MPF EMA Cross Strategy (8~13~21) by Market Pip FactoryThis script is for a complete strategy to win maximum profit on trades whilst keeping losses at a minimum, using sound risk management at no greater than 1.5%
The 3x EMA Strategy uses the following parameters for trade activation and closure.
1/ Daily Time Frame for trend confirmation
2/ 4 Hourly Time Frame for trend confirmation
3/ 1 Hourly Time Frame for trend confirmation AND trade execution
4/ 3x EMAs (Exponential Moving Averages)
* EMA#1 = 8 EMA (Red Color)
* EMA#2 = 13 EMA (Blue Color)
* EMA#3 = 21 EMA (Orange Color)
5/ Fanning of all 3x EMAs and CrossOver/CrossUnder for Trend Confirmation
6/ Price Action touching an 8 EMA for trade activation
7/ Price Action touching a 21 EMA for trade cancellation BEFORE activation
* For LONG trades: 8 EMA would be ABOVE 21 EMA
* For SHORT trades: 8 EMA would be BELOW 21 EMA
* For trade Cancellation, price action would touch the 21 EMA before trade is activated
* For trade Entry, price action would touch 8 EMA
Once trigger parameter is identified, entry is found by:
a) Price action touches 8 EMA (Candle must Close for confirmed Trade preparation)
b) Trade preparation can be cancelled before trade is activated if price action touches 21 EMA
c) Trailing Stop Loss can be used (optional) by counting back 5 candles from current candle
CLOSURE of a Trade is identified by:
e) 8 EMA crossing the 21 EMA, then close trade, no matter LONG or SHORT
f) Trail Stop Loss
IMPORTANT:
g) No more than ONE activated trade per EMA crossover
h) No more than ONE active trade per pair
NOTE: This strategy is to be used in conjunction with Cipher Twister (my other indicator) to reduce trades on
sideways price action and market trends for super high win ratio.
NOTE: Enabling of LONGs and SHORTs Via Cipher Twister is done by using the previous
green or red dot made. Additionally, when the trend changes, so do the dot's validity based
on being above or below the 0 centerline.
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Strategy and Bot Logic
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.....::: FOR SHORT TRADES ONLY :::.....
The Robot must use the following logic to enable and activate the SHORT trades:
Parameters:
$(crossunder)=8EMA,21EMA=Bearish $(crossover)=8EMA,21EMA=Bullish $entry=SELL STOP ORDER (Short)
$EMA#1 = 8 EMA (Red Color) $EMA#2 = 13 EMA (Blue Color) $EMA#3 = 21 EMA (Orange Color)
Strategy Logic:
1/ Check Daily Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=daily and trend=$(crossunder) then goto 2/ *Means: crossunder = ema21 > ema8
$(chart)=daily and trend=$(crossover) then stop (No trades) *Means: crossover = ema8 > ema21
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
2/ Check 4 Hourly Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=4H and trend=$(crossunder) then goto 3/ *Means: crossunder = ema21 > ema8
$(chart)=4H and trend=$(crossover) then stop (No trades) *Means: crossover = ema8 > ema21
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
3/ 1 Hourly Time Frame for trend confirmation AND trade execution if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=1H and trend=$(crossunder) then goto 4/ *Means: crossunder = ema21 > ema8
$(chart)=1H and trend=$(crossover) then stop (No trades) *Means: crossover = ema8 > ema21
4/ Trade preparation:
* if Next (subsequent) candle touches 8EMA, then set STOP LOSS and ENTRY
* $stoploss=3 pips ABOVE current candle HIGH
* $entry=3 pips BELOW current candle LOW
5/ Trade waiting (ONLY BEFORE entry is hit and trade activated):
* if price action touches 21 EMA then cancel trade and goto 1/
Note: Once trade is active this function does not apply !
6/ Trade Activation:
* if price activates/hits ENTRY price, then bot activates trade SHORTs market
7/ Optional Trailing stop:
* if active, then trailing stop 3 pips ABOVE previous HIGH of previous 5th candle
or * Move Stop Loss to Break Even after $X number of pips
NOTE: This means count back and apply accordingly to the 5th previous candle from current candle.
NOTE: This function is switchable. 0=off and 1=on(active). Default = 0 (off)
8/ Trade Close ~ Take Profit:
* Only TP when
$(chart)=1H and trend=$(crossover) then close trade ~ Or obviously if Stop Loss is hit if 7/ is activated.
----------END FOR SHORT TRADES LOGIC----------
.....::: FOR LONG TRADES ONLY :::.....
The Robot must use the following logic to enable and activate the LONG trades:
Parameters:
$(crossunder)=8EMA,21EMA=Bearish $(crossover)=8EMA,21EMA=Bullish $entry=BUY STOP ORDER (Long)
$EMA#1 = 8 EMA (Red Color) $EMA#2 = 13 EMA (Blue Color) $EMA#3 = 21 EMA (Orange Color)
Strategy Logic:
1/ Check Daily Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=daily and trend=$(crossover) then goto 2/ *Means: crossover = ema8 > ema21
$(chart)=daily and trend=$(crossunder) then stop (No trades) *Means: crossunder = ema21 > ema8
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
2/ Check 4 Hourly Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=4H and trend=$(crossover) then goto 3/ *Means: crossover = ema8 > ema21
$(chart)=4H and trend=$(crossunder) then stop (No trades) *Means: crossunder = ema21 > ema8
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
3/ 1 Hourly Time Frame for trend confirmation AND trade execution if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=1H and trend=$(crossover) then goto 4/ *Means: crossover = ema8 > ema21
$(chart)=1H and trend=$(crossunder) then stop (No trades) *Means: crossunder = ema21 > ema8
4/ Trade preparation:
* if Next (subsequent) candle touches 8EMA, then set STOP LOSS and ENTRY
* $stoploss=3 pips BELOW current candle LOW
* $entry=3 pips ABOVE current candle HIGH
5/ Trade waiting (ONLY BEFORE entry is hit and trade activated):
* if price action touches 21 EMA then cancel trade and goto 1/
Note: Once trade is active this function does not apply !
6/ Trade Activation:
* if price activates/hits ENTRY price, then bot activates trade LONGs market
7/ Optional Trailing stop:
* if active, then trailing stop 3 pips BELOW previous LOW of previous 5th candle
or * Move Stop Loss to Break Even after $X number of pips
NOTE: This means count back and apply accordingly to the 5th previous candle from current candle.
NOTE: This function is switchable. 0=off and 1=on(active). Default = 0 (off)
8/ Trade Close ~ Take Profit:
* Only TP when
$(chart)=1H and trend=$(crossunder) then close trade ~ Or obviously if Stop Loss is hit if 7/ is activated.
----------END FOR LONG TRADES LOGIC----------
IMPORTANT:
* If an existing trade is already open for that same pair, & price action touches 8EMA, do NOT open a new trade..
* bot must continuously check if a trade is currently open on the pair that triggers
* New trades are to be only opened if there is no active trade opened on current pair.
* Only 1 trade per pair rule !
* 5 simultaneous open trades (not same pairs) default = 5 but value can be changed accordingly.
* Maximum risk management must not exceed 1.5% on lot size
*** Some features are not yet available autoated, they will be added in due course in subsequent version updates ***
Cerca negli script per "trigger"
Renko Strategy V2Version 2.0 of my previous renko strategy using Renko calculations, this time without using Tilson T3 and without using security for renko calculations to remove repaint!
Seems to work nicely on cryptocurrencies on higher time frames.
== Description ==
Strategy gets Renko values and uses renko close and open to trigger signals.
Base on these results the strategy triggers a long and short orders, where green is uptrending and red is downtrending.
This Renko version is based on ATR, you can Set ATR (in settings) to adjust it.
== Notes ==
Supports alerts.
Supports backtesting time ranges.
Shorts are disabled by default (can be enabled in settings).
Link to previous Renko strategy V1:
Stay tuned for version V3 in the future as i have an in progress prototype, Follow to get updated:
www.tradingview.com
Reverse MACD IndicatorIntroducing the reverse MACD Indicator.
This is my Pinescript implementation of the reverse MACD indicator.
Much respect to Mr Johnny Dough the original creator of this idea.
Feel free to reuse this script, drop me a note below if you find this useful.
Investopedia defines the MACD as a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price.
The MACD is calculated by subtracting the 26-period Exponential Moving Average ( EMA ) from the 12-period EMA .
The result of that calculation is the MACD line.
A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals.
Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line.
Moving Average Convergence Divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
MACD triggers technical signals when it crosses above (to buy) or below (to sell) its signal line.
The speed of crossovers is also taken as a signal of a market is overbought or oversold.
MACD helps investors understand whether the bullish or bearish movement in the price is strengthening or weakening.
The MACD has a positive value (shown as the red line on the price chart ) whenever the 12-period EMA ( indicated by the blue line on the price chart) is above the 26-period EMA (the red line in the price chart) and a negative value when the 12-period EMA is below the 26-period EMA .
The more distant the MACD is above or below its baseline indicates that the distance between the two EMAs is growing.
The baseline here is the white line.
The Reverse function of the MACD provides value by letting the user know the specific price needed to expect a MACD cross over in the opposite direction.
This function can be used to designate risk parameters for a potential trade if using the MACD as their source of edge, letting the user know exactly where and how much their risk is for a potential trade which can be used to design an effective trading plan.
Crypto TrendThis indicator is based off of the Trend Follower system put together by jiehonglim:
This is a trend following system that combines 3 indicators which provide different functionalities, also a concept conceived by VP's No Nonsense FX / NNFX method. I’m primarily modifying this system for Crypto trading (mostly leveraged Crypto Futures). Suggestions/requests welcome.
New Features:
Added position inputs that will generate position labels
For leverage trading, position inputs will calculate your percentage-based stop loss given your entry, leverage and liquidation price
Added optional horizontal line plots for entry, stop loss, 50% take profit and 100% profit levels.
Added non-plotted Didi calculations for alert condition triggers
Added long and short alerts
These alerts will trigger for any of the 3 following conditions:
Baseline cross with volume confirmation
Didi two line cross with volume confirmation
Didi continuation with volume confirmation
1. Baseline
The main baseline filter is an indicator called Modular Filter created by Alex Grover
- www.tradingview.com
- Alex Grover - Modular Filter
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That's the moving average like baseline following price, filtering long and short trends and providing entry signals when the price crosses the baseline.
Entry signal indicated with arrows.
2. Volume / Volatility , I will called it Trend Strength
The next indicator is commonly known as ASH, Absolute Strength Histogram.
This indicator was shared by VP as a two line cross trend confirmation indicator, however I discovered an interesting property when I modified the calculation of the histogram.
- Alex Grover Absolute Strength
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My modification and other info here
- Absolute Strength Histogram v2
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I simplified the display of the trend strength by plotting squares at the bottom of the chart.
- Lighted Squares shows strength
- Dimmed Squares shows weakness
3. Second Confirmation / Exits / Trailing Stop
Finally the last indicator is my usage of QQE (Qualitative Quantitative Estimation), demonstrated in my QQE Trailing Line Indicator
- QQE Trailing Line for Trailing Stop
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Three usages of this amazing indicator, serving as :
- Second trend confirmation
- Exit signal when price crosses the trailing line
- Trailing stop when you scaled out the second trade
This indicator is plotted with crosses.
4. Position Calculator
For non-leveraged trades, set leverage to 1 and liquidation to 0
Fill out the rest of the position field to get labels that will tell you:
Your stop loss given your acceptable percentage of loss for your risk. So, for example if your actual investment is $200 and you’re trading on 20X leverage, you’d like to know what price would have to drop to for you to lose 15% of your $200 risk. This is what the position calculator is doing for you.
