidity represents a daily high or low that has not been revisited (mitigated) by price. These levels act as "magnets" that draw price toward them because:
1. They represent untapped liquidity pools where unfilled orders exist
2. Market makers and institutions often target these levels to fill large orders
3. Price is drawn to these zones to clear pending orders
4. They can serve as potential reversal or continuation zones once liquidity is taken
Methodology
1. Level Tracking
The indicator monitors daily session highs and lows on the 1-hour time-frame, tracking:
- Session high price and time of formation
- Session low price and time of formation
- Whether each level has been breached (mitigated)
- Time elapsed since level formation
2. Clustering Algorithm
Unmitigated levels within a defined tolerance (default 0.5% of price) are grouped together to identify zones where multiple DOLs cluster. Larger clusters indicate stronger liquidity pools.
3. Confidence Scoring (The "AI" Logic)
Each DOL receives a confidence score (0-100%) based on three weighted factors. This is the core "AI" intelligence of the indicator:
**Factor 1: Cluster Size (50% weight)**
- Counts how many unmitigated levels exist within 0.5% of the price zone
- Formula: (levels_in_cluster / total_unmitigated_levels) × 50
- Logic: More unfilled orders clustered together = stronger liquidity pool = higher confidence
- Example: If 5 out of 10 total unmitigated levels cluster at 27,500, cluster score = (5/10) × 50 = 25%
**Factor 2: Time Decay (25% weight)**
- Calculates age of the level since formation
- Fresh levels (< 1 week old): Full 25% score
- Aging penalty: Loses 5% per week of age
- Maximum penalty: 25% (very old levels = 0% time score)
- Formula: max(0, 25 - (weeks_old × 5))
- Logic: Recent liquidity is more relevant than old liquidity that price has ignored for months
**Factor 3: Timeframe Alignment (25% weight)**
- Checks how many timeframes (1H, 4H, D1, W1) point in the same direction
- If multiple timeframes identify DOLs on the same side (all bullish or all bearish): Higher score
- If mixed signals: Lower score
- Formula: (aligned_timeframes / total_timeframes) × 25
- Logic: When multiple timeframes agree, the liquidity zone is validated across different time perspectives
**Total Confidence Score:**
```
Confidence = Cluster_Score + Time_Score + Alignment_Score
= (0-50%) + (0-25%) + (0-25%)
= 0-100%
```
**Example Calculation:**
```
DOL at 27,500:
- 6 out of 12 unmitigated levels cluster here → (6/12) × 50 = 25%
- Level is 2 weeks old → 25 - (2 × 5) = 15%
- 3 out of 4 timeframes bullish toward this level → (3/4) × 25 = 18.75%
- Total Confidence = 25% + 15% + 18.75% = 58.75% ≈ 59%
```
This mathematical approach removes subjectivity and provides objective, data-driven confidence scoring.
4. Multi-Timeframe Analysis
The indicator analyzes DOLs across four timeframes:
- **1H:** Intraday levels (fastest reaction)
- **4H:** Short-term swing levels
- **Daily:** Intermediate-term levels
- **Weekly:** Long-term structural levels
For each timeframe, it identifies:
- Highest confidence unmitigated high
- Highest confidence unmitigated low
- Directional bias (bullish if high > low confidence, bearish if low > high confidence)
5. Primary DOL Selection (AI Auto-Selection Logic)
When "Show AI DOL" is enabled, the indicator uses an automated selection algorithm to identify the most important targets:
**Step 1: Collect All Candidates**
The algorithm gathers all identified DOLs from all timeframes (1H, 4H, D1, W1) that meet minimum criteria:
- Must be unmitigated (not yet swept)
- Must have confidence score > 0%
- Must have at least 1 level in cluster
**Step 2: Calculate Confidence for Each**
Each candidate DOL receives its confidence score using the three-factor formula described above (Cluster + Time + Alignment).
**Step 3: Sort by Confidence**
All candidates are ranked from highest to lowest confidence score.
**Step 4: Select Primary and Secondary**
- **P1 (Primary DOL):** The DOL with the absolute highest confidence score
- **P2 (Secondary DOL):** The DOL with the second highest confidence score
**Why This Matters:**
Instead of manually scanning multiple timeframes and guessing which level is most important, the AI objectively identifies the two highest-probability liquidity targets based on quantifiable data.
**Example AI Selection:**
```
Available DOLs:
- 1H High: 27,400
- 4H High: 27,500
- D1 High: 27,500 ← P1 (Highest)
- W1 High: 27,650 ← P2 (Second Highest)
- 1H Low: 26,800
- D1 Low: 26,500
AI Selection:
P1 = 27,500 (Daily High with 92% confidence)
P2 = 27,650 (Weekly High with 88% confidence)
```
This provides a data-driven target selection rather than subjective manual interpretation. The AI removes emotion and bias, selecting targets based purely on mathematical probability.
Features
Why "AI" DOL?
The term "AI" in this indicator refers to the automated algorithmic selection process, not machine learning or neural networks. Specifically:
**What the AI Does:**
- Automatically evaluates all available DOLs across all timeframes
- Applies a weighted scoring algorithm (Cluster 50%, Time 25%, Alignment 25%)
- Objectively ranks DOLs by probability
- Selects the top 2 highest-confidence targets (P1 and P2)
- Removes human bias and emotion from target selection
**What the AI Does NOT Do:**
- It does not use machine learning or train on historical data
- It does not predict future price movements
- It does not adapt or "learn" over time
- It does not guarantee accuracy
The "AI" is simply an automated decision-making algorithm that applies consistent mathematical rules to identify the most statistically significant liquidity zones. Think of it as a "smart filter" rather than artificial intelligence in the traditional sense.
Visual Components
**Daily Level Lines:**
- Green lines: Unmitigated (not yet breached) levels
- Red lines: Mitigated (already breached) levels
- Dots at origin point showing where level was formed
- X marker when level gets breached
- Lines extend forward to show projection
**DOL Labels:**
- Display timeframe (1H, 4H, D1, W1) or "DOL" for AI selection
- Show confidence percentage in brackets
- Color-coded by timeframe:
- Lime: AI DOL (Smart selection)
- Aqua: 1-hour timeframe
- Blue: 4-hour timeframe
- Purple: Daily timeframe
- Orange: Weekly timeframe
**Info Box (Top Right):**
Displays comprehensive liquidity metrics:
- Total levels tracked
- Active (unmitigated) levels count
- Cleared (mitigated) levels count
- Flow direction (BID PRESSURE / OFFER PRESSURE)
- Most recent sweep
- Primary and Secondary DOL targets
- Multi-timeframe bias analysis
- Overall directional bias
Settings Explained
**Daily Levels Group:**
- Show Daily Highs/Lows: Toggle visibility of all daily level tracking
- Unbreached Color: Color for levels not yet hit
- Breached Color: Color for levels that have been swept
- Show X on Breach: Display marker when level is breached
- Show Dot at Origin: Display marker at level formation point
- Line Width: Thickness of level lines (1-5)
- Line Extension: How many bars forward to project (1-24)
- Max Days to Track: Historical lookback period (5-200 days)
**DOL Settings Group:**
- Cluster Tolerance %: Price range to group DOLs (0.1-2.0%)
- Show Price on Labels: Display actual price value on labels
- Backtest Mode: Only show recent labels for clean historical analysis
- Labels Lookback: Number of bars to show labels when backtesting (10-500)
**Info Box Group:**
- Show Info Box: Toggle info panel visibility
**DOL Toggles Group:**
- Show AI DOL: Display smart auto-selected primary target
- Show 1HR DOL: Display 1-hour timeframe DOLs
- Show 4HR DOL: Display 4-hour timeframe DOLs
- Show Daily DOL: Display daily timeframe DOLs
- Show Weekly DOL: Display weekly timeframe DOLs
**Advanced Group:**
- Manual Mode: Simplified display showing only daily high/low clusters
How to Use This Indicator
Educational Application
This indicator is intended for educational purposes to help traders:
1. **Understand Liquidity Concepts:** Visualize where unfilled orders may exist
2. **Identify Key Levels:** See where price may be drawn to
3. **Analyze Market Structure:** Understand how price interacts with liquidity
4. **Study Multi-Timeframe Alignment:** Observe when multiple timeframes agree
5. **Learn ICT Concepts:** Apply liquidity theory in practice
Interpretation Guidelines
**BID PRESSURE (Flow):**
When lows are being swept more than highs, it suggests:
- Sell-side liquidity being taken
- Potential for upward move to unfilled buy-side liquidity
- Market may be clearing the way for a bullish move
**OFFER PRESSURE (Flow):**
When highs are being swept more than lows, it suggests:
- Buy-side liquidity being taken
- Potential for downward move to unfilled sell-side liquidity
- Market may be clearing the way for a bearish move
**Confidence Scores:**
- 90-100%: Very high probability zone (strong cluster, recent, aligned)
- 80-89%: High probability zone (good cluster, relatively recent)
- 70-79%: Moderate probability zone (decent cluster or older)
- 60-69%: Lower probability zone (small cluster or very old)
- Below 60%: Weak zone (minimal confluence)
**Timeframe Analysis:**
- All timeframes LONG: Strong bullish alignment
- All timeframes SHORT: Strong bearish alignment
- Mixed: Conflicting signals, exercise caution
- Higher timeframes (D1, W1) carry more weight than lower (1H, 4H)
**DIRECTIONAL Indicator:**
- BULLISH: Overall bias suggests upward movement toward buy-side DOLs
- BEARISH: Overall bias suggests downward movement toward sell-side DOLs
- NEUTRAL: No clear directional bias, conflicting signals
Practical Application Examples
**Example 1: Bullish Setup**
```
Flow: BID PRESSURE (lows being swept)
P1: 27,500 (price above current market)
D1: LONG 27,500
W1: LONG 27,650
DIRECTIONAL: BULLISH
```
Interpretation: Price has cleared sell-side liquidity. High confidence buy-side DOL at 27,500. Daily and Weekly timeframes aligned bullish. Watch for move toward 27,500 target.
**Example 2: Bearish Setup**
```
Flow: OFFER PRESSURE (highs being swept)
P1: 26,200 (price below current market)
D1: SHORT 26,200
W1: SHORT 26,100
DIRECTIONAL: BEARISH
```
Interpretation: Price has cleared buy-side liquidity. High confidence sell-side DOL at 26,200. Daily and Weekly timeframes aligned bearish. Watch for move toward 26,200 target.
**Example 3: Mixed Signals - Wait**
```
Flow: BID PRESSURE
P1: 26,800
D1: LONG 27,000
W1: SHORT 26,200
DIRECTIONAL: NEUTRAL
```
Interpretation: Conflicting signals. Flow suggests up, but Weekly bias is down. Confidence scores moderate. Better to wait for clarity.
Important Considerations
This Indicator Does NOT:
- Predict the future
- Guarantee profitable trades
- Provide buy/sell signals
- Replace proper risk management
- Work in isolation without other analysis
This Indicator DOES:
- Visualize liquidity concepts
- Identify potential target zones
- Show timeframe alignment
- Calculate objective confidence scores
- Help understand market structure
Proper Usage:
1. Use as one component of a complete trading strategy
2. Combine with price action analysis
3. Confirm with other technical indicators
4. Consider fundamental factors
5. Always use proper risk management
6. Backtest any strategy before live trading
Risk Disclaimer
**FOR EDUCATIONAL PURPOSES ONLY**
This indicator is for educational purposes only. Trading financial markets involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions.
**Important Limitations:**
- No indicator is 100% accurate, including the AI selection
- The "AI" is an automated algorithm, not predictive artificial intelligence
- DOL levels can be swept and price can continue in the same direction
- Confidence scores are mathematical calculations, not predictions or probabilities of success
- High confidence does not mean guaranteed profit
- Markets can remain irrational longer than you can remain solvent
- Always use stop losses and proper position sizing
**Understanding the AI Component:**
The AI auto-selection feature uses a fixed mathematical formula to rank DOLs. It does not:
- Predict where price will go
- Learn from past performance
- Adapt to market conditions
- Guarantee any level of accuracy
The confidence score represents the mathematical strength of a liquidity cluster based on objective factors (cluster size, recency, timeframe alignment), NOT a probability of the trade succeeding.
**Risk Warning:**
Trading is risky. Most traders lose money. This indicator cannot change that fundamental reality. Use it as an educational tool to understand market structure, not as a trading signal or system.
Technical Requirements
- **Timeframe:** Best used on 1-hour charts (required for accurate daily level tracking)
- **Markets:** Works on any market (forex, crypto, stocks, futures, indices)
- **Updates:** Real-time calculation on each bar close
- **Resources:** Uses max 500 lines and 500 labels (TradingView limits)
Backtesting Features
The indicator includes "Backtest Mode" to keep historical charts clean:
- When enabled, only shows labels from recent bars
- Adjustable lookback period (10-500 bars)
- All lines remain visible
- Helps review past setups without clutter
To use:
1. Enable "Backtest Mode" in settings
2. Adjust "Labels Lookback" to desired period
3. Review historical price action
4. Disable for live trading
Credits and Methodology
This indicator implements concepts from:
- ICT (Inner Circle Trader) liquidity theory
- Smart Money Concepts (SMC)
- Order flow analysis
- Multi-timeframe analysis principles
The clustering algorithm, confidence scoring, and timeframe synthesis are original implementations designed to quantify and visualize these concepts.
Version History
**v1.0 - Initial Release**
- Multi-timeframe DOL detection
- Confidence scoring system
- Info box with liquidity metrics
- Backtest mode for clean charts
- Black/white professional theme
Support and Updates
For questions, feedback, or suggestions, please use the TradingView comments section. Updates and improvements will be released as needed based on user feedback and market evolution.
**Remember:** This is an educational tool. Successful trading requires knowledge, discipline, risk management, and continuous learning. Use this indicator to enhance your understanding of market structure and liquidity, not as a standalone trading system.
BOS TRADER [v 1.0] [Influxum]The name of the tool, BOS Trader, comes from the abbreviation BOS, which stands for Break Of Structure. In simple terms, this tool identifies situations where a change in market structure occurs after liquidity has been grabbed. Following the structural change, it looks for a point where the balance between buyers and sellers will be tested, potentially continuing the price movement in the direction of the structural break.
The goal of this tool is to identify areas where a trader can look for potential entry opportunities based on their entry rules and filters. In our own research, we found that while this tool is not a standalone strategy, it provides a statistical advantage that stems from the nature of the market itself. If you expect the market to reverse at a certain price level against a short-term, medium-term, or long-term trend, that reversal must logically begin with a change in structure – i.e., its break. BOS Trader then highlights the zone where you can expect a strong reaction from traders speculating on the continuation of price in the direction of the break.
Another important piece of the puzzle is the concept of liquidity. Liquidity grabs are generally considered by traders to be events that can trigger market direction changes. That's why BOS Trader is complemented with multiple ways to identify liquidity in the market from a Price Action perspective. We have explored the liquidity concept in depth in our other tools – the Liquidity Tool and Liquidity Strategy Tester – so we won’t go into too much detail on liquidity settings here.
🟪 Pivots
Liquidity can be found beyond pivot extremes – the highest candles in a series of candles. The pivot liquidity setting specifies how many candles must be before and after the pivot candle with a lower high for a pivot high or a higher low for a pivot low. A pivot high is the local highest point of the last 31 candles (15 before the pivot candle, the pivot candle itself, and 15 after). Another option is to set the time period in which the pivot extreme must occur. For example, you can differentiate between pivot highs of the Asian or London session.
🟪 % Percent Change
This setting is based on the well-known Zig Zag indicator and confirms swing highs or swing lows when there is a certain percentage change in price. This helps filter out noise that can occur when the market consolidates and randomly creates pivot highs or lows that aren’t significant.
🟪 Session High/Low
Many popular strategies are based on liquidity defined as the price range of a specific trading session. This doesn't have to be London, Asia, or New York sessions, but could be, for instance, the first hour of the New York session, and so on.
🟪 Day High/Low, Week High/Low, Month High/Low
As the name suggests, liquidity is often defined by the high/low of the previous day, week, or month. These price levels are watched by many market participants, and it's reasonable to expect reactions at these levels. That’s why we included this option in the BOS tool.
Tip for Traders
To avoid common issues with setting the correct session time, we have added the BG option to the tool – the ability to display a background for the configured trading session. This makes it easy to verify that your trading session is set correctly in relation to your time zone.
Delete grabbed liquidity
If a liquidity level is breached by price, it becomes invalid. For those who prefer to keep their charts clean and uncluttered, there is an option to delete grabbed liquidity. This way, only untraded, valid liquidity lines will be visible on the chart.
Bars after liquidity grab
A liquidity grab should be a significant event that triggers a reaction from market participants. To ensure this is a real response to liquidity rather than random market behavior, we added a time test to the BOS tool. A structural break must occur within a specified time after the liquidity grab. You can define this time in the tool as the number of bars after which the structural break is still considered valid following the liquidity grab.
🟪 AOI (Area of Interest) Settings
Initially, it's important to note that there are two main options for setting the behavior of the AOI. The first option is to fix its duration by the number of bars – Duration, and the second is to keep the AOI valid until it is traded through – Extended.
Duration
Since we expect a quick reaction to the liquidity grab, we also expect a fast pullback to the AOI and a swift response of traders. Our research has shown that the strongest reactions typically occur within a maximum of 15 bars from the formation of the AOI (fractally across timeframes). Therefore, this value is set as the default. However, we recommend considering not just the speed of the reaction but also its intensity. After the set number of bars, the AOI stops extending further.
Extended
We have noticed that price has a tendency to return to the AOI even after a longer period and react again. For this reason, we included the option in the BOS tool to extend the AOI into the future, with the ability to freely adjust the Max AOI Length.
🟪 AOI Size Mode
There are two options for setting the size of the AOI. Either it can be calculated as a percentage of the swing size (% of swing) in which the structural break occurred (the default setting is 30%), or you can set a different concept for the AOI size. For example, the well-known Optimal Trade Entry model. Custom values can be set in the FIBO Levels option, where you can define either preferred Fibonacci values or values based on your own criteria.
🟪 Trading Session (signals + alerts + visibility)
The main goal of our tools is to make it easier for traders to identify patterns and opportunities in the market and allow them to be alerted to their occurrence. The time for AOI plotting after a liquidity grab is combined into a single Trading Session function. This controls both the AOI plotting and when the tool will send alerts. All of this is aimed at helping traders avoid spending the entire day in front of their monitors, waiting for trading opportunities. Here, too, you can use the BG feature to plot a background on the chart showing the current session.
🟪 Trading within session range
We found that some traders have difficulty navigating the many AOIs plotted during times when the market consolidates and creates numerous false breakouts. Therefore, we included an option in the BOS tool to track only structural changes at the price extremes of the current day and trading session. The tool will not plot structural changes for internal liquidity grabs (within the session range), but only for external liquidity grabs (highest highs and lowest lows of the session or liquidity from previous days).
Visuals
The BOS tool is, of course, supplemented with the option to customize the appearance of all its components according to your preferences.
AR-Session-Orb-HTF High/LowThis indicator is built for intraday model execution around liquidity grabs, session timing, and higher-timeframe draw-on-liquidity. It maps out sessions, ICT killzones, Session opening ranges (including the US 09:30 cash open), a daily NY “TD Open” line (00:00 → NY close), and key highs/lows from higher timeframes directly onto any lower timeframe chart (down to 1 minute).
________________________________________
1. Sessions (Asia / London / New York)
• Highlights the 3 main sessions with colored boxes:
• Asia
• London
• New York
• Default session times are set in New York local time:
• Asia: 18:00–02:00
• London: 03:00–12:00
• New York: 08:00–17:00
• You can change these times in the settings.
• Each box automatically expands as the session progresses.
Why it matters: these windows show you where liquidity usually builds, where the day “hands off” from Asia → London → NY, and when expansion/displacement typically happens.
