TradingView Alerts to MT4 MT5 + dynamic variables NON-REPAINTINGAccidentally, I’m sharing open-source profitable Forex strategy. Accidentally, because this was aimed to be purely educational material. A few days ago TradingView released a very powerful feature of dynamic values from PineScript now being allowed to be passed in Alerts. And thanks to TradingConnector, they could be instantly executed in MT4 or MT5 platform of any broker in the world. So yeah - TradingConnector works with indices and commodities, too.
The logic of this EURUSD 6h strategy is very simple - it is based on Stochastic crossovers with stop-loss set under most recent pivot point. Setting stop-loss with surgical precision is possible exactly thanks to allowance of dynamic values in alerts. TradingConnector has been also upgraded to take advantage of these dynamic values and it now enables executing trades with pre-calculated stop-loss, take-profit, as well as stop and limit orders.
Another fresh feature of TradingConnector, is closing positions only partly - provided that the broker allows it, of course. A position needs to have trade_id specified at entry, referred to in further alerts with partial closing. Detailed spec of alerts syntax and functionalities can be found at TradingConnector website. How to include dynamic variables in alert messages can be seen at the very end of the script in alertcondition() calls.
The strategy also takes commission into consideration.
Slippage is intentionally left at 0. Due to shorter than 1 second delivery time of TradingConnector, slippage is practically non-existing. This can be achieved especially if you’re using VPS server, hosted in the same datacenter as your brokers’ servers. I am using such setup, it is doable. Small slippage and spread is already included in commission value.
This strategy is NON-REPAINTING and uses NO TRAILING-STOP or any other feature known to be faulty in TradingView backtester. Does it make this strategy bulletproof and 100% success-guaranteed? Hell no! Remember the no.1 rule of backtesting - no matter how profitable and good looking a script is, it only tells about the past. There is zero guarantee the same strategy will get similar results in the future.
To turn this script into study so that alerts can be produced, do 2 things:
1. comment “strategy” line at the beginning and uncomment “study” line
2. comment lines 54-59 and uncomment lines 62-65.
Then add script to the chart and configure alerts.
This script was build for educational purposes only.
Certainly this is not financial advice. Anybody using this script or any of its parts in any way, must be aware of high risks connected with trading.
Thanks @LucF and @a.tesla2018 for helping me with code fixes :)
Wyszukaj w skryptach "take profit"
Any MA bands (TMA bands V2)Hi everyone
Website will be opening very shortly :) Sorting out the last details and we're so excited to finally roll-out our different Algorithm Builders for you guys
Forewords
This present script is an evolution of the TMA bands . I would never have expected that script to become so popular to be honest
This is not only a study or idea but a really proven method and I'm glad that many of you are using it already. But please, whenever you see a new script out there, even if it looks cool and promising, please test it on a demo account for a week or on a LIVE account but with tiny amounts every time.
Many times, what you see on the chart is not what will happen in reality. I know that most of you will agree and I know exactly why we see this behavior... I'll give more details in a later post
I have plenty of methods like that one and I'll detail them on my website (and a bit on TradingView) starting next month
TMA bands on steroids
Someone asked me privately to make a generic version of the TMA bands and make it compatible with other standards Moving Average types. That's it for the specifications really as I didn't do much than re-using some piece of my own code
Suggested (but not mandatory) methodology
1) The Take Profit 1 is the middle line, Take Profit 2 is the opposite band.
2) Once the TP1 is hit, set your Stop Loss to breakeven
3) Once the TP2 is hit, if you still want to stay in the trade, set your Stop Loss to the TP1
It will be a powerful tool in your arsenal for some scalp/intraday trades
Wishing you all of you a great and profitable day
PS
It's strictly forbidden to republish this script without my explicit approval. All my posts are copyrighted from now on
Obviously you can use but not republish and get the credit or even worse... some money from your own clients
Dave
____________________________________________________________
Be sure to hit the thumbs up. Building those indicators take a lot of time and likes are always rewarding for me :) (tips are accepted too)
- If you want to suggest some indicators that I can develop and share with the community, please use my personal TRELLO board
- I'm an officially approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies
Jump on a 1 to 1 coaching with me
- You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
Disclaimer:
Trading involves a high level of financial risk, and may not be appropriate because you may experience losses greater than your deposit. Leverage can be against you.
Do not trade with capital that you can not afford to lose. You must be aware and have a complete understanding of all the risks associated with the market and trading. We can not be held responsible for any loss you incur.
Trading also involves risks of gambling addiction.
Please notice I do not provide financial advice - my indicators, strategies, educational ideas are intended to provide only some source code for anyone interested in improving their trading
The proprietary indicators and strategies developed by Best Trading Indicator, the object of intellectual property rights are and remain the exclusive property of Best Trading Indicator, at the exclusion of images and videos and texts free of rights or provided by the Company or external legal or physical person.
No assignment of intellectual property rights is carried out through these Terms and Conditions.
Any total or partial reproduction, modification or use of these properties for any reason whatsoever is strictly prohibited without the express written authorization of the Company.
Trade Manager (Open Source Version)Hello my young padawans looking for the FORCE to get richer on your next trade
I got pinged at least three times today asking where the hell is the indicator of the day. You asked, I delivered :)
Here's your free open-source Trade Manager Version. My associates might kill me for sharing that one... anyway this is a real GIFT.
I won't share such quality indicators too often for FREE so hope you'll appreciate its value. It can really help with your day to day trading (on top of making your charts looking more awesome)
This is an even better version compared to my previous Trade Manager Trade-Manager . It's basically a standalone version, meaning you'll have to update with 2 lines your own indicator and follow my educational post from yesterday (pasted it below also) to learn how to do it
Please read this educational post I published for you before proceeding further : How-to-connect-your-indicator-with-the-Trade-Manager
From here you normally connected the data source of your own indicator to the Trade Manager. If not, here's a reminder of the article mentionned above
Step 1 - Update your indicator
For the screenshot you see above, I used this indicator : Two-MM-Cross-MACD/ . "But sir are you really advertising your other indicators here ??" ... hmmm.... YES but I gave them for free so ... stop complaining my friend :)
Somewhere in the code you'll have a LONG and a SHORT condition. If not, please go back to study trading for noobs (I'm kidding !!!)
So it should look to something similar
nUP = ma_crossover and macd_crossover
nDN = ma_crossunder and macd_crossunder
What you will need to add at the very end of your script is a Signal plot that will be captured by the Trade Manager. This will give us :
// Signal plot to be used as external
// if crossover, sends 1, otherwise sends -1
Signal = (nUP) ? 1 : (nDN) ? -1 : na
plot(Signal, title="Signal")
The Trade Manager engines expects to receive 1 for a bullishg signal and -1 for bearish .
Step 2 - Add the Trade Manager to your chart and select the right Data Source
I feel the questions coming so I prefer to anticipate :) When you add the Trade Manager to your chart, nothing will be displayed. THIS IS NORMAL because you'll have to select the Data Source to be "Signal"
Remember our Signal variable from the Two MM Cross from before, now we'll capture it and.....drumb rolll...... that's from that moment that your life became even more AWESOME
The Engine will capture the last signal from the MM cross or any indicator actually and will update the Stop Loss, Take Profit levels based on the parameters you set on the Trade Manager
It should work with any indicator as long as you're providing a plot Signal with values 1 and -1 . In any case, you can change the Trade Manager you'll find a better logic for your trading
Now let's cover the different parameters of the tool
It should be straightforward but better to explain everything here
+Label lines : if unchecked, no SL/TPs/... will be displayed
+Show Stop Loss Signal : Will display the stop loss label. You have the choice between three options :
By default, the Stop Loss is set to NONE. You'll have to select a different option to enable the Stop Loss for real
++Percentage : Will set the SL at a percent distance from the price
++Fixed : SL fixed at a static price
++Trailing % : Trailing stop loss based on percentage level
The following is a KEY feature and I got asked for it many times those past two days. I got annoyed of getting the same request so I just did it
++Trailing TP: Will move the Stop Loss if the take profit levels are hit
Example: if TP1 is hit, SL will be moved to breakeven. If TP2 is hit, SL will be moved from TP1 to TP2
+Take Profit 1,2,3 : Visually define the three Take Profit levels. Those are percentage levels .
Meaning if you set TP1 = 2, it will set the TP1 level 2% away from the entry signal
Please note that once a Take profit level is reached, it will magically disappear. This is to be expected
I'll share in the future a way more complete version with invalidation, stop loss/take profits based on indicator, take profit based on supports/resistances, ...
I believe is such a great tool because can be connected to any indicator. I confess that I tried it only with a few... if you find any that's not working with the Trade manager, please let me know and I'll have a look
PS
I want to give a HUUUUUUUGE shoutout to the PineCoders community who helped me finishing it
Wishing you all the best and a pleasant experience with my work
David
Peak Valley Estimation StrategyIntroduction
Its the first strategy that i post here, so don't expect ground breaking stuff, when testing my indicators i always used prorealtime and not tradingview. This strategy use signals generated by the peak/valley estimator indicator i posted long ago, i think the signals generated where sometimes quite accurate in some markets thus providing potential material for a profitable strategy.
The indicator use 3 parameters, therefore the optimisation process is not easy, but i selected what i judged good parameters values at first glance. The strategy is in its more simple form without stop or anything, the detection of peaks and valley can allow for tighter stops since we expect the price to reverse, but take into account that sops and take profits are parameters subject to optimization process except if selected with strict money management rules and not profit optimization.
Of course trading the strategy in this form is far from being great, if we take into account the market non stationarity then we might expect loss during trending markets. Trend strength indicators could help switch from a reversal to breakout strategy thus maybe providing more control.
I really hope you find an use for the strategy.
Notes
Its been three long years since i started tradingview, and i put more efforts in my indicators than in my studies and life overall, this have created complicated situations and i can't afford to follow up with this, therefore i announce that in the end of june i will leave tradingview for quite a long time, at least until i have my degree. I announce it in advance in case some of you want helps of any kind. I will post all the indicators, both in progress and finished i have made during those three years. I hope you can all understand.
Thanks for reading !
makeTPSo this model try to use the the take profit issue as important
the model is based on the early model that I put in last publication , the problem is that the fire point of the buy and sell has a delay and shoot some bars after (its not repaint but a bug due to TV code) . but once it stay it will calculate correctly the take profits . so I add take profit 1 and take profit 2 to the script . and since take profit 1 is correct without delay I add option to use it as buy again or short again . you can the older entry point which is H= high or L =low as your initial buy point but be aware that it sometime shoot too late since the problem in TV script to transfer the price correctly .or to enter to buy again option which is based on take profit 1 . the H and L are correctly detecting most of the time the Highs and the lows so by going on the trend them you can use the TP which are by % to max out your gains .. this is the theory behind this model
see here on amazon the concept
Progressive Profit Taking with Trailing StopThis is version 2 of
Special features:
Added partial profit taking as price rises. Profit taking is triggered by price crossing an EMA.
After profit taking, price has to rise by a user-specified percent before taking profits again.
