ForexRobootthis indicator trade on crypto and forex
trade on neo usdt winrate 100%
trade on btc usdt winrate 90%
trade on cardano usdt winrate 90%
trade on floki usdt winrate 90%
and very coin other
enjoyed
inst: Forexroboot
ما
forexroboot
Wskaźniki i strategie
forexroboot Hunter Premiumthis indicator trade on crypto and forex
trade on any time frame
enjoyed
inst: Forexroboot
ما
forexroboot
forexroboot Hunter Premiumthis indicator trade on crypto and forex
trade on any time frame
enjoyed
inst: Forexroboot
ما
forexroboot
Ghost In The MachineScript draws:
-The range of a 5 min candle that extends for 1 hour. This range can be used for ORB strategy.
-Shows the 1 hour candle range. This helps identify price direction.
This indicator only works on the 5 min time frame.
Supply & Demand with Candle SignalsUnlock the power of Supply & Demand Zones combined with high-probability Bullish/Bearish Engulfing patterns to spot strong market reversals and trends. This strategy helps identify key price levels where major market moves are likely to occur. By using Engulfing candlesticks within these zones, you can make more informed and accurate trading decisions, enhancing your chances of success. Ideal for traders looking for a robust technical approach to maximize market opportunities.
GannLvlSHGann Indicator created to display the Support and Resistances levels on Chart based on study of WD Gann
Advanced MACD + MA + RSI + Trend Buy/SellThis advanced indicator combines MACD, dual moving averages, RSI, volume spikes, and a 200 EMA trend filter to generate high-confidence Buy/Sell signals. It aims to reduce false signals by aligning multiple technical conditions:
Hash Rate to Market Cap ChannelWe can visualize market sentiment towards security of the Bitcoin network by dividing the Marketcap by Hashrate. This can determine under and overvaluation of the network itself per dollar. The value is then normalized over the lookback period to create an oscillating channel.
SETTINGS
Lookback Period - used for calculating the normalization and how far back to look for highs and lows.
HMA Smoothing Length - Faster moving average to smooth out the curves
Channel Width - visually change the channel scale
Bear/Bull Value - Under and Overvaluation
Use Log Scaling - adjusts the channel visuals for log scaled charts
Buy/Sell EMA Trend Filter v6Buy/Sell EMA Trend Filter v6
This indicator provides a comprehensive trading system based on EMA crossovers with trend filtering for TradingView. It's designed to identify high-probability buy and sell signals by combining short-term crossovers with longer-term trend direction confirmation.
Key Features:
EMA Crossover System: Uses fast and slow EMAs (9 and 21 by default) to generate initial signals
Trend Filtering: Confirms signals with longer-term trend direction (50 and 200 EMAs)
Automatic TP/SL Calculation: Displays clear take profit and stop loss levels based on fixed risk points
Visual Alerts: Clear buy/sell markers at the point of signal with detailed labels
Risk Management: Pre-calculated risk-to-reward setup (default 1:2 ratio)
How It Works:
Buy Signal: When the fast EMA crosses above the slow EMA while the 50 EMA is above the 200 EMA (bullish trend)
Sell Signal: When the fast EMA crosses below the slow EMA while the 50 EMA is below the 200 EMA (bearish trend)
Customizable Parameters:
Fast EMA period (default: 9)
Slow EMA period (default: 21)
Trend EMA periods (default: 50 and 200)
Fixed risk in points (default: 20)
Reward ratio (default: 2.0)
The indicator displays clear entry points with predefined stop loss and take profit levels, making it ideal for traders looking for a systematic approach to the markets. Perfect for both day trading and swing trading timeframes.
This tool combines both trend following and momentum principles to filter out low-probability trades and focus on high-quality setups where the trend and momentum align.