________________________________________
2. ICT Killzones
The script includes 4 configurable killzones (NY local by default):
• Asia late session: 20:00–00:00
• London killzone: 02:00–05:00
• New York AM: 07:00–10:00
• New York Midday: 10:00–12:00
For each killzone you can:
• toggle on/off
• adjust the time window
• pick colors
This makes it easy to see when price is trading inside a high-probability delivery period, so you can line it up with liquidity above/below the session or OR.
________________________________________
3. Opening Range Levels
The indicator captures the high and low of the first X minutes (default 15) of each important window and projects those levels as horizontal lines.
It does this for:
• Asia Open Range
• London Open Range
• New York Open Range (08:00)
• NY 09:30 Cash-Open Range
• (in the original idea: NY mid / second NY window)
Behavior:
• Asia OR → after the first X minutes of Asia, the high/low are projected across the rest of the trading day.
• London OR → taken from the London start, but extended only while London is active.
• NY OR (08:00) → taken from the start of the NY session and extended only during NY.
• NY 09:30 OR → this one is special. At exactly 09:30 (cash open) the script starts a second, independent OR for that day, using your chosen length (e.g. 15 minutes). When the window finishes, it freezes the 09:30 high and low and projects them horizontally all the way to the NY session end. You can style it separately (color, labels). This gives you a clean “cash-open dealing range” to watch for sweeps, fake-outs and continuations.
You can:
• choose the range length (1–60 minutes for 09:30, 1–30 for the others)
• show/hide each OR
• color each OR
• show labels such as “Asia OR High”, “Lon OR Low”, “NY 09:30 High”, etc.
• control line padding so labels don’t print on top of the candle
These ORs often become obvious liquidity pools, fail-break zones, or continuation triggers.
________________________________________
4. NY TD Open Line (Daily 00:00)
On every trading day the script also plots a “TD” structure for New York:
• at 00:00 NY time it draws a vertical dashed line to mark the day’s start
• it records that day’s open price
• it then projects a horizontal line from 00:00 → all the way to NY session close (default 17:00)
• the horizontal line is labeled e.g. “NY TD Open”
How to use it:
• see instantly where current price is vs the daily open
• combine with 09:30 OR to know if cash open is opening above/below the day’s open
• good for intraday bias (above = bullish day structure, below = bearish day structure)
• nice anchor when you go down to 1m/3m
You can toggle the TD feature on/off and change its colors.
________________________________________
5. Previous Week High / Low
• Plots last week’s high and low on any timeframe
• Drawn as dashed lines with padding (so they don’t run to infinity)
• Each level is labeled (default “PW High” / “PW Low”)
These are classic weekly liquidity magnets and very useful when London/NY is expanding into an old weekly extreme.
________________________________________
6. Monthly High / Low
The script plots both:
• Previous month high/low
• Current month high/low (live)
Defaults:
• previous month → dashed + purple
• current month → solid + blue
You can change:
• line colors
• label text & colors
• how far the line should extend (bars span)
This gives you higher-TF liquidity targets on your intraday chart without switching to M or W.
________________________________________
7. 4H High / Low (Intra-session Liquidity Map)
On timeframes up to 4H, the script also plots:
• previous 4H high/low
• current 4H high/low
Important design choice: they only live inside their own 4H window.
• the previous 4H range is shown only over the previous 4H time span
• the current 4H range is shown only over the current 4H candle
That means you don’t get messy, stretched 4H lines across the whole day — only where they actually apply. This is super useful for London/NY raids on 4H highs/lows.
________________________________________
8. Customization / Inputs
Almost everything is editable:
• session windows + colors
• killzone windows + colors
• opening-range length
• ON/OFF per OR (Asia, London, NY 08:00, NY 09:30)
• label text, size, bg color, text color
• HTF line length (weekly / monthly)
• TD 00:00 ON/OFF + colors
• line end padding so labels don’t sit on the right edge
The idea is to give you structure, not signals.
________________________________________
How to Use
1. Start from the monthly / weekly / previous week levels to see where price “wants” to go.
2. Drop into the active session box / killzone to know when to pay attention.
3. Trade around opening-range highs/lows — especially the NY 09:30 OR — and look for liquidity sweeps.
4. Check where price is relative to the NY TD Open (00:00) to confirm intraday bias.
5. Refine entries using the 4H highs/lows that fall inside that session.
Result: you get a top-down liquidity map + intraday timing tool, all on one chart.
________________________________________
Notes
• All times are interpreted in the chart/session timezone — keep your chart on NY session if you want the defaults to match the description.
• TradingView has drawing limits; on very low timeframes far back in history, old drawings may recycle.
• Because 09:30 and TD are drawn every day, it’s normal to see more labels the further right you scroll.
________________________________________
Disclaimer
This script is for educational and charting purposes only.
It does not generate trade signals, manage risk, or guarantee profitability.
Trading involves risk — always do your own analysis.
Special Thanks to Sabo & Hive Community
Nov 17
Release Notes
This indicator is built for intraday model execution around liquidity grabs, session timing, and higher-timeframe draw-on-liquidity. It maps out sessions, killzones, opening ranges (including the US 09:30 cash open), a daily NY “TD Open” line (00:00 → NY close), and key highs/lows from higher timeframes directly onto any lower timeframe chart (down to 1 minute).
________________________________________
1. Sessions (Asia / London / New York)
• Highlights the 3 main sessions with colored boxes:
• Asia
• London
• New York
• Default session times are set in New York local time:
• Asia: 18:00–02:00
• London: 03:00–12:00
• New York: 08:00–17:00
• You can change these times in the settings.
• Each box automatically expands as the session progresses.
Why it matters: these windows show you where liquidity usually builds, where the day “hands off” from Asia → London → NY, and when expansion/displacement typically happens.
________________________________________
2. ICT Killzones
The script includes 4 configurable killzones (NY local by default):
• Asia late session: 20:00–00:00
• London killzone: 02:00–05:00
• New York AM: 07:00–10:00
• New York Midday: 10:00–12:00
For each killzone you can:
• toggle on/off
• adjust the time window
• pick colors
This makes it easy to see when price is trading inside a high-probability delivery period, so you can line it up with liquidity above/below the session or OR.
________________________________________
3. Opening Range Levels
The indicator captures the high and low of the first X minutes (default 15) of each important window and projects those levels as horizontal lines.
It does this for:
• Asia Open Range
• London Open Range
• New York Open Range (08:00)
• NY 09:30 Cash-Open Range
• (in the original idea: NY mid / second NY window)
Behavior:
• Asia OR → after the first X minutes of Asia, the high/low are projected across the rest of the trading day.
• London OR → taken from the London start, but extended only while London is active.
• NY OR (08:00) → taken from the start of the NY session and extended only during NY.
• NY 09:30 OR → this one is special. At exactly 09:30 (cash open) the script starts a second, independent OR for that day, using your chosen length (e.g. 15 minutes). When the window finishes, it freezes the 09:30 high and low and projects them horizontally all the way to the NY session end. You can style it separately (color, labels). This gives you a clean “cash-open dealing range” to watch for sweeps, fake-outs and continuations.
You can:
• choose the range length (1–60 minutes for 09:30, 1–30 for the others)
• show/hide each OR
• color each OR
• show labels such as “Asia OR High”, “Lon OR Low”, “NY 09:30 High”, etc.
• control line padding so labels don’t print on top of the candle
These ORs often become obvious liquidity pools, fail-break zones, or continuation triggers.
________________________________________
4. NY TD Open Line (Daily 00:00)
On every trading day the script also plots a “TD” structure for New York:
• at 00:00 NY time it draws a vertical dashed line to mark the day’s start
• it records that day’s open price
• it then projects a horizontal line from 00:00 → all the way to NY session close (default 17:00)
• the horizontal line is labeled e.g. “NY TD Open”
How to use it:
• see instantly where current price is vs the daily open
• combine with 09:30 OR to know if cash open is opening above/below the day’s open
• good for intraday bias (above = bullish day structure, below = bearish day structure)
• nice anchor when you go down to 1m/3m
You can toggle the TD feature on/off and change its colors.
________________________________________
5. Previous Week High / Low
• Plots last week’s high and low on any timeframe
• Drawn as dashed lines with padding (so they don’t run to infinity)
• Each level is labeled (default “PW High” / “PW Low”)
These are classic weekly liquidity magnets and very useful when London/NY is expanding into an old weekly extreme.
________________________________________
6. Monthly High / Low
The script plots both:
• Previous month high/low
• Current month high/low (live)
Defaults:
• previous month → dashed + purple
• current month → solid + blue
You can change:
• line colors
• label text & colors
• how far the line should extend (bars span)
This gives you higher-TF liquidity targets on your intraday chart without switching to M or W.
________________________________________
7. 4H High / Low (Intra-session Liquidity Map)
On timeframes up to 4H, the script also plots:
• previous 4H high/low
• current 4H high/low
Important design choice: they only live inside their own 4H window.
• the previous 4H range is shown only over the previous 4H time span
• the current 4H range is shown only over the current 4H candle
That means you don’t get messy, stretched 4H lines across the whole day — only where they actually apply. This is super useful for London/NY raids on 4H highs/lows.
________________________________________
8. Customization / Inputs
Almost everything is editable:
• session windows + colors
• killzone windows + colors
• opening-range length
• ON/OFF per OR (Asia, London, NY 08:00, NY 09:30)
• label text, size, bg color, text color
• HTF line length (weekly / monthly)
• TD 00:00 ON/OFF + colors
• line end padding so labels don’t sit on the right edge
The idea is to give you structure, not signals.
________________________________________
How to Use
1. Start from the monthly / weekly / previous week levels to see where price “wants” to go.
2. Drop into the active session box / killzone to know when to pay attention.
3. Trade around opening-range highs/lows — especially the NY 09:30 OR — and look for liquidity sweeps.
4. Check where price is relative to the NY TD Open (00:00) to confirm intraday bias.
5. Refine entries using the 4H highs/lows that fall inside that session.
Result: you get a top-down liquidity map + intraday timing tool, all on one chart.
________________________________________
Notes
• All times are interpreted in the chart/session timezone — keep your chart on NY session if you want the defaults to match the description.
• TradingView has drawing limits; on very low timeframes far back in history, old drawings may recycle.
• Because 09:30 and TD are drawn every day, it’s normal to see more labels the further right you scroll.
________________________________________
Disclaimer
This script is for educational and charting purposes only.
It does not generate trade signals, manage risk, or guarantee profitability.
Trading involves risk — always do your own analysis.
Special Thanks to Sabo & Hive Community
Algorithm Predator - ProAlgorithm Predator - Pro: Advanced Multi-Agent Reinforcement Learning Trading System
Algorithm Predator - Pro combines four specialized market microstructure agents with a state-of-the-art reinforcement learning framework . Unlike traditional indicator mashups, this system implements genuine machine learning to automatically discover which detection strategies work best in current market conditions and adapts continuously without manual intervention.
Core Innovation: Rather than forcing traders to interpret conflicting signals, this system uses 15 different multi-armed bandit algorithms and a full reinforcement learning stack (Q-Learning, TD(λ) with eligibility traces, and Policy Gradient with REINFORCE) to learn optimal agent selection policies. The result is a self-improving system that gets smarter with every trade.
Target Users: Swing traders, day traders, and algorithmic traders seeking systematic signal generation with mathematical rigor. Suitable for stocks, forex, crypto, and futures on liquid instruments (>100k daily volume).
Why These Components Are Combined
The Fundamental Problem
No single indicator works consistently across all market regimes. What works in trending markets fails in ranging conditions. Traditional solutions force traders to manually switch indicators (slow, error-prone) or interpret all signals simultaneously (cognitive overload).
This system solves the problem through automated meta-learning: Deploy multiple specialized agents designed for specific market microstructure conditions, then use reinforcement learning to discover which agent (or combination) performs best in real-time.
Why These Specific Four Agents?
The four agents provide orthogonal failure mode coverage —each agent's weakness is another's strength:
Spoofing Detector - Optimal in consolidation/manipulation; fails in trending markets (hedged by Exhaustion Detector)
Exhaustion Detector - Optimal at trend climax; fails in range-bound markets (hedged by Liquidity Void)
Liquidity Void - Optimal pre-breakout compression; fails in established trends (hedged by Mean Reversion)
Mean Reversion - Optimal in low volatility; fails in strong trends (hedged by Spoofing Detector)
This creates complete market state coverage where at least one agent should perform well in any condition. The bandit system identifies which one without human intervention.
Why Reinforcement Learning vs. Simple Voting?
Traditional consensus systems have fatal flaws: equal weighting assumes all agents are equally reliable (false), static thresholds don't adapt, and no learning means past mistakes repeat indefinitely.
Reinforcement learning solves this through the exploration-exploitation tradeoff: Continuously test underused agents (exploration) while primarily relying on proven winners (exploitation). Over time, the system builds a probability distribution over agent quality reflecting actual market performance.
Mathematical Foundation: Multi-armed bandit problem from probability theory, where each agent is an "arm" with unknown reward distribution. The goal is to maximize cumulative reward while efficiently learning each arm's true quality.
The Four Trading Agents: Technical Explanation
Agent 1: 🎭 Spoofing Detector (Institutional Manipulation Detection)
Theoretical Basis: Market microstructure theory on order flow toxicity and information asymmetry. Based on research by Easley, López de Prado, and O'Hara on high-frequency trading manipulation.
What It Detects:
1. Iceberg Orders (Hidden Liquidity Absorption)
Method: Monitors volume spikes (>2.5× 20-period average) with minimal price movement (<0.3× ATR)
Formula: score += (close > open ? -2.5 : 2.5) when volume > vol_avg × 2.5 AND abs(close - open) / ATR < 0.3
Interpretation: Large volume without price movement indicates institutional absorption (buying) or distribution (selling) using hidden orders
Signal Logic: Contrarian—fade false breakouts caused by institutional manipulation
2. Spoofing Patterns (Fake Liquidity via Layering)
Method: Analyzes candlestick wick-to-body ratios during volume spikes
Formula: if upper_wick > body × 2 AND volume_spike: score += 2.0
Mechanism: Spoofing creates large wicks (orders pulled before execution) with volume evidence
Signal Logic: Wick direction indicates trapped participants; trade against the failed move
3. Post-Manipulation Reversals
Method: Tracks volume decay after manipulation events
Formula: if volume > vol_avg × 3 AND volume / volume < 0.3: score += (close > open ? -1.5 : 1.5)
Interpretation: Sharp volume drop after manipulation indicates exhaustion of manipulative orders
Why It Works: Institutional manipulation creates detectable microstructure anomalies. While retail traders see "mysterious reversals," this agent quantifies the order flow patterns causing them.
Parameter: i_spoof (sensitivity 0.5-2.0) - Controls detection threshold
Best Markets: Consolidations before breakouts, London/NY overlap windows, stocks with institutional ownership >70%
Agent 2: ⚡ Exhaustion Detector (Momentum Failure Analysis)
Theoretical Basis: Technical analysis divergence theory combined with VPIN reversals from market microstructure literature.
What It Detects:
1. Price-RSI Divergence (Momentum Deceleration)
Method: Compares 5-bar price ROC against RSI change
Formula: if price_roc > 5% AND rsi_current < rsi : score += 1.8
Mathematics: Second derivative detecting inflection points
Signal Logic: When price makes higher highs but momentum makes lower highs, expect mean reversion
2. Volume Exhaustion (Buying/Selling Climax)
Method: Identifies strong price moves (>5% ROC) with declining volume (<-20% volume ROC)
Formula: if price_roc > 5 AND vol_roc < -20: score += 2.5
Interpretation: Price extension without volume support indicates retail chasing while institutions exit
3. Momentum Deceleration (Acceleration Analysis)
Method: Compares recent 3-bar momentum to prior 3-bar momentum
Formula: deceleration = abs(mom1) < abs(mom2) × 0.5 where momentum significant (> ATR)
Signal Logic: When rate of price change decelerates significantly, anticipate directional shift
Why It Works: Momentum is lagging, but momentum divergence is leading. By comparing momentum's rate of change to price, this agent detects "weakening conviction" before reversals become obvious.
Parameter: i_momentum (sensitivity 0.5-2.0)
Best Markets: Strong trends reaching climax, parabolic moves, instruments with high retail participation
Agent 3: 💧 Liquidity Void Detector (Breakout Anticipation)
Theoretical Basis: Market liquidity theory and order book dynamics. Based on research into "liquidity holes" and volatility compression preceding expansion.
What It Detects:
1. Bollinger Band Squeeze (Volatility Compression)
Method: Monitors Bollinger Band width relative to 50-period average
Formula: bb_width = (upper_band - lower_band) / middle_band; triggers when < 0.6× average
Mathematical Foundation: Regression to the mean—low volatility precedes high volatility
Signal Logic: When volatility compresses AND cumulative delta shows directional bias, anticipate breakout
2. Volume Profile Gaps (Thin Liquidity Zones)
Method: Identifies sharp volume transitions indicating few limit orders
Formula: if volume < vol_avg × 0.5 AND volume < vol_avg × 0.5 AND volume > vol_avg × 1.5
Interpretation: Sudden volume drop after spike indicates price moved through order book to low-opposition area
Signal Logic: Price accelerates through low-liquidity zones
3. Stop Hunts (Liquidity Grabs Before Reversals)
Method: Detects new 20-bar highs/lows with immediate reversal and rejection wick
Formula: if new_high AND close < high - (high - low) × 0.6: score += 3.0
Mechanism: Market makers push price to trigger stop-loss clusters, then reverse
Signal Logic: Enter reversal after stop-hunt completes
Why It Works: Order book theory shows price moves fastest through zones with minimal liquidity. By identifying these zones before major moves, this agent provides early entry for high-reward breakouts.
Parameter: i_liquidity (sensitivity 0.5-2.0)
Best Markets: Range-bound pre-breakout setups, volatility compression zones, instruments prone to gap moves
Agent 4: 📊 Mean Reversion (Statistical Arbitrage Engine)
Theoretical Basis: Statistical arbitrage theory, Ornstein-Uhlenbeck mean-reverting processes, and pairs trading methodology applied to single instruments.
What It Detects:
1. Z-Score Extremes (Standard Deviation Analysis)
Method: Calculates price distance from 20-period and 50-period SMAs in standard deviation units
Formula: zscore_20 = (close - SMA20) / StdDev(50)
Statistical Interpretation: Z-score >2.0 means price is 2 standard deviations above mean (97.5th percentile)
Trigger Logic: if abs(zscore_20) > 2.0: score += zscore_20 > 0 ? -1.5 : 1.5 (fade extremes)
2. Ornstein-Uhlenbeck Process (Mean-Reverting Stochastic Model)
Method: Models price as mean-reverting stochastic process: dx = θ(μ - x)dt + σdW
Implementation: Calculates spread = close - SMA20, then z-score of spread vs. spread distribution
Formula: ou_signal = (spread - spread_mean) / spread_std
Interpretation: Measures "tension" pulling price back to equilibrium
3. Correlation Breakdown (Regime Change Detection)
Method: Compares 50-period price-volume correlation to 10-period correlation
Formula: corr_breakdown = abs(typical_corr - recent_corr) > 0.5
Enhancement: if corr_breakdown AND abs(zscore_20) > 1.0: score += zscore_20 > 0 ? -1.2 : 1.2
Why It Works: Mean reversion is the oldest quantitative strategy (1970s pairs trading at Morgan Stanley). While simple, it remains effective because markets exhibit periodic equilibrium-seeking behavior. This agent applies rigorous statistical testing to identify when mean reversion probability is highest.
Parameter: i_statarb (sensitivity 0.5-2.0)
Best Markets: Range-bound instruments, low-volatility periods (VIX <15), algo-dominated markets (forex majors, index futures)
Multi-Armed Bandit System: 15 Algorithms Explained
What Is a Multi-Armed Bandit Problem?
Origin: Named after slot machines ("one-armed bandits"). Imagine facing multiple slot machines, each with unknown payout rates. How do you maximize winnings?