Also includes condition for fully closing position after meeting specified profit target.
To incorporate into your algo, turn the plotshape functions into alertcondition.
Golden Cross, SMA 200 Moving Average Strategy (by ChartArt)This famous moving average strategy is very easy to follow to decide when to buy (go long) and when to take profit.
The strategy goes long when the faster SMA 50 (the simple moving average of the last 50 bars) crosses above the slower SMA 200. Orders are closed when the SMA 50 crosses below the SMA 200. This simple strategy does not have any other stop loss or take profit money management logic. The strategy does not short and goes long only!
Here is an article explaining the "golden cross" strategy in more detail:
www.stockopedia.com
On the S&P 500 index (symbol "SPX") this strategy worked on the daily chart 81% since price data is available since 1982. And on the DOW Jones Industrial Average (symbol "DOWI") this strategy worked on the daily chart 55% since price data is available since 1916. The low number of trades is in both cases not statistically significant though.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Elder's Market Thermometer [LazyBear]Market temperature, introduced by Dr.Alexander Elder, helps differentiate between sleepy, quiet and hot market periods.
Following is Mr.Elder's explanation on how to use this indicator (from his book "Come in to my Trading Room"):
"When markets are quiet, the adjacent bars tend to overlap. The consensus of value is well established, and the crowd does little buying or selling outside of yesterday’s range. When highs and lows exceed their previous day’s values, they do so only by small margins. Market Thermometer falls and its EMA slants down, indicating a sleepy market. When a market begins to run, either up or down, its daily bars start pushing outside of the previous ranges. The histogram of Market Thermometer grows taller and crosses above its EMA, which soon turns up, confirming the new trend."
"Market Thermometer gives four trading signals, based on the relationship between its histogram and its moving average:
1) The best time to enter new positions is when Market Thermometer falls below its moving average. When Market Thermometer falls below its EMA, it indicates that the market is quiet. If your system flashes an entry signal, try to enter when the market is cooler than usual. When Market Thermometer rises above its moving average, it warns that the market is hot and slippage more likely.
2) Exit positions when Market Thermometer rises to triple the height of its moving average. A spike of Market Thermometer indicates a runaway move. When the crowd feels jarred by a sudden piece of news and surges, it is a good time to take profits. Panics tend to be short-lived, offering a brief opportunity to cash in. If the EMA of Market Thermometer stands at 5 cents, but the Thermometer itself shoots up to 15 cents, take profits. Test these values for the market you are trading.
3) Get ready for an explosive move if the Thermometer stays below its moving average for five to seven trading days. Quiet markets put amateurs to sleep. They become careless and stop watching prices. Volatility and volume fall, and professionals get a chance to run away with the market. Explosive moves often erupt from periods of inactivity.
4) Market Thermometer can help you set a profit target for the next trading day. If you are a short-term trader and are long, add the value of today’s Thermometer EMA to yesterday’s high and place a sell order there. If you are short, subtract the value of the Thermometer’s EMA from yesterday’s low and place an order to cover at that level."
You can configure the "Explosive Move threshold" (default: 3), "Idle Market Threshold" (default: 7) and "Thermometer EMA length" (default: 22) via Options page.
More info:
"Come in to my Trading Room - A complete Guide to Trading" by Dr.Alexander Elder. (Page 162)
List of my other indicators:
- Chart:
- GDoc: docs.google.com
Weekly opening targets +-5%## Summary
This indicator automatically plots key percentage-based price levels above and below the current week's opening price. It is designed to provide traders with a clear map of potential intra-week support, resistance, and target zones based on clean, mathematical levels.
The script is lightweight and focuses on providing a clutter-free visual guide, making it easy to identify significant price areas at a glance.
## Features
Weekly Open Pivot: A central blue line clearly marks the opening price for the current week, acting as the primary baseline for all calculations.
Precise 1% Levels: The indicator calculates and draws horizontal lines at exact 1% increments away from the weekly open, covering a range from +/- 1% up to +/- 5%.
Color-Coded Zones: Levels above the weekly open are colored green (representing potential resistance or target zones), while levels below are colored red (representing potential support).
Real-Time Price Labels: To ensure clarity, clean labels are displayed on the right-hand side of the chart. Each label shows both its percentage deviation and the exact price, updating automatically with the latest data.
## How to Use
This tool is versatile, but here are a few common applications:
Identifying Support & Resistance: The primary use is to watch for price reactions at these calculated levels. A bounce off a lower (red) level could signal support, while a rejection from an upper (green) level could signal resistance.
Setting Profit Targets: The levels serve as excellent, non-subjective price targets. For example, if you enter a long position near the weekly open, the +1% and +2% levels are logical areas to consider taking profit.
Gauging Weekly Momentum: The distance price travels between these levels can help gauge the strength of the weekly trend. Consistently breaking through levels indicates strong momentum, while failing to do so may suggest consolidation.
This indicator is particularly useful for day traders and swing traders who use the weekly open as a key reference point for market sentiment and direction.
Script_Algo - Double Smoothed CCI Strategy📉 The uniqueness of this non-trending oscillator strategy lies in the combination of two smoothed CCI lines: one signals entry into a position from overbought/oversold zones, and the other serves as a trend filter for entries. The smoothing of the fast and slow CCI lines significantly reduces market noise, allowing the filtering of false signals often generated by the standard CCI.
📚 For those unfamiliar with CCI:
The Commodity Channel Index (CCI) is a momentum-based oscillator used to identify overbought and oversold conditions.
It helps traders spot potential trend reversals or confirm trend strength by comparing the current price to its average over a period of time.
1️⃣ General Principle of Operation
⚡ Fast CCI: Generates main signals when exiting oversold and overbought zones.
📈 Slow CCI: Acts as a trend filter. For long positions, the slow CCI must be above zero (confirmation of an uptrend), and for short positions, it must be below zero (confirmation of a downtrend). This prevents the strategy from opening trades against the dominant trend.
🛡️ Dynamic ATR Stop-Loss: Unlike fixed-percentage stop-losses, a stop tied to the Average True Range (ATR) considers market volatility. During calm periods, the stop will be narrower, allowing for more profit capture. In highly volatile periods, the stop becomes wider, protecting against premature closures caused by noise.
📊 Comprehensive Risk Management: The strategy uses not only a take-profit based on signals (exit into the opposite zone) but also a protective ATR stop-loss and a mechanism to close trades upon receiving an opposite signal (e.g., closing a long when a short signal appears).
💡 Usefulness of the Strategy:
👨💻 For traders: Provides clear, mathematically justified entry and exit signals with built-in loss protection.
📉 For analysts: Visualizes the behavior of the double CCI on a separate panel, allowing study of the interaction of the fast and slow lines and their reaction to levels without mandatory trades.
📚 For learning: An excellent example of combining multiple indicators and capital management tools into a single trading system.
2️⃣ Detailed Algorithm Logic
📥 Long Entry Signals:
The fast smoothed CCI was below the oversold level (oversold_level, e.g., -100) and crossed this level upward (fast_exits_oversold).
The slow CCI at this moment is above zero (confirming an uptrend).
If both conditions are met, a long position is opened.
📤 Long Exit: Happens under one of these conditions:
The fast CCI crosses the overbought level (overbought_level) downward (exit_long).
The price reaches a stop-loss level calculated as entry price - (ATR * multiplier).
An opposite short signal appears (enter_short).
📥 Short Entry Signals:
The fast CCI was above the overbought level (overbought_level, e.g., 100) and crossed this level downward (fast_exits_overbought).
The slow CCI at this moment is below zero (confirming a downtrend).
If both conditions are met, a short position is opened.
📤 Short Exit: Happens under one of these conditions:
The fast CCI crosses the oversold level (oversold_level) upward (exit_short).
The price reaches a stop-loss level calculated as entry price + (ATR * multiplier).
An opposite long signal appears (enter_long).
3️⃣ Default Settings Description
⚙️ General Strategy Settings (strategy):
overlay=false: The indicator is displayed in a separate panel below the chart, not overlaid on it.
default_qty_type=strategy.cash, default_qty_value=1000, initial_capital=100000: The strategy manages a virtual capital of 100,000 USD, using 1,000 USD per trade.
commission_value=0.1, slippage=1: Commission (0.1%) and slippage (1 tick) are considered for more realistic testing.
⚡ Fast CCI (Signal Generator):
Length: 8 (short enough for quick price reactions).
Source: hlc3 (average of High, Low, Close).
Smoothing: WMA (Weighted Moving Average) for smoother results than SMA.
Smoothing Length: 5 (removes part of the noise).
📈 Slow CCI (Trend Filter):
Length: 20 (standard mid-term trend period).
Source: close.
Smoothing: WMA.
Smoothing Length: 21 (even stronger smoothing for a clean trend line).
📊 Levels:
Overbought Level: 100 (classic CCI level).
Oversold Level: -100 (classic CCI level).
🛡️ Stop-Loss (ATR):
ATR Length: 6 (short period for quick adaptation).
ATR Multiplier: 10.0 (very wide stop, designed for long-term trade holding and noise filtering).
💰 As seen in backtests, this strategy shows a steadily growing equity curve with minor drawdowns. On the highly liquid crypto pair XRPUSDT, the algorithm demonstrated a fairly high win rate and relatively high profit factor on a 4-hour timeframe over 4 years, though the overall profit is moderate.
⚠️ Important Notes
Always remember: Strategy results may not repeat in the future.
The market constantly changes, so:
✅ Monitor the situation
✅ Backtest regularly
✅ Adjust settings for each asset
Also remember about possible bugs in any algorithmic trading strategy.
Even if a script is well-tested, no one knows what unpredictable events the market may bring tomorrow.
⚠️ Risk Management:
Do not risk more than 1% of your deposit per trade, otherwise you may lose your account balance, since this strategy works without stop losses.
⚠️ Disclaimer
The author of the strategy does not encourage anyone to use this algorithm and bears no responsibility for any possible financial losses resulting from its application!
Any decision to use this strategy is made personally by the owners of TradingView accounts and cryptocurrency exchange accounts.
📝 Final Notes
This is not the final version. I already have ideas on how to improve it further, so follow me to not miss updates.
🐞 Bug Reports
If you notice any bugs or inconsistencies in my algorithm,
please let me know — I will try to fix them as quickly as possible.
💬 Feedback & Suggestions
If you have any ideas on how this or any of my other strategies can be improved, feel free to write to me. I will try to implement your suggestions in the script.
Wishing everyone good luck and stable profits! 🚀💰
Marubozu Detector with Dynamic SL/TP
Strategy Overview:
This indicator detects a "Marubozu" bullish pattern or a “Marubozu” bearish pattern to suggest potential buy and sell opportunities. It uses dynamic Stop Loss (SL) and Take Profit (TP) management, based on either market volatility (ATR) or liquidity zones.
This tool is intended for educational and informational purposes only.
Key Features:
Entry: Based on detecting Marubozu bullish or bearish candle pattern.
Exit: Targets are managed through ATR multiples or previous liquidity levels (swing highs or swing lows).
Smart Liquidity: Optionally identify deeper liquidity targets.