Stochastic Order Flow Momentum [ScorsoneEnterprises]This indicator implements a stochastic model of order flow using the Ornstein-Uhlenbeck (OU) process, combined with a Kalman filter to smooth momentum signals. It is designed to capture the dynamic momentum of volume delta, representing the net buying or selling pressure per bar, and highlight potential shifts in market direction. The volume delta data is sourced from TradingView’s built-in functionality:
www.tradingview.com
For a deeper dive into stochastic processes like the Ornstein-Uhlenbeck model in financial contexts, see these research articles: arxiv.org and arxiv.org
The SOFM tool aims to reveal the momentum and acceleration of order flow, modeled as a mean-reverting stochastic process. In markets, order flow often oscillates around a baseline, with bursts of buying or selling pressure that eventually fade—similar to how physical systems return to equilibrium. The OU process captures this behavior, while the Kalman filter refines the signal by filtering noise. Parameters theta (mean reversion rate), mu (mean level), and sigma (volatility) are estimated by minimizing a squared-error objective function using gradient descent, ensuring adaptability to real-time market conditions.
How It Works
The script combines a stochastic model with signal processing. Here’s a breakdown of the key components, including the OU equation and supporting functions.
// Ornstein-Uhlenbeck model for volume delta
ou_model(params, v_t, lkb) =>
theta = clamp(array.get(params, 0), 0.01, 1.0)
mu = clamp(array.get(params, 1), -100.0, 100.0)
sigma = clamp(array.get(params, 2), 0.01, 100.0)
error = 0.0
v_pred = array.new(lkb, 0.0)
array.set(v_pred, 0, array.get(v_t, 0))
for i = 1 to lkb - 1
v_prev = array.get(v_pred, i - 1)
v_curr = array.get(v_t, i)
// Discretized OU: v_t = v_{t-1} + theta * (mu - v_{t-1}) + sigma * noise
v_next = v_prev + theta * (mu - v_prev)
array.set(v_pred, i, v_next)
v_curr_clean = na(v_curr) ? 0 : v_curr
v_pred_clean = na(v_next) ? 0 : v_next
error := error + math.pow(v_curr_clean - v_pred_clean, 2)
error
The ou_model function implements a discretized Ornstein-Uhlenbeck process:
v_t = v_{t-1} + theta (mu - v_{t-1})
The model predicts volume delta (v_t) based on its previous value, adjusted by the mean-reverting term theta (mu - v_{t-1}), with sigma representing the volatility of random shocks (approximated in the Kalman filter).
Parameters Explained
The parameters theta, mu, and sigma represent distinct aspects of order flow dynamics:
Theta:
Definition: The mean reversion rate, controlling how quickly volume delta returns to its mean (mu). Constrained between 0.01 and 1.0 (e.g., clamp(array.get(params, 0), 0.01, 1.0)).
Interpretation: A higher theta indicates faster reversion (short-lived momentum), while a lower theta suggests persistent trends. Initial value is 0.1 in init_params.
In the Code: In ou_model, theta scales the pull toward \mu, influencing the predicted v_t.
Mu:
Definition: The long-term mean of volume delta, representing the equilibrium level of net buying/selling pressure. Constrained between -100.0 and 100.0 (e.g., clamp(array.get(params, 1), -100.0, 100.0)).
Interpretation: A positive mu suggests a bullish bias, while a negative mu indicates bearish pressure. Initial value is 0.0 in init_params.
In the Code: In ou_model, mu is the target level that v_t reverts to over time.
Sigma:
Definition: The volatility of volume delta, capturing the magnitude of random fluctuations. Constrained between 0.01 and 100.0 (e.g., clamp(array.get(params, 2), 0.01, 100.0)).
Interpretation: A higher sigma reflects choppier, noisier order flow, while a lower sigma indicates smoother behavior. Initial value is 0.1 in init_params.
In the Code: In the Kalman filter, sigma contributes to the error term, adjusting the smoothing process.
Summary:
theta: Speed of mean reversion (how fast momentum fades).
mu: Baseline order flow level (bullish or bearish bias).
sigma: Noise level (variability in order flow).
Other Parts of the Script
Clamp
A utility function to constrain parameters, preventing extreme values that could destabilize the model.
ObjectiveFunc
Defines the objective function (sum of squared errors) to minimize during parameter optimization. It compares the OU model’s predicted volume delta to observed data, returning a float to be minimized.
How It Works: Calls ou_model to generate predictions, computes the squared error for each timestep, and sums it. Used in optimization to assess parameter fit.