Formal Definition: K arms (agents), each with unknown reward distribution with mean μᵢ. Goal: Maximize cumulative reward over T trials. Challenge: Balance exploration (trying uncertain arms to learn quality) vs. exploitation (using known-best arm for immediate reward).
Trading Application: Each agent is an "arm." After each trade, receive reward (P&L). Must decide which agent to trust for next signal.
Algorithm Categories
Bayesian Approaches (probabilistic, optimal for stationary environments):
Thompson Sampling
Bootstrapped Thompson Sampling
Discounted Thompson Sampling
Frequentist Approaches (confidence intervals, deterministic):
UCB1
UCB1-Tuned
KL-UCB
SW-UCB (Sliding Window)
D-UCB (Discounted)
Adversarial Approaches (robust to non-stationary environments):
EXP3-IX
Hedge
FPL-Gumbel
Reinforcement Learning Approaches (leverage learned state-action values):
Q-Values (from Q-Learning)
Policy Network (from Policy Gradient)
Simple Baseline:
Epsilon-Greedy
Softmax
Key Algorithm Details
Thompson Sampling (DEFAULT - RECOMMENDED)
Theoretical Foundation: Bayesian decision theory with conjugate priors. Published by Thompson (1933), rediscovered for bandits by Chapelle & Li (2011).
How It Works:
Model each agent's reward distribution as Beta(α, β) where α = wins, β = losses
Each step, sample from each agent's beta distribution: θᵢ ~ Beta(αᵢ, βᵢ)
Select agent with highest sample: argmaxᵢ θᵢ
Update winner's distribution after observing outcome
Mathematical Properties:
Optimality: Achieves logarithmic regret O(K log T) (proven optimal)
Bayesian: Maintains probability distribution over true arm means
Automatic Balance: High uncertainty → more exploration; high certainty → exploitation
⚠️ CRITICAL APPROXIMATION: This is a pseudo-random approximation of true Thompson Sampling. True implementation requires random number generation from beta distributions, which Pine Script doesn't provide. This version uses Box-Muller transform with market data (price/volume decimal digits) as entropy source. While not mathematically pure, it maintains core exploration-exploitation balance and learns agent preferences effectively.
When To Use: Best all-around choice. Handles non-stationary markets reasonably well, balances exploration naturally, highly sample-efficient.
UCB1 (Upper Confidence Bound)
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Interpretation: First term (exploitation) + second term (exploration bonus for less-tested arms)
Mathematical Properties:
Deterministic : Always selects same arm given same state
Regret Bound: O(K log T) — same optimality as Thompson Sampling
Interpretable: Can visualize confidence intervals
When To Use: Prefer deterministic behavior, want to visualize uncertainty, stable markets
EXP3-IX (Exponential Weights - Adversarial)
Theoretical Foundation: Adversarial bandit algorithm. Assumes environment may be actively hostile (worst-case analysis).
How It Works:
Maintain exponential weights: w_i = exp(η × cumulative_reward_i)
Select agent with probability proportional to weights: p_i = (1-γ)w_i/Σw_j + γ/K
After outcome, update with importance weighting: estimated_reward = observed_reward / p_i
Mathematical Properties:
Adversarial Regret: O(sqrt(TK log K)) even if environment is adversarial
No Assumptions: Doesn't assume stationary or stochastic reward distributions
Robust: Works even when optimal arm changes continuously
When To Use: Extreme non-stationarity, don't trust reward distribution assumptions, want robustness over efficiency
KL-UCB (Kullback-Leibler Upper Confidence Bound)
Theoretical Foundation: Uses KL-divergence instead of Hoeffding bounds. Tighter confidence intervals.
Formula (conceptual): Find largest q such that: n × KL(p||q) ≤ ln(t) + 3×ln(ln(t))
Mathematical Properties:
Tighter Bounds: KL-divergence adapts to reward distribution shape
Asymptotically Optimal: Better constant factors than UCB1
Computationally Intensive: Requires iterative binary search (15 iterations)
When To Use: Maximum sample efficiency needed, willing to pay computational cost, long-term trading (>500 bars)
Q-Values & Policy Network (RL-Based Selection)
Unique Feature: Instead of treating agents as black boxes with scalar rewards, these algorithms leverage the full RL state representation .
Q-Values Selection:
Uses learned Q-values: Q(state, agent_i) from Q-Learning
Selects agent via softmax over Q-values for current market state
Advantage: Selects based on state-conditional quality (which agent works best in THIS market state)
Policy Network Selection:
Uses neural network policy: π(agent | state, θ) from Policy Gradient
Direct policy over agents given market features
Advantage: Can learn non-linear relationships between market features and agent quality
When To Use: After 200+ RL updates (Q-Values) or 500+ updates (Policy Network) when models converged
Machine Learning & Reinforcement Learning Stack
Why Both Bandits AND Reinforcement Learning?
Critical Distinction:
Bandits treat agents as contextless black boxes: "Agent 2 has 60% win rate"
Reinforcement Learning adds state context: "Agent 2 has 60% win rate WHEN trend_score > 2 and RSI < 40"
Power of Combination: Bandits provide fast initial learning with minimal assumptions. RL provides state-dependent policies for superior long-term performance.
Component 1: Q-Learning (Value-Based RL)
Algorithm: Temporal Difference Learning with Bellman equation.
State Space: 54 discrete states formed from:
trend_state = {0: bearish, 1: neutral, 2: bullish} (3 values)
volatility_state = {0: low, 1: normal, 2: high} (3 values)
RSI_state = {0: oversold, 1: neutral, 2: overbought} (3 values)
volume_state = {0: low, 1: high} (2 values)
Total states: 3 × 3 × 3 × 2 = 54 states
Action Space: 5 actions (No trade, Agent 1, Agent 2, Agent 3, Agent 4)
Total state-action pairs: 54 × 5 = 270 Q-values
Bellman Equation:
Q(s,a) ← Q(s,a) + α ×
Parameters:
α (learning rate): 0.01-0.50, default 0.10 - Controls step size for updates
γ (discount factor): 0.80-0.99, default 0.95 - Values future rewards
ε (exploration): 0.01-0.30, default 0.10 - Probability of random action
Update Mechanism:
Position opens with state s, action a (selected agent)
Every bar position is open: Calculate floating P&L → scale to reward
Perform online TD update
When position closes: Perform terminal update with final reward
Gradient Clipping: TD errors clipped to ; Q-values clipped to for stability.
Why It Works: Q-Learning learns "quality" of each agent in each market state through trial and error. Over time, builds complete state-action value function enabling optimal state-dependent agent selection.
Component 2: TD(λ) Learning (Temporal Difference with Eligibility Traces)
Enhancement Over Basic Q-Learning: Credit assignment across multiple time steps.
The Problem TD(λ) Solves:
Position opens at t=0
Market moves favorably at t=3
Position closes at t=8
Question: Which earlier decisions contributed to success?
Basic Q-Learning: Only updates Q(s₈, a₈) ← reward
TD(λ): Updates ALL visited state-action pairs with decayed credit
Eligibility Trace Formula:
e(s,a) ← γ × λ × e(s,a) for all s,a (decay all traces)
e(s_current, a_current) ← 1 (reset current trace)
Q(s,a) ← Q(s,a) + α × TD_error × e(s,a) (update all with trace weight)
Lambda Parameter (λ): 0.5-0.99, default 0.90
λ=0: Pure 1-step TD (only immediate next state)
λ=1: Full Monte Carlo (entire episode)
λ=0.9: Balance (recommended)
Why Superior: Dramatically faster learning for multi-step tasks. Q-Learning requires many episodes to propagate rewards backwards; TD(λ) does it in one.
Component 3: Policy Gradient (REINFORCE with Baseline)
Paradigm Shift: Instead of learning value function Q(s,a), directly learn policy π(a|s).
Policy Network Architecture:
Input: 12 market features
Hidden: None (linear policy)
Output: 5 actions (softmax distribution)
Total parameters: 12 features × 5 actions + 5 biases = 65 parameters
Feature Set (12 Features):
Price Z-score (close - SMA20) / ATR
Volume ratio (volume / vol_avg - 1)
RSI deviation (RSI - 50) / 50
Bollinger width ratio
Trend score / 4 (normalized)
VWAP deviation
5-bar price ROC
5-bar volume ROC
Range/ATR ratio - 1
Price-volume correlation (20-period)
Volatility ratio (ATR / ATR_avg - 1)
EMA50 deviation
REINFORCE Update Rule:
θ ← θ + α × ∇log π(a|s) × advantage
where advantage = reward - baseline (variance reduction)
Why Baseline? Raw rewards have high variance. Subtracting baseline (running average) centers rewards around zero, reducing gradient variance by 50-70%.
Learning Rate: 0.001-0.100, default 0.010 (much lower than Q-Learning because policy gradients have high variance)
Why Policy Gradient?
Handles 12 continuous features directly (Q-Learning requires discretization)
Naturally maintains exploration through probability distribution
Can converge to stochastic optimal policy
Component 4: Ensemble Meta-Learner (Stacking)
Architecture: Level-1 meta-learner combines Level-0 base learners (Q-Learning, TD(λ), Policy Gradient).
Three Meta-Learning Algorithms:
1. Simple Average (Baseline)
Final_prediction = (Q_prediction + TD_prediction + Policy_prediction) / 3
2. Weighted Vote (Reward-Based)
weight_i ← 0.95 × weight_i + 0.05 × (reward_i + 1)
3. Adaptive Weighting (Gradient-Based) — RECOMMENDED
Loss Function: L = (y_true - ŷ_ensemble)²
Gradient: ∂L/∂weight_i = -2 × (y_true - ŷ_ensemble) × agent_contribution_i
Updates weights via gradient descent with clipping and normalization
Why It Works: Unlike simple averaging, meta-learner discovers which base learner is most reliable in current regime. If Policy Gradient excels in trending markets while Q-Learning excels in ranging, meta-learner learns these patterns and weights accordingly.
Feature Importance Tracking
Purpose: Identify which of 12 features contribute most to successful predictions.
Update Rule: importance_i ← 0.95 × importance_i + 0.05 × |feature_i × reward|
Use Cases:
Feature selection: Drop low-importance features
Market regime detection: Importance shifts reveal regime changes
Agent tuning: If VWAP deviation has high importance, consider boosting agents using VWAP
RL Position Tracking System
Critical Innovation: Proper reinforcement learning requires tracking which decisions led to outcomes.
State Tracking (When Signal Validates):
active_rl_state ← current_market_state (0-53)
active_rl_action ← selected_agent (1-4)
active_rl_entry ← entry_price
active_rl_direction ← 1 (long) or -1 (short)
active_rl_bar ← current_bar_index
Online Updates (Every Bar Position Open):
floating_pnl = (close - entry) / entry × direction
reward = floating_pnl × 10 (scale to meaningful range)
reward = clip(reward, -5.0, 5.0)
Update Q-Learning, TD(λ), and Policy Gradient
Terminal Update (Position Close):
Final Q-Learning update (no next Q-value, terminal state)
Update meta-learner with final result
Update agent memory
Clear position tracking
Exit Conditions:
Time-based: ≥3 bars held (minimum hold period)
Stop-loss: 1.5% adverse move
Take-profit: 2.0% favorable move
Market Microstructure Filters
Why Microstructure Matters
Traditional technical analysis assumes fair, efficient markets. Reality: Markets have friction, manipulation, and information asymmetry. Microstructure filters detect when market structure indicates adverse conditions.
Filter 1: VPIN (Volume-Synchronized Probability of Informed Trading)
Theoretical Foundation: Easley, López de Prado, & O'Hara (2012). "Flow Toxicity and Liquidity in a High-Frequency World."
What It Measures: Probability that current order flow is "toxic" (informed traders with private information).
Calculation:
Classify volume as buy or sell (close > close = buy volume)
Calculate imbalance over 20 bars: VPIN = |Σ buy_volume - Σ sell_volume| / Σ total_volume
Compare to moving average: toxic = VPIN > VPIN_MA(20) × sensitivity
Interpretation:
VPIN < 0.3: Normal flow (uninformed retail)
VPIN 0.3-0.4: Elevated (smart money active)
VPIN > 0.4: Toxic flow (informed institutions dominant)
Filter Logic:
Block LONG when: VPIN toxic AND price rising (don't buy into institutional distribution)
Block SHORT when: VPIN toxic AND price falling (don't sell into institutional accumulation)
Adaptive Threshold: If VPIN toxic frequently, relax threshold; if rarely toxic, tighten threshold. Bounded .
Filter 2: Toxicity (Kyle's Lambda Approximation)
Theoretical Foundation: Kyle (1985). "Continuous Auctions and Insider Trading."
What It Measures: Price impact per unit volume — market depth and informed trading.
Calculation:
price_impact = (close - close ) / sqrt(Σ volume over 10 bars)
impact_zscore = (price_impact - impact_mean) / impact_std
toxicity = abs(impact_zscore)
Interpretation:
Low toxicity (<1.0): Deep liquid market, large orders absorbed easily
High toxicity (>2.0): Thin market or informed trading
Filter Logic: Block ALL SIGNALS when toxicity > threshold. Most dangerous when price breaks from VWAP with high toxicity.
Filter 3: Regime Filter (Counter-Trend Protection)
Purpose: Prevent counter-trend trades during strong trends.
Trend Scoring:
trend_score = 0
trend_score += close > EMA8 ? +1 : -1
trend_score += EMA8 > EMA21 ? +1 : -1
trend_score += EMA21 > EMA50 ? +1 : -1
trend_score += close > EMA200 ? +1 : -1
Range:
Regime Classification:
Strong Bull: trend_score ≥ +3 → Block all SHORT signals
Strong Bear: trend_score ≤ -3 → Block all LONG signals
Neutral: -2 ≤ trend_score ≤ +2 → Allow both directions
Filter 4: Liquidity Boost (Signal Enhancer)
Unique: Unlike other filters (which block), this amplifies signals during low liquidity.
Logic: if volume < vol_avg × 0.7: agent_scores × 1.2
Why It Works: Low liquidity often precedes explosive moves (breakouts). By increasing agent sensitivity during compression, system catches pre-breakout signals earlier.
Technical Implementation & Approximations
⚠️ Critical Approximations Required by Pine Script
1. Thompson Sampling: Pseudo-Random Beta Distribution
Academic Standard: True random sampling from beta distributions using cryptographic RNG
This Implementation: Box-Muller transform for normal distribution using market data (price/volume decimal digits) as entropy source, then scale to beta distribution mean/variance
Impact: Not cryptographically random, may have subtle biases in specific price ranges, but maintains correct mean and approximate variance. Sufficient for bandit agent selection.
2. VPIN: Simplified Volume Classification
Academic Standard: Lee-Ready algorithm or exchange-provided aggressor flags with tick-by-tick data
This Implementation: Bar-based classification: if close > close : buy_volume += volume
Impact: 10-15% precision loss. Works well in directional markets, misclassifies in choppy conditions. Still captures order flow imbalance signal.
3. Policy Gradient: Simplified Per-Action Updates
Academic Standard: Full softmax gradient updating all actions (selected action UP, others DOWN proportionally)
This Implementation: Only updates selected action's weights
Impact: Valid approximation for small action spaces (5 actions). Slower convergence than full softmax but still learns optimal policy.
4. Kyle's Lambda: Simplified Price Impact
Academic Standard: Regression over multiple time scales with signed order flow
This Implementation: price_impact = Δprice_10 / sqrt(Σvolume_10); z_score calculation
Impact: 15-20% precision loss. No proper signed order flow. Still detects informed trading signals at extremes (>2σ).
5. Other Simplifications:
Hawkes Process: Fixed exponential decay (0.9) not MLE-optimized
Entropy: Ratio approximation not true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Feature Engineering: 12 features vs. potential 100+ with polynomial interactions
RL Hybrid Updates: Both online and terminal (non-standard but empirically effective)
Overall Precision Loss Estimate: 10-15% compared to academic implementations with institutional data feeds.
Practical Trade-off: For retail trading with OHLCV data, these approximations provide 90%+ of the edge while maintaining full transparency, zero latency, no external dependencies, and runs on any TradingView plan.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Select Trading Mode: Start with "Balanced" for most users
Enable ML/RL System: Toggle to TRUE, select "Full Stack" ML Mode
Bandit Configuration: Algorithm: "Thompson Sampling", Mode: "Switch" or "Blend"
Microstructure Filters: Enable all four filters, enable "Adaptive Microstructure Thresholds"
Visual Settings: Enable dashboard (Top Right), enable all chart visuals
Learning Phase (First 50-100 Signals)
What To Monitor:
Agent Performance Table: Watch win rates develop (target >55%)
Bandit Weights: Should diverge from uniform (0.25 each) after 20-30 signals
RL Core Metrics: "RL Updates" should increase when position open
Filter Status: "Blocked" count indicates filter activity
Optimization Tips:
Too few signals: Lower min_confidence to 0.25, increase agent sensitivities to 1.1-1.2
Too many signals: Raise min_confidence to 0.35-0.40, decrease agent sensitivities to 0.8-0.9
One agent dominates (>70%): Consider "Lock Agent" feature
Signal Interpretation
Dashboard Signal Status:
⚪ WAITING FOR SIGNAL: No agent signaling
⏳ ANALYZING...: Agent signaling but not confirmed
🟡 CONFIRMING 2/3: Building confirmation (2 of 3 bars)
🟢 LONG ACTIVE : Validated long entry
🔴 SHORT ACTIVE : Validated short entry
Kill Zone Boxes: Entry price (triangle marker), Take Profit (Entry + 2.5× ATR), Stop Loss (Entry - 1.5× ATR). Risk:Reward = 1:1.67
Risk Management
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Capital × Risk%) / (Entry - StopLoss)
Stop-Loss Placement:
Initial: Entry ± 1.5× ATR (shown in kill zone)
Trailing: After 1:1 R:R achieved, move stop to breakeven
Take-Profit Strategy:
TP1 (2.5× ATR): Take 50% off
TP2 (Runner): Trail stop at 1× ATR or use opposite signal as exit
Memory Persistence
Why Save Memory: Every chart reload resets the system. Saving learned parameters preserves weeks of learning.
When To Save: After 200+ signals when agent weights stabilize
What To Save: From Memory Export panel, copy all alpha/beta/weight values and adaptive thresholds
How To Restore: Enable "Restore From Saved State", input all values into corresponding fields
What Makes This Original
Innovation 1: Genuine Multi-Armed Bandit Framework
This implements 15 mathematically rigorous bandit algorithms from academic literature (Thompson Sampling from Chapelle & Li 2011, UCB family from Auer et al. 2002, EXP3 from Auer et al. 2002, KL-UCB from Garivier & Cappé 2011). Each algorithm maintains proper state, updates according to proven theory, and converges to optimal behavior. This is real learning, not superficial parameter changes.
Innovation 2: Full Reinforcement Learning Stack
Beyond bandits learning which agent works best globally, RL learns which agent works best in each market state. After 500+ positions, system builds 54-state × 5-action value function (270 learned parameters) capturing context-dependent agent quality.
Innovation 3: Market Microstructure Integration
Combines retail technical analysis with institutional-grade microstructure metrics: VPIN from Easley, López de Prado, O'Hara (2012), Kyle's Lambda from Kyle (1985), Hawkes Processes from Hawkes (1971). These detect informed trading, manipulation, and liquidity dynamics invisible to technical analysis.
Innovation 4: Adaptive Threshold System
Dynamic quantile-based thresholds: Maintains histogram of each agent's score distribution (24 bins, exponentially decayed), calculates 80th percentile threshold from histogram. Agent triggers only when score exceeds its own learned quantile. Proper non-parametric density estimation automatically adapts to instrument volatility, agent behavior shifts, and market regime changes.
Innovation 5: Episodic Memory with Transfer Learning
Dual-layer architecture: Short-term memory (last 20 trades, fast adaptation) + Long-term memory (condensed episodes, historical patterns). Transfer mechanism consolidates knowledge when STM reaches threshold. Mimics hippocampus → neocortex consolidation in human memory.