Full Alerts: Buy and Sell signals supported with customizable alerts.
Visualized Trades: Entry, SL, and TP levels are plotted on the chart.
User Inputs:
ATR Length, ATR Multipliers
Take Profit Mode (Liquidity/ATR)
Swing Lookback and Strength
Toggleable Buy/Sell alerts
All Time Frames
📖 How to Use:
Add the Indicator:
Apply the script to your chart from the TradingView indicators panel.
Look for Buy Signals:
A buy signal is triggered when the script detects a "Marubozu" bullish pattern.
Entry, Stop Loss, and Take Profit levels are plotted automatically.
Look for Sell Signals:
A Sell signal is triggered when the script detects a "Marubozu" bearish pattern.
Entry, Stop Loss, and Take Profit levels are plotted automatically.
Choose Take Profit Mode:
ATR Mode: TP is based on a volatility target.
Liquidity Mode: TP is based on past swing highs.
Set Alerts (Optional):
Enable Buy/Sell alerts in the settings to receive real-time notifications.
Practice First:
Always backtest and paper trade before live use.
📜 Disclaimer:
This script does not offer financial advice.
No guarantees of profit or performance are made.
Use in demo accounts or backtesting first.
Always practice proper risk management and seek advice from licensed professionals if needed.
✅ Script Compliance:
This script is designed in full accordance with TradingView’s House Rules for educational tools.
No financial advice is provided, no performance is guaranteed, and users are encouraged to backtest thoroughly.
SPX EMA 9/21 + VWAP Strategy1. Temporality: 2 minutes.
2. EMA 9 and EMA 21:
• Purchase Call: when EMA 9 crosses up EMA 21 and the price is > VWAP.
• Put : when EMA 9 crosses down EMA 21 and the price is < VWAP.
3. Stop and Take Profit:
• Stop: candle closure on the other side of the VWAP.
• TP: configurable in points (e.g. +10 pts, +20 pts) or up to the opposite crossing of EMAs.
• Long enters when EMA 9 crosses up 21 and the price is above VWAP.
• Short enters when the EMA 9 crosses down the 21 and the price is below VWAP.
• TP and SL in SPX points (configurable in inputs).
• You can run in 2 minutes on SPX.
Sunmool's Silver Bullet Model FinderICT Silver Bullet Model Indicator - Complete Guide
📈 Overview
The ICT Silver Bullet Model indicator is a supplementary tool for utilizing ICT's (Inner Circle Trader) market structure analysis techniques. This indicator detects institutional liquidity hunting patterns and automatically identifies structural levels, helping traders analyze market structure more effectively.
🎯 Core Features
1. Structural Level Identification
STL (Short Term Low): Recent support levels formed in the short term
STH (Short Term High): Recent resistance levels formed in the short term
ITL (Intermediate Term Low): Stronger support levels with more significance
ITH (Intermediate Term High): Stronger resistance levels with more significance
2. Kill Zone Time Display
London Kill Zone: 02:00-05:00 (default)
New York Kill Zone: 08:30-11:00 (default)
These are the most active trading hours for institutional players where significant price movements occur
3. Smart Sweep Detection
Bear Sweep (🔻): Pattern where price sweeps below lows then recovers - Simply indicates sweep occurrence
Bull Sweep (🔺): Pattern where price sweeps above highs then declines - Simply indicates sweep occurrence
Important: Sweep labels only mark liquidity hunting locations, not directional bias.
🔧 Configuration Parameters
Basic Settings
Sweep Detection Lookback: Number of candles for sweep detection (default: 20)
Structure Point Lookback: Number of candles for structural point detection (default: 10)
Sweep Threshold: Percentage threshold for sweep validation (default: 0.1%)
Time Settings
London Kill Zone: Active hours for London session
New York Kill Zone: Active hours for New York session
Visualization Settings
Customizable colors for each level type
Enable/disable alert notifications
📊 How to Use
1. Chart Setup
Most effective on 1-minute to 1-hour timeframes
Recommended for major currency pairs (EUR/USD, GBP/USD, etc.)
Also applicable to cryptocurrencies and indices
2. Signal Interpretation
🔻 Bear Sweep / 🔺 Bull Sweep Labels
Simply indicate liquidity hunting occurrence points
Not directional bias indicators
Reference for understanding overall context on HTF
🟢 Silver Bullet Long (Huge Green Triangle)
After Bear Sweep occurrence
Within Kill Zone timeframe
Current price positioned above swept level
→ Actual BUY entry signal
🔴 Silver Bullet Short (Huge Red Triangle)
After Bull Sweep occurrence
Within Kill Zone timeframe
Current price positioned below swept level
→ Actual SELL entry signal
3. Risk Management
Use swept levels as stop-loss reference points
Approach signals outside Kill Zone hours with caution
Recommended to use alongside other technical analysis tools
💡 Trading Strategies
Silver Bullet Strategy
Preparation Phase: Monitor charts 30 minutes before Kill Zone
Sweep Observation: Identify liquidity hunting points with 🔻🔺 labels (reference only)
Entry: Enter ONLY when huge triangle Silver Bullet signal appears within Kill Zone
Take Profit: Target opposite structural level or 1:2 reward ratio
Stop Loss: Beyond the swept level
Important: Small sweep labels are NOT trading signals!
Multi-Timeframe Approach
Step 1: HTF (Higher Time Frame) Sweep Reference
Observe 🔻🔺 sweep labels on 4-hour and daily charts
Reference only sweeps occurring at major structural levels
HTF sweeps are used to identify liquidity hunting points
Reference only, not for directional bias
Step 2: Transition to LTF (Lower Time Frame)
Move to 15-minute, 5-minute, and 1-minute charts
Analyze LTF with reference to HTF sweep information
Use STL, STH, ITL, ITH for precise entry point identification
Structural levels on LTF are the core of actual trading decisions
Only huge triangle (Silver Bullet) signals are actual entry signals
Recommended Usage
Identify overall sweep occurrence points on HTF (🔻🔺 labels)
Use this indicator on LTF to identify structural levels
Reference only huge triangle signals for actual trading during Kill Zone
Small sweep labels (🔻🔺) are for reference only, not entry signals
📋 Information Table Interpretation
Real-time information in the top-right table:
Kill Zone Status: Current active session status
Level Counts: Number of each structural level type
⚠️ Important Disclaimers
Backtesting results do not guarantee future performance
Exercise caution during high market volatility periods
Always apply proper risk management
Recommend comprehensive analysis with other analytical tools
🎓 Learning Resources
Study original ICT concepts through free YouTube educational content
Research Market Structure analysis techniques
Optimize through backtesting for personal use
🔬 Technical Implementation
Algorithm Logic
Pivot Point Detection: Uses TradingView's built-in pivot functions to identify swing highs and lows
Classification System: Automatically categorizes levels based on recent price action frequency
Sweep Validation: Confirms legitimate sweeps through price action analysis
Time-Based Filtering: Prioritizes signals during institutional active hours
Performance Optimization
Efficient array management prevents memory overflow
Dynamic level cleanup maintains chart clarity
Real-time calculation ensures minimal lag
🛠️ Customization Tips
Adjust lookback periods based on market volatility
Modify kill zone times for different market sessions
Experiment with sweep threshold for different instruments
Color-code levels according to personal preference
📈 Expected Outcomes
When properly implemented, this indicator can help traders:
Identify high-probability reversal points
Time entries with institutional flow
Reduce false signals through kill zone filtering
Improve risk-to-reward ratios
This indicator automates ICT's concepts into a user-friendly tool that can be enhanced through continuous learning and practical application. Success depends on understanding the underlying market structure principles and combining them with proper risk management techniques.
HMK-2 | PCA-1 + Rejim + Chebyshev + VWAP (Input'lu, v6)📌 HMK-2 | PCA-1 + Regime + Chebyshev + VWAP Strategy
1️⃣ Core Structure
Instead of relying on a single indicator, this system uses the Z-Score normalized average of three oscillators (RSI, MFI, ROC).
Signal (PCA-1):
RSI(14), MFI(14), ROC(5) → each is converted into a z-score.
Their average becomes the “composite signal,” our PCA-1 value.
Trend direction: If the Z-score EMA is rising → trend UP. If falling → trend DOWN.
2️⃣ Side Filters
Regime Filter (ADX + EMA)
ADX is calculated manually.
If ADX > 20 → trend exists → a 50-period EMA of this value smooths it.
This turns “trend regime” into a probability between 0–1.
Chebyshev Filter
A return series is checked against mean ± k*sigma bands.
If the return is within this band → valid signal. Extreme moves are filtered out.
VWAP Filter
Long trades: price must be above VWAP.
Short trades: price must be below VWAP.
Trades are only taken on the correct side of institutional cost averages.
3️⃣ Entry Conditions
Long:
PCA-1 signal crosses above threshold.
Trend Up + Regime OK + Chebyshev OK + Above VWAP.
Short:
PCA-1 signal crosses below threshold.
Trend Down + Regime OK + Chebyshev OK + Below VWAP.
4️⃣ Exit Mechanism
Main Exit: ATR-based stop/target.
Stop = entry price – ATR × (SL factor).
Take profit = entry price + ATR × (TP factor).
Additional Exit:
If price crosses to the opposite side of VWAP.
If PCA-1 signal crosses zero.
👉 Prevents trades from being locked, makes exits adaptive.
5️⃣ Labels / Visualization
AL / SHORT → entry points.
SAT / COVER → exit points.
VWAP line plotted in blue.
🧩 Strategy Features
Optimizable parameters:
Z-window (zWin)
Threshold
Chebyshev factor
ATR stop/target multipliers
This system works with:
Disciplined core (PCA-1 signal)
Triple protection (Regime + Chebyshev + VWAP)
Adaptive exits (ATR + VWAP/signal cross)
👉 Not a “single-indicator robot,” but a multi-filtered trade direction engine.
💡 Final Note
This is a base model of the system — open for further development.
I’ve shared the logic to give you a roadmap.
If you spot errors, fix them → that’s how you’ll improve it.
Don’t waste time asking me questions — refine and build it better yourselves.
Wishing you profitable trades. Stay well 🙏
Instant Breakout Strategy with RSI & VWAPInstant Breakout Strategy with RSI & VWAP
This TradingView strategy (Pine Script v6) trades breakouts using pivot points, with optional filters for volume, momentum, RSI, and VWAP. It’s optimized for the 1-second timeframe.
Overview
The strategy identifies breakouts when price crosses above resistance (pivot highs) or below support (pivot lows). It can use basic pivot breakouts or add filters for stronger signals. Take-profit and stop-loss levels are set using ATR, and signals are shown on the chart.
Inputs
Left/Right Pivot Bars: Bars to detect pivots (default: 3). Lower values increase sensitivity.
Volume Surge Multiplier: Volume threshold vs. 20-period average (default: 1.5).
Momentum Threshold: Minimum % price change from bar open (default: 1%).
Take-Profit ATR Multiplier: ATR multiplier for take-profit (default: 9.0).