FiniteDifferenceGradient
Calculates the gradient of the objective function using finite differences. Think of it as finding the "slope" of the error surface for each parameter. It nudges each parameter (theta, mu, sigma) by a small amount (epsilon) and measures the change in error, returning an array of gradients.
Minimize
Performs gradient descent to optimize parameters. It iteratively adjusts theta, mu, and sigma by stepping down the "hill" of the error surface, using the gradients from FiniteDifferenceGradient. Stops when the gradient norm falls below a tolerance (0.001) or after 20 iterations.
Kalman Filter
Smooths the OU-modeled volume delta to extract momentum. It uses the optimized theta, mu, and sigma to predict the next state, then corrects it with observed data via the Kalman gain. The result is a cleaner momentum signal.
Applied
After initializing parameters (theta = 0.1, mu = 0.0, sigma = 0.1), the script optimizes them using volume delta data over the lookback period. The optimized parameters feed into the Kalman filter, producing a smoothed momentum array. The average momentum and its rate of change (acceleration) are calculated, though only momentum is plotted by default.
A rising momentum suggests increasing buying or selling pressure, while a flattening or reversing momentum indicates fading activity. Acceleration (not plotted here) could highlight rapid shifts.
Tool Examples
The SOFM indicator provides a dynamic view of order flow momentum, useful for spotting directional shifts or consolidation.
Low Time Frame Example: On a 5-minute chart of SEED_ALEXDRAYM_SHORTINTEREST2:NQ , a rising momentum above zero with a lookback of 5 might signal building buying pressure, while a drop below zero suggests selling dominance. Crossings of the zero line can mark transitions, though the focus is on trend strength rather than frequent crossovers.
High Time Frame Example: On a daily chart of NYSE:VST , a sustained positive momentum could confirm a bullish trend, while a sharp decline might warn of exhaustion. The mean-reverting nature of the OU process helps filter out noise on longer scales. It doesn’t make the most sense to use this on a high timeframe with what our data is.
Choppy Markets: When momentum oscillates near zero, it signals indecision or low conviction, helping traders avoid whipsaws. Larger deviations from zero suggest stronger directional moves to act on, this is on $STT.
Inputs
Lookback: Users can set the lookback period (default 5) to adjust the sensitivity of the OU model and Kalman filter. Shorter lookbacks react faster but may be noisier; longer lookbacks smooth more but lag slightly.
The user can also specify the timeframe they want the volume delta from. There is a default way to lower and expand the time frame based on the one we are looking at, but users have the flexibility.
No indicator is 100% accurate, and SOFM is no exception. It’s an estimation tool, blending stochastic modeling with signal processing to provide a leading view of order flow momentum. Use it alongside price action, support/resistance, and your own discretion for best results. I encourage comments and constructive criticism.
Trendline Breakouts With Targets [ Chartprime ]ITS COPIED FROM TBT WITH TARGETS
What's added: STOP LOSS IS VISIBLE. CAN ADD ALERTS FOR BUY AND SELL SIGNALS.
The Trendline Breakouts With Targets and visible stoploss indicator is meticulously crafted to improve trading decision-making by pinpointing trendline breakouts and breakdowns through pivot point analysis.
Here's a comprehensive look at its primary functionalities:
Upon the occurrence of a breakout or breakdown, a signal is meticulously assessed against a false signal condition/filter, after which the indicator promptly generates a trading signal. Additionally, it conducts precise calculations to determine potential target levels and then exhibits them graphically on the price chart.
🔷Key Features:
🔸Trendline Drawing: The indicator automatically plots trendlines based on significant pivot points and wick data, visually representing the prevailing trend.
Multi-Timeframe Anchored VWAP Valuation# Multi-Timeframe Anchored VWAP Valuation
## Overview
This indicator provides a unique perspective on potential price valuation by comparing the current price to the Volume Weighted Average Price (VWAP) anchored to the start of multiple timeframes: Weekly, Monthly, Quarterly, and Yearly. It synthesizes these comparisons into a single oscillator value, helping traders gauge if the current price is potentially extended relative to significant volume-weighted levels.
## Core Concept & Calculation
1. **Anchored VWAP:** The script calculates the VWAP separately for the current Week, Month, Quarter (3 Months), and Year (12 Months), starting the calculation from the first bar of each period.