Your 50% take profit point
Your 100% take profit point
Check the “Show Position Lines” to plot horizontal lines for entry, stop loss, 50% TP and 100%TP
Alerts
You just get a Long Alert or Short Alert option. This was for two reasons, the first and most important was to reduce the number of alerts needed for this system to get maximum coverage. The second was just to keep things simple. Get an alert for your desired direction for any interesting signal and then check the chart manually to determine if a viable entry has presented itself. The three alert conditions are:
Main trend indicator, baseline cross with volume confirmation
Didi two line cross entry with volume confirmation
Didi continuation signal with volume confirmation
Additional plots and information
Bar Color
- Green for longs, Red for shorts, White when the baseline direction conflicts with the QQE trailing line direction
- When it's white, it's usually ranging and not trending, ASH will also keep you off ranging periods.
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ATR Filter
- White circles along the baseline, they will show up if the price has moved more than one ATR from the baseline
- The default allowance is 1 ATR.
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The previous and current ATR value
- Label on the right side of the chart showing the previous and current value of ATR
Grimes Modified MACD Supply DemandA follower of mine asked me if I could make a version of my www.tradingview.com script using the MACD. Well it just so happens I was making a few modifications to my MACD script: just as this question came up so I went ahead and threw this together.
The MACD that triggers the SR zones is pictured below, with key trigger points encircled to illustrate how it works.
BTC - RVPM: Run Velocity & Probability MapBTC – RVPM: Run Velocity & Probability Map | RM
Strategic Context: Understanding Price Runs
A "Price Run" (also known as a streak or consecutive sessions) is a foundational concept in time-series analysis that measures the duration of a price movement without a significant counter-signal. While common indicators like RSI or MACD measure magnitude or momentum, they often ignore the Persistence of the trend. Historically, markets move through cycles of expansion and mean-reversion. A Price Run represents a period of "Unidirectional Flow" — a fingerprint of institutional accumulation or systematic distribution. However, standard "run-counting" is often too simplistic for the volatile crypto markets.
What Makes RVPM Special?
Most community run-counters are binary; they simply tell you if X days were green or red. The RVPM distinguishes itself through three proprietary layers:
• The Intensity Filter: It doesnt just count days; it counts effort . By ignoring "flat" days through a percentage-return threshold, it filters out noise that would otherwise skew the statistical probability.
• Dynamic Benchmarking: Instead of using an arbitrary number (like "7 days"), the RVPM looks back at 200 bars of history to find the local "Persistence Ceiling." It adapts to the current volatility regime of Bitcoin.
• The Velocity Score: It transform simple counts into a -100 to +100 histogram, allowing traders to see momentum "decaying" (e.g., dropping from 90 to 70) even if the price continues to rise.
The 3 Pillars of the Engine
1. Velocity Mapping (Persistence Histogram)
The histogram calculates the density of directional effort within a defined window. It functions as the "Pulse" of the trend, mapping market behavior into three distinct zones:
• High Velocity Zone (> 80 or < -80): Institutional Expansion. This identifies a "clean" move where one side of the market possesses total structural control. In this zone, the trend is efficient, and counter-signals are immediately absorbed.
• The Neutral Zone (Near Zero): Momentum Equilibrium. When the histogram fluctuates near the zero line, the market is in a "Recharge Phase." Neither bulls nor bears are achieving persistent dominance. Tactically, this is the "Waiting Room" where range-bound chop is likely, and traders should wait for a new "Expansion" spike before committing.
• Velocity Decay: The Exhaustion Warning. Velocity Decay occurs when the indicator moves from an extreme (e.g., +95) back toward the zero line (e.g., +50) while the price is still rising. This is a "Persistence Divergence." It tells you that while the trend is still moving, the consistency of the bars is fragmenting. The "fuel" is being depleted, and the trend is transitioning from an "Institutional Expansion" into a "Speculative Exhaustion."
2. n-of-m Consistency (The Pips)
The "Pips" (Circles) mark when a specific consistency threshold is met (e.g., 5 out of 7 bars in one direction). This identifies "Leaky Trends" that are still statistically dominated by one side of the ledger.
3. Statistical Exhaustion (The Arrows)
The Dark Red (Top) and Dark Green (Bottom) triangles represent the engine's "Mean-Reversion Signal." The calculation is based on a Relative Maximum Streak (RMS) logic: the script tracks the current linear, consecutive bar count (ignoring bars that fail the Intensity Filter) and continuously benchmarks this against the highest streak recorded over the last 200 bars ( ta.highest(streak, 200) ). The triangles are triggered specifically when the current run reaches 80% of this historical record (the "Anomaly Threshold"). Mathematically, this identifies a move that is statistically pushing against its half-year limit. By using this dynamic threshold rather than a fixed number, the "Extreme" signal automatically tightens during low-volatility regimes and expands during high-volatility expansions, ensuring the signal only appears when the "statistical rubber band" is at a true breaking point.
Operational Interface: The RVPM Dashboard
The Status Dashboard (Top Right) serves as a real-time monitor for momentum health, providing a clean summary of the underlying persistence data:
• Current STREAK: The active, consecutive count of bars meeting the Intensity Filter. It is dynamically color-coded (Cyan/Bullish or Red/Bearish) to provide an instant read on trend seniority.
• WINDOW Consistency: Measures the Momentum Density (the n-of-m value). A value of "6" in a "7-bar" window indicates a high-conviction regime that is successfully absorbing pullbacks without losing its primary trajectory.
Tactical Playbook: The Mean-Reversion Rule
Price action typically follows a "Rubber Band" effect. The further it is stretched without a break, the more "unstable" the trend becomes as the pool of available buyers or sellers is depleted.
• The Setup: Wait for the Triangle Arrows to appear.
• The Logic: The move has reached a 200-day anomaly. A "Liquidity Vacuum" is forming on the opposite side.
• The Action: This is a high-probability Mean-Reversion signal. It is a tactical time to take profits or look for a sharp snap-back move toward the 20-period moving average or the "Institutional Mean."
Settings & Parameters
• Window Length (m): The lookback window used to calculate the Velocity Score.
• Required Days (n): The minimum number of directional bars needed within the window to trigger a "Consistency Pip."
• Intensity Filter (%): The minimum % change required for a bar to be counted toward a run.
• Lookback Period: The historical window (Default: 200 bars) used to calculate the "Maximum Streak" records for exhaustion alerts.
Timeframe Recommendation
The RVPM is best viewed on the Daily (1D) timeframe. This filters out intraday noise and provides the most reliable statistical mapping for macro exhaustion points.
Credits & Verification
The RVPM logic aligns with institutional "Persistence" models and Glassnode's Price Stretch benchmarks. By benchmarking against a rolling 200-day window, the indicator automatically adapts to changing market volatility.
Risk Disclaimer & No Financial Advice
The information, data, and analytical models provided in this publication are for educational and informational purposes only. This script does not constitute financial, investment, or trading advice. Trading cryptocurrencies and other financial instruments carries a high degree of risk, and statistical anomalies or "Extreme Runs" do not guarantee future price action. Past performance is never indicative of future results. Every trader is responsible for their own due diligence and risk management. Rob Maths and the associated entities are not liable for any financial losses incurred through the use of this tool. Always consult with a certified financial professional before making significant investment decisions.
Tags:
bitcoin, btc, persistence, streaks, price-runs, momentum, mean-reversion, exhaustion, Rob Maths
Account GuardianAccount Guardian: Dynamic Risk/Reward Overlay
Introduction
Account Guardian is an open-source indicator for TradingView designed to help traders evaluate trade setups before entering positions. It automatically calculates Risk-to-Reward ratios based on market structure, displays visual Stop Loss and Take Profit zones, and provides real-time position sizing recommendations.
The indicator addresses a fundamental question every trader should ask before entering a trade: "Does this setup make mathematical sense?" Account Guardian answers this question visually and numerically, helping traders avoid impulsive entries with poor risk profiles.
Core Functionality
Account Guardian performs four primary functions:
Detects swing highs and swing lows to identify logical stop loss placement levels
Calculates Risk-to-Reward ratios for both long and short setups in real-time
Displays visual SL/TP zones on the chart for immediate trade planning
Computes position sizing based on your account size and risk tolerance
The goal is to provide traders with instant feedback on whether a potential trade meets their minimum risk/reward criteria before committing capital.
How It Works
Swing Detection
The indicator uses pivot point detection to identify recent swing highs and swing lows on the chart. These swing points serve as logical areas for stop loss placement:
For Long Trades: The most recent swing low becomes the stop loss level. Price breaking below this level would invalidate the bullish thesis.
For Short Trades: The most recent swing high becomes the stop loss level. Price breaking above this level would invalidate the bearish thesis.
The swing detection lookback period is configurable, allowing you to adjust sensitivity based on your trading timeframe and style.
It automatically adjusts the tp and sl when it is applied to your chart so it is always moving up and down!
Risk/Reward Calculation
Once swing levels are identified, the indicator calculates:
Entry Price: Current close price (where you would enter)
Stop Loss: Recent swing low (for longs) or swing high (for shorts)
Risk: Distance from entry to stop loss
Take Profit: Entry plus (Risk × Target Multiplier)
R:R Ratio: Reward divided by Risk
The R:R ratio is then evaluated against your configured thresholds to determine if the setup is valid, marginal, or poor.
Visual Elements
SL/TP Zones
When enabled, the indicator draws colored boxes on the chart showing:
Red Zone: Stop Loss area - the region between your entry and stop loss
Green/Gold/Red Zone: Take Profit area - colored based on R:R quality
The color coding provides instant visual feedback:
Green: R:R meets or exceeds your "Good R:R" threshold (default 3:1)
Gold: R:R meets minimum threshold but below "Good" (between 2:1 and 3:1)
Red: R:R below minimum threshold - setup should be avoided
Swing Point Markers
Small circles mark detected swing points on the chart:
Green circles: Swing lows (potential support / long SL levels)
Red circles: Swing highs (potential resistance / short SL levels)
Dashboard Panel
The dashboard in the top-right corner displays comprehensive trade planning information:
R:R Row: Current Risk-to-Reward ratio for long and short setups
Status Row: VALID, OK, BAD, or N/A based on R:R thresholds
Stop Loss Row: Exact price level for stop loss placement
Take Profit Row: Exact price level for take profit placement
Pos Size Row: Recommended position size based on your risk parameters
Risk $ Row: Dollar amount at risk per trade
Position Sizing Logic
The indicator calculates position size using the formula:
Position Size = Risk Amount / Risk per Unit
Where:
Risk Amount = Account Size × (Risk Percentage / 100)
Risk per Unit = Entry Price - Stop Loss Price
For example, with a $10,000 account risking 1% per trade ($100), if your entry is at 100 and stop loss at 98 (risk of 2 per unit), your position size would be 50 units.
Input Parameters
Swing Detection:
Swing Lookback: Number of bars to look back for pivot detection (default: 10). Higher values find more significant swing points but may be slower to update.
Target Multiplier: Multiplier applied to risk to calculate take profit distance (default: 2). A value of 2 means TP is 2× the distance of SL from entry.
Risk/Reward Thresholds:
Minimum R:R: Minimum acceptable Risk-to-Reward ratio (default: 2.0). Setups below this show as "BAD" in red.
Good R:R: Threshold for excellent setups (default: 3.0). Setups at or above this show as "VALID" in green.
Account Settings:
Account Size ($): Your trading account size in dollars (default: 10,000). Used for position sizing calculations.