Limitations & Disclaimers
General Limitations
No Predictive Guarantee: Pattern recognition ≠ prediction. Past performance ≠ future results.
Learning Period Required: Minimum 50-100 bars for reliable statistics. Initial performance may be suboptimal.
Overfitting Risk: System learns patterns in historical data. May not generalize to unprecedented conditions.
Approximation Limitations: See technical implementation section (10-15% precision loss vs. academic standards)
Single-Instrument Limitation: No multi-asset correlation, sector context, or VIX integration.
Forward-Looking Bias Disclaimer
CRITICAL TRANSPARENCY: The RL system uses an 8-bar forward-looking window for reward calculation.
What This Means: System learns from rewards incorporating future price information (bars 101-108 relative to entry at bar 100).
Why Acceptable:
✅ Signals do NOT look ahead: Entry decisions use only data ≤ entry bar
✅ Learning only: Forward data used for optimization, not signal generation
✅ Real-time mirrors backtest: In live trading, system learns identically
⚠️ Implication: Dashboard "Agent Win%" reflects this 8-bar evaluation. Real-time performance may differ slightly if positions held longer, slippage/fees not captured, or market microstructure changes.
Risk Warnings
No Guarantee of Profit: All trading involves risk of loss
System Failures: Bugs possible despite extensive testing
Market Conditions: Optimized for liquid markets (>100k daily volume). Performance degrades in illiquid instruments, major news events, flash crashes
Broker-Specific Issues: Execution slippage, commission/fees, overnight financing costs
Appropriate Use
This Indicator Is:
✅ Entry trigger system
✅ Risk management framework (stop/target)
✅ Adaptive agent selection engine
✅ Learning system that improves over time
This Indicator Is NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for fundamental analysis
❌ Guaranteed profit generator
❌ Suitable for complete beginners without training
Recommended Complementary Analysis: Market context (support/resistance), volume profile, fundamental catalysts, correlation with related instruments, broader market regime
Recommended Settings by Instrument
Stocks (Large Cap, >$1B):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Switch
Agent Sensitivity: Spoofing 1.0-1.2, Exhaustion 0.9-1.1, Liquidity 0.8-1.0, StatArb 1.1-1.3
Microstructure: All enabled, VPIN 1.2, Toxicity 1.5 | Timeframe: 15min-1H
Forex Majors (EURUSD, GBPUSD):
Mode: Balanced to Conservative | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Blend
Agent Sensitivity: Spoofing 0.8-1.0, Exhaustion 0.9-1.1, Liquidity 0.7-0.9, StatArb 1.2-1.5
Microstructure: All enabled, VPIN 1.0-1.1, Toxicity 1.3-1.5 | Timeframe: 5min-30min
Crypto (BTC, ETH):
Mode: Aggressive to Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling OR EXP3-IX
Agent Sensitivity: Spoofing 1.2-1.5, Exhaustion 1.1-1.3, Liquidity 1.2-1.5, StatArb 0.7-0.9
Microstructure: All enabled, VPIN 1.4-1.6, Toxicity 1.8-2.2 | Timeframe: 15min-4H
Futures (ES, NQ, CL):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: UCB1 or Thompson Sampling
Agent Sensitivity: All 1.0-1.2 (balanced)
Microstructure: All enabled, VPIN 1.1-1.3, Toxicity 1.4-1.6 | Timeframe: 5min-30min
Conclusion
Algorithm Predator - Pro synthesizes academic research from market microstructure theory, reinforcement learning, and multi-armed bandit algorithms. Unlike typical indicator mashups, this system implements 15 mathematically rigorous bandit algorithms, deploys a complete RL stack (Q-Learning, TD(λ), Policy Gradient), integrates institutional microstructure metrics (VPIN, Kyle's Lambda), adapts continuously through dual-layer memory and meta-learning, and provides full transparency on approximations and limitations.
The system is designed for serious algorithmic traders who understand that no indicator is perfect, but through proper machine learning, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Risk disclosure applies. Past performance ≠ future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Dinkan Price Action Pro | Pure Price Action Toolkit🔸 Overview
Dinkan Price Action Pro is a pure price-action research toolkit that automatically detects and visualizes Order Blocks (OB), Fair Value Gaps (FVG), merged-candle hidden structures, liquidity zones (including HTF bias liquidity), and trendline & chart-pattern liquidity.
This indicator helps traders align with the Higher Time Frame (HTF) bias — the direction of the dominant institutional wave — and uncover hidden candlestick structures that normal timeframe charts never show.
⚙️ Core Features
✅ Automatic Order Block detection (bullish & bearish)
✅ Fair Value Gaps with real-time fill tracking
✅ Merged-Candle Engine — reveals hidden structures between standard timeframes
✅ Liquidity Zones — equal highs/lows, trendline liquidity & HTF liquidity pools
✅ HTF Bias Engine — detect directional bias across multiple timeframes
✅ Auto Trendlines & Chart Pattern Liquidity
🔍 How It Works (Step by Step)
🕯️ A. Merged Candle Engine (Hidden Structure)
1️⃣ Choose how many candles to merge (e.g., 3–5).
2️⃣ The script groups candles backward from the current bar in continuous sets.
3️⃣ Each merged candle forms using:
• Open = first candle’s open • Close = last candle’s close
• High = highest high • Low = lowest low
4️⃣ These new candles expose “hidden” structures between fixed timeframes — revealing true base-impulse patterns missed by normal charts.
🟩 B. Order Block Detection
Detects consolidation (base) followed by strong impulse.
Marks demand (green) and supply (red) zones automatically.
Strength calculated using impulse range (and volume, if available).
Older, mitigated OBs can be hidden for clarity.
🟦 C. Fair Value Gaps (FVG)
Automatically detects imbalances between consecutive candles.
Unfilled FVGs are highlighted; once filled, zones fade or gray out.
Works dynamically across merged and standard candles.
🟧 D. Liquidity Zones
Finds equal highs/lows, wick clusters, and structural liquidity.
Trendline liquidity and chart-pattern liquidity detected in real time.
Projects HTF liquidity zones from higher charts down to current timeframe.
🔺 E. HTF Bias Engine
Analyzes higher and medium timeframes (HTF/MTF) using CISD-style confirmation.
Bias auto-adjusts or can be manually selected.
🧭 Purpose: Identify the dominant institutional flow and trade in its direction.
⏰ Timeframe Alignment
Recommended structure:
HTF: 4H or 1D
MTF: 1H or 30M
LTF: 15M or 5M
Users may let the script auto-adjust or manually configure each timeframe combination.
📘 Inputs & Settings
🔹 OB sensitivity (Low / Medium / High)
🔹 Volume weighting toggle
🔹 HTF & MTF selection (Auto / Manual)
🔹 Multi-symbol mode
🔹 Visual toggles (OB, FVG, trendlines, merged candles, bias labels)
🔹 Alert toggles (zone touch, bias flip, hidden structure detection)
📊 How to Use — Workflow Example
1️⃣ Load the indicator on your chart.
2️⃣ Check the HTF Bias direction — trade only in that direction.
3️⃣ Identify nearby Order Blocks or FVGs inside HTF liquidity areas.
4️⃣ Watch the Merged Candle View to confirm hidden structures (base + impulse).
5️⃣ Wait for LTF confirmation (e.g., small structure break, wick rejection).
6️⃣ Place stop beyond the opposite OB edge; target next liquidity cluster.
🎯 This workflow aligns your lower-timeframe trades with the dominant higher-timeframe flow.
🧱 Repainting & Stability
Completed OBs and FVGs remain static — they do not repaint.
Real-time zones during candle formation can update until candle closes (standard behavior).
Merged candles are recalculated each bar; once a group closes, it remains fixed historically.
⚠️ Limitations
This is not a buy/sell signal generator.
Volume-weighted features require volume data.
Use responsible risk management and independent confirmation methods.
🔒 Invite-Only / Locked Code
The script is published as invite-only to protect proprietary implementations of:
The merged-candle engine
Liquidity and bias-detection heuristics
Invite-only publishing complies with TradingView rules.
All logic, purpose, and usage are fully described here for transparency.
🧩 Originality & Usefulness
This script is an original integrated system, not a simple mashup.
Each module is interconnected to provide a unified analytical process:
The Merged Candle Engine creates hybrid bars that expose hidden base–impulse patterns.
These merged bars feed into the Order Block and Fair Value Gap logic, refining zone accuracy.
The Liquidity Detector references those zones and merged bars to locate valid structural pools.
Finally, the HTF Bias Engine confirms directional context across multiple pairs and timeframes.
Together, these elements form a dynamic framework that interprets institutional footprints and structure flow — something no single indicator can achieve individually.
The combination produces new analytical value: a precise, adaptive HTF bias alignment and structure-based liquidity map in one visual system.
📜 Disclaimer
This tool is for educational and analytical use only.
It does not constitute financial advice.
Trading involves risk — always perform independent analysis and practice sound risk management.
Past performance does not guarantee future results.
Smart Volume S/R Pro [The_lurker]مؤشر "Smart Volume S/R Pro " هو أداة تحليل فني متقدمة مصممة لمساعدة المتداولين في تحديد مستويات الدعم والمقاومة القوية بناءً على حجم التداول، مع إضافة ميزات تحليلية متطورة مثل تصفية الاتجاه ، مناطق الثقة ، تقييم القوة ، حساب احتمالية الاختراق ، قياس السيولة ، تحديد الأهداف السعرية ، ومستويات فيبوناتشي . وايضا تقديم تسميات (Labels) بجانب كل مستوى دعم ومقاومة، تحتوي على أرقام ومعلومات دقيقة تعكس حالة السوق. هذه التسميات ليست مجرد زينة، بل أدوات تحليلية تساعد المتداولين على اتخاذ قرارات مستنيرة بناءً على بيانات السوقيهدف هذا المؤشر إلى توفير رؤية شاملة للسوق .
الوظائف الرئيسية للمؤشر
1- تحديد مستويات الدعم والمقاومة بناءً على حجم التداول العالي
يقوم المؤشر بتحليل الأشرطة (Bars) السابقة (حتى 300 شريط افتراضيًا) لتحديد النقاط التي شهدت أعلى مستويات حجم التداول.
يرسم خطوط أفقية تمثل مستويات المقاومة (عند أعلى سعر في تلك الأشرطة) والدعم (عند أدنى سعر)، ويمكن للمستخدم اختيار عدد الخطوط المعروضة (من 1 إلى 6).
2- تصفية الاتجاه باستخدام مؤشر ADX
يستخدم المؤشر مؤشر الاتجاه المتوسط (ADX) لتقييم قوة الاتجاه في السوق.
عندما تكون قوة الاتجاه عالية (تتجاوز عتبة محددة، 25 افتراضيًا)، يقلل المؤشر عدد مستويات الدعم والمقاومة المعروضة للتركيز فقط على المستويات الأكثر أهمية.
3- مناطق الثقة الديناميكية
يضيف المؤشر مناطق حول مستويات الدعم والمقاومة بناءً على متوسط المدى الحقيقي (ATR)، مما يساعد المتداولين على تصور النطاقات التي قد يتفاعل فيها السعر مع هذه المستويات.
يمكن تعديل عرض هذه المناطق باستخدام مضاعف ATR.
4- تقييم قوة المستويات
يحسب المؤشر قوة كل مستوى بناءً على حجم التداول، عدد المرات التي تم اختبار المستوى فيها (Touch Count)، وقرب السعر الحالي من المستوى.
يتم عرض درجة القوة (من 0 إلى 100) بجانب كل مستوى إذا تم تفعيل هذه الخاصية.
5- احتمالية الاختراق
يقدّر المؤشر احتمالية اختراق كل مستوى بناءً على الزخم (ROC)، قوة المستوى، والمسافة بين السعر الحالي والمستوى.
يظهر الاحتمال كنسبة مئوية إذا تم تفعيل الخيار، مما يساعد المتداولين على توقع الحركات المحتملة.
6- تحليل السيولة التاريخية
يقيس المؤشر السيولة حول كل مستوى بناءً على حجم التداول في النطاقات القريبة منه.
يمكن عرض قيم السيولة في التسميات أو استخدامها لتعديل عرض الخطوط (الخطوط الأكثر سيولة تظهر أعرض).
7- الأهداف السعرية
عند تفعيل هذه الخاصية، يحسب المؤشر أهداف سعرية للاختراق (Breakout) والارتداد (Reversal) بناءً على الزخم وقوة المستوى وATR.
يمكن عرض هذه الأهداف كنصوص في التسميات أو كخطوط أفقية على الرسم البياني.
8- مستويات فيبوناتشي
يرسم المؤشر مستويات فيبوناتشي (0.0، 0.236، 0.382، 0.5، 0.618، 0.786، 1.0) بناءً على أعلى وأدنى سعر في فترة النظرة الخلفية.
يمكن للمستخدم اختيار أي من هذه المستويات لعرضها أو إخفائها.
9- تنبيه شامل للاختراق
يوفر المؤشر تنبيهًا واحدًا يشمل جميع المستويات، حيث يُطلق التنبيه عندما يخترق السعر أي مستوى دعم أو مقاومة مع رسالة توضح نوع الاختراق والمستوى المخترق.
كيفية عمل المؤشر
الخطوة الأولى: يحدد المؤشر الأشرطة ذات الحجم العالي خلال فترة النظرة الخلفية المحددة (Lookback Period).
الخطوة الثانية: يرسم مستويات الدعم والمقاومة بناءً على أعلى وأدنى الأسعار في تلك الأشرطة، مع مراعاة عدد الخطوط المختارة من المستخدم.
الخطوة الثالثة: يطبق مرشح الاتجاه (إذا كان مفعلاً) لتقليل عدد المستويات في حالة الاتجاه القوي.
الخطوة الرابعة: يضيف التحليلات الإضافية مثل القوة، السيولة، احتمالية الاختراق، والأهداف السعرية، ويرسم مناطق الثقة ومستويات فيبوناتشي حسب الإعدادات.
الخطوة الخامسة: يراقب السعر ويطلق تنبيهًا عند الاختراق.
الإعدادات القابلة للتخصيص
1- فترة النظرة الخلفية (Lookback Period): عدد الأشرطة التي يتم تحليلها (افتراضيًا 300).
2- عدد الخطوط (Number of Lines): من 1 إلى 6 مستويات دعم ومقاومة.
3- الألوان والأنماط: يمكن تغيير ألوان الخطوط وأنماطها (ممتلئة، متقطعة، منقطة).
4- التسميات: تفعيل/تعطيل التسميات، وحجمها، وموقعها، ولون النص.
5- مرشح الاتجاه: تفعيل/تعطيل ADX، وتعديل طوله وعتبته.
6- مناطق الثقة: تفعيل/تعطيل، وتعديل طول ATR ومضاعفه.
7- القوة واحتمالية الاختراق: تفعيل/تعطيل العرض، وتعديل طول ROC.
8- السيولة: تفعيل/تعطيل تأثير السيولة على عرض الخطوط وقيمها في التسميات.
9- الأهداف السعرية: تفعيل/تعطيل الأهداف وعرضها كخطوط.
10- فيبوناتشي: اختيار المستويات المعروضة ولون الخطوط.
فوائد المؤشر
دقة عالية: يعتمد على حجم التداول لتحديد المستويات، مما يجعله أكثر موثوقية من المستويات العشوائية.
مرونة: يوفر خيارات تخصيص واسعة تتيح للمتداولين تكييفه حسب استراتيجياتهم.
تحليل شامل: يجمع بين الدعم والمقاومة، الاتجاه، السيولة، والأهداف في أداة واحدة.
سهولة الاستخدام: التسميات والتنبيهات تجعل من السهل متابعة السوق دون تعقيد.
==================================================================================تسميات (Labels) بجانب كل مستوى دعم ومقاومة، تحتوي على أرقام ومعلومات دقيقة تعكس حالة السوق. هذه التسميات ليست مجرد زينة، بل أدوات تحليلية تساعد المتداولين على اتخاذ قرارات مستنيرة بناءً على بيانات السوق. في هذا الشرح، سنستعرض كل رقم أو قيمة تظهر في التسميات ومعناها العملي.
مكونات التسميات
التسميات تظهر بجانب كل مستوى دعم (Support) ومقاومة (Resistance) وتبدأ بحرف "S" للدعم أو "R" للمقاومة، تليها مجموعة من الأرقام والقيم التي يمكن تفعيلها أو تعطيلها حسب إعدادات المستخدم. إليك تفصيل كل عنصر:
1- عدد اللمسات (Touch Count)
الرمز: يظهر مباشرة بعد "S" أو "R" (مثال: "R: 5" أو "S: 3").
المعنى: يشير إلى عدد المرات التي اختبر فيها السعر هذا المستوى دون اختراقه.
الفائدة: كلما زاد عدد اللمسات، كلما كان المستوى أقوى وأكثر أهمية. على سبيل المثال، إذا كان "R: 5"، فهذا يعني أن السعر ارتد من هذا المستوى 5 مرات، مما يجعله مقاومة قوية محتملة.
2- قوة المستوى (Strength Rating)
الرمز: يظهر بين قوسين مربعين (مثال: " ").
المعنى: قيمة من 0 إلى 100 تعكس قوة المستوى بناءً على عوامل مثل حجم التداول، عدد اللمسات، وقرب السعر الحالي من المستوى.
الفائدة: القيم العالية (مثل 75 أو أكثر) تشير إلى مستوى قوي يصعب اختراقه، بينما القيم المنخفضة (مثل 30 أو أقل) تدل على ضعف المستوى وسهولة اختراقه. يمكن للمتداول استخدام هذا لتحديد المستويات الأكثر موثوقية.
3- احتمالية الاختراق (Breakout Probability)
الرمز: يبدأ بحرف "B" متبوعًا بنسبة مئوية (مثال: "B: 60%").
المعنى: نسبة من 0% إلى 100% تُظهر احتمالية اختراق السعر للمستوى بناءً على الزخم الحالي، قوة المستوى، والمسافة بين السعر والمستوى.
الفائدة: نسبة مرتفعة (مثل 60% أو أكثر) تعني أن السعر قد يخترق المستوى قريبًا، بينما النسب المنخفضة (مثل 20%) تشير إلى احتمال ارتداد السعر. هذا مفيد لتوقع الحركة التالية.
4- قيمة السيولة (Liquidity Value)
الرمز: يبدأ بحرف "L" متبوعًا برقم (مثال: "L: 1200").
المعنى: يمثل متوسط حجم التداول في النطاق القريب من المستوى، مما يعكس السيولة التاريخية حوله.
الفائدة: القيم العالية تدل على وجود سيولة كبيرة، مما يعني أن السعر قد يتفاعل بقوة مع هذا المستوى (إما بالارتداد أو الاختراق). القيم المنخفضة تشير إلى سيولة ضعيفة، مما قد يجعل المستوى أقل تأثيرًا.
5- الأهداف السعرية (Price Targets)
الرمز: يبدأ بـ "BT" (هدف الاختراق) و"RT" (هدف الارتداد) متبوعين بأرقام (مثال: "BT: 150.50 RT: 148.20").
المعنى:
BT (Breakout Target): السعر المحتمل الذي قد يصل إليه السعر بعد اختراق المستوى.
RT (Reversal Target): السعر المحتمل الذي قد يصل إليه السعر إذا ارتد من المستوى.
الفائدة: تساعد المتداولين في تحديد نقاط الخروج المحتملة بعد الاختراق أو الارتداد، مما يسهل وضع خطة تداول دقيقة.
أمثلة عملية
تسمية مقاومة: "R: 4 B: 25% L: 1500 BT: 155.00 RT: 152.00"
المستوى اختُبر 4 مرات، قوته 80 (قوي جدًا)، احتمالية الاختراق 25% (منخفضة، أي احتمال ارتداد أعلى)، السيولة 1500 (مرتفعة)، هدف الاختراق 155.00، هدف الارتداد 152.00.
الاستنتاج: المستوى قوي ومن المرجح أن يرتد السعر منه، لكن إذا اخترق، فقد يصل إلى 155.00.