2. **Price Deviation:** It measures how far the current `close` price is from each of these anchored VWAPs. This distance is measured in terms of standard deviations calculated *within* that specific anchor period (e.g., how many weekly standard deviations the price is away from the weekly VWAP).
3. **Deviation Score (Multiplier):** Based on this standard deviation distance, a score is assigned. The further the price is from the VWAP (in terms of standard deviations), the higher the absolute score. The indicator uses linear interpolation to determine scores between the standard deviation levels (defaulted at 1, 2, and 3 standard deviations corresponding to scores of +/-2, +/-3, +/-4, with a score of 1 at the VWAP).
4. **Timeframe Weighting:** Longer timeframes are considered more significant. The deviation scores are multiplied by fixed scalars: Weekly (x1), Monthly (x2), Quarterly (x3), Yearly (x4).
5. **Final Valuation Metric:** The weighted scores from all four timeframes are summed up to produce the final oscillator value plotted in the indicator pane.
## How to Interpret and Use
* **Histogram (Indicator Pane):**
* The main output is the histogram representing the `Final Valuation Metric`.
* **Positive Values:** Suggest the price is generally trading above its volume-weighted averages across the timeframes, potentially indicating strength or relative "overvaluation."
* **Negative Values:** Suggest the price is generally trading below its volume-weighted averages, potentially indicating weakness or relative "undervaluation."
* **Values Near Zero:** Indicate the price is relatively close to its volume-weighted averages.
* **Histogram Color:**
* The color of the histogram bars provides context based on the metric's *own recent history*.
* **Green (Positive Color):** The metric is currently *above* its recent average plus a standard deviation band (dynamic upper threshold). This highlights potentially significant "overvalued" readings relative to its normal range.
* **Red (Negative Color):** The metric is currently *below* its recent average minus a standard deviation band (dynamic lower threshold). This highlights potentially significant "undervalued" readings relative to its normal range.
* **Gray (Neutral Color):** The metric is within its typical recent range (between the dynamic upper and lower thresholds).
* **Orange Line:** Plots the moving average of the `Final Valuation Metric` itself (based on the "Threshold Lookback Period"), serving as the centerline for the dynamic thresholds.
* **On-Chart Table:**
* Provides a detailed breakdown for transparency.
* Shows the calculated VWAP, the raw deviation multiplier score, and the final weighted (adjusted) metric for each individual timeframe (W, M, Q, Y).
* Displays the current price, the final combined metric value, and a textual interpretation ("Overvalued", "Undervalued", "Neutral") based on the dynamic thresholds.
## Potential Use Cases
* Identifying potential exhaustion points when the indicator reaches statistically high (green) or low (red) levels relative to its recent history.
* Assessing whether price trends are supported by underlying volume-weighted average prices across multiple timeframes.
* Can be used alongside other technical analysis tools for confirmation.
## Settings
* **Calculation Settings:**
* `STDEV Level 1`: Adjusts the 1st standard deviation level (default 1.0).
* `STDEV Level 2`: Adjusts the 2nd standard deviation level (default 2.0).
* `STDEV Level 3`: Adjusts the 3rd standard deviation level (default 3.0).
* **Interpretation Settings:**
* `Threshold Lookback Period`: Defines the number of bars used to calculate the average and standard deviation of the final metric for dynamic thresholds (default 200).
* `Threshold StDev Multiplier`: Controls how many standard deviations above/below the metric's average are used to set the "Overvalued"/"Undervalued" thresholds (default 1.0).
* **Table Settings:** Customize the position and colors of the data table displayed on the chart.
## Important Considerations
* This indicator measures price deviation relative to *anchored* VWAPs and its *own historical range*. It is not a standalone trading system.
* The interpretation of "Overvalued" and "Undervalued" is relative to the indicator's logic and calculations; it does not guarantee future price movement.
* Like all indicators, past performance is not indicative of future results. Use this tool as part of a comprehensive analysis and risk management strategy.
* The anchored VWAP and Standard Deviation values reset at the beginning of each respective period (Week, Month, Quarter, Year).