Risk Per Trade (%): Percentage of account to risk per trade (default: 1.0%). Professional traders typically risk 0.5-2% per trade.
Display:
Show SL/TP Zones: Toggle visibility of the colored zone boxes on chart (default: enabled)
Show Dashboard: Toggle visibility of the information panel (default: enabled)
Analyze Direction: Choose to analyze Long only, Short only, or Both directions (default: Both)
How to Use This Indicator
Basic Workflow:
Add the indicator to your chart
Configure your account size and risk percentage in the settings
Set your minimum and good R:R thresholds based on your trading rules
Look at the dashboard to see current R:R for potential long and short entries
Only consider trades where the status shows "VALID" or at minimum "OK"
Use the displayed SL and TP levels for your order placement
Use the position size recommendation to determine lot/contract size
Interpreting the Dashboard:
VALID (Green): Excellent setup - R:R meets your "Good" threshold. This is the ideal scenario for taking a trade.
OK (Gold): Acceptable setup - R:R meets minimum but isn't optimal. Consider taking if other confluence factors align.
BAD (Red): Poor setup - R:R below minimum threshold. Avoid this trade or wait for better entry.
N/A (Gray): Cannot calculate - usually means no valid swing point detected yet.
Best Practices:
Use this indicator as a filter, not a signal generator. It tells you IF a trade makes sense, not WHEN to enter.
Combine with your existing entry strategy - use Account Guardian to validate setups from other analysis.
Adjust the swing lookback based on your timeframe. Lower timeframes may need smaller lookback values.
Be honest with your account size input - accurate position sizing requires accurate inputs.
Consider the target multiplier carefully. Higher multipliers mean larger potential reward but lower probability of hitting TP.
Alerts
The indicator includes four alert conditions:
Good Long Setup: Triggers when long R:R reaches or exceeds your "Good R:R" threshold
Good Short Setup: Triggers when short R:R reaches or exceeds your "Good R:R" threshold
Bad Long Setup: Triggers when long R:R falls below your minimum threshold
Bad Short Setup: Triggers when short R:R falls below your minimum threshold
These alerts can help you monitor multiple charts and get notified when favorable setups appear.
Technical Implementation
The indicator is built using Pine Script v6 and includes:
Pivot-based swing detection using ta.pivothigh() and ta.pivotlow()
Dynamic box drawing for visual SL/TP zones
Table-based dashboard for clean information display
Color-coded visual feedback system
Persistent variable tracking for swing levels
Code Structure:
// Swing Detection
float swingHi = ta.pivothigh(high, swingLen, swingLen)
float swingLo = ta.pivotlow(low, swingLen, swingLen)
// R:R Calculation for Long
float longSL = recentSwingLo
float longRisk = entry - longSL
float longTP = entry + (longRisk * targetMult)
float longRR = (longTP - entry) / longRisk
// Position Sizing
float riskAmount = accountSize * (riskPct / 100)
float posSize = riskAmount / longRisk
Limitations
The indicator uses historical swing points which may not always represent optimal SL placement for your specific strategy
Position sizing assumes you can trade fractional units - adjust accordingly for instruments with minimum lot sizes
R:R calculations assume linear price movement and don't account for gaps or slippage
The indicator doesn't predict price direction - it only evaluates the mathematical viability of a setup
Swing detection has inherent lag due to the lookback period required for pivot confirmation
Recommended Settings by Trading Style
Scalping (1-5 minute charts):
Swing Lookback: 5-8
Target Multiplier: 1-2
Minimum R:R: 1.5
Good R:R: 2.0
Day Trading (15-60 minute charts):
Swing Lookback: 8-12
Target Multiplier: 2
Minimum R:R: 2.0
Good R:R: 3.0
Swing Trading (4H-Daily charts):
Swing Lookback: 10-20
Target Multiplier: 2-3
Minimum R:R: 2.5
Good R:R: 4.0
Why Risk/Reward Matters
Many traders focus solely on win rate, but profitability depends on the combination of win rate AND risk/reward ratio. Consider these scenarios:
50% win rate with 1:1 R:R = Breakeven (before costs)
50% win rate with 2:1 R:R = Profitable
40% win rate with 3:1 R:R = Profitable
60% win rate with 1:2 R:R = Losing money
Account Guardian helps ensure you only take trades where the math works in your favor, even if you're wrong more often than you're right.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not intended as financial, investment, trading, or any other type of advice or recommendation.
Trading involves substantial risk of loss and is not suitable for all investors. The calculations provided by this indicator are based on historical price data and mathematical formulas that may not accurately predict future price movements.
Position sizing recommendations are estimates based on user inputs and should be verified before placing actual trades. Always consider factors such as leverage, margin requirements, and broker-specific rules when determining actual position sizes.
The Risk-to-Reward ratios displayed are theoretical calculations based on swing point detection. Actual trade outcomes will vary based on market conditions, execution quality, and other factors not captured by this indicator.
Past performance does not guarantee future results. Users should thoroughly test any trading approach in a demo environment before risking real capital. The authors and publishers of this indicator are not responsible for any losses or damages arising from its use.
Always consult with a qualified financial advisor before making investment decisions.
Latent Energy Reactor [The_lurker]Latent Energy Reactor | مفاعل الطاقة الكامنة
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🔬 THE PHILOSOPHY
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Markets operate in cycles of compression and expansion. Before every significant price movement, there exists a period where buyers and sellers reach a temporary equilibrium — a consolidation zone where energy accumulates like pressure building in a reactor.
The Latent Energy Reactor was designed to identify these critical zones, measure the energy building within them, and predict the direction of the inevitable breakout.
This indicator transforms the abstract concept of "market energy" into a quantifiable, visual system that traders can use to anticipate high-probability breakout opportunities.
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🎯 THE THREE BOX STATES
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Understanding the three box states is crucial for proper interpretation:
📦 STATE 1: ACTIVE ZONE (GRAY BOX)
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Visual Characteristics:
• Color: Gray/Neutral with 3D depth effect
• Extends to the right edge of the chart (future projection)
• Contains pressure lines (dotted horizontal lines inside)
• Displays gravity center line (dashed line showing volume-weighted center)
• Energy progress bar beneath the box
• Real-time information panel appears on screen
What It Means:
The gray box represents a LIVE consolidation zone currently forming. Price is contained within the boundaries, and energy is actively accumulating. This is the "waiting phase" where the reactor is charging.
What to Watch:
• Energy percentage climbing toward critical levels (80%+)
• Gravity center position (upper half = bullish bias, lower half = bearish bias)
• Top and bottom rejection counts in the information panel
• Phase progression (Forming → Growth → Mature → Exhaustion)
Trading Approach:
Do NOT trade inside the gray box. This is the preparation phase. Monitor the energy levels and predicted direction, but wait for confirmation.
📦 STATE 2: BULLISH BREAKOUT BOX (GREEN BOX)
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Visual Characteristics:
• Color: Green with 3D depth effect
• Box boundaries are now fixed (no longer extending right)
• Displays "BUY" text centered inside the box
• Stop Loss line appears below the box (orange)
• Three Take Profit lines appear above (teal/cyan)
• Entry line at the box's upper boundary (white dashed)
What It Means:
The green box indicates a CONFIRMED bullish breakout. Price has broken above the consolidation zone's upper boundary, releasing the accumulated energy upward.
Automatic Calculations Displayed:
• Entry Price: Upper boundary of the box
• Stop Loss: Lower boundary minus ATR buffer
• TP1: Entry + (Risk × 1.0) — 1:1 reward ratio
• TP2: Entry + (Risk × 1.5) — 1.5:1 reward ratio
• TP3: Entry + (Risk × 2.0) — 2:1 reward ratio
Trading Approach:
Consider long positions with the displayed SL/TP levels as guidelines. The higher the energy level and breakout quality score were before the breakout, the more reliable the signal.
📦 STATE 3: BEARISH BREAKOUT BOX (RED BOX)
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Visual Characteristics:
• Color: Red with 3D depth effect
• Box boundaries are now fixed
• Displays "SELL" text centered inside the box
• Stop Loss line appears above the box (orange)
• Three Take Profit lines appear below (teal/cyan)
• Entry line at the box's lower boundary (white dashed)
What It Means:
The red box indicates a CONFIRMED bearish breakout. Price has broken below the consolidation zone's lower boundary, releasing the accumulated energy downward.
Automatic Calculations Displayed:
• Entry Price: Lower boundary of the box
• Stop Loss: Upper boundary plus ATR buffer
• TP1: Entry - (Risk × 1.0) — 1:1 reward ratio
• TP2: Entry - (Risk × 1.5) — 1.5:1 reward ratio
• TP3: Entry - (Risk × 2.0) — 2:1 reward ratio
Trading Approach:
Consider short positions with the displayed SL/TP levels as guidelines. Stronger setups have higher pre-breakout energy and quality scores.
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⚛️ THE ENERGY CALCULATION SYSTEM
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The energy percentage (0-100%) is calculated using four factors:
Compression Score (up to 40 points)
Measures how tight the range is relative to normal volatility (ATR). Tighter compression = higher energy storage.
Time Score (up to 35 points)
Longer consolidation periods accumulate more energy. Each bar adds to the score up to the maximum.
Maturity Bonus (up to 15 points)
Zones that reach mature phases receive bonus energy points, recognizing that extended consolidations often produce more powerful breakouts.
Tightness Bonus (up to 10 points)
Extra points awarded when the range height is exceptionally small relative to ATR.
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📊 THE GRAVITY CENTER SYSTEM
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How It Works:
The gravity center is the volume-weighted average price within the consolidation zone. It reveals where the majority of trading activity (and thus institutional interest) is concentrated.
Interpretation:
• Gravity center in UPPER half → Institutions accumulating → Bullish bias
• Gravity center in LOWER half → Institutions distributing → Bearish bias
• Gravity center at MIDDLE → Neutral/Uncertain
Visual Display:
A dashed line with a ⚖️ symbol marks the gravity center inside active zones. The line color matches the directional bias.
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🏦 INSTITUTIONAL FOOTPRINT DETECTION
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What It Measures:
The indicator scans for volume anomalies — bars where volume significantly exceeds the average while price remains contained within the zone.
Why It Matters:
Large volume without price movement often indicates institutional players building positions. They cannot accumulate or distribute large quantities without leaving a "footprint" in the volume data.
Score Interpretation:
• Below 30%: Normal retail activity
• 30-50%: Some institutional interest detected
• Above 50%: Significant institutional footprint (marked with 🏦 icon)
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📈 MATURITY PHASES
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⚒ Forming Phase
The zone has just been identified. Energy is low, and the pattern needs more time to develop. Premature breakouts during this phase have higher failure rates.
📈 Growth Phase
The zone is developing nicely. Energy is building, and the consolidation pattern is becoming more defined. Watch for increasing rejection counts at boundaries.
✅ Mature Phase
Optimal trading phase. The zone has accumulated significant energy, institutional footprints are often visible, and breakout quality scores are typically highest.
⚠ Exhaustion Phase
The zone has persisted beyond typical duration. While energy remains high, the pattern may be losing its predictive power.
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🎨 VISUAL ELEMENTS GUIDE
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3D Box Effect
The 3D rendering creates visual depth with a top face and side face, making boxes stand out clearly. Adjustable via "3D Depth" and "3D Height %" settings.
Pressure Lines
Dotted horizontal lines inside active zones visualize internal pressure distribution. Lines closer to the gravity center are more opaque.
Energy Progress Bar
A horizontal bar beneath each zone shows energy level visually. Color progresses: green (low) → yellow (moderate) → orange (high) → red (critical).