Stop-Loss ATR Multiplier: ATR multiplier for stop-loss (default: 1.0).
Use Filters: Enable/disable volume, momentum, RSI, and VWAP filters (default: off).
How It Works
1. Pivot Detection
Finds pivot highs (resistance) and lows (support) using ta.pivothigh and ta.pivotlow.
Tracks the latest pivot levels.
2. Volume Surge
Compares current volume to a 20-period volume average.
A surge occurs if volume exceeds the average times the multiplier.
3. Momentum
Measures price change from the bar’s open.
Bullish: Price rises >1% from open.
Bearish: Price falls >1% from open.
4. RSI and VWAP
RSI: 3-period RSI. Above 50 is bullish; below 50 is bearish.
VWAP: Price above VWAP is bullish; below is bearish.
5. ATR
14-period ATR sets take-profit (close ± atr * 9.0) and stop-loss (close ± atr * 1.0).
Trading Rules
Breakout Conditions
Bullish Breakout:
Price crosses above the latest pivot high.
With filters: Volume surge, bullish momentum, RSI > 50, price > VWAP.
Without filters: Only the crossover is needed.
Bearish Breakout:
Price crosses below the latest pivot low.
With filters: Volume surge, bearish momentum, RSI < 50, price < VWAP.
Without filters: Only the crossunder is needed.
Entries and Exits
Long: Enter on bullish breakout. Set take-profit and stop-loss. Close any short position.
Short: Enter on bearish breakout. Set take-profit and stop-loss. Close any long position.
Visuals
Signals: Green triangles (bullish) below bars, red triangles (bearish) above bars.
Pivot Levels: Green line (resistance), red line (support).
Indicators: RSI (blue, separate pane), VWAP (purple, on chart).
How to Use
Apply to a 1-second chart in TradingView for best results.
Adjust inputs (e.g., pivot bars, multipliers). Enable filters for stricter signals.
Watch for buy/sell triangles and monitor RSI/VWAP.
Use ATR-based take-profit/stop-loss for risk management.
Notes
Best on 1-second timeframe due to fast RSI and responsiveness.
Disable filters for more signals (less confirmation).
Backtest before live trading to check performance.
This strategy uses pivots, volume, momentum, RSI, and VWAP for clear breakout trades on the 1-second timeframe.
PowerTrend Pro Strategy – Gold OptimizedTired of false signals on Gold?
PowerTrend Pro combines VWAP, Supertrend, RSI, and smart MA filters with trailing stops & break-even logic to deliver high-probability trades on XAUUSD.
PowerTrend Pro Strategy is a professional-grade trading system designed to capture high-probability swing and intraday opportunities on XAUUSD (Gold) and other volatile markets.
🔑 Core Features
VWAP Anchoring – institutional fair value reference to filter trades.
Supertrend (ATR-based) – adaptive trend filter tuned for Gold’s volatility.
Multi-Timeframe RSI – confirms momentum alignment across intraday and higher timeframe.
EMA + SMA Combo – ensures trades follow strong directional bias, reducing false signals.
Dynamic Risk Management
Adjustable Take Profit / Stop Loss (%)
Trailing Stop that locks in profits on extended moves
Break-Even Logic (stop loss moves to entry once price is in profit)
⚡ Gold-Tuned Presets
XAUUSD 1H → tighter TP/SL & faster entries for active intraday trading.
XAUUSD 4H → wider ATR filter & trailing stops to capture bigger swings.
Generic Mode → works on Forex, Indices, and Crypto (fully customizable).
🎯 Why It Works
Gold is notoriously volatile — quick spikes wipe out weak strategies. PowerTrend Pro solves this by combining:
✅ Institutional bias (VWAP)
✅ Adaptive trend filter (Supertrend)
✅ Momentum confirmation (RSI MTF)
✅ Robust trend structure (EMA + SMA)
✅ Smart exits (TP, SL, trailing & breakeven)
This multi-layer confirmation makes entries stronger and keeps risk under control.
🛠️ Usage
Add the strategy to your chart.
Choose a preset (XAUUSD 1H, 4H, or Generic).
Run Strategy Tester for performance metrics.
Optimize TP/SL and ATR values for your broker & market conditions.
🔥 Pro Tip: Combine this strategy with a session filter (London/NY overlap) or volume confirmation to boost accuracy in Gold.
Elliott Wave - Impulse + Corrective Detector (Demo) เทคนิคการใช้
สำหรับมือใหม่
ดูเฉพาะ Impulse Wave ก่อน
เทรดตาม direction ของ impulse
ใช้ Fibonacci เป็น support/resistance
สำหรับ Advanced
ใช้ Corrective Wave หาจุด reversal
รวม Triangle กับ breakout strategy
ใช้ Complex correction วางแผนระยะยาว
⚙️ การปรับแต่ง
ถ้าเจอ Pattern น้อยเกินไป
ลด Swing Length เป็น 3-4
เพิ่ม Max History เป็น 500
ถ้าเจอ Pattern เยอะเกินไป
เพิ่ม Swing Length เป็น 8-12
ปิด patterns ที่ไม่ต้องการ
สำหรับ Timeframe ต่างๆ
H1-H4: Swing Length = 5-8
Daily: Swing Length = 3-5
Weekly: Swing Length = 2-3
⚠️ ข้อควรระวัง
Elliott Wave เป็น subjective analysis
ใช้ร่วมกับ indicators อื่นๆ
Backtest ก่อนใช้เงินจริง
Pattern อาจเปลี่ยนได้ตลอดเวลา
🎓 สรุป
โค้ดนี้เป็นเครื่องมือช่วยวิเคราะห์ Elliott Wave ที่:
✅ ใช้งานง่าย
✅ ตรวจจับอัตโนมัติ
✅ มี confidence scoring
✅ แสดงผล Fibonacci levels
✅ ส่ง alerts เรียลไทม์
เหมาะสำหรับ: Trader ที่ต้องการใช้ Elliott Wave ในการวิเคราะห์เทคนิค แต่ไม่มีเวลานั่งหา pattern เอง
💡 Usage Tips
For Beginners
Focus on Impulse Waves first
Trade in the direction of impulse
Use Fibonacci as support/resistance levels
For Advanced Users
Use Corrective Waves to find reversal points
Combine Triangles with breakout strategies
Use Complex corrections for long-term planning
⚙️ Customization
If You See Too Few Patterns
Decrease Swing Length to 3-4
Increase Max History to 500
If You See Too Many Patterns
Increase Swing Length to 8-12
Turn off unwanted pattern types
For Different Timeframes
H1-H4: Swing Length = 5-8
Daily: Swing Length = 3-5
Weekly: Swing Length = 2-3
⚠️ Important Warnings
Elliott Wave is subjective analysis
Use with other technical indicators
Backtest before using real money
Patterns can change at any time
🔧 Troubleshooting
No Patterns Showing
Check if you have enough price history
Adjust Swing Length settings
Make sure pattern detection is enabled
Too Many False Signals
Increase confidence threshold requirements
Use higher timeframes
Combine with trend analysis
Performance Issues
Reduce Max History setting
Turn off unnecessary visual elements
Use on liquid markets only
📈 Trading Applications
Entry Strategies
Wave 3 Entry: After Wave 2 completion (61.8%-78.6% retracement)
Wave 5 Target: Equal to Wave 1 or Fibonacci extensions
Corrective Bounce: Trade reversals at C wave completion
Risk Management
Stop Loss: Beyond pattern invalidation levels
Take Profit: Fibonacci extension targets
Position Sizing: Based on pattern confidence
🎓 Summary
This code is an Elliott Wave analysis tool that offers:
✅ Easy to use interface
✅ Automatic pattern detection
✅ Confidence scoring system
✅ Fibonacci level display
✅ Real-time alerts
Perfect for: Traders who want to use Elliott Wave analysis but don't have time to manually identify patterns.
📚 Quick Reference
Pattern Hierarchy (Most to Least Reliable)
Impulse Waves (90% confidence)
Expanded Flats (85% confidence)
Zigzags (80% confidence)
Triangles (75% confidence)
Complex Corrections (70% confidence)
Best Practices
Start with higher timeframes for main trend
Use lower timeframes for precise entries
Always confirm with volume and momentum
Don't trade against strong fundamental news
Keep a trading journal to track performance
Remember: Elliott Wave is an art as much as a science. This tool helps identify potential patterns, but always use your judgment and additional analysis before making trading decisions.
Crypto Pulse Signals+ Precision
Crypto Pulse Signals
Institutional-grade background signals for BTC/ETH low-timeframe trading (2m/5m/15m).
🔵 BLUE TINT = Valid LONG signal (enter when candle closes)
🔴 RED TINT = Valid SHORT signal (enter when candle closes)
🌫️ NO TINT = No signal (avoid trading)
✅ BTC Momentum Filter: ETH signals only fire when BTC confirms (avoids 78% of fakeouts)
✅ Volatility-Adaptive: Signals auto-adjust to market conditions (no manual tuning)
✅ Dark Mode Optimized: Perfect contrast on all chart themes
Pro Trading Protocol:
Trade ONLY during NY/London overlap (12-16 UTC)
Enter on candle close when tint appears
Stop loss: Below/above signal candle's wick
Take profit: 1.8x risk (68% win rate in backtests)
Based on live trading during 2024 bull run - no repaint, no lag.
🔍 Why This Description Converts
Element Purpose
Clear visual cues "🔵 BLUE TINT = LONG" works instantly for scanners
BTC filter emphasis Highlights institutional edge (ETH traders' #1 pain point)
Time-specific protocol Filters out low-probability Asian session signals
Backtested stats Builds credibility without hype ("68% win rate" = believable)
Dark mode mention Targets 83% of crypto traders who use dark charts
📈 Real Dark Mode Performance
(Tested on TradingView Dark Theme - ETH/USDT 5m chart)
UTC Time Signal Color Visibility Result
13:27 🔵 LONG Perfect contrast against black background +4.1% in 11 min
15:42 🔴 SHORT Red pops without bleeding into red candles -3.7% in 8 min
03:19 None Zero visual noise during Asian session Avoided 2 fakeouts
Pro Tip: On dark mode, the optimized #4FC3F7 blue creates a subtle "watermark" effect - visible in peripheral vision but never distracting from price action.
✅ How to Deploy
Paste code into Pine Editor
Apply to BTC/USDT or ETH/USDT chart (Binance/Kraken)
Set timeframe to 2m, 5m, or 15m
Trade signals ONLY between 12-16 UTC (NY/London overlap)
This is what professional crypto trading desks actually use - stripped of all noise, optimized for real screens, and battle-tested in volatile markets. No bottom indicators. No clutter. Just pure signals.
LANZ Strategy 6.0🔷 LANZ Strategy 6.0 — NY Session Entry Tool & Multi-Account Risk Manager
LANZ Strategy 6.0 - Is a trading tool designed to help traders plan, execute, and manage operations with a focus on risk management, multi-account handling, and visual clarity.
It works exclusively on the 1-hour timeframe ⏳ and is optimized for the New York market opening dynamics.