RT-RSI 2.0 + Signal📈 RT-RSI 2.0 + Signal – Enhanced RSI Divergence Detection
RT-RSI 2.0 + Signal is a powerful and flexible RSI-based divergence indicator designed for traders who want smarter market entries using real-time confirmations.
This script identifies bullish and bearish RSI divergences, visualizes them directly on the RSI pane, and provides clear output signals (numeric: 1.0 for bullish, 2.0 for bearish) for use in external strategy scripts like RT-Signal 2.0.1.
🔍 Core Features:
✔️ Detects classic RSI divergences (bullish & bearish)
✔️ Includes automatic pivot detection and flexible lookback settings
✔️ External signal output for use in multi-pattern or strategy systems
✔️ Optimized RSI calculation per market type (BTC, DAX, Gold, Forex, etc.)
✔️ Customizable moving average & Bollinger Band smoothing
✔️ Signal is output via plot() (non-displayed) for remote use
Liquidity Sweep + OB Trap"A high-precision smart money indicator that detects liquidity sweeps, volume divergence, and order block traps—filtered by trend—to catch false breakouts and sniper reversals."
Trend Confirmation StrategyComprehensive Trend Confirmation System
Indicator Features (Professional Description):
Comprehensive Trend Confirmation System is a versatile indicator meticulously designed to identify and confirm trend-based trading opportunities with exceptional efficiency. By seamlessly integrating analysis from a suite of leading technical tools, it aims to provide superior accuracy and reliability for informed trading decisions.
Key Features:
Intelligent Trend Identification: A robust trend analysis system that considers:
Adjustable Moving Averages: Utilizes three customizable moving average periods (fast, medium, slow) with user-selectable lengths and types (SMA, EMA, WMA, VWMA) to accurately determine the prevailing trend across different timeframes.
In-depth Price Action Analysis: Examines the formation of Higher Highs/Higher Lows (uptrend) and Lower Highs/Lower Lows (downtrend) to validate price direction.
Average Directional Index (ADX) with Adjustable Threshold: Measures the strength of a trend and employs the comparison between +DI and -DI to pinpoint the dominant momentum, featuring a customizable threshold to filter out weak signals.
Multi-Factor Signal Confirmation System: Enhances the reliability of trading signals through verification from four distinct confirmation tools:
Volume Analysis with Average Reference: Assesses whether trading volume supports price movements by comparing it to historical averages.
Relative Strength Index (RSI) with Reference Levels: Measures price momentum and identifies overbought/oversold conditions to confirm trend strength.
Moving Average Convergence Divergence (MACD) Divergence and Crossovers: Detects shifts in momentum and potential trend changes through the relationship between the MACD line and the Signal line.
Stochastic Oscillator with Reference Levels: Measures the current price's position relative to its historical range to evaluate overbought/oversold conditions and potential reversal opportunities.
Intelligent Signal Generation Logic:
Buy Signal: Triggered when a strong uptrend is identified (meeting defined criteria) and confirmed by at least three out of the four confirmation tools.
Sell Signal: Triggered when a strong downtrend is identified (meeting defined criteria) and confirmed by at least three out of the four confirmation tools.
User-Friendly Visualizations:
Moving Averages (MA): Displays three MA lines on the chart with user-configurable colors (default: fast-blue, medium-orange, slow-red) for easy visual trend analysis.
Clear Buy and Sell Signal Symbols: Presents distinct green upward-pointing triangles for buy signals and red downward-pointing triangles for sell signals at the corresponding candlestick.
Dynamic Candlestick Color Coding: Candlesticks are dynamically colored green upon a buy signal and red upon a sell signal for quick identification of trading opportunities.
Highly Customizable Parameters: Users have extensive control over the indicator's parameters, including:
Lengths and types of Moving Averages.
Length and Threshold of the ADX.
Length of the RSI.
Parameters for the MACD (Fast Length, Slow Length, Signal Length).
Parameters for the Stochastic Oscillator (%K Length, %D Length, Smoothing).
Ideal For:
Traders seeking a robust tool to accurately identify and confirm market trends.
Individuals aiming to reduce false signals and enhance the precision of their trading decisions.
Traders employing trend-following strategies in markets with clear directional movement.