Imminent Breakout Warning
When energy reaches critical threshold (default 80%), a warning label "⚠ IMMINENT!" appears above the active zone.
Information Panel
Real-time table displaying: Energy Level, Phase, Prediction, Breakout Quality, Institutional Footprint, Top/Bottom Rejections.
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📊 READING THE SIGNALS
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Energy Levels:
• Below 40%: Low energy — breakout unlikely soon
• 40-60%: Moderate energy — zone developing
• 60-80%: High energy — prepare for potential breakout
• Above 80%: Critical energy — breakout imminent
Breakout Quality Score:
• Below 50%: Weak setup — higher false breakout risk
• 50-70%: Moderate setup — proceed with caution
• Above 70%: Strong setup — high probability trade
Direction Confidence:
• Below 55%: Neutral — wait for clearer signals
• 55-70%: Moderate confidence
• Above 70%: High confidence prediction
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⚙️ RECOMMENDED SETTINGS
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For Scalping (1-15 min):
Min Bars in Range: 10-15 | ATR Period: 10 | Range ATR Multiplier: 2.0
For Day Trading (15min-1H):
Min Bars in Range: 15-20 | ATR Period: 14 | Range ATR Multiplier: 2.5
For Swing Trading (4H-Daily):
Min Bars in Range: 20-30 | ATR Period: 20 | Range ATR Multiplier: 3.0
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🔔 ALERTS
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• New Zone Alert: Triggers when a new consolidation zone is identified
• Imminent Breakout Alert: Triggers when energy reaches critical levels
• Bullish Breakout Alert: Triggers on confirmed bullish breakout
• Bearish Breakout Alert: Triggers on confirmed bearish breakout
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⚠️ DISCLAIMER
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This indicator is designed as a technical analysis tool to identify consolidation patterns and anticipate potential breakout directions. No indicator can predict the future with certainty. The displayed SL/TP levels are suggestions based on mathematical calculations, not guarantees.
This indicator is for educational and analytical purposes only. It does not constitute financial, investment, or trading advice. Use it in conjunction with your own strategy and risk management. Neither TradingView nor the developer is liable for any financial decisions or losses.
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مفاعل الطاقة الكامنة | Latent Energy Reactor
🔬 الفلسفة
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تعمل الأسواق في دورات من الضغط والتمدد. قبل كل حركة سعرية كبيرة، توجد فترة يصل فيها المشترون والبائعون إلى توازن مؤقت — منطقة تجميع حيث تتراكم الطاقة مثل الضغط المتراكم في مفاعل.
صُمم مفاعل الطاقة الكامنة لتحديد هذه المناطق الحرجة، وقياس الطاقة المتراكمة داخلها، والتنبؤ باتجاه الاختراق الحتمي.
يحوّل هذا المؤشر المفهوم المجرد لـ "طاقة السوق" إلى نظام قابل للقياس والعرض البصري يمكن للمتداولين استخدامه لتوقع فرص الاختراق عالية الاحتمالية.
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🎯 حالات الصندوق الثلاث
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فهم حالات الصندوق الثلاث ضروري للتفسير الصحيح:
📦 الحالة الأولى: المنطقة النشطة (الصندوق الرمادي)
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الخصائص البصرية:
• اللون: رمادي/محايد مع تأثير عمق ثلاثي الأبعاد
• يمتد إلى الحافة اليمنى للرسم البياني (إسقاط مستقبلي)
• يحتوي على خطوط الضغط (خطوط أفقية منقطة بالداخل)
• يعرض خط مركز الثقل (خط متقطع يُظهر المركز المرجح بالحجم)
• شريط تقدم الطاقة أسفل الصندوق
• تظهر لوحة المعلومات الفورية على الشاشة
ماذا يعني:
الصندوق الرمادي يمثل منطقة تجميع حَيّة تتشكل حالياً. السعر محتوى داخل الحدود، والطاقة تتراكم بنشاط. هذه هي "مرحلة الانتظار" حيث المفاعل يشحن.
ما يجب مراقبته:
• نسبة الطاقة تصعد نحو المستويات الحرجة (80%+)
• موقع مركز الثقل (النصف العلوي = ميل صعودي، النصف السفلي = ميل هبوطي)
• عدد الرفض العلوي والسفلي في لوحة المعلومات
• تقدم المرحلة (تشكّل ← نمو ← نضج ← إرهاق)
نهج التداول:
لا تتداول داخل الصندوق الرمادي. هذه مرحلة الإعداد. راقب مستويات الطاقة والاتجاه المتوقع، لكن انتظر التأكيد.
📦 الحالة الثانية: صندوق الاختراق الصعودي (الصندوق الأخضر)
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الخصائص البصرية:
• اللون: أخضر مع تأثير عمق ثلاثي الأبعاد
• حدود الصندوق ثابتة الآن (لم تعد تمتد لليمين)
• يعرض نص "شراء" أو "BUY" في منتصف الصندوق
• يظهر خط وقف الخسارة أسفل الصندوق (برتقالي)
• تظهر ثلاثة خطوط أهداف فوق الصندوق (فيروزي)
• خط الدخول عند الحد العلوي للصندوق (أبيض متقطع)
ماذا يعني:
الصندوق الأخضر يشير إلى اختراق صعودي مُؤَكَّد. كسر السعر فوق الحد العلوي لمنطقة التجميع، محرراً الطاقة المتراكمة للأعلى.
الحسابات التلقائية المعروضة:
• سعر الدخول: الحد العلوي للصندوق
• وقف الخسارة: الحد السفلي ناقص حاجز ATR
• الهدف 1: الدخول + (المخاطرة × 1.0) — نسبة مكافأة 1:1
• الهدف 2: الدخول + (المخاطرة × 1.5) — نسبة مكافأة 1.5:1
• الهدف 3: الدخول + (المخاطرة × 2.0) — نسبة مكافأة 2:1
نهج التداول:
فكر في صفقات شراء مع مستويات وقف الخسارة والأهداف المعروضة كإرشادات. كلما ارتفع مستوى الطاقة ودرجة جودة الاختراق قبل الكسر، كانت الإشارة أكثر موثوقية.
📦 الحالة الثالثة: صندوق الاختراق الهبوطي (الصندوق الأحمر)
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الخصائص البصرية:
• اللون: أحمر مع تأثير عمق ثلاثي الأبعاد
• حدود الصندوق ثابتة الآن
• يعرض نص "بيع" أو "SELL" في منتصف الصندوق
• يظهر خط وقف الخسارة فوق الصندوق (برتقالي)
• تظهر ثلاثة خطوط أهداف أسفل الصندوق (فيروزي)
• خط الدخول عند الحد السفلي للصندوق (أبيض متقطع)
ماذا يعني:
الصندوق الأحمر يشير إلى اختراق هبوطي مُؤَكَّد. كسر السعر تحت الحد السفلي لمنطقة التجميع، محرراً الطاقة المتراكمة للأسفل.
الحسابات التلقائية المعروضة:
• سعر الدخول: الحد السفلي للصندوق
• وقف الخسارة: الحد العلوي زائد حاجز ATR
• الهدف 1: الدخول - (المخاطرة × 1.0) — نسبة مكافأة 1:1
• الهدف 2: الدخول - (المخاطرة × 1.5) — نسبة مكافأة 1.5:1
• الهدف 3: الدخول - (المخاطرة × 2.0) — نسبة مكافأة 2:1
نهج التداول:
فكر في صفقات بيع مع مستويات وقف الخسارة والأهداف المعروضة كإرشادات. الإعدادات الأقوى لديها طاقة ودرجات جودة أعلى قبل الاختراق.
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⚛️ نظام حساب الطاقة
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تُحسب نسبة الطاقة (0-100%) باستخدام أربعة عوامل:
درجة الضغط (حتى 40 نقطة)
تقيس مدى ضيق النطاق نسبة للتقلب الطبيعي (ATR). ضغط أشد = تخزين طاقة أعلى.
درجة الوقت (حتى 35 نقطة)
فترات التجميع الأطول تراكم طاقة أكثر. كل شمعة تضيف للدرجة حتى الحد الأقصى.
مكافأة النضج (حتى 15 نقطة)
المناطق التي تصل لمراحل النضج تحصل على نقاط طاقة إضافية، اعترافاً بأن التجميعات الممتدة غالباً تنتج اختراقات أقوى.
مكافأة الضيق (حتى 10 نقاط)
نقاط إضافية تُمنح عندما يكون ارتفاع النطاق صغيراً استثنائياً نسبة لـ ATR.
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📊 نظام مركز الثقل
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كيف يعمل:
مركز الثقل هو متوسط السعر المرجح بالحجم داخل منطقة التجميع. يكشف أين يتركز معظم النشاط التداولي (وبالتالي الاهتمام المؤسسي).
التفسير:
• مركز الثقل في النصف العلوي ← المؤسسات تجمّع ← ميل صعودي
• مركز الثقل في النصف السفلي ← المؤسسات توزّع ← ميل هبوطي
• مركز الثقل في المنتصف ← محايد/غير مؤكد
العرض البصري:
خط متقطع مع رمز ⚖️ يحدد مركز الثقل داخل المناطق النشطة. لون الخط يطابق الميل الاتجاهي.
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🏦 كشف البصمة المؤسسية
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ما يقيسه:
يفحص المؤشر الشذوذات الحجمية — شموع حجمها يتجاوز المتوسط بشكل كبير بينما يبقى السعر محتوى داخل المنطقة.
لماذا هذا مهم:
الحجم الكبير بدون حركة سعرية غالباً يشير إلى لاعبين مؤسسيين يبنون مراكز. لا يمكنهم تجميع أو توزيع كميات كبيرة بدون ترك "بصمة" في بيانات الحجم.
تفسير الدرجة:
• أقل من 30%: نشاط تجزئة عادي
• 30-50%: بعض الاهتمام المؤسسي مكتشف
• فوق 50%: بصمة مؤسسية كبيرة (تُحدد بأيقونة 🏦)
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📈 مراحل النضج
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⚒ مرحلة التشكّل
المنطقة تم تحديدها للتو. الطاقة منخفضة، والنمط يحتاج وقتاً أكثر للتطور. الاختراقات المبكرة خلال هذه المرحلة لديها معدلات فشل أعلى.
📈 مرحلة النمو
المنطقة تتطور بشكل جيد. الطاقة تتراكم، ونمط التجميع يصبح أكثر تحديداً. راقب زيادة عدد الرفض عند الحدود.
✅ مرحلة النضج
مرحلة التداول المثلى. المنطقة راكمت طاقة كبيرة، البصمات المؤسسية غالباً مرئية، ودرجات جودة الاختراق عادة في أعلى مستوياتها.
⚠ مرحلة الإرهاق
المنطقة استمرت أطول من المدة النموذجية. بينما تبقى الطاقة مرتفعة، قد يفقد النمط قوته التنبؤية.
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🎨 دليل العناصر البصرية
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تأثير الصندوق ثلاثي الأبعاد
العرض ثلاثي الأبعاد يخلق عمقاً بصرياً مع وجه علوي ووجه جانبي، مما يجعل الصناديق بارزة بوضوح. قابل للتعديل عبر إعدادات "عمق 3D" و"ارتفاع 3D %".
خطوط الضغط
خطوط أفقية منقطة داخل المناطق النشطة تصور توزيع الضغط الداخلي. الخطوط الأقرب لمركز الثقل أكثر وضوحاً.
شريط تقدم الطاقة
شريط أفقي أسفل كل منطقة يُظهر مستوى الطاقة بصرياً. اللون يتدرج: أخضر (منخفض) ← أصفر (متوسط) ← برتقالي (مرتفع) ← أحمر (حرج).