تسمية دعم: "S: 2 B: 70% L: 800 BT: 145.00 RT: 147.50"
المستوى اختُبر مرتين، قوته 40 (متوسطة إلى ضعيفة)، احتمالية الاختراق 70% (مرتفعة)، السيولة 800 (متوسطة)، هدف الاختراق 145.00، هدف الارتداد 147.50.
الاستنتاج: المستوى ضعيف ومن المحتمل أن يخترقه السعر ليهبط إلى 145.00.
كيفية الاستفادة من التسميات
تحديد القوة والضعف: استخدم قوة المستوى (Strength) لمعرفة ما إذا كان المستوى موثوقًا للارتداد أو عرضة للاختراق.
توقع الحركة: انظر إلى احتمالية الاختراق (Breakout Probability) لتحديد ما إذا كنت ستنتظر اختراقًا أو ترتدًا.
إدارة المخاطر: استخدم الأهداف السعرية (BT وRT) لتحديد نقاط جني الأرباح أو وقف الخسارة.
تقييم السيولة: ركز على المستويات ذات السيولة العالية لأنها غالبًا تكون نقاط تحول رئيسية في السوق.
تأكيد التحليل: ادمج عدد اللمسات مع القوة والسيولة للحصول على صورة كاملة عن أهمية المستوى.
تخصيص التسميات
يمكن للمستخدم تفعيل أو تعطيل أي من هذه القيم (القوة، الاحتمالية، السيولة، الأهداف) من إعدادات المؤشر.
يمكن أيضًا تغيير حجم التسميات (صغير، عادي، كبير)، موقعها (يمين، يسار، أعلى، أسفل)، ولون النص لتناسب احتياجاتك.
التسميات في هذا المؤشر هي بمثابة لوحة تحكم صغيرة بجانب كل مستوى دعم ومقاومة، تقدم لك معلومات فورية عن قوته، احتمالية اختراقه، سيولته، وأهدافه السعرية. بفهم هذه الأرقام، يمكنك تحسين قراراتك في التداول، سواء كنت تبحث عن نقاط دخول، خروج، أو إدارة مخاطر. إذا كنت تريد أداة تجمع بين البساطة والعمق التحليلي .
تنويه:
المؤشر هو أداة مساعدة فقط ويجب استخدامه مع التحليل الفني والأساسي لتحقيق أفضل النتائج.
إخلاء المسؤولية
لا يُقصد بالمعلومات والمنشورات أن تكون، أو تشكل، أي نصيحة مالية أو استثمارية أو تجارية أو أنواع أخرى من النصائح أو التوصيات المقدمة أو المعتمدة من TradingView.
The Smart Volume S/R Pro indicator is an advanced technical analysis tool designed to help traders identify strong support and resistance levels based on trading volume, with the addition of advanced analytical features such as trend filtering, confidence zones, strength assessment, breakout probability calculation, liquidity measurement, price target identification, and Fibonacci levels. It also provides labels next to each support and resistance level, containing accurate numbers and information that reflect the market condition. These labels are not just decorations, but analytical tools that help traders make informed decisions based on market data. This indicator aims to provide a comprehensive view of the market.
Main functions of the indicator
1- Identifying support and resistance levels based on high trading volume
The indicator analyzes previous bars (up to 300 bars by default) to identify the points that witnessed the highest levels of trading volume.
It draws horizontal lines representing resistance levels (at the highest price in those bars) and support (at the lowest price), and the user can choose the number of lines displayed (from 1 to 6).
2- Filtering the trend using the ADX indicator
The indicator uses the Average Directional Index (ADX) to assess the strength of a trend in the market.
When the strength of the trend is high (exceeding a specified threshold, 25 by default), the indicator reduces the number of support and resistance levels displayed to focus only on the most important levels.
3- Dynamic Confidence Zones
The indicator adds zones around support and resistance levels based on the Average True Range (ATR), helping traders visualize the ranges in which the price may interact with these levels.
The width of these zones can be adjusted using the ATR multiplier.
4- Assessing the Strength of Levels
The indicator calculates the strength of each level based on trading volume, the number of times the level has been tested (Touch Count), and the proximity of the current price to the level.
A strength score (from 0 to 100) is displayed next to each level if this feature is enabled.
5- Breakout Probability
The indicator estimates the probability of breaking each level based on momentum (ROC), the strength of the level, and the distance between the current price and the level.
The probability is displayed as a percentage if the option is enabled, helping traders anticipate potential moves.
6- Historical Liquidity Analysis
The indicator measures liquidity around each level based on the trading volume in the ranges near it.
The liquidity values can be displayed in the labels or used to adjust the width of the lines (the most liquid lines appear wider).
7- Price Targets
When this feature is enabled, the indicator calculates price targets for breakout and reversal based on momentum, level strength and ATR.
These targets can be displayed as text in the labels or as horizontal lines on the chart.
8- Fibonacci Levels
The indicator plots Fibonacci levels (0.0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0) based on the highest and lowest price in the lookback period.
The user can choose which of these levels to display or hide.
9- Comprehensive Breakout Alert
The indicator provides a single alert that includes all levels, where the alert is triggered when the price breaks any support or resistance level with a message explaining the type of breakout and the level broken.
How the indicator works
Step 1: The indicator identifies the bars with high volume during the specified Lookback Period.
Step 2: Draws support and resistance levels based on the highest and lowest prices in those bars, taking into account the number of lines selected by the user.
Step 3: Apply the trend filter (if enabled) to reduce the number of levels in case of a strong trend.
Step 4: Adds additional analyses such as strength, liquidity, breakout probability, and price targets, and draws confidence zones and Fibonacci levels according to the settings.
Step 5: Monitors the price and triggers an alert when the breakout occurs.
Customizable Settings
1- Lookback Period: Number of bars to analyze (default 300).
2- Number of Lines: From 1 to 6 support and resistance levels.
3- Colors and Styles: Line colors and styles can be changed (filled, dashed, dotted).
4- Labels: Enable/disable labels, their size, location, and text color.
5- Trend Filter: Enable/disable ADX, and modify its length and threshold.
6- Confidence Zones: Enable/disable, and modify the ATR length and multiplier.
7- Strength and Breakout Probability: Enable/disable the display, and modify the ROC length.
8- Liquidity: Enable/disable the effect of liquidity on the display of the lines and their values in the labels.
9- Price Targets: Enable/disable the targets and display them as lines.
10- Fibonacci: Choose the displayed levels and the color of the lines.
Indicator Benefits
High Accuracy: It relies on trading volume to determine the levels, which makes it more reliable than random levels.
Flexibility: It provides extensive customization options that allow traders to adapt it to their strategies.
Comprehensive Analysis: Combines support and resistance, trend, liquidity, and targets in one tool. Ease of Use: Labels and alerts make it easy to follow the market without complexity.
Labels next to each support and resistance level contain accurate numbers and information that reflect the market situation. These labels are not just decorations, but analytical tools that help traders make informed decisions based on market data. In this explanation, we will review each number or value that appears in the labels and their practical meaning.
Label Components
Labels appear next to each support and resistance level and begin with the letter "S" for support or "R" for resistance, followed by a set of numbers and values that can be enabled or disabled according to the user's settings. Here is a breakdown of each element:
1- Touch Count
Symbol: Appears immediately after "S" or "R" (example: "R: 5" or "S: 3").
Meaning: Indicates the number of times the price has tested this level without breaking it.
Benefit: The more touches, the stronger and more important the level. For example, if it is "R: 5", it means that the price has bounced off this level 5 times, making it a potentially strong resistance.
2- Strength Rating
Symbol: Appears between square brackets (example: " ").
Meaning: A value from 0 to 100 that reflects the strength of the level based on factors such as trading volume, number of touches, and proximity of the current price to the level.
Benefit: High values (such as 75 or more) indicate a strong level that is difficult to break, while low values (such as 30 or less) indicate a weak level that is easy to break. A trader can use this to determine the most reliable levels.
3- Breakout Probability
Symbol: Starts with the letter "B" followed by a percentage (example: "B: 60%").
Meaning: A percentage from 0% to 100% that shows the probability of the price breaking the level based on the current momentum, the strength of the level, and the distance between the price and the level.
Interest: A high percentage (such as 60% or more) means that the price may soon break through the level, while low percentages (such as 20%) indicate that the price may bounce. This is useful for anticipating the next move.
4- Liquidity Value
Symbol: Starts with the letter "L" followed by a number (example: "L: 1200").
Meaning: Represents the average trading volume in the range near the level, reflecting historical liquidity around it.
Interest: High values indicate high liquidity, meaning that the price may react strongly to this level (either by bouncing or breaking through). Low values indicate low liquidity, which may make the level less influential.
5- Price Targets
Symbol: Starts with "BT" (breakout target) and "RT" (rebound target) followed by numbers (example: "BT: 150.50 RT: 148.20").
Meaning:
BT (Breakout Target): The potential price that the price may reach after breaking the level.
RT (Reversal Target): The potential price that the price may reach if it rebounds from the level.
Utility: Helps traders identify potential exit points after a breakout or rebound, making it easier to develop an accurate trading plan.
Working examples
Resistance label: "R: 4 B: 25% L: 1500 BT: 155.00 RT: 152.00"
Level tested 4 times, strength 80 (very strong), probability of breakout 25% (low, i.e. higher probability of rebound), liquidity 1500 (high), breakout target 155.00, rebound target 152.00.
Conclusion: The level is strong and the price is likely to rebound from it, but if it breaks, it may reach 155.00.
Support Label: "S: 2 B: 70% L: 800 BT: 145.00 RT: 147.50"
Level tested twice, Strength 40 (medium to weak), Breakout Probability 70% (high), Liquidity 800 (medium), Breakout Target 145.00, Rebound Target 147.50.
Conclusion: The level is weak and the price is likely to break it to drop to 145.00.
How to use labels
Determine strength and weakness: Use the level's strength to see if the level is reliable for a bounce or vulnerable to a breakout.
Predict the move: Look at the Breakout Probability to determine whether to wait for a breakout or a bounce.
Risk Management: Use price targets (BT and RT) to set take profit or stop loss points.
Liquidity Evaluation: Focus on levels with high liquidity as they are often key turning points in the market.
Analysis Confirmation: Combine the number of touches with strength and liquidity to get a complete picture of the level’s importance.
Customize Labels
The user can enable or disable any of these values (strength, probability, liquidity, targets) from the indicator settings.
The size of the labels (small, normal, large), their position (right, left, top, bottom), and the color of the text can also be changed to suit your needs.
The labels in this indicator act as a small dashboard next to each support and resistance level, providing you with instant information about its strength, probability of breakout, liquidity, and price targets. By understanding these numbers, you can improve your trading decisions, whether you are looking for entry points, exit points, or risk management. If you want a tool that combines simplicity with analytical depth.
Disclaimer:
The indicator is an auxiliary tool only and should be used in conjunction with technical and fundamental analysis for best results.
Disclaimer
The information and posts are not intended to be, or constitute, any financial, investment, trading or other types of advice or recommendations provided or endorsed by TradingView.
OrderFlow [Adjustable] | FractalystWhat's the indicator's purpose and functionality?
This indicator is designed to assist traders in identifying real-time probabilities of buyside and sellside liquidity .
It allows for an adjustable pivot level , enabling traders to customize the level they want to use for their entries.
By doing so, traders can evaluate whether their chosen entry point would yield a positive expected value over a large sample size, optimizing their strategy for long-term profitability.
For advanced traders looking to enhance their analysis, the indicator supports the incorporation of up to 7 higher timeframe biases .
Additionally, the higher timeframe pivot level can be adjusted according to the trader's preferences,
Offering maximum adaptability to different strategies and needs, further helping to maximize positive EV.
EV=(P(Win)×R(Win))−(P(Loss)×R(Loss))
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What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
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How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "⏸" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
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What does the multi-timeframe functionality offer?
In the adjustable version of the orderflow indicator, you can incorporate up to 7 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
This multi-timeframe functionality helps traders:
1. Simplify decision-making by offering a comprehensive view of multiple timeframes at once.
2. Identify confluence between timeframes, enhancing the confidence in trade setups.
3. Adapt strategies more effectively, as the higher timeframe pivot levels can be customized to meet individual preferences and goals.
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What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
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How does the Indicator Identifies Positive Expected Values?
OrderFlow indicator instantly calculates whether a trade setup has the potential for positive expected value (EV) in the long run.
To determine a positive EV setup, the indicator uses the formula:
EV=(P(Win)×R(Win))−(P(Loss)×R(Loss))
where:
P(Win) is the probability of a winning trade.
R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
P(Loss) is the probability of a losing trade.
R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value over a large sample size.
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How can I know that the setup I'm going to trade with has a postive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
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What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
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How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
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How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable . In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
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How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
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What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request : The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
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What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
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How to use the indicator effectively?
For Amateur Traders:
Start Simple: Begin by focusing on one timeframe at a time with the pivot level set to the default (50%). This helps you understand the basic functionality of the indicator.
Entry and Exit Strategy: Focus on entering trades at the pivot level while targeting the higher probability side for take profit and the lower probability side for stop loss.
Use simulation or paper trading to practice this strategy.
Adjustments: Once you have a solid understanding of how the indicator works, you can start adjusting the pivot level to other values that suit your strategy.
Ensure that the RR labels are colored (blue or red) to indicate positive EV setups before executing trades.
For Advanced Traders:
1. Select Higher Timeframe Bias: Choose a higher timeframe (HTF) as your main bias. Start with the default pivot level and ensure the confidence level is above 95% to validate the probabilities.
2. Align Lower Timeframes: Switch between lower timeframes to identify which ones align with your predefined HTF bias. This helps in synchronizing your trading decisions across different timeframes.
3. Set Entries with Current Pivot Level: Use the current pivot level for trade entries. Ensure the HTF status label is active, indicating that the probabilities are valid and in play.
4. Target HTF Liquidity Level: Aim for liquidity levels that correspond to the higher timeframe, as these levels are likely to offer better trading opportunities.
5. Adjust Pivot Levels: As you gain experience, adjust the pivot levels to further optimize your strategy for high EV. Fine-tune these levels based on the aggregated data from multiple timeframes.
6. Practice on Paper Trading: Test your strategies through paper trading to eliminate discretion and refine your approach without financial risk.
7. Focus on Trade Management: Ultimately, effective trade management is crucial. Concentrate on managing your trades well to ensure long-term success. By aiming for setups that produce positive EV, you can position yourself similarly to how a casino operates.
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🎲 Becoming the House (Gaining Edge Over the Market):
In American roulette, the house has a 5.26% edge due to the 0 and 00. This means that while players have a 47.37% chance of winning on even-money bets, the true odds are 50%. The discrepancy between the true odds and the payout ensures that, statistically, the casino will win over time.
From the Trader's Perspective: In trading, you gain an edge by focusing on setups with positive expected value (EV). If you have a 55.48% chance of winning with a 1:1 risk-to-reward ratio, your setup has a higher probability of profitability than the losing side. By consistently targeting such setups and managing your trades effectively, you create a statistical advantage, similar to the casino’s edge.
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🎰 Applying the Concept to Trading:
Just as casinos rely on their mathematical edge, you can achieve long-term success in trading by focusing on setups with positive EV. By ensuring that your probabilities and risk-to-reward (RR) ratios are in your favor, you create an edge similar to that of the house.
And by systematically targeting trades with favorable probabilities and managing your trades effectively, you improve your chances of profitability over the long run. Which is going to help you “become the house” in your trading, leveraging statistical advantages to enhance your overall performance.
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What makes this indicator original?
Real-Time Probability Calculations: The indicator provides real-time calculations of buy and sell probabilities based on historical data, allowing traders to assess the likelihood of positive expected value (EV) setups instantly.
Adjustable Pivot Levels: It features an adjustable pivot level that traders can modify according to their preferences, enhancing the flexibility to align with different trading strategies.
Multi-Timeframe Integration: The indicator supports up to 7 higher timeframes, displaying their probabilities and biases in a single view, which helps traders make informed decisions without switching timeframes.
Confidence Levels: It includes confidence levels based on sample sizes, offering insights into the reliability of the probabilities. Traders can gauge the strength of the data before making trades.
Dynamic EV Labels: The indicator provides color-coded EV labels that change based on the validity of the setup. Blue indicates positive EV in a long bias, red indicates positive EV in a short bias and gray signals caution, making it easier for traders to identify high-quality setups.
HTF Probability Table: The HTF probability table displays buy and sell probabilities from user-defined higher timeframes, helping traders integrate broader market context into their decision-making process.
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
LuxAlgo® - Price Action Concepts™Price Action Concepts™ is a first of it's kind all-in-one indicator toolkit which includes various features specifically based on pure price action.
Order Blocks w/ volume data, real-time market structure (BOS, CHoCH, EQH/L) w/ 'CHoCH+' being a more confirmed reversal signal, a MTF dashboard, Trend Line Liquidity Zones (real-time), Chart Pattern Liquidity Zones, Liquidity Grabs, and much more detailed customization to get an edge trading price action automatically.
Many traders argue that trading price action is better than using technical indicators due to lag, complexity, and noisy charts. Popular ideas within the trading space that cater towards price action trading include "trading like the banks" or "Smart Money Concepts trading" (SMC), most prominently known within the forex community.
What differentiates price action trading from others forms of technical analysis is that it's main focus is on raw price data opposed to creating values or plots derived from price history.
Mostly all of the features within this script are generated purely from price action, more specifically; swing highs, swing lows, and market structure... which allows users to automate their analysis of price action for any market / timeframe.
🔶 FEATURES
This script includes many features based on Price Action; these are highlighted below:
Market structure (BOS, CHoCH, CHoCH+, EQH/L) (Internal & Swing) multi-timeframe
Volumetric Order Blocks & mitigation methods (bullish & bearish)
Liquidity Concepts
Trend Line Liquidity Zones
Chart Pattern Liquidity
Liquidity Grabs Feature
Imbalance Concepts MTF w/ multiple mitigation methods
Fair Value Gaps
Balanced Price Range
Activity Asymmetry
Strong/Weak Highs & Lows w/ volume percentages
Premium & Discount Zones included
Candle Coloring based on market structure
Previous Highs/Lows (Daily, Monday's, Weekly, Monthly, Quarterly)
Multi-Timeframe Dashboard (15m, 1h, 4h, 1d)
Built-in alert conditions & Any Alert() Function Call Conditions
Advanced Alerts Creator to create step-by-step alerts with various conditions
+ more (see changelog below for current features)
🔶 BASIC DEMONSTRATION
In the image above we can see a demonstration of the market structure labeling within this indicator. The automatic BOS & CHoCH labels on top of dashed lines give clear indications of breakouts & reversals within the internal market structure (short term price action). The "CHoCH+" label is also demonstrated as it triggers only if price has already made a new higher low, or lower high.
We can also see a solid line with a larger BOS label in the middle of the chart. This label demonstrates a break of structure taking into account the swing market structure (longer term price action). All of these labels are generated in real-time.
🔶 USAGE & EXAMPLES
In the image below we can see how a trade setup could be created using Order Blocks w/ volume metrics to find points of interest in the market, swing / internal market structure to get indications of longer & shorter term reversals, and trend line liquidity zones to find more likely impulses & breakouts within trends.
We can see in the next image below that price came down to the highest volume order block marked out previously as our point of interest for an entry used in confluence with the overall market structure being bullish (swing CHoCH). Due to price closing below the middle Order Block at (24.77%), we saw it was mitigated, and then price revisited liquidity above the Trend Line zone above, leading us to the first Order Block as a target.
You will notice the % values adjust as Order Blocks are touched & mitigated, aligning with the correct volume detected when the Order Block was established.
In the image below we can see more features from within Price Action Concepts™ indicator, including Chart Pattern Liquidity, Fair Value Gaps (one of many Imbalance Concepts), Liquidity Grabs, as well as the primary market structures & OBs.