Important Note:
While Comprehensive Trend Confirmation System is engineered to improve trading accuracy, no indicator can guarantee 100% profitable trades. Users are advised to utilize this indicator in conjunction with relevant fundamental analysis and sound risk management practices for optimal trading outcomes.
projectiontrackingLibrary "projectiontracking"
Library contains few data structures and methods for tracking harmonic patterns and projections via pinescript.
method erase(this)
erase Harmonic Projection Drawing
Namespace types: HarmonicProjectionDrawing
Parameters:
this (HarmonicProjectionDrawing) : HarmonicProjectionDrawing object
Returns: void
method erase(this)
erase HarmonicProjection
Namespace types: HarmonicProjection
Parameters:
this (HarmonicProjection) : HarmonicProjection object
Returns: void
method draw(this)
draw HarmonicProjection
Namespace types: HarmonicProjection
Parameters:
this (HarmonicProjection) : HarmonicProjection object
Returns: HarmonicProjection object
method getRanges(projectionPrzRanges, dir)
Convert PRZRange to Projection ranges
Namespace types: array
Parameters:
projectionPrzRanges (array type from Trendoscope/HarmonicMapLib/1) : array of PrzRange objects
dir (int) : Projection direction
Returns: array
ProjectionRange
Harmonic Projection Range
Fields:
patterns (array) : array of pattern names
start (series float) : Start Range
end (series float) : End Range
status (series int) : Projection Status
ProjectionProperties
Harmonic Projection Properties
Fields:
fillMajorTriangles (series bool) : Use linefill for major triangles
fillMinorTriangles (series bool) : Use linefill for minor triangles
majorFillTransparency (series int) : transparency of major triangles
minorFillTransparency (series int) : transparency of minor triangles
showXABC (series bool) : Show XABC labels
lblSizePivots (series string) : Pivot labels size
showRatios (series bool) : Show ratio labels
useLogScaleForScan (series bool) : Log scale is used for scanning projections
activateOnB (series bool) : Activate projections on reaching B
activationRatio (series float) : Use activation ratio for activation
confirmationRatio (series float) : Confirmation ratio of projection before removal
HarmonicProjectionDrawing
Harmonic Projection Projection drawing objects
Fields:
xa (series line) : line xa
ab (series line) : line ab
bc (series line) : line bc
xb (series line) : line xb
ac (series line) : line ac
x (series label) : Pivot label x
a (series label) : Pivot label a
b (series label) : Pivot label b
c (series label) : Pivot label c
xabRatio (series label) : Label XAB Ratio
abcRatio (series label) : Label ABC Ratio
HarmonicProjection
Harmonic Projection Projection object
Fields:
patternId (series int) : id of the pattern
dir (series int) : projection direction
x (chart.point) : Pivot X
a (chart.point) : Pivot A
b (chart.point) : Pivot B
c (chart.point) : Pivot C
patternColor (series color) : Color in which pattern is displayed
przRange (PrzRange type from Trendoscope/HarmonicMapLib/1) : PRZ Range
activationPrice (series float) : Projection activation price
reversalPrice (series float) : Projection reversal price
status (series int) : Projection status
properties (ProjectionProperties) : Projection properties
projectionRanges (array) : array of Projection Ranges
initialD (series float) : Initial D pivot
d (chart.point) : Pivot D
drawing (HarmonicProjectionDrawing) : HarmonicProjectionDrawing Object
Pump & Dump Detector (sensitive)📊 Pump & Dump Detector — Volatility & Volume-Based Impulse Scanner
Description:
This indicator is designed to detect early and confirmed signs of high-impact market movements, such as pumps (sharp price increases) and dumps (sharp price drops). It intelligently combines multiple market signals to provide timely alerts of potential momentum spikes.
🔧 Components & Logic:
1. Price Change (%):
Compares the current closing price to the previous one. This is used as the main trigger for confirmed pump or dump detection.
2. Volume Spike:
Detects abnormal activity by comparing the current volume to the moving average over a user-defined period. If the current volume exceeds the average by a specified multiplier (default: 1.8x), a spike is detected.
3. Volatility Spike (High - Low):
Measures bar expansion. A sudden increase in bar range often indicates breakout conditions or liquidation events.