تحذير الاختراق الوشيك
عندما تصل الطاقة للعتبة الحرجة (افتراضياً 80%)، يظهر تحذير "⚠ كسر وشيك!" فوق المنطقة النشطة.
لوحة المعلومات
جدول فوري يعرض: مستوى الطاقة، المرحلة، التوقع، جودة الاختراق، البصمة المؤسسية، الرفض العلوي/السفلي.
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📊 قراءة الإشارات
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مستويات الطاقة:
• أقل من 40%: طاقة منخفضة — الاختراق غير مرجح قريباً
• 40-60%: طاقة متوسطة — المنطقة في طور التطور
• 60-80%: طاقة مرتفعة — استعد لاختراق محتمل
• فوق 80%: طاقة حرجة — الاختراق وشيك
درجة جودة الاختراق:
• أقل من 50%: إعداد ضعيف — خطر اختراق كاذب أعلى
• 50-70%: إعداد متوسط — تقدم بحذر
• فوق 70%: إعداد قوي — صفقة عالية الاحتمالية
ثقة الاتجاه:
• أقل من 55%: محايد — انتظر إشارات أوضح
• 55-70%: ثقة متوسطة
• فوق 70%: توقع عالي الثقة
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⚙️ الإعدادات الموصى بها
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للمضاربة السريعة (1-15 دقيقة):
الحد الأدنى للشموع: 10-15 | فترة ATR: 10 | مضاعف ATR: 2.0
للتداول اليومي (15 دقيقة - ساعة):
الحد الأدنى للشموع: 15-20 | فترة ATR: 14 | مضاعف ATR: 2.5
للتداول المتأرجح (4 ساعات - يومي):
الحد الأدنى للشموع: 20-30 | فترة ATR: 20 | مضاعف ATR: 3.0
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🔔 التنبيهات
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• تنبيه منطقة جديدة: يُفعّل عند تشكّل منطقة تجميع جديدة
• تنبيه اختراق وشيك: يُفعّل عند وصول الطاقة لمستويات حرجة
• تنبيه اختراق صعودي: يُفعّل عند تأكيد كسر صعودي
• تنبيه اختراق هبوطي: يُفعّل عند تأكيد كسر هبوطي
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⚠️ إخلاء المسؤولية
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هذا المؤشر مصمم كأداة تحليل فني لتحديد أنماط التجميع وتوقع اتجاهات الاختراق المحتملة. لا يمكن لأي مؤشر التنبؤ بالمستقبل بيقين. مستويات وقف الخسارة والأهداف المعروضة هي اقتراحات مبنية على حسابات رياضية، وليست ضمانات.
هذا المؤشر لأغراض تعليمية وتحليلية فقط. لا يُمثل نصيحة مالية أو استثمارية أو تداولية. استخدمه بالتزامن مع استراتيجيتك الخاصة وإدارة المخاطر. لا يتحمل TradingView ولا المطور مسؤولية أي قرارات مالية أو خسائر.
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure.
To use this engine successfully, you must adopt a specific optimization mindset:
Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless.
Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the trade is rejected.
This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal.
Module 2: Correlation Trend Indicator (CTI)
Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend).
Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise).
Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts).
Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support.
Module 6: Crypto Market Breadth (CMB)
Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges.
Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data.
Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart.
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen.
Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up.
Module 11: HSRS Compression / Super AO
Logic: Two options in one.
HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands.
Super AO: A combination of the Awesome Oscillator and SuperTrend logic.
Function: Great for catching explosive moves that result from periods of low volatility (consolidation).
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked.
Bitcoin Halving Logic:
Hardcoded dates for past and projected future Bitcoin halvings (up to 2040).
Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes.
Miner Capitulation:
Uses Hash Rate Ribbons (Moving averages of Hash Rate).
If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat.
ADX Filter (Flat Market Protocol):
If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market.
CryptoCap Trend:
Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins.
6. Risk Management & The Dump Protection Team (DPT)
Gypsy Bot separates "Entry Logic" from "Risk Management Logic."
Dump Protection Team (DPT)
This is a specialized logic branch designed to save the account during Black Swan events.
Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit.
Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction.
Advanced Adaptive Trailing Stop (AATS)
Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic.
Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks.
Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital.
Staged Take Profits
TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win.
TP2: Take the bulk of profit.
TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance.
Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative).
Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals).
Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
X FP Imbalancesprovides advanced volume profile analysis by isolating and visualizing market aggression at a granular price level. It is a powerful tool for short-term and intraday traders seeking objective confirmation of supply and demand dynamics, primarily used to identify high-probability reversal or continuation points based on order flow principles.
Key Functionality and Methodology
The indicator operates by transforming standard time-based candle data into a Volume-at-Price footprint, focusing specifically on aggressive market activity.
Granular Aggression Measurement (Delta)
The script dynamically segments the price range into discrete price levels (tickAmount). This granularity is controlled either by a user-defined fixed tick count or automatically adjusted using the Average True Range (ATR) to adapt the box size to current market volatility.
The script uses lower timeframe data (e.g., 1-minute bars) to accurately distribute the total volume into each price level, distinguishing between aggressive buying (Up Volume) and aggressive selling (Down Volume).
The core output is Delta, which is the net difference between aggressive buying and aggressive selling at each price level.
Stacked Imbalance Identification
The indicator identifies an imbalance when the volume from one side (e.g., aggressive buyers) overwhelms the total volume at that level by a user-defined percentage (imbalanceP).
A single price level where the Delta percentage exceeds the threshold is defined as an Imbalance.
The Stacked Imbalance is the primary signal, triggered when the imbalance is detected on a user-defined number of consecutive price levels (stacked) in the same direction (e.g., 3 consecutive levels of aggressive buying). This signals a high-conviction structural break or strong rejection.
Stacked imbalances are visually highlighted and can trigger real-time alerts upon bar close.
Strategic Applications
This indicator is invaluable for traders who integrate order flow concepts into their decision-making process.
One-Sided Stack (Supply/Demand Zone): Aggressive selling (Red Stack) at a high price, followed by price reversal, identifies a Structural Supply Zone (Resistance). The level is where sellers aggressively rejected demand, leaving an untested area of supply.
Overlapping Stacks (Climax Reversal): Consecutive Buy Stacks followed immediately by Sell Stacks in a tight range signals Buyer Exhaustion and an immediate Climax Reversal. The buying power was absorbed and instantly overwhelmed by waiting supply.
Absence of Stack: When price moves sharply through a level without creating any Stacked Imbalances, it suggests an Orderly Move or Liquidity Void. The absence of resistance means the market move is structurally weak and often vulnerable to a retest.
The choice between a Fixed Tick Distance (for micro-pattern precision) and ATR-based sizing (for volatility-adjusted analysis) allows the user to tailor the indicator to specific asset classes and trading styles.
White Crow**White Crow — cluster reversal signals + market structure**
> Indicator that helps you read market structure (pivots, trend, last extremes) and spot potential reversals through CCI/RSI signal clusters. This is *not* a standalone trading system and does not guarantee any result — it is a tool for filtering and confirming your own market ideas.
---
## 1. Concept
White Crow combines three core blocks:
1. **Pivots & market structure**
Automatically detects **local tops/bottoms** and derives a *Bullish / Bearish / Sideways* bias from them.
In the top-right corner you see a compact panel with current trend and **Last Bottom / Last Top** prices.
2. **Momentum & overbought/oversold zones**
Inside, the indicator uses:
* **CCI** with fixed levels `+100 / -100`;
* an optional **RSI filter** with overbought/oversold levels (`80 / 20`).
These generate basic *Buy / Close* signals.
3. **Cluster signals Buy X / CloseV**
The script tracks **clusters of signals inside a 4-bar window** and highlights rarer, “amplified” events:
* **Buy X** — cluster buy signal (multiple buy conditions in a row);
* **CloseV** — cluster signal for exit/reversal.
**Buy X and CloseV are the strongest and most reliable signals in this indicator** because they are based on repeated conditions rather than a single bar. They work **best on higher timeframes (1H–4H)**, where they reflect meaningful shifts in order flow instead of noise.
> ⚠️ Important: Buy X and CloseV are *only signals*. They must be used as **one of several confirmation factors** for your own view of market structure (support/resistance, trend, price action, volume, etc.), not as standalone reasons to enter or exit trades.
---
## 2. How it works
### 2.1. Pivots and trend detection
* The indicator builds a **zigzag-like structure**:
after a local high, once price retraces down by a given percentage (`pivotSigma`), a **Top** is marked;
after a local low, once price retraces up by the same percentage, a **Bottom** is marked.
* Using the sequence of recent tops and bottoms, the script determines the trend:
* *Bullish* — the last low is higher than the previous one (HL);
* *Bearish* — the last high is lower than the previous one (LH);
* otherwise — *Sideways*.
* The info table shows:
* **Market Trend** — Bullish / Bearish / Sideways;
* **Last Bottom / Last Top** with adaptive decimal precision (works for crypto, FX, stocks, etc.).
### 2.2. Base Buy / Close signals
* **Long condition (Buy):**
* `CCI < -100` (oversold),
* if RSI filter is enabled — `RSI < 20`.
* **Short/Exit condition (Close):**
* `CCI > +100` (overbought),
* if RSI filter is enabled — `RSI > 80`.
These conditions generate the regular **Buy** and **Close** labels on the chart.
### 2.3. Clusters: Buy X and CloseV
To reduce noise, the indicator evaluates not only the current bar, but also the **last 4 bars**:
* `buy_count` — how many times the long condition was true within the last 4 bars;
* `sell_count` — how many times the short condition was true within the last 4 bars.
Then:
* **Buy X** appears when:
* `buy_count ≥ 2` (conditions for Buy were met on at least 2 of the last 4 bars),
* the time filter between two Buy X signals is satisfied (`Min Bars Between Signals`).
* **CloseV** appears when:
* `sell_count ≥ 2`,
* the required number of bars has passed since the previous CloseV.
> ✅ This is why **Buy X / CloseV are stronger and more trustworthy than single Buy/Close signals**, especially on **1H–4H** timeframes: the market confirms the same overbought/oversold condition several times in a row.
### 2.4. Order Blocks
* When `Show Order Blocks` is enabled, the indicator highlights **impulsive candles** whose body exceeds a threshold based on ATR.
* Colored rectangles mark **potential order blocks** (areas where strong buying or selling previously occurred).
## 3. Inputs and customization
Inputs are grouped in TradingView-friendly categories.
### 3.1. Pivot Settings
* `Show Pivots` — enable/disable **Top / Bottom** markers.
* `Sigma (% retracement)` — pivot sensitivity (minimum retracement in % required to confirm a pivot).
* Colors for Top/Bottom — for visual tuning.
**Tip:**
On H1–H4 you can keep near-default values.
On lower timeframes, reduce `Sigma` if you want more detailed local structure.
### 3.2. CCI / RSI Settings
* `CCI Period` — CCI length (short by default for faster reaction).
* `Enable RSI Filter` / `RSI Period` — toggle and length for RSI filter.
* RSI levels are fixed at **20 / 80** to mark strong oversold/overbought zones.
**Usage:**
* For more conservative entries — keep the RSI filter enabled.
* For more frequent signals (e.g. scalping) — you can disable the RSI filter.
### 3.3. Order Blocks
* `Show Order Blocks` — display order block zones.
* `Block Threshold (ATR multiplier)` — how large a candle must be (vs ATR) to be considered significant.
### 3.4. Signals & Filters
* `Show Buy / Show Buy X / Show Close / Show CloseV` — choose which labels you want to see.