By using multiple features as such, users can develop a greater interpretation of where liquidity rests in the market, which allows them to develop trading plans a lot easier. Liquidity Grabs are highlighted as blue/red boxes on the wicks during specific price action that indicates the market has made an impulse specifically to take out resting buy or sell side orders.
We can notice in the trade demonstrated below (hindsight example) how price often moves to the areas of the most liquidity, even if unexpected according to classical technical analysis performed by retail traders such as chart patterns. Wicks to take out orders above & potentially trap traders are much more noticeable with features such as these.
The Chart Patterns which can be detected include:
Ascending/Descending Wedges (Asc/Desc Wedge)
Ascending/Descending Broadening Wedges (Asc/Desc BW)
Ascending/Descending/Symmetrical Triangles (Asc/Desc/Sym Triangle)
Double Tops/Bottoms (Double Top/Double BTM)
Head & Shoulders (H&S)
Inverted Head & Shoulders (IH&S)
General support & resistance during undetected patterns
In the image below we can see more features from within the indicator, including Balanced Price Range (another imbalance method similar to FVG), Market Structure Candle Coloring, Accumulation & Distribution zones, Premium & Discount zones w/ a percentage on each zone, the MTF dashboard, as well as the Previous Daily Highs & Lows (one of many highs/lows) displayed on the chart automatically.
The colored candles use more specific market structure analysis, specifically allowing users to visualize when trends are considered "normal" or "strong". By utilizing other features alongside this market structure analysis, such as noticing price retesting the PDL level + the Equilibrium as resistance, a Balanced Price Range below price, the discount with a high 72% metric, and the MTF dashboard displaying an overall bearish structure...
...users can instantly gain a deeper interpretation of price action, make highly confluent trading plans while avoiding classical technical indicators, and use traditional retail trading concepts such as chart patterns / trend lines to their advantage in finding logical areas of liquidity & points of interest in the market.
The image below shows the previous chart zoomed in with 2 liquidity concepts re-enabled & used alongside a new range targeting the same Discount zone.
🔶 SETTINGS
Market Structure Internal: Allows the user to select which internal structures to display (BOS, CHoCH, or None).
Market Structure Swing: Allows the user to select which swing structures to display (BOS, CHoCH, or None).
MTF Scanner: See market structure on various timeframes & how many labels are active consecutively.
Equal Highs & Lows: Displays EQH / EQL labels on chart for detecting equal highs & lows.
Color Candles: Plots candles based on the internal & swing structures from within the indicator on the chart.
Order Blocks Internal: Enables Internal Order Blocks & allows the user to select how many most recent Internal Order Blocks appear on the chart as well as select a color.
Order Blocks Swing: Enables Swing Order Blocks & allows the user to select how many most recent Swing Order Blocks appear on the chart as well as select a color.
Mitigation Method: Allows the user to select how the script mitigates an Order Block (close, wick, or average).
Internal Buy/Sell Activity: Allows the user to display buy/sell activity within Order Blocks & decide their color.
Show Metrics: Allows the user to display volume % metrics within the Order Blocks.
Trend Line Liquidity Zones: Allows the user to display Trend Line Zones on the chart, select the number of Trend Lines visible, & their colors.
Chart Pattern Liquidity: Allows the user to display Chart Patterns on the chart, select the significance of the pattern detection, & their colors.
Liquidity Grabs: Allows the user to display Liquidity Grabs on the chart.
Imbalance Concepts: Allows the user to select the type of imbalances to display on the chart as well as the styling, mitigation method, & timeframe.
Auto FVG Threshold: Filter out non-significant fair value gaps.
Premium/ Discount Zones: Allows the user to display Premium, Discount , and Equilibrium zones on the chart
Accumulation / Distribution: Allows the user to display accumulation & distribution consolidation zones with an optional Consolidation Zig-Zag setting included.
Highs/Lows MTF: Displays previous highs & lows as levels on the chart for the previous Day, Monday, Week, Month, or quarter (3M).
General Styling: Provides styling options for market structure labels, market structure theme, and dashboard customization.
Any Alert() Function Call Conditions: Allows the user to select multiple conditions to use within 1 alert.
🔶 CONCLUSION
Price action trading is a widely respected method for its simplicity & realistic approach to understanding the market itself. Price Action Concepts™ is an extremely comprehensive product that opens the possibilities for any trader to automatically display useful metrics for trading price action with enhanced details in each. While this script is useful, it's critical to understand that past performance is not necessarily indicative of future results and there are many more factors that go into being a profitable trader.
🔶 HOW TO GET ACCESS
You can see the Author's instructions below to get instant access to this indicator & our premium suite.
SMC Pro+ ICT v4 Enhanced - FINAL🎯 SMC Pro+ ICT v4 Enhanced - Complete Smart Money Trading System📊 Professional All-in-One Indicator for Smart Money Concepts & ICT MethodologyThe SMC Pro+ ICT v4 Enhanced is a comprehensive trading system that combines Smart Money Concepts (SMC) with Inner Circle Trader (ICT) methodology. This indicator provides institutional-grade market structure analysis, liquidity mapping, and volume profiling in one powerful package.✨ CORE FEATURES🏗️ Advanced Market Structure Detection
MSS (Market Structure Shift) - Identifies major trend reversals with precision
BOS (Break of Structure) - Confirms trend continuation moves
CHoCH (Change of Character) - Detects internal structure shifts
Modern LuxAlgo-Style Lines - Clean, professional visualization
Dual Sensitivity System - External structure (major swings) + Internal structure (minor swings)
Customizable Labels - Tiny, Small, or Normal sizes
Structure Break Visualization - Clear break point markers
💎 Supply & Demand Zones (POI - Point of Interest)
Institutional Order Blocks - Where smart money enters/exits
ATR-Based Zone Sizing - Dynamically adjusted to market volatility
Smart Overlap Detection - Prevents cluttered charts
Historical Zone Tracking - Maintains up to 50 zones
POI Central Lines - Pinpoint entry/exit levels
Auto-Extension - Zones extend to current price
Auto-Cleanup - Removes broken zones automatically
📦 Fair Value Gap (FVG) Detection
Bullish & Bearish FVGs - Institutional inefficiencies
Consequent Encroachment (CE) - 50% fill levels
Auto-Delete Filled Gaps - Keeps charts clean
Customizable Lookback - 1-30 days of history
Color-Coded Zones - Easy visual identification
CE Line Styles - Dotted, Dashed, or Solid
🚀 Enhanced PVSRA Volume Analysis
This is one of the most powerful features:
200% Volume Candles - Extreme institutional activity (Lime/Red)
150% Volume Candles - High institutional interest (Blue/Fuchsia)
Volume Climax Detection - Major reversal signals with 2.5x+ volume
Exhaustion Signals - Identifies buying/selling exhaustion with high accuracy
Enhanced Volume Divergence - NEW! High-quality reversal detection
Price makes lower low, Volume makes higher low = Bullish Divergence
Price makes higher high, Volume makes lower high = Bearish Divergence
Strict trend context filtering for accuracy
Rising/Falling Volume Patterns - Momentum confirmation (allows 1 exception in 3 bars)
Volume Spread Analysis - Price range × Volume for true strength
Body/Wick Ratio Analysis - Candle structure quality
ATR Normalization - Adjusts for different market volatility
Volume Profile Indicators - 🔥 EXTREME, ⚡ VERY HIGH, 📈 HIGH, ✅ ABOVE AVG
💧 Advanced Liquidity System
Smart money targets these levels:
Weekly High/Low Liquidity - Major institutional targets
Daily High/Low Liquidity - Intraday key levels
4H Session Liquidity - Short-term targets
Distance Indicators - Shows % distance from current price
Strength Indicators - Identifies high-probability sweeps
Swept Level Detection - Tracks executed liquidity grabs
Customizable Line Styles - Width, length, offset controls
Color-Coded Levels - Easy visual hierarchy
🎯 Master Bias System
Data-driven directional bias with 9-factor scoring:
Bull/Bear Bias Calculation - 0-100% scoring system
Multi-Timeframe Analysis - Daily, 4H, 1H trend alignment
Kill Zone Integration - London (2-5 AM) & NY (8-11 AM) sessions
EMA Alignment Factor - Trend confirmation
Volume Confirmation - Adds 5% when volume supports direction
Range Filter Integration - Adds 10% for trending markets
Session Context - Above/below session midpoint scoring
Bias Strength Rating - STRONG (>75%), MODERATE (60-75%), WEAK (<60%)
Real-Time Updates - Dynamic recalculation
📈 Premium & Discount Zones
Fibonacci-based institutional pricing:
Extreme Premium - Above 78.6% (Overvalued)
Premium Zone - 61.8% - 78.6% (Expensive)
Equilibrium - 38.2% - 61.8% (Fair Value)
Discount Zone - 21.4% - 38.2% (Cheap)
Extreme Discount - Below 21.4% (Undervalued)
Visual Zone Boxes - Color-coded for instant recognition
200-500 Bar Lookback - Customizable range calculation
🔄 Range Filter
Advanced trend detection:
Smoothed Range Calculation - Eliminates noise
Dynamic Support/Resistance - Auto-adjusting levels
Upward/Downward Counters - Measures trend strength
Color-Coded Line - Green (uptrend), Red (downtrend), Orange (ranging)
Adjustable Period - 1-200 bars
Multiplier Control - Fine-tune sensitivity (0.1-10.0)
🌊 Liquidity Zones (Vector Zones)
PVSRA-based horizontal liquidity:
Above Price Zones - Resistance clusters
Below Price Zones - Support clusters
Maximum 500 Zones - Professional-grade capacity
Body/Wick Definition - Choose zone boundaries
Auto-Cleanup - Removes cleared zones
Color Override - Custom styling options
Transparency Control - 0-100% opacity
📊 EMA System
Triple EMA trend confirmation:
Fast EMA (9) - Green line - Immediate trend
Medium EMA (21) - Blue line - Short-term trend
Slow EMA (50) - Red line - Major trend
EMA Alignment Detection - Bull/Bear stack confirmation
Dashboard Integration - Status: 📈 BULL ALIGN, 📉 BEAR ALIGN, 🔀 MIXED
Adjustable Lengths - Customize all three EMAs (5-200)
🎯 IDM (Institutional Decision Maker) Levels
Key institutional price levels:
Latest IDM Detection - 20-bar pivot lookback
Extended Lines - Projects 50 bars into future
Customizable Styles - Solid, Dashed, or Dotted
Line Width Control - 1-5 pixels
Color Selection - Match your chart theme
Price Label - Shows exact level with tick precision
📱 Professional Dashboard
Real-time market intelligence panel:
🎯 SIGNAL - 🟢 LONG, 🔴 SHORT, ⏳ WAIT, 🛑 NO TRADE
🎲 BIAS - Bull/Bear with STRONG/MODERATE/WEAK rating
📊 BULL/BEAR Scores - 0-100% percentage display
💎 ZONE - Current premium/discount location
🕐 KZ - Kill Zone status (🇬🇧 LONDON/🇺🇸 NY/⏸️ OFF)
🏗️ STRUCT - Market structure status (BULLISH/BEARISH/NEUTRAL)
⚡ EVENT - Last structure event (MSS/BOS)
⚡ INT - Internal structure trend
🎯 IDM - Latest institutional level
📊 EMA - EMA alignment status
🔄 RF - Range Filter direction
📊 PVSRA - Volume status (🚀 CLIMAX/📈 RISING/📉 FALLING)
📅 MTF - Multi-timeframe alignment (✅ FULL/⚠️ PARTIAL/❌ CONFLICT)
💪 CONF - Confidence score (0-100%)
📊 VOL - Volume ratio (e.g., 1.8x average)
Advanced Metrics (Toggle On/Off):
📏 RSI - Value + Status (OVERBOUGHT/STRONG/NEUTRAL/WEAK/OVERSOLD)
📈 MACD - Value + Direction (BULL/BEAR)
🌪️ VOL - Volatility state (⚠️ EXTREME/🔥 HIGH/📊 NORMAL/😴 LOW)
🔊 VOL PROF - Volume profile ratio
⏱️ TF - Current timeframe
Dashboard Customization:
4 Positions - Top Left, Top Right, Bottom Left, Bottom Right
3 Sizes - Small, Normal, Large
2 Modes - Compact (MTF combined) or Full (separate rows)
Professional Design - Dark theme with color-coded cells
🎮 TRADING SIGNALS & SETUP SCORING🟢 LONG Setup Requirements (9-Factor Confidence Score)
MTF Alignment - Daily/4H/1H/Structure all bullish (+2 points for full, +1 for partial)
Volume Confirmation - Above 1.2x average (+1 point)
Structure Event - MSS or BOS bullish (+2 points)
EMA Alignment - 9 > 21 > 50 (+1 point)
Kill Zone Active - London/NY + Bull bias >75% (+2 points)
Bias Match - Master bias matches structure trend (+1 point)
Confidence Threshold - >60% minimum for signal
🔴 SHORT Setup Requirements
Same 9-factor system but inverted for bearish conditions.💪 Confidence Levels
75-100% - ⭐ HIGH CONFIDENCE (Strong setup, all factors aligned)
50-74% - ⚠️ MODERATE (Good setup, partial alignment)
0-49% - ❌ LOW CONFIDENCE (Wait for better setup)
🎯 Signal Output
🟢 LONG - Bull bias + Bullish structure + >60% confidence
🔴 SHORT - Bear bias + Bearish structure + >60% confidence
⏳ WAIT LONG - Bull bias but low confidence
⏳ WAIT SHORT - Bear bias but low confidence
🛑 NO TRADE - Neutral bias or conflicting signals
🔔 COMPREHENSIVE ALERT SYSTEM (12 Alerts)Structure Alerts
⚡ MSS Bullish - Major bullish reversal
⚡ MSS Bearish - Major bearish reversal
📈 BOS Bullish - Bullish continuation
📉 BOS Bearish - Bearish continuation
⚠️ CHoCH Bullish - Internal bullish shift
⚠️ CHoCH Bearish - Internal bearish shift
Bias & Confidence Alerts
🟢 Bias Shift Bull - Master bias turns bullish
🔴 Bias Shift Bear - Master bias turns bearish
⭐ High Confidence - Setup reaches 75%+ confidence
Volume Alerts (High Probability)
🚀 Volume Climax Buy - Extreme bullish volume spike
💥 Volume Climax Sell - Extreme bearish volume spike
⚠️ Selling Exhaustion - Potential bullish reversal
⚠️ Buying Exhaustion - Potential bearish reversal
📊 Bullish Volume Divergence - High-quality bullish reversal signal
📊 Bearish Volume Divergence - High-quality bearish reversal signal
🎨 EXTENSIVE CUSTOMIZATIONColors & Styling
✅ All colors customizable for every component
✅ Supply/Demand zone colors + outlines
✅ FVG colors (bullish/bearish)
✅ PVSRA candle colors (6 types)
✅ Liquidity level colors (Weekly/Daily/4H/Swept)
✅ Structure line colors
✅ Premium/Equilibrium/Discount zone colorsDisplay Controls
✅ Toggle each feature on/off independently
✅ Adjustable sensitivities (Structure: 5-30, Internal: 3-15)
✅ Label size controls (Tiny/Small/Normal)
✅ Line width adjustments (1-5 pixels)
✅ Transparency controls (0-100%)
✅ Extension lengths (20-100 bars)
✅ Lookback periods (50-500 bars)Volume Settings
✅ PVSRA symbol override (trade one asset, analyze another)
✅ Climax threshold (2.0-5.0x)
✅ Rising volume bar count (2-5 bars)
✅ Divergence filters (Strict/Lenient)
✅ Divergence minimum bars (10-30)
✅ Volume threshold multiplier (1.0-2.0x)Dashboard Settings
✅ Position (4 corners)
✅ Size (Small/Normal/Large)
✅ Compact/Full mode
✅ Show/Hide advanced metrics
✅ Show/Hide EMA status💡 BEST PRACTICES & USAGE TIPS⏰ Optimal Timeframes
Scalping - 1m, 5m (Use Kill Zones, Volume Climax, FVG)
Day Trading - 5m, 15m, 1H (Use Structure, Liquidity, Bias)
Swing Trading - 4H, Daily (Use MTF, Premium/Discount, Structure)
Position Trading - Daily, Weekly (Use major structure, liquidity)
🎯 Asset Classes
✅ Forex - All pairs (especially majors during Kill Zones)
✅ Crypto - BTC, ETH, altcoins (24/7 liquidity)
✅ Stocks - All stocks and indices (use session times)
✅ Commodities - Gold, Silver, Oil (high volume periods)
✅ Indices - S&P 500, NASDAQ, DAX, etc.🔥 High-Probability Setups
The Perfect Storm
MSS in direction of daily trend
Kill Zone active
Volume climax
Confidence >75%
Price in discount (long) or premium (short)
Volume Divergence Play
Enhanced volume divergence signal
CHoCH confirms direction change
Price near liquidity level
FVG forms for entry
Liquidity Sweep
Price sweeps weekly/daily high/low
Immediate rejection (selling/buying exhaustion)
Structure shift (MSS)
Volume confirmation
Structure Retest
BOS breaks structure
Price returns to POI/FVG
Volume confirms (>1.2x)
Kill Zone active
📊 Multi-Timeframe Analysis
Higher Timeframe - Identify trend & structure (Daily/4H)
Trading Timeframe - Find entries (15m/1H)
Lower Timeframe - Precise entries (1m/5m)
Look for MTF alignment - Dashboard shows ✅ FULL or ⚠️ PARTIAL
⚠️ Risk Management
Always use stop-loss (below/above recent structure)
Position size: 1-2% risk per trade
Target liquidity levels for take profit
Use supply/demand zones for SL placement
Watch for exhaustion signals near targets
Smart Money Decoded [GOLD]Title: Smart Money Decoded
Description:
Introduction
Smart Money Decoded is a comprehensive, institutional-grade visualization suite designed to simplify the complex world of Smart Money Concepts (SMC). While many indicators flood the chart with noise, this tool focuses on clarity, precision, and high-probability structure.
This script is built for traders who follow the "Inner Circle Trader" (ICT) methodologies but struggle to identify valid Zones, Displacement, and Liquidity Sweeps in real-time.
💎 Key Features & Logic
1. Refined Market Structure (BOS & CHoCH)
Instead of marking every minor pivot, this script uses a filtered Swing High/Low detection system.
HH/LL/LH/HL Labels: Only significant structure points are mapped.
BOS (Break of Structure): Marks trend continuations in the direction of the bias.
CHoCH (Change of Character): Marks potential trend reversals.
2. Advanced Order Blocks (with "Strict Mode")
Not all down-candles before an up-move are Order Blocks. This script separates the weak from the strong.
Standard OBs: Visualized with standard transparency.
⚡ SWEEP OBs (High Probability): Order Blocks that explicitly swept liquidity (Stop Hunt) before the reversal are highlighted with a thicker border, brighter color, and a ⚡ symbol. These are your high-probability "Turtle Soup" entries.
Strict Mode Toggle: In the settings, you can choose to hide all weak OBs and only see the ones that swept liquidity.
3. Dynamic Breaker Blocks
A true ICT Breaker is a failed Order Block that trapped liquidity.
This script automatically detects when a valid OB is mitigated (broken through) and projects it forward as a Breaker Block.
This ensures you are trading off valid flipped zones (Support becomes Resistance, Resistance becomes Support).
4. Fair Value Gaps (FVG)
Automatically detects Imbalances (Imbalance/Inefficiency).
Includes an ATR Filter to ignore tiny, insignificant gaps, keeping your chart clean.
Option to show the Consequent Encroachment (50% CE) level for precision entries.
5. Liquidity Zones (BSL / SSL)
Automatically plots Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) at key swing points.
Once price sweeps these levels, the zone is removed or marked as "Swept," helping you identify when the draw on liquidity has been met.
6. Institutional Data Panel
A dashboard in the top right corner displays:
Market Bias: Bullish/Bearish/Neutral based on structure.
Premium/Discount: Tells you if price is in the expensive (Premium) or cheap (Discount) part of the current dealing range.