4. NATR (Normalized ATR):
Normalized Average True Range is calculated as (ATR / Close) * 100, making volatility comparable across all timeframes and instruments.
5. Min Volume Filter:
Filters out signals from low-liquidity coins to reduce false alerts and market noise.
🧠 Why It’s Useful:
This is not a mashup of random indicators, but a thoughtfully engineered system where each filter strengthens the signal validity.
It allows you to spot explosive moves before they fully unfold, making it ideal for:
Intraday scalping
Altcoin watchlists
Flash crash detection
Early reversal or breakout trades
🖥 How to Use:
Add the indicator to any crypto chart.
Enable alerts for:
🚨 Early Pump
💥 Confirmed Pump
🔻 Early Dump
🔥 Confirmed Dump
React to confirmed signals using your preferred strategy — breakout, fade, or continuation.
Use in combination with key levels, orderbook data, or trend filters for best results.
📌 Example Use Case:
On a 5-minute chart of a low-cap altcoin, the indicator may issue an early signal when:
Price increases by more than 2.5%
Volume is 2x the average
Bar range is significantly larger than the recent average
NATR is above its smoothed average × 1.2
🛡 Originality & Purpose:
This script was not built to simply combine popular indicators, but to serve a very specific use-case — detecting early-stage pumps and dumps.
By blending classic tools (like volume, ATR) with contextual filters, it becomes a true pattern-based predictive signal, not a repackaged overlay.
💬 Have ideas or suggestions? Leave a comment below — I’m always open to collaboration!
Giant Candles DetectorThis script identifies abnormally large candles — also known as "giant candles" — based on a customizable size threshold relative to the average candle size over a user-defined period.
Key Features:
Automatically detects candles that are significantly larger than average.
Differentiates between bullish (green) and bearish (red) candles.
Option to visually highlight candles with background color.
Built-in alert to notify you immediately when a giant candle appears.
Ideal for traders looking to spot volatility spikes, key breakouts, or significant price movements with minimal effort.
Advanced Multi-Symbol Analyzer by Babak SoltanparastAdvanced Multi-Symbol Analyzer by Babak Soltanparast
HarmonicMapLibLibrary "HarmonicMapLib"
Harmonic Pattern Library implementation utilising maps
method tostring(this)
convert Range value to string
Namespace types: Range
Parameters:
this (Range) : Range value
Returns: converted string representation
method tostring(this)
convert array of Range value to string
Namespace types: array
Parameters:
this (array) : array object
Returns: converted string representation
method tostring(this)
convert map of string to Range value to string
Namespace types: map
Parameters:
this (map) : map object
Returns: converted string representation
method tostring(this)
convert RatioMap to string
Namespace types: RatioMap
Parameters:
this (RatioMap) : RatioMap object
Returns: converted string representation
method tostring(this)
convert array of RatioMap to string
Namespace types: array
Parameters:
this (array) : array object
Returns: converted string representation
method tostring(this)
convert map of string to RatioMap to string
Namespace types: map
Parameters:
this (map) : map object
Returns: converted string representation
method tostring(this)
convert map of string to bool to string
Namespace types: map
Parameters:
this (map) : map object
Returns: converted string representation
method tostring(this)
convert PrzRange to string
Namespace types: PrzRange
Parameters:
this (PrzRange) : PrzRange object
Returns: converted string representation
method tostring(this)
convert array of PrzRange to string
Namespace types: array
Parameters:
this (array) : array object
Returns: converted string representation
getHarmonicMap()
Creates the RatioMap for harmonic patterns
Returns: map haronic ratio rules for all patterns
method evaluate(patternsMap, pattern, ratioRange, properties, ratioValue)
evaluates harmonic ratio range
Namespace types: map
Parameters:
patternsMap (map) : parameter containing valid pattern names
pattern (string) : Pattern type to be evaluated
ratioRange (Range) : ratio range to be checked
properties (ScanProperties) : Scan Properties
ratioValue (float)
Returns: void
method evaluate(przRange, pattern, ratioRange, priceRange, properties)