* `Enable Time Filter` — enable minimum spacing between amplified signals.
* `Min Bars Between Signals` — how many bars must pass between two Buy X or two CloseV signals.
**Tip:**
If you see too many amplified signals, increase `Min Bars Between Signals`.
If you want more activity, decrease it.
### 3.5. Alerts
* `Buy Alerts / Buy X Alerts / Close Alerts / CloseV Alerts` — choose which signal types should trigger alerts.
* `One Alert Per Bar` — when enabled, alerts are triggered only once per bar (recommended for H1–H4).
Alerts are generated via `alert()`, with messages that include signal type, ticker, timeframe and current price.
---
## 4. How to trade with White Crow
### 4.1. Recommended timeframes
* 📌 **Main focus: 1H–4H.**
On these timeframes:
* pivots and trend are more stable;
* CCI/RSI reflect meaningful swings;
* **Buy X / CloseV clusters** filter out a lot of intrabar noise.
You can still experiment on M1–M15, but expect more signals and more sensitivity to noise.
### 4.2. Reading the signals step by step
1. **Start with context**
* Look at **Market Trend / Last Bottom / Last Top** in the info panel.
* See where price is relative to these points: near resistance, near support, inside a range, etc.
2. **Identify zones of interest**
* Use pivots and order blocks as potential support/resistance areas.
* Wait for price to approach these zones.
3. **Watch the signals**
* **Buy** — early sign of local oversold conditions.
* **Buy X** — amplified cluster signal; more weight than a single Buy.
* **Close** — early warning of potential exhaustion in the current move.
* **CloseV** — amplified cluster exit/reversal signal.
4. **Practical approach**
* In a *Bullish* trend:
* focus on **Buy / Buy X** near bottoms and demand blocks;
* use **Close / CloseV** for partial profit-taking or tightening stops.
* In a *Bearish* trend:
* focus on **Close / CloseV** near tops and supply blocks;
* use **Buy / Buy X** mainly for countertrend scalps with strict risk control.
---
## 5. Important notes and disclaimer
1. **Buy X / CloseV are stronger — but not “magic” signals.**
They are statistically more meaningful than single Buy/Close signals because:
* they require multiple confirmations within a cluster;
* they are time-filtered.
However, **false signals are still possible**, especially in news spikes and low-liquidity conditions.
2. **Best performance on higher timeframes (1H–4H).**
Here, Buy X and CloseV usually reflect genuine shifts in supply/demand rather than micro noise.
3. **This is a confirmation tool, not a complete system.**
Pro Trading White Crow:
* does not manage risk;
* does not define position size or stop-loss;
* does not replace your own analysis.
Always use its signals as **one of several confluence factors** together with structure, trend, price action, volume, and your trading plan.
4. **Educational purpose only.**
This script and description are for educational and analytical purposes only.
They **do not constitute investment advice or a guarantee of profit**.
You are fully responsible for all trading decisions and risk management.
---
---
## White Crow — кластерные сигналы разворота + структура рынка
> Индикатор помогает читать рыночную структуру (пивоты, тренд, последние экстремумы) и находить потенциальные развороты через кластеры сигналов CCI/RSI. Это *не* готовая торговая система и *не* гарантия результата — а инструмент для фильтрации и подтверждения ваших собственных идей по рынку.
---
## 1. Концепция
White Crow объединяет три ключевых блока:
1. **Пивоты и структура рынка**
Автоматически находит **локальные вершины и впадины** и на их основе формирует трендовое смещение: *Bullish / Bearish / Sideways*.
В правом верхнем углу — компактная панель с текущим трендом и ценами **Last Bottom / Last Top**.
2. **Моментум и зоны перегрева**
Внутри используются:
* **CCI** с фиксированными уровнями `+100 / -100`;
* опциональный **фильтр RSI** с уровнями перепроданности/перекупленности (`20 / 80`).
По ним строятся базовые сигналы *Buy / Close*.
3. **Кластерные сигналы Buy X / CloseV**
Скрипт отслеживает **кластеры сигналов внутри окна в 4 бара** и выделяет более редкие, «усиленные» события:
* **Buy X** — кластерный сигнал покупки (несколько buy-условий подряд);
* **CloseV** — кластерный сигнал выхода/разворота.
Именно **Buy X и CloseV являются наиболее сильными и достоверными сигналами индикатора**, так как возникают при повторяющемся выполнении условий, а не на одном баре. Лучше всего они работают **на старших таймфреймах (1–4 часа)**, где отражают реальное смещение баланса спроса/предложения, а не рыночный шум.
> ⚠️ Важно: Buy X и CloseV — *это всего лишь сигналы*. Они должны использоваться **как один из факторов подтверждения** вашего видения структуры рынка (уровни, тренд, price action, объём и т.д.), а не как единственная причина для входа или выхода.
---
## 2. Как это работает
### 2.1. Пивоты и определение тренда
* Индикатор строит **структуру в стиле зигзага**:
после локального максимума, когда цена откатывает вниз на заданный процент (`pivotSigma`), отмечается **Top**;
после локального минимума, когда цена откатывает вверх на тот же процент, отмечается **Bottom**.
* По последовательности последних вершин и впадин определяется тренд:
* *Bullish* — последний минимум выше предыдущего (HL);
* *Bearish* — последний максимум ниже предыдущего (LH);
* иначе — *Sideways*.
* В информационной таблице отображаются:
* **Market Trend** — Bullish / Bearish / Sideways;
* **Last Bottom / Last Top** с адаптивным количеством знаков (подходит под крипту, форекс, акции и т.д.).
### 2.2. Базовые сигналы Buy / Close
* **Условие для Buy (лонг):**
* `CCI < -100` (зона перепроданности),
* при включённом фильтре — `RSI < 20`.
* **Условие для Close (шорт/выход):**
* `CCI > +100` (зона перекупленности),
* при включённом фильтре — `RSI > 80`.
По этим условиям индикатор рисует обычные метки **Buy** и **Close**.
### 2.3. Кластеры: Buy X и CloseV
Чтобы отсеять лишний шум, индикатор оценивает не только текущий бар, но и **4 последних бара**:
* `buy_count` — сколько раз условие на покупку выполнялось за последние 4 бара;
* `sell_count` — сколько раз условие на продажу/выход выполнялось за последние 4 бара.
Далее:
* **Buy X** появляется, когда:
* `buy_count ≥ 2` (минимум на 2 из 4 баров были условия для покупки),
* соблюдён фильтр по времени между усиленными сигналами (`Min Bars Between Signals`).
* **CloseV** появляется, когда:
* `sell_count ≥ 2`,
* прошло достаточно баров с момента предыдущего CloseV.
> ✅ Поэтому **Buy X и CloseV заметно сильнее и надёжнее одиночных Buy/Close**, особенно на **таймфреймах 1–4 часа**: рынок несколько раз подряд подтверждает один и тот же перегрев/разрядку момента.
### 2.4. Order Blocks
* При включённом `Show Order Blocks` индикатор выделяет **импульсные свечи**, чьё тело больше заданного множителя ATR.
* По таким свечам строятся цветные прямоугольники — **потенциальные блоки ордеров** (области поддержек/сопротивлений, где ранее проходил крупный объём).
---
## 3. Настройки и кастомизация
Настройки сгруппированы в привычные разделы TradingView.
### 3.1. Pivot Settings
* `Show Pivots` — включить/выключить метки **Top / Bottom**.
* `Sigma (% retracement)` — чувствительность к пивотам (минимальная глубина отката в процентах).
* Цвета Top/Bottom — визуальная настройка.
**Совет:**
На H1–H4 можно оставить значения близкие к стандартным.
На младших ТФ уменьшайте `Sigma`, если нужна более детальная структура.
### 3.2. CCI / RSI Settings
* `CCI Period` — период CCI (по умолчанию короткий, для более быстрой реакции).
* `Enable RSI Filter` / `RSI Period` — включение и длина RSI-фильтра.
* Уровни RSI фиксированы: **20 / 80**, выделяя сильную перепроданность/перекупленность.
**Использование:**
* Для более консервативной торговли — держите фильтр RSI включённым.
* Для более частых сигналов (скальпинг и т.п.) — можно фильтр отключить.
### 3.3. Order Blocks
* `Show Order Blocks` — отображение блоков ордеров.
* `Block Threshold (ATR multiplier)` — насколько большой должна быть свеча относительно ATR, чтобы считаться значимой.
### 3.4. Signals & Filters
* `Show Buy / Show Buy X / Show Close / Show CloseV` — выбор типов отображаемых меток.
* `Enable Time Filter` — включение минимального интервала между усиленными сигналами.
* `Min Bars Between Signals` — сколько баров должно пройти между двумя Buy X или двумя CloseV.
**Совет:**
Если усиленных сигналов слишком много — увеличьте `Min Bars Between Signals`.
Если хотите больше активности — уменьшите это значение.
### 3.5. Alerts
* `Buy Alerts / Buy X Alerts / Close Alerts / CloseV Alerts` — выбор типов сигналов для алертов.
* `One Alert Per Bar` — при включении алерты отправляются один раз на бар (рекомендуется для H1–H4).
Алерты формируются через `alert()` с сообщением, включающим тип сигнала, тикер, таймфрейм и текущую цену.
---
## 4. Как использовать White Crow в торговле
### 4.1. Рекомендуемые таймфреймы
* 📌 **Основной фокус: 1–4 часа.**
На этих ТФ:
* структура по пивотам и тренд более стабильны;
* CCI/RSI отражают существенные ценовые колебания;
* кластеры **Buy X / CloseV** лучше отсеивают шум.
На M1–M15 индикатор тоже можно применять, но нужно быть готовым к большему количеству сигналов и чувствительности к микродвижениям.
### 4.2. Пошаговое чтение сигналов
1. **Начните с контекста**
* Посмотрите на **Market Trend / Last Bottom / Last Top** в панели.
* Определите, где находитесь относительно этих уровней: у сопротивления, у поддержки, внутри диапазона и т.п.
2. **Найдите зоны интереса**
* Используйте пивоты и order blocks как потенциальные области спроса/предложения.
* Ждите подхода цены к этим зонам.
3. **Отслеживайте сигналы**
* **Buy** — ранний признак локальной перепроданности.
* **Buy X** — усиленный кластерный сигнал, более значимый, чем одиночный Buy.
* **Close** — ранний сигнал возможного ослабления текущего движения.
* **CloseV** — усиленный кластерный сигнал выхода/разворота.
4. **Практическое применение**
* В *бычьем* тренде:
* фокус на **Buy / Buy X** возле впадин и зон спроса;
* **Close / CloseV** использовать для частичной фиксации и подтягивания стопа.
* В *медвежьем* тренде:
* фокус на **Close / CloseV** возле вершин и зон предложения;
* **Buy / Buy X** — для аккуратных контртрендовых входов с жестким риском.
---
## 5. Важные замечания и дисклеймер
1. **Buy X / CloseV сильнее, но не «волшебные» сигналы.**
Они статистически более значимы, чем одиночные Buy/Close, потому что:
* требуют нескольких подтверждений в кластере;
* фильтруются по времени.
Однако **ложные срабатывания всё равно возможны**, особенно на новостях и в условиях низкой ликвидности.
2. **Оптимальная область применения — старшие ТФ (1–4 часа).**
Здесь Buy X и CloseV обычно отражают реальное изменение баланса спроса/предложения, а не шум.
3. **Это инструмент подтверждения, а не полноценная система.**
Pro Trading White Crow:
* не управляет рисками;
* не считает размер позиции и уровень стоп-лосса;
* не заменяет ваше собственное видение рынка.