Active Zones: Counts of current open arrays.
⚙️ How To Use This Indicator
Identify Bias: Look at the Structure Labels (HH/LL) and the Panel. Are we making Higher Highs?
Wait for the Trap: Look for a Liquidity Sweep (BSL/SSL taken) or a ⚡ Sweep OB.
Entry Confirmation: Watch for a return to a Fair Value Gap (FVG) or a retest of a Breaker Block (BRK).
Manage Risk: Use the visuals to place stops above/below invalidation points.
Customization:
Go to the settings to toggle "Strict Mode" for Order Blocks, change colors to match your theme, or adjust the lookback periods to fit your specific asset (Forex, Crypto, or Indices).
📚 Credits & Acknowledgments
This script is an educational tool based on the public teachings of Michael J. Huddleston (The Inner Circle Trader - ICT).
Concepts used: Order Blocks, Breakers, FVGs, Market Structure, Liquidity Pools.
Credit is fully given to ICT for originating these concepts and sharing them with the world.
⚠️ Disclaimer
This script is NOT affiliated with, endorsed by, or connected to Michael J. Huddleston (ICT) in any way. It is an independent coding project intended for educational purposes and visual assistance.
Trading involves substantial risk. This indicator does not guarantee profits. Always use proper risk management. Trust your analysis first, and use indicators as confluence.
#Smart Money Concepts, #SMC, #ICT,#Liquidity, #Market Structure, #Trend, #Price Action.
CandelaCharts - Turtle Soup Model📝 Overview
The ICT Turtle Soup Model indicator is a precision-engineered tool designed to identify high-probability reversal setups based on ICT’s renowned Turtle Soup strategy.
The Turtle Soup Model is a classic reversal setup that exploits false breakouts beyond previous swing highs or lows. It targets areas where retail traders are trapped into breakout trades, only for the price to reverse sharply in the opposite direction.
Price briefly breaks a previous high (for short setups) or low (for long setups), triggering stop orders and pulling in breakout traders. Once that liquidity is taken, smart money reverses price back inside the range, creating a high-probability fade setup.
📦 Features
Liquidity Levels: Projects forward-looking liquidity levels after a Turtle Soup model is formed, highlighting potential price targets. These projected zones act as magnet levels—areas where price is likely to reach based on the liquidity draw narrative. This allows traders to manage exits and partials with more precision.
Market Structure Shift (MSS): Confirms reversal strength by detecting a bullish or bearish MSS after a sweep. Acts as a secondary confirmation to filter out weak setups.
Custom TF Pairing: Choose your own combination of entry timeframe and context timeframe. For example, trade 5m setups inside a 1h HTF bias — perfect for aligning microstructure with macro intent.
HTF & LTF PD Arrays: Displays HTF PD Arrays (e.g., Fair Value Gaps, Inversion Fair Value Gaps) to serve as confluence zones.
History: Review and backtest past Turtle Soup setups directly on the chart. Toggle historical models on/off to study model behavior across different market conditions.
Killzone Filter: Limit signals to specific trading sessions or time blocks (e.g., New York AM, London, Asia, etc). Avoid signals in low-liquidity or choppy environments.
Standard Deviation: Calculates and projects four levels of standard deviation from the point of model confirmation. These zones help identify overextended moves, mean-reversion opportunities, and confluence with liquidity or PD arrays.
Dashboard: The dashboard displays the active model type, remaining time of the HTF candle, current bias, asset name, and date—providing real-time context and signal clarity at a glance.
⚙️ Settings
Core
Status: Filter models based on status
Bias: Controls what model type will be displayed, bullish or bearish
Fractal: Controls the timeframe pairing that will be used
High Probability Models: Detects and plots only the high-probability models
Sweeps
Sweep: Shows the sweep that forms a model
I-sweep: Controls the visibility of invalidated sweeps
D-purge: Plots the double purge sweeps
S-area: Highlights the sweep area
Liquidity
Liquidity: Displays the liquidity levels that belong to the model
MSS
MSS: Displays the Market Structure Shift for a model
History
History: Controls the number of past models displayed on the chart
Filters
Asia: Filter models based on Asia Killzone hours
London: Filter models based on London Killzone hours
NY AM: Filter models based on NY AM Killzone hours
NY Launch: Filter models based on NY Launch Killzone hours
NY PM: Filter models based on NY PM Killzone hours
Custom: Filter models based on user Custom hours
HTF
Candles: Controls the number of HTF candles that will be visible on the chart
Candles T: Displays the model’s third timeframe candle, which serves as a confirmation of directional bias
NY Open: Display True Day Open line
Offset: Controls the distance of HTF from the current chart
Space: Controls the space between HTF candles
Size: Controls the size of HTF candles
PD Array: Displays ICT PD Arrays
CE Line: Style the equilibrium line of PD Array
Border: Style the border of the PD Array
LTF
H/L Line: Displays on the LTF chart the High and Low of each HTF candle
O/C Line: Displays on the LTF chart the Open and Close of each HTF candle
PD Array: Displays ICT PD Arrays
CE Line: Style the equilibrium line of PD Array
Border: Style the border of the PD Array
Standard Deviation
StDev: Controls standard deviation of available levels
Labels: Controls the size of standard deviation levels
Lines: Controls the line widths and color of standard deviation levels
Dashboard
Panel: Display information about the current model
💡 Framework
The Turtle Soup Model is designed to detect and interpret false breakout patterns by analyzing key price action components, each playing a vital role in identifying liquidity traps and generating actionable reversal signals.
The model incorporates the following timeframe pairing:
15s - 5m - 15m
1m - 5m - 1H
2m - 15m - 2H
3m - 30m - 3H
5m - 60m - 4H
15m - 1H - 8H
30m - 3H - 12H
1H - 4H - 1D
4H - 1D - 1W
1D - 1W - 1M
1W - 1M - 6M
1M - 6M - 12M
Below are the key components that make up the model:
Sweep
D-purge
MSS
Liquidity
Standard Deviation
HTF & LTF PD Arrays
The Turtle Soup Model operates through a defined lifecycle that identifies its current state and determines the validity of a trade opportunity.
The model's lifecycle includes the following statuses:
Formation (grey)
Invalidation (red)
Pre-Invalidation (purple)
Success (green)
By incorporating the phases of Formation, Invalidation, and Success, traders can effectively manage risk, optimize position handling, and capitalize on the high-probability opportunities presented by the Turtle Soup Model.
⚡️ Showcase
Introducing the Turtle Soup Model — a powerful trading tool engineered to detect high-probability false breakout reversals. This indicator helps you pinpoint liquidity sweeps, confirm market structure shifts, and identify precise entry and exit points, enabling more confident, informed, and timely trading decisions.
LTF PD Array
LTF PD Arrays are essential for model formation—a valid Turtle Soup setup will only trigger if a qualifying LTF PD Array is present near the sweep zone.
HTF PD Array
HTF PD Arrays provide macro-level context and are used to validate the direction and strength of the potential reversal.
Timeframe Alignment
In the Turtle Soup trading model, timeframe alignment is an essential structural component. The model relies on multi-timeframe context to identify high-probability reversal setups based on failed breakouts.
High-Probability Model
A high-probability setup forms when key elements align: a Sweep, Market Structure Shift (MSS), LTF and HTF PD Arrays.
Killzone Filters
Filter Turtle Soup Models based on key market sessions: Asia, London, New York AM, New York Launch, and New York PM . This allows you to focus on high-liquidity periods where smart money activity is most likely to occur, improving both the quality and timing of your trade setups.
Unlock your trading edge with the Turtle Soup Model — your go-to tool for sharper insights, smarter decisions, and more confident execution in the markets.
🚨 Alerts
This script offers alert options for all model types. The alerts need to be set up manually from TradingView.
Bearish Model
A bearish model alert is triggered when a model forms, signaling a high sweep, MS,S and LTF PD Array.
Bullish Model
A bullish model alert is triggered when a model forms, signaling a low sweep, MSS and LTF PD Array.
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
CandelaCharts - Buyside & Sellside 📝 Overview
The Buyside & Sellside Liquidity Indicator is designed to identify and emphasize one of the foundational concepts within the ICT (Inner Circle Trader) trading methodology: liquidity levels.
This tool focuses on pinpointing key areas in the market where buy-side and sell-side liquidity is concentrated, providing traders with insights into potential price targets, reversal zones, and institutional order flow behavior.
By highlighting these liquidity zones, the indicator serves as a strategic aid in understanding market dynamics and enhancing decision-making in alignment with ICT principles.
📦 Features
Buyside & Sellside Liquidity
Invalidated Liquidity
Threshold
Styling
⚙️ Settings
Liquidity: Controls visibility of Bullish/Bearish Liquidity levels.
Invalidated: Displays the invalidated liquidity levels.
Levels: Controls the number of Liquidity levels that will be displayed.
Line Style: Customize the line style and width.
Threshold: Filter by swing points the Liquidity levels.
Labels: Control the Labels visibility.
⚡️ Showcase
Buyside & Sellside
Invalidated
🚨 Alerts
This script offers alert options for all signal types.
Bearish Signal
A bearish signal is generated when the price reaches a Buyside Liquidity level.
Bullish Signal
A bullish signal is generated when the price reaches a Sellside Liquidity level.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
RSI Analysis with Statistical Summary Scientific Analysis of the Script "RSI Analysis with Statistical Summary"
Introduction
I observed that there are outliers in the price movement liquidity, and I wanted to understand the RSI value at those points and whether there are any notable patterns. I aimed to analyze this statistically, and this script is the result.
Explanation of Key Terms
1. Outliers in Price Movement Liquidity: An outlier is a data point that significantly deviates from other values. In this context, an outlier refers to an unusually high or low liquidity of price movement, which is the ratio of trading volume to the price difference between the open and close prices. These outliers can signal important market changes or unusual trading activities.
2. RSI (Relative Strength Index): The RSI is a technical indicator that measures the speed and change of price movements. It ranges from 0 to 100 and helps identify overbought or oversold conditions of a trading instrument. An RSI value above 70 indicates an overbought condition, while a value below 30 suggests an oversold condition.
3. Mean: The mean is a measure of the average of a dataset. It is calculated by dividing the sum of all values by the number of values. In this script, the mean of the RSI values is calculated to provide a central tendency of the RSI distribution.
4. Standard Deviation (stdev): The standard deviation is a measure of the dispersion or variation of a dataset. It shows how much the values deviate from the mean. A high standard deviation indicates that the values are widely spread, while a low standard deviation indicates that the values are close to the mean.
5. 68% Confidence Interval: A confidence interval indicates the range within which a certain percentage of values of a dataset lies. The 68% confidence interval corresponds to a range of plus/minus one standard deviation around the mean. It indicates that about 68% of the data points lie within this range, providing insight into the distribution of values.
Overview
This Pine Script™, written in Pine version 5, is designed to analyze the Relative Strength Index (RSI) of a stock or other trading instrument and create statistical summaries of the distribution of RSI values. The script identifies outliers in price movement liquidity and uses this information to calculate the frequency of RSI values. At the end, it displays a statistical summary in the form of a table.
Structure and Functionality of the Script
1. Input Parameters
- `rsi_len`: An integer input parameter that defines the length of the RSI (default: 14).
- `outlierThreshold`: An integer input parameter that defines the length of the outlier threshold (default: 10).
2. Calculating Price Movement Liquidity
- `priceMovementLiquidity`: The volume is divided by the absolute difference between the close and open prices to calculate the liquidity of the price movement.
3. Determining the Boundary for Liquidity and Identifying Outliers
- `liquidityBoundary`: The boundary is calculated using the Exponential Moving Average (EMA) of the price movement liquidity and its standard deviation.
- `outlier`: A boolean value that indicates whether the price movement liquidity exceeds the set boundary.
4. Calculating the RSI
- `rsi`: The RSI is calculated with a period length of 14, using various moving averages (e.g., SMA, EMA) depending on the settings.
5. Storing and Limiting RSI Values
- An array `rsiFrequency` stores the frequency of RSI values from 0 to 100.
- The function `f_limit_rsi` limits the RSI values between 0 and 100.
6. Updating RSI Frequency on Outlier Occurrence
- On an outlier occurrence, the limited and rounded RSI value is updated in the `rsiFrequency` array.
7. Statistical Summary
- Various variables (`mostFrequentRsi`, `leastFrequentRsi`, `maxCount`, `minCount`, `sum`, `sumSq`, `count`, `upper_interval`, `lower_interval`) are initialized to perform statistical analysis.
- At the last bar (`bar_index == last_bar_index`), a loop is run to determine the most and least frequent RSI values and their frequencies. Sum and sum of squares of RSI values are also updated for calculating mean and standard deviation.
- The mean (`mean`) and standard deviation (`stddev`) are calculated. Additionally, a 68% confidence interval is determined.
8. Creating a Table for Result Display
- A table `resultsTable` is created and filled with the results of the statistical analysis. The table includes the most and least frequent RSI values, the standard deviation, and the 68% confidence interval.
9. Graphical Representation
- The script draws horizontal lines and fills to indicate overbought and oversold regions of the RSI.
Interpretation of the Results
The script provides a detailed analysis of RSI values based on specific liquidity outliers. By calculating the most and least frequent RSI values, standard deviation, and confidence interval, it offers a comprehensive statistical summary that can help traders identify patterns and anomalies in the RSI. This can be particularly useful for identifying overbought or oversold conditions of a trading instrument and making informed trading decisions.
Critical Evaluation
1. Robustness of Outlier Identification: The method of identifying outliers is solely based on the liquidity of price movement. It would be interesting to examine whether other methods or additional criteria for outlier identification would lead to similar or improved results.
2. Flexibility of RSI Settings: The ability to select various moving averages and period lengths for the RSI enhances the adaptability of the script, allowing users to tailor it to their specific trading strategies.
3. Visualization of Results: While the tabular representation is useful, additional graphical visualizations, such as histograms of RSI distribution, could further facilitate the interpretation of the results.
In conclusion, this script provides a solid foundation for analyzing RSI values by considering liquidity outliers and enables detailed statistical evaluation that can be beneficial for various trading strategies.
Fractal Consolidations [Pro+]Introduction:
Fractal Consolidations Pro+ pushes the boundaries of Algorithmic Price Delivery Analysis. Tailored for traders seeking precision and efficiency to unlock hidden insights, this tool empowers you to dissect market Consolidations on your terms, live, in all asset classes.
What is a Fractal Consolidation?
Consolidations occur when price is trading in a range. Normally, Consolidation scripts use a static number of "lookback candles", checking whether price is continuously trading inside the highest and lowest price points of said Time window.
After years spent studying price action and numerous programming attempts, this tool succeeds in veering away from the lookback candle approach. This Consolidation script harnesses the delivery mechanisms and Time principles of the Interbank Price Delivery Algorithm (IPDA) to define Fractal Consolidations – solely based on a Timeframe Input used for context.
Description:
This concept was engineered around price delivery principles taught by the Inner Circle Trader (ICT). As per ICT, it's integral for an Analyst to understand the four phases of price delivery: Consolidation , Expansion , Retracement , and Reversal .
According to ICT, any market movement originates from a Consolidation, followed by an Expansion .
When Consolidation ranges begin to break and resting liquidity is available, cleaner Expansions will take place. This tool's value is to visually aid Analysts and save Time in finding Consolidations in live market conditions, to take advantage of Expansion moves.
CME_MINI:ES1! 15-Minute Consolidation setting up an Expansion move, on the 10 Minute Chart:
Fractal Consolidations Pro+ doesn't only assist in confirming Higher Timeframe trend continuations and exposing opportunities on Lower Timeframes. It's also designed for both advanced traders and new traders to save Time and energy in navigating choppy or rangebound environments.
CME_MINI:ES1! 30 Minute Consolidation forming Live, on the 5 Minute Chart:
By analyzing past price action, traders will find algorithmic signatures when Consolidations are taking place, therefore providing a clearer view of where and when price is likely to contract, continue consolidating, breakout, retrace, or reverse. A prominent signature to consider when using this script is ICT's Market Maker Buy/Sell Models. These signatures revolve around the engineering of Consolidations to manipulate price in a specific direction, to then reverse at the appropriate Time. Each stage of the Market Maker Model can be identified and taken advantage of using Fractal Consolidations.
CME_MINI:NQ1! shift of the Delivery Curve from a Sell Program to a Buy Program, Market Maker Buy Model
Key Features:
Tailored Timeframes: choose the Timeframe that suits your model. Whether you're a short-term enthusiast eyeing 1 Hour Consolidations or a long-term trend follower analyzing 4 Hour Consolidations, this tool gives you the freedom to choose.
FOREXCOM:EURUSD Fractal Consolidations on a 15 Minute Chart:
Auto-Timeframe Convenience: for those who prefer a more dynamic and adaptive approach, our Auto Timeframe feature effortlessly adjusts to the most relevant Timeframe, ensuring you stay on top of market consolidations without manually adjusting settings.
Consolidation Types: define consolidations as contractions of price based on either its wick range or its body range.
COMEX:GC1! 4 Hour Consolidation differences between Wick-based and Body-based on a 1 Hour Chart:
Filtering Methods: combine previous overlapping Consolidations, merging them into one uniform Consolidation. This feature is subject to repainting only while a larger Consolidation is forming , as smaller Consolidations are confirmed. However once established, the larger Consolidation will not repaint .
FOREXCOM:GBPUSD 15 Minute Consolidation Differences between Filter Consolidations ON and OFF:
IPDA Data Range Filtering: this feature gives the Analyst control for selective visibility of Consolidations in the IPDA Data Range Lookback . The Analyst can choose between 20, 40, and 60 days as per ICT teachings, or manually adjust through Override.
INDEX:BTCUSD IPDA40 Data Range vs. IPDA20 Data Range:
Extreme Float: this feature provides reference points when the price is outside the highest or lowest liquidity levels in the chosen IPDA Data Range Lookback. These Open Float Extremes offer critical insights when the market extends beyond the Lookback Consolidation Liquidity Levels . This feature helps identify liquidity extremes of interest that IPDA will consider, which is crucial for traders in understanding market movements beyond the IPDA Data Ranges.
INDEX:ETHUSD Extreme Float vs. Non-Extreme Float Liquidity:
IPDA Override: the Analyst can manually override the default settings of the IPDA Data Range Lookback, enabling more flexible and customized analysis of market data. This is particularly useful for focusing on recent price actions in Lower Timeframes (like viewing the last 3 days on a 1-minute timeframe) or for incorporating a broader data range in Higher Timeframes (like using 365 days to analyze Weekly Consolidations on a daily timeframe).
Liquidity Insight: gain a deeper understanding of market liquidity through customizable High Resistance Liquidity Run (HRLR) and Low Resistance Liquidity Run (LRLR) Consolidation colors. This feature helps distinguishing between HRLR (high resistance, delayed price movement) and LRLR (low resistance, smooth price movement) Consolidations, aiding in quick assessment of market liquidity types.
TVC:DXY Low Resistance vs. High Resistance Consolidation Liquidity Behaviour and Narrative:
Liquidity Raid Type: decide whether to categorize a Consolidation liquidity raid by a wick or body trading through a level.
CBOT:ZB1! Wick vs. Body Liquidity Raid Type:
Customizable User Interface: tailor the visual representation to align with your preferences. Personalize your trading experience by adjusting the colors of consolidation liquidity (highs and lows) and equilibrium, as well as line styles.
Płatny skrypt
Titan VSA + SMC Prime (Professional Institutional System)Titan VSA + SMC Prime is a comprehensive, hybrid trading system designed to bridge the gap between Volume Spread Analysis (VSA) and Smart Money Concepts (SMC) By Sultan of Multan. This script is built for traders who want to identify institutional activity, spot liquidity traps, and trade in harmony with the "Smart Money."
Unlike standard indicators that repaint or lag, Titan Prime focuses on price action, structural shifts, and volume anomalies to generate high-probability setups.
🔥 Key Features
1. Smart Money Concepts (SMC) Suite
Market Structure: Automatically maps BOS (Break of Structure) and CHoCH (Change of Character) with real-time trend identification (Bullish/Bearish).