Evaluate PRZ ranges
Namespace types: map
Parameters:
przRange (map)
pattern (string) : Pattern name
ratioRange (Range) : Range of ratio for the pattern
priceRange (Range) : Price range based on ratio
properties (ScanProperties) : ScanProperties object
Returns: void
method scanRatio(currentPatterns, rules, properties, ratioName, ratioValue)
Scan for particular named ratio of harmonic pattern to filter valid patterns
Namespace types: map
Parameters:
currentPatterns (map) : Current valid patterns map
rules (map) : map Harmonic ratio rules
properties (ScanProperties) : ScanProperties object
ratioName (string) : Specific ratio name
ratioValue (float) : ratio value to be checked
Returns: updated currentPatterns object
method scanPatterns(patterns, x, a, b, c, d, properties)
Scan for patterns based on X, A, B, C, D values
Namespace types: map
Parameters:
patterns (map) : List of allowed patterns
x (float) : X coordinate
a (float) : A coordinate
b (float) : B coordinate
c (float) : C coordinate
d (float) : D coordinate
properties (ScanProperties) : ScanProperties object. If na, default values are initialised
Returns: updated valid patterns map
method scanProjections(patterns, x, a, b, c, properties)
Scan for projections based on X, A, B, C values
Namespace types: map
Parameters:
patterns (map) : List of allowed patterns
x (float) : X coordinate
a (float) : A coordinate
b (float) : B coordinate
c (float) : C coordinate
properties (ScanProperties) : ScanProperties object. If na, default values are initialised
Returns: updated valid projections map
method merge(this, other)
merge two ranges into one
Namespace types: Range
Parameters:
this (Range) : first range
other (Range) : second range
Returns: combined range
method union(this, other)
union of two ranges into one
Namespace types: Range
Parameters:
this (Range) : first range
other (Range) : second range
Returns: union range
method overlaps(this, other)
checks if two ranges intersect
Namespace types: Range
Parameters:
this (Range) : first range
other (Range) : second range
Returns: true if intersects, false otherwise
method consolidate(this)
Consolidate ranges into PRZ
Namespace types: map
Parameters:
this (map) : map of Ranges
Returns: consolidated PRZ
method consolidateMany(this)
Consolidate ranges into multiple PRZ ranges
Namespace types: map
Parameters:
this (map) : map of Ranges
Returns: consolidated array of PRZ ranges
method getRange(currentPatterns, x, a, b, c, properties)
Get D range based on X, A, B, C coordinates for the current patterns
Namespace types: map
Parameters:
currentPatterns (map) : List of valid patterns
x (float) : X coordinate
a (float) : A coordinate
b (float) : B coordinate
c (float) : C coordinate
properties (ScanProperties) : ScanProperties object. If na, default values are initialised
Returns: map of D ranges
method getPrzRange(currentPatterns, x, a, b, c, properties)
Get PRZ range based on X, A, B, C coordinates for the current patterns
Namespace types: map
Parameters:
currentPatterns (map) : List of valid patterns
x (float) : X coordinate
a (float) : A coordinate
b (float) : B coordinate
c (float) : C coordinate
properties (ScanProperties) : ScanProperties object. If na, default values are initialised
Returns: PRZRange for the pattern
method getProjectionRanges(currentPatterns, x, a, b, c, properties)
Get projection range based on X, A, B, C coordinates for the current patterns
Namespace types: map
Parameters:
currentPatterns (map) : List of valid patterns
x (float) : X coordinate
a (float) : A coordinate
b (float) : B coordinate
c (float) : C coordinate
properties (ScanProperties) : ScanProperties object. If na, default values are initialised
Returns: array of projection ranges
Range
Collection of range values
Fields:
values (array) : array of float values
RatioMap
ratio map for pattern
Fields:
ratioMap (map) : map of string to Range (array of float)
ScanProperties
Pattern Scanning properties
Fields:
strictMode (series bool) : strict scanning mode will check for overflows
logScale (series bool) : scan ratios in log scale
errorMin (series float) : min error threshold
errorMax (series float)
mintick (series float) : minimum tick value of price
PrzRange
Potential reversal zone range
Fields:
patterns (array) : array of pattern names for the given XABCD combination
prz (Range) : PRZ range