🧠 Core Concept
The strategy identifies bullish trading opportunities based on the 09:00 NY candle. Once detected, it automatically calculates and draws:
EP (Entry Price) — The exact level where the trade setup triggers.
SL (Stop Loss) — Based on a customizable percentage of the candle's high–low range or wick extremes.
TP (Take Profit) — Calculated using your chosen Risk–Reward Ratio (e.g., 1:5, 1:3, etc.).
⚙️ Main Features
⏳ Time-Specific Execution
Operates only when the 09:00 NY candle closes bullish.
Ideal for traders who align with the New York Session market structure.
💰 Multi-Account Lot Size Management
Up to 5 independent accounts can be configured with their own capital and risk %, showing the exact lot size to use for each.
📏 Adaptive Risk Control
Supports both Forex and non-Forex assets (indices, gold, oil).
For non-Forex, you can manually define the pip value according to your broker’s specs.
🎨 Visual Trade Map
Automatically plots clean and easy-to-read EP, SL, and TP lines with customizable colors, styles, and thickness.
A floating information panel displays levels, pip distances, and lot sizes.
🔔 Real-Time Alerts
Alerts for:
Entry signal detection.
Stop Loss hit.
Take Profit hit.
Manual close at the defined session end.
📊 Example
If you trade GBPUSD with Account #1 set to $10,000 and 2% risk,
and the 09:00 NY candle closes bullish with SL = 30 pips and RR = 5:1:
EP, SL, and TP levels are drawn instantly.
Risk = $200 (2% of $10,000).
Lot size is calculated automatically.
All details are shown in the on-chart panel.
🛠️ How to Use
Load the indicator on a 1-hour chart.
Configure risk settings and account data.
Wait for the 09:00 NY candle to close bullish.
Use the displayed lot size and levels to execute your trade.
Let the tool alert you for SL, TP, or manual close.
⚠️ Disclaimer:
This script is for educational purposes only. It does not guarantee profits and past performance does not represent future results. Always manage your risk responsibly.
👨💻 Credits:
💡 Developed by: LANZ
🧠 Execution Model & Logic Design: LANZ
📅 Designed for: 1H timeframe and NY-based entries
Kelly Position Size CalculatorThis position sizing calculator implements the Kelly Criterion, developed by John L. Kelly Jr. at Bell Laboratories in 1956, to determine mathematically optimal position sizes for maximizing long-term wealth growth. Unlike arbitrary position sizing methods, this tool provides a scientifically solution based on your strategy's actual performance statistics and incorporates modern refinements from over six decades of academic research.
The Kelly Criterion addresses a fundamental question in capital allocation: "What fraction of capital should be allocated to each opportunity to maximize growth while avoiding ruin?" This question has profound implications for financial markets, where traders and investors constantly face decisions about optimal capital allocation (Van Tharp, 2007).
Theoretical Foundation
The Kelly Criterion for binary outcomes is expressed as f* = (bp - q) / b, where f* represents the optimal fraction of capital to allocate, b denotes the risk-reward ratio, p indicates the probability of success, and q represents the probability of loss (Kelly, 1956). This formula maximizes the expected logarithm of wealth, ensuring maximum long-term growth rate while avoiding the risk of ruin.
The mathematical elegance of Kelly's approach lies in its derivation from information theory. Kelly's original work was motivated by Claude Shannon's information theory (Shannon, 1948), recognizing that maximizing the logarithm of wealth is equivalent to maximizing the rate of information transmission. This connection between information theory and wealth accumulation provides a deep theoretical foundation for optimal position sizing.
The logarithmic utility function underlying the Kelly Criterion naturally embodies several desirable properties for capital management. It exhibits decreasing marginal utility, penalizes large losses more severely than it rewards equivalent gains, and focuses on geometric rather than arithmetic mean returns, which is appropriate for compounding scenarios (Thorp, 2006).
Scientific Implementation
This calculator extends beyond basic Kelly implementation by incorporating state of the art refinements from academic research:
Parameter Uncertainty Adjustment: Following Michaud (1989), the implementation applies Bayesian shrinkage to account for parameter estimation error inherent in small sample sizes. The adjustment formula f_adjusted = f_kelly × confidence_factor + f_conservative × (1 - confidence_factor) addresses the overconfidence bias documented by Baker and McHale (2012), where the confidence factor increases with sample size and the conservative estimate equals 0.25 (quarter Kelly).
Sample Size Confidence: The reliability of Kelly calculations depends critically on sample size. Research by Browne and Whitt (1996) provides theoretical guidance on minimum sample requirements, suggesting that at least 30 independent observations are necessary for meaningful parameter estimates, with 100 or more trades providing reliable estimates for most trading strategies.
Universal Asset Compatibility: The calculator employs intelligent asset detection using TradingView's built-in symbol information, automatically adapting calculations for different asset classes without manual configuration.
ASSET SPECIFIC IMPLEMENTATION
Equity Markets: For stocks and ETFs, position sizing follows the calculation Shares = floor(Kelly Fraction × Account Size / Share Price). This straightforward approach reflects whole share constraints while accommodating fractional share trading capabilities.
Foreign Exchange Markets: Forex markets require lot-based calculations following Lot Size = Kelly Fraction × Account Size / (100,000 × Base Currency Value). The calculator automatically handles major currency pairs with appropriate pip value calculations, following industry standards described by Archer (2010).
Futures Markets: Futures position sizing accounts for leverage and margin requirements through Contracts = floor(Kelly Fraction × Account Size / Margin Requirement). The calculator estimates margin requirements as a percentage of contract notional value, with specific adjustments for micro-futures contracts that have smaller sizes and reduced margin requirements (Kaufman, 2013).
Index and Commodity Markets: These markets combine characteristics of both equity and futures markets. The calculator automatically detects whether instruments are cash-settled or futures-based, applying appropriate sizing methodologies with correct point value calculations.
Risk Management Integration
The calculator integrates sophisticated risk assessment through two primary modes:
Stop Loss Integration: When fixed stop-loss levels are defined, risk calculation follows Risk per Trade = Position Size × Stop Loss Distance. This ensures that the Kelly fraction accounts for actual risk exposure rather than theoretical maximum loss, with stop-loss distance measured in appropriate units for each asset class.
Strategy Drawdown Assessment: For discretionary exit strategies, risk estimation uses maximum historical drawdown through Risk per Trade = Position Value × (Maximum Drawdown / 100). This approach assumes that individual trade losses will not exceed the strategy's historical maximum drawdown, providing a reasonable estimate for strategies with well-defined risk characteristics.
Fractional Kelly Approaches
Pure Kelly sizing can produce substantial volatility, leading many practitioners to adopt fractional Kelly approaches. MacLean, Sanegre, Zhao, and Ziemba (2004) analyze the trade-offs between growth rate and volatility, demonstrating that half-Kelly typically reduces volatility by approximately 75% while sacrificing only 25% of the growth rate.
The calculator provides three primary Kelly modes to accommodate different risk preferences and experience levels. Full Kelly maximizes growth rate while accepting higher volatility, making it suitable for experienced practitioners with strong risk tolerance and robust capital bases. Half Kelly offers a balanced approach popular among professional traders, providing optimal risk-return balance by reducing volatility significantly while maintaining substantial growth potential. Quarter Kelly implements a conservative approach with low volatility, recommended for risk-averse traders or those new to Kelly methodology who prefer gradual introduction to optimal position sizing principles.
Empirical Validation and Performance
Extensive academic research supports the theoretical advantages of Kelly sizing. Hakansson and Ziemba (1995) provide a comprehensive review of Kelly applications in finance, documenting superior long-term performance across various market conditions and asset classes. Estrada (2008) analyzes Kelly performance in international equity markets, finding that Kelly-based strategies consistently outperform fixed position sizing approaches over extended periods across 19 developed markets over a 30-year period.
Several prominent investment firms have successfully implemented Kelly-based position sizing. Pabrai (2007) documents the application of Kelly principles at Berkshire Hathaway, noting Warren Buffett's concentrated portfolio approach aligns closely with Kelly optimal sizing for high-conviction investments. Quantitative hedge funds, including Renaissance Technologies and AQR, have incorporated Kelly-based risk management into their systematic trading strategies.
Practical Implementation Guidelines
Successful Kelly implementation requires systematic application with attention to several critical factors:
Parameter Estimation: Accurate parameter estimation represents the greatest challenge in practical Kelly implementation. Brown (1976) notes that small errors in probability estimates can lead to significant deviations from optimal performance. The calculator addresses this through Bayesian adjustments and confidence measures.
Sample Size Requirements: Users should begin with conservative fractional Kelly approaches until achieving sufficient historical data. Strategies with fewer than 30 trades may produce unreliable Kelly estimates, regardless of adjustments. Full confidence typically requires 100 or more independent trade observations.
Market Regime Considerations: Parameters that accurately describe historical performance may not reflect future market conditions. Ziemba (2003) recommends regular parameter updates and conservative adjustments when market conditions change significantly.
Professional Features and Customization
The calculator provides comprehensive customization options for professional applications:
Multiple Color Schemes: Eight professional color themes (Gold, EdgeTools, Behavioral, Quant, Ocean, Fire, Matrix, Arctic) with dark and light theme compatibility ensure optimal visibility across different trading environments.
Flexible Display Options: Adjustable table size and position accommodate various chart layouts and user preferences, while maintaining analytical depth and clarity.
Comprehensive Results: The results table presents essential information including asset specifications, strategy statistics, Kelly calculations, sample confidence measures, position values, risk assessments, and final position sizes in appropriate units for each asset class.
Limitations and Considerations
Like any analytical tool, the Kelly Criterion has important limitations that users must understand:
Stationarity Assumption: The Kelly Criterion assumes that historical strategy statistics represent future performance characteristics. Non-stationary market conditions may invalidate this assumption, as noted by Lo and MacKinlay (1999).
Independence Requirement: Each trade should be independent to avoid correlation effects. Many trading strategies exhibit serial correlation in returns, which can affect optimal position sizing and may require adjustments for portfolio applications.
Parameter Sensitivity: Kelly calculations are sensitive to parameter accuracy. Regular calibration and conservative approaches are essential when parameter uncertainty is high.
Transaction Costs: The implementation incorporates user-defined transaction costs but assumes these remain constant across different position sizes and market conditions, following Ziemba (2003).
Advanced Applications and Extensions
Multi-Asset Portfolio Considerations: While this calculator optimizes individual position sizes, portfolio-level applications require additional considerations for correlation effects and aggregate risk management. Simplified portfolio approaches include treating positions independently with correlation adjustments.
Behavioral Factors: Behavioral finance research reveals systematic biases that can interfere with Kelly implementation. Kahneman and Tversky (1979) document loss aversion, overconfidence, and other cognitive biases that lead traders to deviate from optimal strategies. Successful implementation requires disciplined adherence to calculated recommendations.
Time-Varying Parameters: Advanced implementations may incorporate time-varying parameter models that adjust Kelly recommendations based on changing market conditions, though these require sophisticated econometric techniques and substantial computational resources.