Institutional Zones: clearly plots Order Blocks (OB), Breaker Blocks (BB), Fair Value Gaps (FVG), and Supply/Demand Zones.
Mitigation Tracking: Zones are automatically marked as "Mitigated" or removed once price has tested them, keeping your chart clean.
Premium & Discount Zones: Automatically draws the Equilibrium (EQ) to help you sell in Premium and buy in Discount areas.
2. Advanced Liquidity & Traps
Liquidity Sweeps (⚔): Identifies when key Highs or Lows are swept to grab liquidity.
Inducement (IDM 🪤): Highlights short-term highs/lows that act as "traps" for retail traders before the real move occurs. This helps you avoid false breakouts.
3. Volume Spread Analysis (VSA) Engine
Volume Bar Coloring: Candles are color-coded based on volume intensity:
🟨 Yellow: Ultra High Volume (Institutional Activity).
⬜ Gray: Low Volume (Lack of interest).
VSA Signals: Automatically detects powerful VSA patterns including:
No Demand (ND) / No Supply (NS)
Stopping Volume & Climaxes (SC/BC)
UpThrusts (UT) & Springs
Effort to Rise / Fall
Absorption
4. The "Smart Entry" System
This is the core of the indicator. It does not spam signals. It waits for a specific institutional sequence:
Liquidity Sweep: Price grabs liquidity.
Displacement: Price reverses aggressively.
Retest: The system waits for a pullback to the Order Block or FVG.
Confirmation: Only then does it display a "RETEST COMPLETE ✅ - SMART ENTRY" label with suggested TP/SL levels.
5. Professional Dashboards
Trade Status Panel (Top-Right): Monitors active signals, Entry, Stop Loss, Take Profit, and VSA Trend Score.
SMC Status Panel (Bottom-Right): A live scanner showing the status of Supply/Demand, FVGs, Structure, and overall Market Bias at a glance.
How to Use
Identify Trend: Use the dashboard to check if the market structure is Bullish or Bearish.
Wait for Traps: Look for IDM or Liquidity Sweep (⚔) labels. Smart moves usually happen after these traps.
Entry Confirmation: Do not enter blindly. Wait for the "RETEST COMPLETE" label which confirms that price has respected a Smart Money Zone.
Confluence: The best trades occur when an SMC Zone aligns with a VSA Signal (e.g., A Buying Climax inside a Demand Zone).
Customization
Visual Control: Fully adjustable text sizes, colors, and box lengths to fit your charting style.
Zoom Stability: Labels and text are pinned to ensure they remain readable when zooming in or out.
Disclaimer
This tool is for educational and analytical purposes. Always manage your risk and do not rely solely on any single indicator for financial decisions.
Pressure Pivots - MPIPressure Pivots - MPI
A multi-factor reversal detection system built on a proprietary Market Pressure Index (MPI) that combines institutional order flow analysis, liquidity dynamics, and momentum exhaustion to identify high-probability pivot points with automated win rate validation.
What This System Does
This indicator solves the core challenge of reversal trading: distinguishing genuine exhaustion pivots from temporary retracements. It combines six independent detection mechanisms—divergence, liquidity sweeps, order flow imbalance, wick rejection, volume surges, and velocity exhaustion—weighted by reliability and unified through a custom pressure oscillator.
Three-Layer Architecture:
Layer 1 - Market Pressure Index (MPI): Proprietary volume-weighted pressure oscillator that measures buying vs. selling pressure using proportional intrabar allocation and dual-timeframe normalization (-1.0 to +1.0 range).
Layer 2 - Weighted Confluence Engine: Six detection factors scored hierarchically (divergence: 3.0 pts, liquidity: 2.5 pts, order flow: 2.0 pts, velocity: 1.5 pts, wick: 1.5 pts, volume: 1.0 pt). Premium signals (DIV/LIQ/OF) require 6.0+ score, standard signals (STD) require 4.0+ score.
Layer 3 - Automated Win Rate Validation: Every signal tracked forward and validated against actual pivot formation within 10-bar window. Real-time performance statistics displayed by signal type and direction.
The Market Pressure Index - Original Calculation
What MPI Measures: The balance of aggressive buying vs. aggressive selling within each bar, smoothed and normalized to create a continuous oscillator.
Calculation Methodology:
Step 1: Intrabar Pressure Decomposition
Buy Pressure = Volume × (Close - Low) / (High - Low)
Sell Pressure = Volume × (High - Close) / (High - Low)
Net Pressure = Buy Pressure - Sell Pressure
Step 2: Exponential Smoothing
Smooth Pressure = EMA(Net Pressure, 14)
Step 3: Normalization
Avg Absolute Pressure = SMA(|Net Pressure|, 28)
MPI Raw = Smooth Pressure / Avg Absolute Pressure
Step 4: Sensitivity Amplification
MPI = clamp(MPI Raw × 1.5, -1.0, +1.0)
Why This Is Different:
• vs. RSI: RSI measures price momentum without volume context. MPI integrates volume magnitude and distribution within each bar.
• vs. OBV: OBV uses binary classification (up bar = buy volume). MPI uses proportional allocation based on close position within range.
• vs. Money Flow Index: MFI uses typical price × volume. MPI uses intrabar positioning, revealing pressure balance regardless of bar-to-bar movement.
• vs. VWAP: VWAP shows average price. MPI shows directional pressure balance (who controls the bar).
MPI Interpretation:
• +0.7 to +1.0: Extreme buying pressure (strong uptrends, potential exhaustion)
• +0.3 to +0.7: Moderate buying pressure (healthy uptrends)
• -0.3 to +0.3: Neutral/balanced (ranging, consolidation)
• -0.7 to -0.3: Moderate selling pressure (healthy downtrends)
• -1.0 to -0.7: Extreme selling pressure (strong downtrends, potential exhaustion)
Critical Insight: MPI at extremes indicates pressure exhaustion risk , not automatic reversal. Reversals occur when extreme MPI coincides with confluence factors.
Six Confluence Factors - Detection Arsenal
1. Divergence Detection (Weight: 3.0 - Highest Priority)
Detects: Price making higher highs while MPI makes lower highs (bearish), or price making lower lows while MPI makes higher lows (bullish).
Why It Matters: Reveals weakening pressure behind price moves. Declining participation signals potential reversal.
Signal Type: Premium (DIV) - Historically highest win rates.
2. Liquidity Sweep Detection (Weight: 2.5)
Detects: Price penetrates recent swing high/low (triggering stops), then immediately reverses and closes back inside range.
Calculation: High breaks swing high by <0.3× ATR but closes below it (bearish), or low breaks swing low by <0.3× ATR but closes above it (bullish).
Why It Matters: Stop hunts mark institutional accumulation/distribution zones. Often pinpoints exact pivot points.
Signal Type: Premium (LIQ) - Extremely reliable with volume confirmation.
3. Order Flow Imbalance (Weight: 2.0)
Detects: Aggressive directional ordering where price consistently closes in upper/lower third of bars with elevated volume.
Calculation:
Close Position = (Close - Low) / (High - Low)
Aggressive Buy = Volume when Close Position > 0.65
Aggressive Sell = Volume when Close Position < 0.35
Imbalance = EMA(Aggressive Buy, 5) - EMA(Aggressive Sell, 5)
Strong Flow = |Imbalance| > 1.5 × Average
Why It Matters: Reveals institutional accumulation/distribution footprints before directional moves.
Signal Type: Premium (OF)
4. Wick Rejection Patterns (Weight: 1.5)
Detects: Pin bars, hammers, shooting stars where wick exceeds 60% of total bar range.
Why It Matters: Large wicks demonstrate failed attempts to push price, indicating strong opposition.
5. Volume Spike Detection (Weight: 1.0)
Detects: Volume exceeding 2× the 20-bar average.
Why It Matters: Confirms institutional participation vs. retail noise. Most effective when combined with wick rejection or liquidity sweeps.
6. Velocity Exhaustion (Weight: 1.5)
Detects: Parabolic moves (velocity >2.0× ATR over 3 bars) showing deceleration while MPI at extremes.
Calculation:
Velocity = Change(Close, 3) / ATR(14)
Exhaustion = |Velocity| > 2.0 AND MPI > |0.5| AND Velocity Slowing
Why It Matters: Extended moves are unsustainable. Momentum deceleration from extremes precedes reversals.
Signal Classification & Scoring
Weighted Confluence Scoring:
Each factor contributes points when present. Signals fire when total score exceeds thresholds:
Bearish Example:
+ At recent high (1.0)
+ Bearish divergence (3.0)
+ Wick rejection (1.5)
+ Volume spike (1.0)
+ Velocity slowing (1.5)
= 8.0 total score → BEARISH DIV SIGNAL
Bullish Example:
+ At recent low (1.0)
+ Liquidity sweep (2.5)
+ Strong buy flow (2.0)
+ Wick rejection (1.5)
= 7.0 total score → BULLISH LIQ SIGNAL
Dual Threshold System:
• Premium Signals (DIV/LIQ/OF): Require 6.0+ points. Must include divergence, liquidity sweep, or order flow. Higher win rates.
• Standard Signals (STD): Require 4.0+ points. No premium factors. More frequent, moderate win rates.
Visual Signal Color-Coding:
• Purple Triangle: DIV (Divergence signal)
• Orange Triangle: LIQ (Liquidity sweep signal)
• Aqua Triangle: OF (Order flow signal)
• Red/Green Triangle: STD (Standard signal)
• Yellow Diamond: Warning (setup forming, not confirmed)
Warning System - Early Alerts
Yellow diamond warnings fire when 2+ factors present but full confluence not met:
• At recent 10-bar high/low
• Wick rejection present
• Volume spike present
• MPI extreme or accelerating/decelerating
Critical: Warnings are NOT trade signals. They indicate potential setups forming. Wait for colored triangle confirmation.
Win Rate Validation - Transparent Performance Tracking
How It Works:
Signal Storage: Every signal recorded (bar index, price, type, direction)
Pivot Confirmation: System monitors next 10 bars for confirmed pivot formation at signal price (±2%)
Validation: If pivot forms within window → Win. If not → Loss.
Statistics: Win Rate = Validated Signals / Total Mature Signals × 100
Dashboard Displays:
• Overall win rate with visual bar
• Bearish signal win rate
• Bullish signal win rate
• Win rate by signal type (DIV/LIQ/OF/STD)
• Wins/Total for each category
Why This Matters:
After 30-50 signals, you'll know exactly which patterns work on your instrument:
Example Performance Analysis:
Overall: 58% (35/60)
Bearish: 52% | Bullish: 65%
DIV: 72% | LIQ: 68% | OF: 50% | STD: 38%
Insight: Focus on bullish DIV/LIQ signals (72%/68% win rate), avoid STD signals (38%), investigate bearish underperformance.
This transforms the indicator from signal generator to learning system.
Dynamic Microstructure Visualization
Fibonacci Retracement Levels
• Auto-detects last swing high + swing low
• Draws 11 levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%, 127.2%, 161.8%, 200%, 261.8%
• Removes crossed levels automatically
• Clears on new signal (fresh structure analysis)
• Color gradient (bullish to bearish across range)
• Key levels (0.618, 0.5, 1.0) highlighted with solid lines
Support/Resistance Lines
• Resistance: 50-bar highest high (red, only shown when above price)
• Support: 50-bar lowest low (green, only shown when below price)
• Auto-removes when price crosses
Usage: Signals firing at key Fibonacci levels (38.2%, 50%, 61.8%) or major S/R zones have enhanced structural significance.
Dashboard - Real-Time Intelligence
MPI Status:
• Current pressure reading with interpretation
• Color-coded background (green/red/gray zones)
Signal Status:
• Active signal type and direction
• Confidence score with visual bar (20 blocks, color-coded)
• Scanning status when no signal active
Divergence Indicator:
• Highlights active divergence separately (highest priority factor)
Performance Stats:
• Overall win rate with 10-block visual bar
• Directional breakdown (bearish vs. bullish)
• Signal type breakdown (DIV/LIQ/OF/STD individual win rates)
• Sample size for each category
Customization:
• Position: 9 locations (Top/Middle/Bottom × Left/Center/Right)
• Size: Tiny/Small/Normal/Large
• Toggle sections independently
How to Use This System
Initial Setup (10 Minutes)
1. MPI Configuration:
• Period: 14 (balanced) | 5-10 for scalping | 21-30 for swing
• Sensitivity: 1.5 (moderate) | Increase if MPI rarely hits ±0.7 | Decrease if constantly maxed
2. Detection Thresholds:
• Wick Threshold: 0.6 (60% of bar must be wick)
• Volume Spike: 2.0× average (lower to 1.5-1.8 for stocks, raise to 2.5-3.0 for crypto)
• Velocity: 2.0 ATR (raise to 2.5-3.0 for crypto)
3. Confluence Settings:
• Enable Divergence (highest win rate factor)
• Pivot Lookback: 5 (day trading) | 8-10 (swing trading)
• Keep default weights initially
4. Thresholds:
• Premium: 6.0 (quality over quantity)
• Standard: 4.0 (balanced)
• Warning: 2 factors minimum
Trading Workflow
When Warning Fires (Yellow Diamond):
Note warning type (bearish/bullish)
Do not enter - this is preparation only
Monitor for full signal confirmation
Prepare entry parameters
When Signal Fires (Colored Triangle):
Identify type from color (Purple=DIV, Orange=LIQ, Aqua=OF, Red/Green=STD)
Check dashboard confidence score
Verify confluence on chart (wick, volume, MPI extreme, Fib level)
Confirm with your analysis (context, higher timeframe, news)
Enter with proper risk management
Risk Management (Not Provided by Indicator):
• Stop Loss: Beyond recent swing or 1.5-2.0× ATR
• Position Size: Risk 0.5-2% of capital per trade
• Take Profit: 2-3× ATR or next structural level
Performance Analysis (After 30-50 Signals)
Review Dashboard Statistics:
Overall Win Rate:
• Target >50% for profitability with 1:1.5+ RR
• <45% = system may not suit instrument
• >65% = consider tightening thresholds
Directional Analysis:
• Bullish >> Bearish = uptrend bias, avoid counter-trend shorts
• Bearish >> Bullish = downtrend bias, avoid counter-trend longs
Signal Type Ranking:
• Focus on highest win rate types (typically DIV/LIQ)
• If STD <40% = raise threshold or ignore STD signals
• If premium type <50% = investigate (may need parameter adjustment)
Optimize Settings:
• Too many weak signals → Raise thresholds (premium 7.0-8.0, standard 5.0-6.0)
• Too few signals → Lower thresholds or reduce detection strictness
• Adjust factor weights based on what appears in winning signals
What Makes This Original
1. Proprietary Market Pressure Index
Unique Methodology:
• Proportional intrabar allocation: Unlike binary volume classification (OBV), MPI uses close position within range for proportional pressure assignment
• Dual-timeframe normalization: EMA smoothing (14) + SMA normalization (28) for responsiveness with context
• Bounded oscillator with sensitivity control: -1 to +1 range enables cross-instrument comparison while sensitivity allows customization
• Active signal integration: MPI drives divergence detection, extreme requirements, exhaustion confirmation (not just display)
vs. Existing Indicators:
• MFI uses typical price × volume (different pressure measure)
• CMF accumulates over time (not bounded oscillator)
• OBV is cumulative and binary (not proportional or normalized)
2. Hierarchical Confluence Engine
Why Simple Mashups Fail: Most multi-indicator systems create decision paralysis (RSI says sell, MACD says buy).
This System's Solution:
• Six factors weighted by reliability (3.0 down to 1.0)
• Dual thresholds (premium 6.0, standard 4.0)
• Automatic signal triage by quality tier
• Color-coded visual prioritization
Orthogonal Detection: Each factor detects different failure mode:
• Divergence = momentum exhaustion
• Liquidity = institutional manipulation
• Order Flow = smart money positioning
• Wick = supply/demand rejection
• Volume = participation confirmation
• Velocity = parabolic exhaustion
Complementary, not redundant. Weighted synthesis creates unified confidence measure.
3. Self-Validating Performance System
The Problem: Most indicators never reveal actual performance. Traders never know if it works on their instrument.
This Solution:
• Forward-looking validation (signals tracked to pivot confirmation)
• Pivot-based success criteria (objective, mechanical)
• Segmented statistics (by direction and type)
• Real-time dashboard updates
Result: After 30-50 signals, you have statistically meaningful data on what actually works on your specific market. Transforms indicator into adaptive learning system.
Technical Notes
No Repainting:
• All signals use confirmed bar data (closed bars only)
• Pivot detection has inherent lookback lag (5 bars)
• Divergence lines drawn after confirmation (retroactive visualization)
• Signals fire on bar close
Forward-Looking Disclosure:
• Win rate validation looks forward 10 bars for pivot confirmation
• Creates forward bias in statistics , not signal generation
• Real-time performance may differ until validation period elapses
Lookback Limits:
• Fibonacci/S/R: Limited by limitDrawBars (default 100)
• MPI calculation: 28 bars maximum
• Signal storage: 20 per direction (configurable)
Visual Limits:
• Max lines/labels/boxes: 500 each
• Auto-clearing prevents overflow
Limitations & Disclaimers
Not a Complete Trading System:
• Does not provide stop loss, take profit, or position sizing
• Requires trader risk management and market context analysis
Reversal Bias:
• Designed specifically for reversal trading
• Not optimized for trend continuation or breakouts
Learning Period:
• Statistics meaningless until 20-30 mature signals
• Preferably 50+ for statistical confidence
Instrument Dependency:
• Best: Liquid instruments (major forex, large-caps, BTC/ETH)
• Poor: Illiquid small-caps, low-volume altcoins (order flow unreliable)
Timeframe Dependency:
• Optimal: 15m - 4H charts
• Not Recommended: <5m (noise) or >Daily (insufficient signals)
No Guarantee of Profit:
• Win rate >50% does not guarantee profitability (depends on RR, sizing, execution)
• Past performance ≠ future performance
• All trading involves risk of loss
Warning Signals:
• Warnings are NOT trade signals
• Trading warnings produces lower win rates
• For preparation only
Recommended Settings by Instrument
Forex Majors (15m-1H):
• MPI Sensitivity: 1.3-1.5 | Volume: 2.0 | Thresholds: 6.0/4.0
Crypto BTC/ETH (15m-4H):
• MPI Sensitivity: 2.0-2.5 | Volume: 2.5-3.0 | Velocity: 2.5-3.0 | Thresholds: 6.5-7.0/4.5-5.0
Large-Cap Stocks (5m-1H):
• MPI Sensitivity: 1.2-1.5 | Volume: 1.8-2.0 | Thresholds: 6.0/4.0
Index Futures ES/NQ (5m-30m):
• MPI Period: 10-14 | Sensitivity: 1.5 | Velocity: 1.8-2.0 | Thresholds: 5.5-6.0/4.0
Altcoins High Vol (1H-4H):
• MPI Period: 21 | Sensitivity: 2.0-3.0 | Volume: 3.0+ | Thresholds: 7.0-8.0/5.0 (very selective)
Alert Configuration
Built-In Alerts:
Bullish Signal (all types)
Bearish Signal (all types)
Bullish Divergence (DIV only)
Bearish Divergence (DIV only)
Setup:
• TradingView Alert → Select "Pressure Pivots - MPI"
• Choose condition
• Frequency: "Once Per Bar Close" (prevents repainting)
• Configure notifications (popup/email/SMS/webhook)
Recommended:
• Active traders: Enable all signals
• Selective traders: DIV only (highest quality)
In-Code Documentation
Every input parameter includes extensive tooltips (800+ words total) providing:
• What it controls
• How it affects calculations
• Range guidance (low/medium/high implications)
• Default justification
• Asset-specific recommendations
• Timeframe adjustments
Access: Hover over (i) icon next to any setting. Creates self-documenting learning system—no external docs required.
DskyzInvestments | Trade with insight. Trade with anticipation.