Всегда используйте его сигналы **как один из факторов согласованности** вместе со структурой, трендом, price action, объёмом и персональным торговым планом.
4. **Образовательный характер.**
Скрипт и описание предназначены для обучения и анализа графиков.
Они **не являются инвестиционной рекомендацией и не гарантируют прибыль**.
Вы самостоятельно принимаете все торговые решения и несёте полную ответственность за риск.
---
Session Opening Range Breakout (ORBO)This strategy automates a classic Opening Range Breakout (ORBO) approach: it builds a price range for the first minutes after the market opens, then looks for strong breakouts above or below that range to catch early directional moves.
Concept
The idea behind ORBO is simple:
The first minutes after the session open are often highly informative.
Price forms an “opening range” that acts as a mini support/resistance zone.
A clean breakout beyond this zone can lead to high-momentum moves.
This script turns that logic into a fully backtestable strategy in TradingView.
How the strategy works
Opening Range Session
Default session: 09:30–09:50 (exchange time)
During this window, the script tracks:
orHigh → highest high within the session
orLow → lowest low within the session
This forms your Opening Range for the day.
Breakout Logic (after the window ends)
Once the defined session ends:
Long Entry:
If the close crosses above the Opening Range High (orHigh),
→ strategy.entry("OR Long", strategy.long) is triggered.
Short Entry:
If the close crosses below the Opening Range Low (orLow),
→ strategy.entry("OR Short", strategy.short) is triggered.
Only one opening range per day is considered, which keeps the logic clean and easy to interpret.
Daily Reset
At the start of a new trading day, the script resets:
orHigh := na
orLow := na
A fresh Opening Range is then built using the next session’s 09:30–09:50 candles.
This ensures entries are always based on today’s structure, not yesterday’s.
Visuals & Inputs
Inputs:
Opening range session → default: "0930-0950"
Show OR levels → toggle visibility of OR High / Low lines
Fill range body → optional shaded zone between OR High and OR Low
Chart visuals:
A green line marks the Opening Range High.
A red line marks the Opening Range Low.
Optional yellow fill highlights the entire OR zone.
Background shading during the session shows when the range is currently being built.
These visuals make it easy to see:
Where the OR sits relative to current price
How clean / noisy the breakout was
How often price respects or rejects the opening zone
Backtesting & Optimization
Because this is written as a strategy():
You can use TradingView’s Strategy Tester to view:
Win rate
Net profit
Drawdown
Profit factor
Equity curve
Ideas to experiment with:
Change the session window (e.g., 09:15–09:45, 10:00–10:30)
Apply to different:
Markets: indices, FX, crypto, stocks
Timeframes: 1m / 5m / 15m
Add your own:
Stop Loss & Take Profit levels
Time filters (only trade certain days / times)
Volatility filters (e.g., ATR, range size thresholds)
Higher-timeframe trend filter (e.g., only take longs above 200 EMA)
Liquidity Structure & Sweeps [Visualized]Liquidity Structure & Sweeps | 流动性结构与猎杀
1. Design Philosophy & Logic
This indicator is designed based on Smart Money Concepts (SMC) and Market Microstructure principles. Unlike traditional indicators that rely on lagging averages or repainting fractals, this script focuses on "Objective Structure" and "Liquidity Grabs".
The core design philosophy rests on three pillars:
Zero Repainting (Real-time Integrity): We utilize a strict "Left-Side Confirmation" algorithm. A structure level is only stored in memory when the candle is fully closed (barstate.isconfirmed). This ensures that the historical signals you see are exactly what happened in real-time.
Institutional Memory (Visualized): Markets "remember" key levels. This script draws dashed lines extending from valid pivot points. These lines represent "resting liquidity" (Stop Orders). They remain on the chart until the price interacts with them.
Sweep vs. Breakout: Not all breaches are equal. We specifically look for "Sweeps" (Liquidity Grabs) — where price pierces a level but closes back inside. This is a classic sign of absorption and potential reversal, distinct from a structural breakout.
2. Key Features
Visualized Order Blocks: Automatically draws potential support (Green Dotted) and resistance (Red Dotted) lines based on fractal points.
Wick Detection: Filters out strong momentum breakouts. Signals are only generated when a specific "Wick Ratio" is met, indicating a rejection.
Clean Charts: Features a "Garbage Collection" mechanism. Once a level is swept, the line is removed, and a signal dot is placed. Old, untouched levels are automatically cycled out to prevent chart clutter.
3. How to Use
The Lines (Context):
Red Dotted Line: Buy-side Liquidity (Resistance). Expect potential shorts or breakouts here.
Green Dotted Line: Sell-side Liquidity (Support). Expect potential longs or breakdowns here.
The Signals (Action):
Red Dot (Bearish Sweep): Price spiked above a Resistance Line but closed below it. This suggests long stops were hunted, and bears are stepping in.
Green Dot (Bullish Sweep): Price spiked below a Support Line but closed above it. This suggests short stops were hunted, and bulls are stepping in.
Configuration:
Structure Length: Adjusts sensitivity. Higher values (e.g., 20-50) find major swing points; lower values (e.g., 5-10) find scalping setups.
Wick Filter %: The minimum size of the wick relative to the breakout. Increase this to filter for only the most dramatic rejections.
4. Developer Notes & Considerations
Why do lines disappear? In this logic, liquidity is treated as "Fuel". Once a level is swept (the stop orders are triggered), the fuel is consumed. Keeping the line would clutter the chart with invalid data.
Why is the dot small? The indicator is designed to be part of a toolchain, not a standalone signal. The minimalist design prevents visual interference with price action or other indicators.
1. 设计思路与核心逻辑
本指标基于 聪明钱概念 (SMC) 与 市场微观结构 原理设计。不同于依赖滞后均线或存在重绘问题的传统分形指标,本脚本专注于捕捉 “客观结构” 与 “流动性猎杀 (Liquidity Grabs)”。
核心设计哲学包含三大支柱:
零重绘 (Zero Repainting): 我们采用了严格的“左侧确认”算法。所有的结构位仅在K线完全收盘 (barstate.isconfirmed) 后才会被记录。这保证了您回测看到的信号与实盘完全一致,杜绝“未来函数”陷阱。
可视化的机构记忆: 市场是有记忆的。本脚本会从有效的波段高低点引出虚线。这些虚线代表了“沉睡的流动性”(止损盘聚集区)。它们会一直延伸,直到价格触碰它们。
区分“猎杀”与“突破”: 并不是所有的破位都是一样的。我们专注于识别“扫损(Sweep)”——即价格刺破了关键位,但收盘价收回了关键位内部。这是典型的吸筹或派发信号,与趋势延续的真突破有本质区别。
2. 主要功能
结构可视化: 自动基于分形点绘制潜在的支撑线(绿色虚线)和阻力线(红色虚线)。
插针检测: 过滤掉强势的实体突破。只有当价格出现明显的“长影线”拒绝行为时,才会触发信号。
图表自清洁: 内置“垃圾回收”机制。一旦某个关键位的流动性被猎杀(触发信号),该线条会被自动删除。过旧且未被触碰的线条也会被自动替换,保持图表整洁。
3. 使用指南
线条 (市场语境):
红色虚线: 买方流动性池(阻力位)。
绿色虚线: 卖方流动性池(支撑位)。
信号点 (交易动作):
红色圆点 (看跌猎杀): 价格刺破了红色阻力线,但收盘价回落到线下方。这暗示多头止损被触发,主力可能正在建立空单。
绿色圆点 (看涨猎杀): 价格刺破了绿色支撑线,但收盘价反弹到线上方。这暗示空头止损被触发,主力可能正在建立多单。
参数设置建议:
Structure Length (结构周期): 调整灵敏度。数值越大(如 20-50)锁定大级别波段;数值越小(如 5-10)适合短线剥头皮。
Wick Filter % (影线过滤): 设置影线占价格波动的最小比例。调大该数值可以只看最剧烈的反转信号。
4. 开发者注记与潜在考量
为什么线条会消失? 在本逻辑中,流动性被视为“燃料”。一旦发生猎杀(止损单成交),该位置的燃料即被消耗。移除线条是为了防止无效数据干扰判断。
为什么圆点设计得很小? 该指标旨在成为您交易工具链的一部分,而非唯一的决策依据。极简设计是为了避免干扰裸K形态或其他指标的观察。
===============================================================
这个脚本(我们称之为 Liq Structure Script)本质上是一个基于价格行为(Price Action)的结构猎杀探测器。
以下是详细的深度对比分析:
1. 如何使用? (实战操作手册)
不要把它当作“红灯停绿灯行”的傻瓜指标。把它当作一个**“战场地图”**。
第一阶段:观察结构 (The Setup)
图表上会自动画出 红色虚线(上方压力)和 绿色虚线(下方支撑)。
解读:告诉自己,“这里埋着很多人的止损单”。不要在这里盲目追涨杀跌。
第二阶段:等待猎杀 (The Trigger)
耐心等待价格冲向这些虚线。
关键动作:价格刺破虚线,然后迅速收回。
信号确认:虚线消失,留下一个 红点(顶部猎杀)或 绿点(底部猎杀)。
第三阶段:进场逻辑 (The Execution)
做空逻辑:出现红点 + K线留长上影线 → 说明多头试图突破失败,被主力“倒了一盆冷水”。此时可尝试做空,止损设在刚刚那个最高点上方一点点。
做多逻辑:出现绿点 + K线留长下影线 → 说明空头试图砸盘失败,被主力接住了。
传统爆量是“燃料”,Liq 脚本是“引爆点”。没有引爆点的爆量可能是空转;没有爆量的引爆点可能是假摔。Liq 脚本是一个免费、轻量级、基于K线逻辑的替代品。它不需要你买昂贵的数据服务,它利用的是“图表形态学”中的流动性共识。
结论:如何定位这个工具?