Comprehensive Usage Instructions and Practical Examples
Implementation begins with loading the calculator on your desired trading instrument's chart. The system automatically detects asset type across stocks, forex, futures, and cryptocurrency markets while extracting current price information. Navigation to the indicator settings allows input of your specific strategy parameters.
Strategy statistics configuration requires careful attention to several key metrics. The win rate should be calculated from your backtest results using the formula of winning trades divided by total trades multiplied by 100. Average win represents the sum of all profitable trades divided by the number of winning trades, while average loss calculates the sum of all losing trades divided by the number of losing trades, entered as a positive number. The total historical trades parameter requires the complete number of trades in your backtest, with a minimum of 30 trades recommended for basic functionality and 100 or more trades optimal for statistical reliability. Account size should reflect your available trading capital, specifically the risk capital allocated for trading rather than total net worth.
Risk management configuration adapts to your specific trading approach. The stop loss setting should be enabled if you employ fixed stop-loss exits, with the stop loss distance specified in appropriate units depending on the asset class. For stocks, this distance is measured in dollars, for forex in pips, and for futures in ticks. When stop losses are not used, the maximum strategy drawdown percentage from your backtest provides the risk assessment baseline. Kelly mode selection offers three primary approaches: Full Kelly for aggressive growth with higher volatility suitable for experienced practitioners, Half Kelly for balanced risk-return optimization popular among professional traders, and Quarter Kelly for conservative approaches with reduced volatility.
Display customization ensures optimal integration with your trading environment. Eight professional color themes provide optimization for different chart backgrounds and personal preferences. Table position selection allows optimal placement within your chart layout, while table size adjustment ensures readability across different screen resolutions and viewing preferences.
Detailed Practical Examples
Example 1: SPY Swing Trading Strategy
Consider a professionally developed swing trading strategy for SPY (S&P 500 ETF) with backtesting results spanning 166 total trades. The strategy achieved 110 winning trades, representing a 66.3% win rate, with an average winning trade of $2,200 and average losing trade of $862. The maximum drawdown reached 31.4% during the testing period, and the available trading capital amounts to $25,000. This strategy employs discretionary exits without fixed stop losses.
Implementation requires loading the calculator on the SPY daily chart and configuring the parameters accordingly. The win rate input receives 66.3, while average win and loss inputs receive 2200 and 862 respectively. Total historical trades input requires 166, with account size set to 25000. The stop loss function remains disabled due to the discretionary exit approach, with maximum strategy drawdown set to 31.4%. Half Kelly mode provides the optimal balance between growth and risk management for this application.
The calculator generates several key outputs for this scenario. The risk-reward ratio calculates automatically to 2.55, while the Kelly fraction reaches approximately 53% before scientific adjustments. Sample confidence achieves 100% given the 166 trades providing high statistical confidence. The recommended position settles at approximately 27% after Half Kelly and Bayesian adjustment factors. Position value reaches approximately $6,750, translating to 16 shares at a $420 SPY price. Risk per trade amounts to approximately $2,110, representing 31.4% of position value, with expected value per trade reaching approximately $1,466. This recommendation represents the mathematically optimal balance between growth potential and risk management for this specific strategy profile.
Example 2: EURUSD Day Trading with Stop Losses
A high-frequency EURUSD day trading strategy demonstrates different parameter requirements compared to swing trading approaches. This strategy encompasses 89 total trades with a 58% win rate, generating an average winning trade of $180 and average losing trade of $95. The maximum drawdown reached 12% during testing, with available capital of $10,000. The strategy employs fixed stop losses at 25 pips and take profit targets at 45 pips, providing clear risk-reward parameters.
Implementation begins with loading the calculator on the EURUSD 1-hour chart for appropriate timeframe alignment. Parameter configuration includes win rate at 58, average win at 180, and average loss at 95. Total historical trades input receives 89, with account size set to 10000. The stop loss function is enabled with distance set to 25 pips, reflecting the fixed exit strategy. Quarter Kelly mode provides conservative positioning due to the smaller sample size compared to the previous example.
Results demonstrate the impact of smaller sample sizes on Kelly calculations. The risk-reward ratio calculates to 1.89, while the Kelly fraction reaches approximately 32% before adjustments. Sample confidence achieves 89%, providing moderate statistical confidence given the 89 trades. The recommended position settles at approximately 7% after Quarter Kelly application and Bayesian shrinkage adjustment for the smaller sample. Position value amounts to approximately $700, translating to 0.07 standard lots. Risk per trade reaches approximately $175, calculated as 25 pips multiplied by lot size and pip value, with expected value per trade at approximately $49. This conservative position sizing reflects the smaller sample size, with position sizes expected to increase as trade count surpasses 100 and statistical confidence improves.
Example 3: ES1! Futures Systematic Strategy
Systematic futures trading presents unique considerations for Kelly criterion application, as demonstrated by an E-mini S&P 500 futures strategy encompassing 234 total trades. This systematic approach achieved a 45% win rate with an average winning trade of $1,850 and average losing trade of $720. The maximum drawdown reached 18% during the testing period, with available capital of $50,000. The strategy employs 15-tick stop losses with contract specifications of $50 per tick, providing precise risk control mechanisms.
Implementation involves loading the calculator on the ES1! 15-minute chart to align with the systematic trading timeframe. Parameter configuration includes win rate at 45, average win at 1850, and average loss at 720. Total historical trades receives 234, providing robust statistical foundation, with account size set to 50000. The stop loss function is enabled with distance set to 15 ticks, reflecting the systematic exit methodology. Half Kelly mode balances growth potential with appropriate risk management for futures trading.
Results illustrate how favorable risk-reward ratios can support meaningful position sizing despite lower win rates. The risk-reward ratio calculates to 2.57, while the Kelly fraction reaches approximately 16%, lower than previous examples due to the sub-50% win rate. Sample confidence achieves 100% given the 234 trades providing high statistical confidence. The recommended position settles at approximately 8% after Half Kelly adjustment. Estimated margin per contract amounts to approximately $2,500, resulting in a single contract allocation. Position value reaches approximately $2,500, with risk per trade at $750, calculated as 15 ticks multiplied by $50 per tick. Expected value per trade amounts to approximately $508. Despite the lower win rate, the favorable risk-reward ratio supports meaningful position sizing, with single contract allocation reflecting appropriate leverage management for futures trading.
Example 4: MES1! Micro-Futures for Smaller Accounts
Micro-futures contracts provide enhanced accessibility for smaller trading accounts while maintaining identical strategy characteristics. Using the same systematic strategy statistics from the previous example but with available capital of $15,000 and micro-futures specifications of $5 per tick with reduced margin requirements, the implementation demonstrates improved position sizing granularity.
Kelly calculations remain identical to the full-sized contract example, maintaining the same risk-reward dynamics and statistical foundations. However, estimated margin per contract reduces to approximately $250 for micro-contracts, enabling allocation of 4-5 micro-contracts. Position value reaches approximately $1,200, while risk per trade calculates to $75, derived from 15 ticks multiplied by $5 per tick. This granularity advantage provides better position size precision for smaller accounts, enabling more accurate Kelly implementation without requiring large capital commitments.
Example 5: Bitcoin Swing Trading
Cryptocurrency markets present unique challenges requiring modified Kelly application approaches. A Bitcoin swing trading strategy on BTCUSD encompasses 67 total trades with a 71% win rate, generating average winning trades of $3,200 and average losing trades of $1,400. Maximum drawdown reached 28% during testing, with available capital of $30,000. The strategy employs technical analysis for exits without fixed stop losses, relying on price action and momentum indicators.
Implementation requires conservative approaches due to cryptocurrency volatility characteristics. Quarter Kelly mode is recommended despite the high win rate to account for crypto market unpredictability. Expected position sizing remains reduced due to the limited sample size of 67 trades, requiring additional caution until statistical confidence improves. Regular parameter updates are strongly recommended due to cryptocurrency market evolution and changing volatility patterns that can significantly impact strategy performance characteristics.
Advanced Usage Scenarios
Portfolio position sizing requires sophisticated consideration when running multiple strategies simultaneously. Each strategy should have its Kelly fraction calculated independently to maintain mathematical integrity. However, correlation adjustments become necessary when strategies exhibit related performance patterns. Moderately correlated strategies should receive individual position size reductions of 10-20% to account for overlapping risk exposure. Aggregate portfolio risk monitoring ensures total exposure remains within acceptable limits across all active strategies. Professional practitioners often consider using lower fractional Kelly approaches, such as Quarter Kelly, when running multiple strategies simultaneously to provide additional safety margins.
Parameter sensitivity analysis forms a critical component of professional Kelly implementation. Regular validation procedures should include monthly parameter updates using rolling 100-trade windows to capture evolving market conditions while maintaining statistical relevance. Sensitivity testing involves varying win rates by ±5% and average win/loss ratios by ±10% to assess recommendation stability under different parameter assumptions. Out-of-sample validation reserves 20% of historical data for parameter verification, ensuring that optimization doesn't create curve-fitted results. Regime change detection monitors actual performance against expected metrics, triggering parameter reassessment when significant deviations occur.
Risk management integration requires professional overlay considerations beyond pure Kelly calculations. Daily loss limits should cease trading when daily losses exceed twice the calculated risk per trade, preventing emotional decision-making during adverse periods. Maximum position limits should never exceed 25% of account value in any single position regardless of Kelly recommendations, maintaining diversification principles. Correlation monitoring reduces position sizes when holding multiple correlated positions that move together during market stress. Volatility adjustments consider reducing position sizes during periods of elevated VIX above 25 for equity strategies, adapting to changing market conditions.
Troubleshooting and Optimization
Professional implementation often encounters specific challenges requiring systematic troubleshooting approaches. Zero position size displays typically result from insufficient capital for minimum position sizes, negative expected values, or extremely conservative Kelly calculations. Solutions include increasing account size, verifying strategy statistics for accuracy, considering Quarter Kelly mode for conservative approaches, or reassessing overall strategy viability when fundamental issues exist.
Extremely high Kelly fractions exceeding 50% usually indicate underlying problems with parameter estimation. Common causes include unrealistic win rates, inflated risk-reward ratios, or curve-fitted backtest results that don't reflect genuine trading conditions. Solutions require verifying backtest methodology, including all transaction costs in calculations, testing strategies on out-of-sample data, and using conservative fractional Kelly approaches until parameter reliability improves.
Low sample confidence below 50% reflects insufficient historical trades for reliable parameter estimation. This situation demands gathering additional trading data, using Quarter Kelly approaches until reaching 100 or more trades, applying extra conservatism in position sizing, and considering paper trading to build statistical foundations without capital risk.
Inconsistent results across similar strategies often stem from parameter estimation differences, market regime changes, or strategy degradation over time. Professional solutions include standardizing backtest methodology across all strategies, updating parameters regularly to reflect current conditions, and monitoring live performance against expectations to identify deteriorating strategies.
Position sizes that appear inappropriately large or small require careful validation against traditional risk management principles. Professional standards recommend never risking more than 2-3% per trade regardless of Kelly calculations. Calibration should begin with Quarter Kelly approaches, gradually increasing as comfort and confidence develop. Most institutional traders utilize 25-50% of full Kelly recommendations to balance growth with prudent risk management.
Market condition adjustments require dynamic approaches to Kelly implementation. Trending markets may support full Kelly recommendations when directional momentum provides favorable conditions. Ranging or volatile markets typically warrant reducing to Half or Quarter Kelly to account for increased uncertainty. High correlation periods demand reducing individual position sizes when multiple positions move together, concentrating risk exposure. News and event periods often justify temporary position size reductions during high-impact releases that can create unpredictable market movements.
Performance monitoring requires systematic protocols to ensure Kelly implementation remains effective over time. Weekly reviews should compare actual versus expected win rates and average win/loss ratios to identify parameter drift or strategy degradation. Position size efficiency and execution quality monitoring ensures that calculated recommendations translate effectively into actual trading results. Tracking correlation between calculated and realized risk helps identify discrepancies between theoretical and practical risk exposure.
Monthly calibration provides more comprehensive parameter assessment using the most recent 100 trades to maintain statistical relevance while capturing current market conditions. Kelly mode appropriateness requires reassessment based on recent market volatility and performance characteristics, potentially shifting between Full, Half, and Quarter Kelly approaches as conditions change. Transaction cost evaluation ensures that commission structures, spreads, and slippage estimates remain accurate and current.
Quarterly strategic reviews encompass comprehensive strategy performance analysis comparing long-term results against expectations and identifying trends in effectiveness. Market regime assessment evaluates parameter stability across different market conditions, determining whether strategy characteristics remain consistent or require fundamental adjustments. Strategic modifications to position sizing methodology may become necessary as markets evolve or trading approaches mature, ensuring that Kelly implementation continues supporting optimal capital allocation objectives.
Professional Applications
This calculator serves diverse professional applications across the financial industry. Quantitative hedge funds utilize the implementation for systematic position sizing within algorithmic trading frameworks, where mathematical precision and consistent application prove essential for institutional capital management. Professional discretionary traders benefit from optimized position management that removes emotional bias while maintaining flexibility for market-specific adjustments. Portfolio managers employ the calculator for developing risk-adjusted allocation strategies that enhance returns while maintaining prudent risk controls across diverse asset classes and investment strategies.
Individual traders seeking mathematical optimization of capital allocation find the calculator provides institutional-grade methodology previously available only to professional money managers. The Kelly Criterion establishes theoretical foundation for optimal capital allocation across both single strategies and multiple trading systems, offering significant advantages over arbitrary position sizing methods that rely on intuition or fixed percentage approaches. Professional implementation ensures consistent application of mathematically sound principles while adapting to changing market conditions and strategy performance characteristics.
Conclusion
The Kelly Criterion represents one of the few mathematically optimal solutions to fundamental investment problems. When properly understood and carefully implemented, it provides significant competitive advantage in financial markets. This calculator implements modern refinements to Kelly's original formula while maintaining accessibility for practical trading applications.
Success with Kelly requires ongoing learning, systematic application, and continuous refinement based on market feedback and evolving research. Users who master Kelly principles and implement them systematically can expect superior risk-adjusted returns and more consistent capital growth over extended periods.
The extensive academic literature provides rich resources for deeper study, while practical experience builds the intuition necessary for effective implementation. Regular parameter updates, conservative approaches with limited data, and disciplined adherence to calculated recommendations are essential for optimal results.
References
Archer, M. D. (2010). Getting Started in Currency Trading: Winning in Today's Forex Market (3rd ed.). John Wiley & Sons.
Baker, R. D., & McHale, I. G. (2012). An empirical Bayes approach to optimising betting strategies. Journal of the Royal Statistical Society: Series D (The Statistician), 61(1), 75-92.
Breiman, L. (1961). Optimal gambling systems for favorable games. In J. Neyman (Ed.), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability (pp. 65-78). University of California Press.
Brown, D. B. (1976). Optimal portfolio growth: Logarithmic utility and the Kelly criterion. In W. T. Ziemba & R. G. Vickson (Eds.), Stochastic Optimization Models in Finance (pp. 1-23). Academic Press.
Browne, S., & Whitt, W. (1996). Portfolio choice and the Bayesian Kelly criterion. Advances in Applied Probability, 28(4), 1145-1176.
Estrada, J. (2008). Geometric mean maximization: An overlooked portfolio approach? The Journal of Investing, 17(4), 134-147.
Hakansson, N. H., & Ziemba, W. T. (1995). Capital growth theory. In R. A. Jarrow, V. Maksimovic, & W. T. Ziemba (Eds.), Handbooks in Operations Research and Management Science (Vol. 9, pp. 65-86). Elsevier.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Kaufman, P. J. (2013). Trading Systems and Methods (5th ed.). John Wiley & Sons.
Kelly Jr, J. L. (1956). A new interpretation of information rate. Bell System Technical Journal, 35(4), 917-926.
Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton University Press.
MacLean, L. C., Sanegre, E. O., Zhao, Y., & Ziemba, W. T. (2004). Capital growth with security. Journal of Economic Dynamics and Control, 28(4), 937-954.
MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific.
Michaud, R. O. (1989). The Markowitz optimization enigma: Is 'optimized' optimal? Financial Analysts Journal, 45(1), 31-42.
Pabrai, M. (2007). The Dhandho Investor: The Low-Risk Value Method to High Returns. John Wiley & Sons.
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
Tharp, V. K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill.
Thorp, E. O. (2006). The Kelly criterion in blackjack sports betting, and the stock market. In L. C. MacLean, E. O. Thorp, & W. T. Ziemba (Eds.), The Kelly Capital Growth Investment Criterion: Theory and Practice (pp. 789-832). World Scientific.
Van Tharp, K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill Education.
Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons.
Vince, R., & Zhu, H. (2015). Optimal betting under parameter uncertainty. Journal of Statistical Planning and Inference, 161, 19-31.
Ziemba, W. T. (2003). The Stochastic Programming Approach to Asset, Liability, and Wealth Management. The Research Foundation of AIMR.
Further Reading
For comprehensive understanding of Kelly Criterion applications and advanced implementations:
MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific.
Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons.
Thorp, E. O. (2017). A Man for All Markets: From Las Vegas to Wall Street. Random House.
Cover, T. M., & Thomas, J. A. (2006). Elements of Information Theory (2nd ed.). John Wiley & Sons.
Ziemba, W. T., & Vickson, R. G. (Eds.). (2006). Stochastic Optimization Models in Finance. World Scientific.
ATR+CCI Monetary Risk Tool - TP/SL⚙️ ATR+CCI Monetary Risk Tool — Volatility-aware TP/SL & Position Sizing
Exact prices (no rounding), ATR-percentile dynamic stops, and risk-budget sizing for consistent execution.
🧠 What this indicator is
A risk-first planning tool. It doesn’t generate orders; it gives you clean, objective levels (Entry, SL, TP) and position size derived from your risk budget. It shows only the latest setup to keep charts readable, and a compact on-chart table summarizing the numbers you actually act on.
✨ What makes it different
Dynamic SL by regime (ATR percentile): Instead of a fixed multiple, the SL multiplier adapts to the current volatility percentile (low / medium / high). That helps avoid tight stops in noisy markets and over-wide stops in quiet markets.
Risk budgeting, not guesswork: Size is computed from Account Balance × Max Risk % divided by SL distance × point value. You risk the same dollars across assets/timeframes.
Precision that matches your instrument: Entry, TP, SL, and SL Distance are displayed as exact prices (no rounding), truncated to syminfo.mintick so they align with broker/exchange precision.
Symbol-aware point value: Uses syminfo.pointvalue so you don’t maintain tick tables.
Non-repaint option: Work from closed bars to keep the plan stable.
🔧 How to use (quick start)
Add to chart and pick your timeframe and symbol.
In settings:
Set Account Balance (USD) and Max Risk per Trade (%).
Choose R:R (1:1 … 1:5).
Pick ATR Period and CCI Period (defaults are sensible).
Keep Dynamic ATR ON to adapt SL by regime.
Keep Use closed-bar values ON to avoid repaint when planning.
Read the labels (Entry/TP/SL) and the table (SL Distance, Position Size, Max USD Risk, ATR Percentile, effective SL Mult).
Combine with your entry trigger (price action, levels, momentum, etc.). This indicator handles risk & targets.
📐 How levels are computed
Bias: CCI ≥ 0 ⇒ long, otherwise short.
ATR Percentile: Percent rank of ATR(atrPeriod) over a lookback window.
Effective SL Mult:
If percentile < Low threshold ⇒ use Low SL Mult (tighter).
If between thresholds ⇒ use Base SL Mult.
If percentile > High threshold ⇒ use High SL Mult (wider).
Stop-Loss: SL = Entry ± ATR × SL_Mult (minus for long, plus for short).
Take-Profit: TP = Entry ± (Entry − SL) × R (R from the R:R dropdown).
Position Size:
USD Risk = Balance × Risk%
Contracts = USD Risk ÷ (|Entry − SL| × PointValue)
For futures, quantity is floored to whole contracts.
Exact prices: Entry/TP/SL and SL Distance are not rounded; they’re truncated to mintick so what you see matches valid price increments.
📊 What you’ll see on chart
Latest Entry (blue), TP (green), SL (red) with labels (optional emojis: ➡️ 🎯 🛑).
Info Table with:
Bias, Entry, TP, SL (exact, truncated to mintick)
SL Distance (exact, truncated)
Position Size (contracts/units)
Max USD Risk
Point Value
ATR Percentile and effective SL Mult
🧪 Practical examples
High-volatility session (e.g., XAUUSD, 1H): ATR percentile is high ⇒ wider SL, smaller size. Reduces churn from normal noise during macro events.
Range-bound market (e.g., EURUSD, 4H): ATR percentile low ⇒ tighter SL, better R:R. Helps you avoid carrying unnecessary risk.
Index swing planning (e.g., ES1!, Daily): Non-repaint levels + risk budgeting = consistent sizing across days/weeks, easier to review and journal.
🧭 Why traders should use it
Consistency: Same dollar risk regardless of instrument or volatility regime.
Clarity: One-trade view forces focus; you see the numbers that matter.
Adaptivity: Stops calibrated to the market’s current behavior, not last month’s.
Discipline: A visible checklist (SL distance, size, USD risk) before you hit buy/sell.
🔧 Input guide (practical defaults)
CCI Period: 100 by default; use as a bias filter, not an entry signal.
ATR Period: 14 by default; raise for smoother, lower for more reactive.
ATR Percentile Lookback: 200 by default (stable regime detection).
Percentile thresholds: 33/66 by default; widen the gap to change how often regimes switch.
SL Mults: Start ~1.5 / 2.0 / 2.5 (low/base/high). Tune by asset.
Risk % per trade: Common pro ranges are 0.25–1.0%; adjust to your risk tolerance.
R:R: Start with 1:2 or 1:3 for balanced skew; adapt to strategy edge.
Closed-bar values: Keep ON for planning/live; turn OFF only for exploration.
💡 Best practices
Combine with your entry logic (structure, momentum, liquidity levels).
Review ATR percentile and effective SL Mult across sessions so you understand regime shifts.
For futures, remember size is floored to whole contracts—safer by design.
Journal trades with the table snapshot to improve risk discipline over time.
⚠️ Notes & limitations
This is not a strategy; it does not place orders or alerts.
No slippage/commissions modeled here; build a strategy() version for backtests that mirror your broker/exchange.
Displayed non-price metrics use two decimals; prices and SL Distance are exact (truncated to mintick).
📎 Disclaimer
For educational purposes only. Not financial advice. Markets involve risk. Test thoroughly before trading live.
Mutanabby_AI | Ultimate Algo | Remastered+Overview
The Mutanabby_AI Ultimate Algo Remastered+ represents a sophisticated trend-following system that combines Supertrend analysis with multiple moving average confirmations. This comprehensive indicator is designed specifically for identifying high-probability trend continuation and reversal opportunities across various market conditions.
Core Algorithm Components
**Supertrend Foundation**: The primary signal generation relies on a customizable Supertrend indicator with adjustable sensitivity (1-20 range). This adaptive trend-following tool uses Average True Range calculations to establish dynamic support and resistance levels that respond to market volatility.
**SMA Confirmation Matrix**: Multiple Simple Moving Averages (SMA 4, 5, 9, 13) provide layered confirmation for signal strength. The algorithm distinguishes between regular signals and "Strong" signals based on SMA 4 vs SMA 5 relationship, offering traders different conviction levels for position sizing.
**Trend Ribbon Visualization**: SMA 21 and SMA 34 create a visual trend ribbon that changes color based on their relationship. Green ribbon indicates bullish momentum while red signals bearish conditions, providing immediate visual trend context.
**RSI-Based Candle Coloring**: Advanced 61-tier RSI system colors candles with gradient precision from deep red (RSI ≤20) through purple transitions to bright green (RSI ≥79). This visual enhancement helps traders instantly assess momentum strength and overbought/oversold conditions.
Signal Generation Logic
**Buy Signal Criteria**:
- Price crosses above Supertrend line
- Close price must be above SMA 9 (trend confirmation)
- Signal strength determined by SMA 4 vs SMA 5 relationship
- "Strong Buy" when SMA 4 ≥ SMA 5
- Regular "Buy" when SMA 4 < SMA 5
**Sell Signal Criteria**:
- Price crosses below Supertrend line
- Close price must be below SMA 9 (trend confirmation)
- Signal strength based on SMA relationship
- "Strong Sell" when SMA 4 ≤ SMA 5
- Regular "Sell" when SMA 4 > SMA 5
Advanced Risk Management System
**Automated TP/SL Calculation**: The indicator automatically calculates stop loss and take profit levels using ATR-based measurements. Risk percentage and ATR length are fully customizable, allowing traders to adapt to different market conditions and personal risk tolerance.
**Multiple Take Profit Targets**:
- 1:1 Risk-Reward ratio for conservative profit taking
- 2:1 Risk-Reward for balanced trade management
- 3:1 Risk-Reward for maximum profit potential
**Visual Risk Display**: All risk management levels appear as both labels and optional trend lines on the chart. Customizable line styles (solid, dashed, dotted) and positioning ensure clear visualization without chart clutter.
**Dynamic Level Updates**: Risk levels automatically recalculate with each new signal, maintaining current market relevance throughout position lifecycles.
Visual Enhancement Features
**Customizable Display Options**: Toggle trend ribbon, TP/SL levels, and risk lines independently. Decimal precision adjustments (1-8 decimal places) accommodate different instrument price formats and personal preferences.
**Professional Label System**: Clean, informative labels show entry points, stop losses, and take profit targets with precise price levels. Labels automatically position themselves for optimal chart readability.
**Color-Coded Momentum**: The gradient RSI candle coloring system provides instant visual feedback on momentum strength, helping traders assess market energy and potential reversal zones.
Implementation Strategy
**Timeframe Optimization**: The algorithm performs effectively across multiple timeframes, with higher timeframes (4H, Daily) providing more reliable signals for swing trading. Lower timeframes work well for day trading with appropriate risk adjustments.
**Sensitivity Adjustment**: Lower sensitivity values (1-5) generate fewer but higher-quality signals, ideal for conservative approaches. Higher sensitivity (15-20) increases signal frequency for active trading styles.
**Risk Management Integration**: Use the automated risk calculations as baseline parameters, adjusting risk percentage based on account size and market conditions. The 1:1, 2:1, 3:1 targets enable systematic profit-taking strategies.
Market Application
**Trend Following Excellence**: Primary strength lies in capturing significant trend movements through the Supertrend foundation with SMA confirmation. The dual-layer approach reduces false signals common in single-indicator systems.
**Momentum Assessment**: RSI-based candle coloring provides immediate momentum context, helping traders assess signal strength and potential continuation probability.
**Range Detection**: The trend ribbon helps identify ranging conditions when SMA 21 and SMA 34 converge, alerting traders to potential breakout opportunities.
Performance Optimization
**Signal Quality**: The requirement for both Supertrend crossover AND SMA 9 confirmation significantly improves signal reliability compared to basic trend-following approaches.
**Visual Clarity**: The comprehensive visual system enables rapid market assessment without complex calculations, ideal for traders managing multiple instruments.
**Adaptability**: Extensive customization options allow fine-tuning for specific markets, trading styles, and risk preferences while maintaining the core algorithm integrity.
## Non-Repainting Design
**Educational Note**: This indicator uses standard TradingView functions (Supertrend, SMA, RSI) with normal behavior patterns. Real-time updates on current candles are expected and standard across all technical indicators. Historical signals on closed candles remain fixed and unchanged, ensuring reliable backtesting and analysis.
**Signal Confirmation**: Final signals are confirmed only when candles close, following standard technical analysis principles. The algorithm provides clear distinction between developing signals and confirmed entries.
Technical Specifications
**Supertrend Parameters**: Default sensitivity of 4 with ATR length of 11 provides balanced signal generation. Sensitivity range from 1-20 allows adaptation to different market volatilities and trading preferences.
**Moving Average Configuration**: SMA periods of 8, 9, and 13 create multi-layered trend confirmation, while SMA 21 and 34 form the visual trend ribbon for broader market context.
**Risk Management**: ATR-based calculations with customizable risk percentage ensure dynamic adaptation to market volatility while maintaining consistent risk exposure principles.
Recommended Settings
**Conservative Approach**: Sensitivity 4-5, RSI length 14, higher timeframes (4H, Daily) for swing trading with maximum signal reliability.
**Active Trading**: Sensitivity 6-8, RSI length 8-10, intermediate timeframes (1H) for balanced signal frequency and quality.
**Scalping Setup**: Sensitivity 10-15, RSI length 5-8, lower timeframes (15-30min) with enhanced risk management protocols.
## Conclusion
The Mutanabby_AI Ultimate Algo Remastered+ combines proven trend-following principles with modern visual enhancements and comprehensive risk management. The algorithm's strength lies in its multi-layered confirmation approach and automated risk calculations, providing both novice and experienced traders with clear signals and systematic trade management.
Success with this system requires understanding the relationship between signal strength indicators and adapting sensitivity settings to match current market conditions. The comprehensive visual feedback system enables rapid decision-making while the automated risk management ensures consistent trade parameters.
Practice with different sensitivity settings and timeframes to optimize performance for your specific trading style and risk tolerance. The algorithm's systematic approach provides an excellent framework for disciplined trend-following strategies across various market environments.
Ayman – Full Smart Suite Auto/Manual Presets + PanelIndicator Name
Ayman – Full Smart Suite (OB/BoS/Liq/FVG/Pin/ADX/HTF) + Auto/Manual Presets + Panel
This is a multi-condition trading tool for TradingView that combines advanced Smart Money Concepts (SMC) with classic technical filters.
It generates BUY/SELL signals, draws Stop Loss (SL) and Take Profit (TP1, TP2) levels, and displays a control panel with all active settings and conditions.
1. Main Features
Smart Money Concepts Filters:
Order Block (OB) Zones
Break of Structure (BoS)
Liquidity Sweeps
Fair Value Gaps (FVG)
Pin Bar patterns
ADX filter
Higher Timeframe EMA filter (HTF EMA)
Two Operating Modes:
Auto Presets: Automatically adjusts all settings (buffers, ATR multipliers, RR, etc.) based on your chart timeframe (M1/M5/M15).
Manual Mode: Fully customize all parameters yourself.
Trade Management Levels:
Stop Loss (SL)
TP1 – partial profit
TP2 – full profit
Visual Panel showing:
Current settings
Filter status
Trend direction
Last swing levels
SL/TP status
Alerts for BUY/SELL conditions
2. Entry Conditions
A BUY signal is generated when all these are true:
Trend: Price above EMA (bullish)
HTF EMA: Higher timeframe trend also bullish
ADX: Trend strength above threshold
OB: Price in a valid bullish Order Block zone
BoS: Structure break to the upside
Liquidity Sweep: Sweep of recent lows in bullish context
FVG: A bullish Fair Value Gap is present
Pin Bar: Bullish Pin Bar pattern detected (if enabled)
A SELL signal is generated when the opposite conditions are met.
3. Stop Loss & Take Profits
SL: Placed just beyond the last swing low (BUY) or swing high (SELL), with a small ATR buffer.
TP1: Partial profit target, defined as a ratio of the SL distance.
TP2: Full profit target, based on Reward:Risk ratio.
4. How to Use
Step 1 – Apply Indicator
Open TradingView
Go to your chart (recommended: XAUUSD, M1/M5 for scalping)
Add the indicator script
Step 2 – Choose Mode
AUTO Mode: Leave “Use Auto Presets” ON – parameters adapt to your timeframe.
MANUAL Mode: Turn Auto OFF and adjust all lengths, buffers, RR, and filters.
Step 3 – Filters
In the Filters On/Off section, enable/disable specific conditions (OB, BoS, Liq, FVG, Pin Bar, ADX, HTF EMA).
Step 4 – Trading the Signals
Wait for a BUY or SELL arrow to appear.
SL and TP levels will be plotted automatically.
TP1 can be used for partial close and TP2 for full exit.
Step 5 – Alerts
Set alerts via BUY Signal or SELL Signal to receive notifications.
5. Best Practices
Scalping: Use M1 or M5 with AUTO mode for gold or forex pairs.
Swing Trading: Use M15+ and adjust buffers/ATR manually.
Combine with price action confirmation before entering trades.
For higher accuracy, wait for multiple filter confirmations rather than acting on the first arrow.
6. Summary Table
Feature Purpose Can Disable?
Order Block Finds key supply/demand zones ✅
Break of Structure Detects trend continuation ✅
Liquidity Sweep Finds stop-hunt moves ✅
Fair Value Gap Confirms imbalance entries ✅
Pin Bar Price action reversal filter ✅
ADX Trend strength filter ✅
HTF EMA Higher timeframe confirmation ✅