这个脚本不是“预测未来的水晶球”,而是一个**“高胜率区域提示器”**。
用它来找位置(哪里有陷阱?)。
用成交量来做确认(是不是真的有主力介入?)。
用宏观逻辑来定方向(现在该做多还是做空?)。
它是你交易工具链中负责**“微观入场时机(Timing)”**的那一环。
Bull Flag & Flat Top Breakout DetectorBull Flag & Flat Top Detector - Quick Reference Guide
Pattern Overview
🚩 Bull Flag
╱╲
╱ ╲ ← Pullback (2-5 red candles)
╱ ╲
╱ ╲____
╱ ╲
│ │
│ THE POLE │ ← Strong upward move (3+ green candles)
│ │
└──────────────┘
What to look for:
Strong initial move (the "pole") - 3+ green candles, 3%+ move
Brief pullback - 2-5 candles, less than 50% retracement
Pullback should "drift" lower, not crash
Entry on first candle to make new high after pullback
📊 Flat Top Breakout
════════════════ ← Resistance (multiple touches)
↑ ↑ ↑
╱╲ ╱╲ ╱╲
╱ ╲╱ ╲╱ ╲ ← Consolidation
╱ ╲
╱ ╲
What to look for:
Multiple touches of same resistance level (2+)
Tight consolidation range
Each failed breakout builds pressure
Entry on convincing break above resistance with volume
Signal Types
SignalShapeColorMeaningBull Flag Breakout▲ TriangleLimeEntry signal - go longFlat Top Breakout◆ DiamondAquaEntry signal - go longBear Flag Breakout▼ TriangleRedShort entry (if enabled)Pattern Forming🚩 FlagFaded GreenBull flag developingPattern Forming■ SquareFaded BlueFlat top developing
Level Lines Explained
LineColorStyleMeaningEntryLimeSolidBreakout trigger priceStop LossRedDashedExit if price falls hereTarget 1AquaDottedFirst profit target (2R)Target 2YellowDottedSecond profit target (3R)
Info Table Reference
FieldWhat It ShowsBull FlagScanning / Forming 🚩 / Breakout ✓Flat TopScanning / Forming 📊 / Breakout ✓PullbackCandle count + retracement %Rel VolumeCurrent bar vs averageEMA 20Above ✓ or Below ✗VWAPAbove ✓ or Below ✗Green StreakConsecutive green candles (pole)ResistanceTouch count for flat top
Trading Checklist
Before Entry ✅
Pattern status shows "FORMING" or "BREAKOUT"
Price above EMA (table shows ✓)
Price above VWAP (table shows ✓)
Relative volume 1.5x+ (ideally 2x+)
Stock is in play (up 5%+ on day, has catalyst)
Market direction supportive (not fighting trend)
Entry Execution
Wait for breakout candle to form
Confirm volume spike on breakout
Enter as close to entry line as possible
Set stop loss at red dashed line
Know your target levels
Trade Management
If no immediate follow-through → consider exit ("breakout or bailout")
Take 50% off at Target 1
Move stop to breakeven
Let remainder run toward Target 2
Exit fully if price returns below entry
Bull Flag Quality Checklist
Pole Quality:
FactorIdealAcceptableAvoidGreen candles5+3-4Less than 3Move size10%+3-10%Less than 3%VolumeIncreasingSteadyDecliningCandle bodiesLargeMediumSmall/doji
Pullback Quality:
FactorIdealAcceptableAvoidCandle count2-34-56+RetracementUnder 38%38-50%Over 50%VolumeDecliningSteadyIncreasingCharacterOrderly driftChoppySharp drop
Flat Top Quality Checklist
FactorGood SetupWeak SetupTouches3+ at same levelOnly 2, widely spacedToleranceVery tight (0.2%)Loose (1%+)Duration5-15 barsToo short or too longVolumeDrying upErraticPrior trendUpSideways/down
Common Mistakes to Avoid
❌ Entering too early
Wait for actual breakout, not anticipation
"Forming" ≠ "Breakout"
❌ Ignoring volume
No volume = likely false breakout
Require 1.5x+ relative volume minimum
❌ Fighting the trend
Check EMA and VWAP status
Both should be ✓ for high probability
❌ Wide stops
Stop should be below pullback low
If stop is too wide, skip the trade
❌ Holding losers
"Breakout or bailout" - if it doesn't work, exit
Failed breakouts often reverse hard
❌ Chasing extended moves
If you missed entry, wait for next pattern
Don't chase 5+ candles after breakout
Risk Management Rules
Position Sizing
Risk Amount = Account × Risk % (typically 1-2%)
Position Size = Risk Amount ÷ (Entry - Stop)
Example:
Account: $25,000
Risk: 1% = $250
Entry: $5.00
Stop: $4.70
Risk per share: $0.30
Position Size: $250 ÷ $0.30 = 833 shares
Risk-Reward Targets
TargetR MultipleExample (risk $0.30)Target 12:1+$0.60 ($5.60)Target 23:1+$0.90 ($5.90)
Timeframe Guide
TimeframeProsConsBest For1-minMore patterns, precise entryNoisy, false signalsScalping5-minGood balance, cleaner patternsFewer signalsDay trading15-minHigh quality patternsMiss fast movesSwing entries
Settings Quick Reference
Default Settings (Balanced)
Pole: 3 candles, 3% move
Pullback: 2-5 candles, 50% max retrace
Volume: 1.5x required
Filters: EMA + VWAP ON
Aggressive Settings
Pole: 2 candles, 2% move
Pullback: 2-6 candles, 60% max retrace
Volume: 1.2x required
Filters: VWAP OFF
Conservative Settings
Pole: 4 candles, 5% move
Pullback: 2-4 candles, 40% max retrace
Volume: 2.0x required
Filters: Both ON
Alert Setup
Recommended Alerts
"Bull Flag Forming"
Get early warning as pattern develops
Prepare your position size and levels
"Bull Flag Breakout"
Primary entry alert
React quickly when triggered
"Any Bullish Breakout"
Catch both bull flags and flat tops
Good for watchlist scanning
Alert Setup Steps
Right-click chart → Add Alert
Condition: Select "Bull Flag & Flat Top Breakout Detector"
Choose alert type from dropdown
Set expiration and notification method
Troubleshooting
Q: Patterns not detecting?
Lower the Min Pole Move % setting
Reduce Min Pole Candles requirement
Check that price is in acceptable range
Q: Too many false signals?
Increase volume multiplier to 2.0x
Enable both EMA and VWAP filters
Increase Min Pole Move %
Q: Levels not showing?
Enable "Show Entry Line", "Show Stop Loss", "Show Targets"
Check "Max Patterns to Display" setting
Q: Info table not visible?
Enable "Show Info Table" in settings
Try different table position
Pattern Combinations
Best Setups (A+ Quality)
Bull flag on a gap day (Gap & Go → Bull Flag)
Flat top at pre-market high resistance
Pattern forming above VWAP with 5x+ volume
Avoid These
Bull flag below VWAP
Flat top in downtrending stock
Low volume patterns
Patterns late in the day (after 2pm)
Daily Routine
Pre-Market (7-9am)
Build watchlist of gappers (5%+, high volume)
Apply indicator to top 3-5 candidates
Note pre-market levels
Market Open (9:30-10:30am)
Watch for "FORMING" status on watchlist
Prepare entries as patterns develop
Execute on breakout signals
Manage trades according to plan
Midday (10:30am-2pm)
Look for second-wave patterns
Be more selective (less momentum)
Consider tighter stops
Close (2-4pm)
Generally avoid new patterns
Manage existing positions
Review day's trades
Rotation SentinelROTATION SENTINEL v1.1 — OVERVIEW
Rotation Sentinel is a macro rotation engine that tracks 10 institutional-grade dominance, liquidity, and trend signals to identify when capital is flowing into altcoins.
Each row outputs Green / Yellow / Red, and the system produces a 0–10 Rotation Score plus a final regime:
🔴 NO ROTATION (0–4)
🟡 ROTATION STARTING (5–6)
🟢 ALTSEASON (7–10)
Use on Daily timeframe for best accuracy.
KEY SIGNALS
1️⃣ BTC.D ex-stables
Shows true BTC vs alt strength.
🟢 Falling = capital rotating into alts.
🔴 Rising = alts bleeding. (Master switch.)
2️⃣ OTHERS.D
Broad altcoin dominance.
🟢 Rising = early alt strength.
🔴 Falling = weak participation.
3️⃣ ETH/BTC
Rotation ignition.
🟢 ETH outperforming = rotation can start.
🔴 ETH lagging = altseason impossible.
4️⃣ STABLE.C.D
Crypto “fear index.”
🟢 Falling = risk-on environment.
🔴 Rising = capital hiding in stables.
5️⃣ USDT.D
Real-time risk positioning.
🟢 Falling = capital deploying.
🔴 Rising = defensive.
6️⃣ TOTAL3 (HTF Trend)
Structural alt market health.
🟢 Above SMA + rising = bullish structure.
🔴 Below SMA + falling = systematic weakness.
7️⃣ TOTAL3 / TOTAL2
Depth of rotation.
🟢 Mid/small caps outperforming = deep rotation.
🔴 Only large caps moving = shallow cycle.
8️⃣ Risk Ratio (OTHERS.D / STABLE.C.D)
Pure risk appetite.
🟢 Alts gaining on stables = risk-on.
9️⃣ OTHERS/BTC
Alt value vs BTC.
🟢 Rising = alts outperforming BTC.
🔟 Liquidation Heatmap (Manual)
Update from Hyblock/Coinalyze.
🟢 Liquidity above = upside easier.
ALTSEASON TRIGGER
Fires only when all 6 core conditions turn GREEN:
BTC.D ex-stables
OTHERS.D
ETH/BTC
STABLE.C.D
TOTAL3 structure
Rotation Score ≥ threshold (default 7)
BEST PRACTICES
Use Daily timeframe (macro rotation, not intraday noise)
Score < 5 → defensive / selective trades
Score 5–6 → early rotation window
Score ≥ 7 → confirmed altseason regime
Let alerts notify you; no need to manually monitor
INCLUDED ALERTS
🚨 ALTSEASON TRIGGERED
⚠️ Rotation Score Crossed Threshold
📈 ETH/BTC Rotation Clock Activated
🔥 OTHERS.D Breaking Higher
ATH대비 지정하락률에 도착 시 매수 - 장기홀딩 선물 전략(ATH Drawdown Re-Buy Long Only)본 스크립트는 과거 하락 데이터를 이용하여, 정해진 하락 %가 발생하는 경우 자기 자본의 정해진 %만큼을 진입하게 설계되어진 스트레티지입니다.
레버리지를 사용할 수 있으며 기본적으로 셋팅해둔 값이 내장되어있습니다.(자유롭게 바꿔서 쓰시면 됩니다.) 추가적으로 2번의 진입 외에도 다른 진입 기준, 진입 %를 설정하실 수 있으며 - ChatGPT에게 요청하면 수정해줄 것입니다.
실제 사용용도로는 KillSwitch 기능을 꺼주세요. 바 돋보기 기능을 켜주세요.
ATH Drawdown Re-Buy Long Only 전략 설명
1. 전략 개요
ATH Drawdown Re-Buy Long Only 전략은 자산의 역대 최고가(ATH, All-Time High)를 기준으로 한 하락폭(드로우다운)을 활용하여,
특정 구간마다 단계적으로 롱 포지션을 구축하는 자동 재매수(Long Only) 전략입니다.
본 전략은 다음과 같은 목적을 가지고 설계되었습니다.
급격한 조정 구간에서 체계적인 분할 매수 및 레버리지 활용
ATH를 기준으로 한 명확한 진입 규칙 제공
실시간으로
평단가
레버리지
청산가 추정
계좌 MDD
수익률
등을 시각적으로 제공하여 리스크와 포지션 상태를 직관적으로 확인할 수 있도록 지원
※ 본 전략은 교육·연구·백테스트 용도로 제공되며,
어떠한 형태의 투자 권유 또는 수익을 보장하지 않습니다.
2. 전략의 핵심 개념
2-1. ATH(역대 최고가) 기준 드로우다운
전략은 차트 상에서 항상 가장 높은 고가(High)를 ATH로 기록합니다.
새로운 고점이 형성될 때마다 ATH를 갱신하고, 해당 ATH를 기준으로 다음을 계산합니다.
현재 바의 저가(Low)가 ATH에서 몇 % 하락했는지
현재 바의 종가(Close)가 ATH에서 몇 % 하락했는지
그리고 사전에 설정한 두 개의 드로우다운 구간에서 매수를 수행합니다.
1차 진입 구간: ATH 대비 X% 하락 시
2차 진입 구간: ATH 대비 Y% 하락 시
각 구간은 ATH가 새로 갱신될 때마다 한 번씩만 작동하며,
새로운 ATH가 생성되면 다시 “1차 / 2차 진입 가능 상태”로 초기화됩니다.
2-2. 첫 포지션 100% / 300% 특수 규칙
이 전략의 중요한 특징은 **“첫 포지션 진입 시의 예외 규칙”**입니다.
전략이 현재 어떠한 포지션도 들고 있지 않은 상태에서
최초로 롱 포지션을 진입하는 시점(첫 포지션)에 대해:
기본적으로는 **자산의 100%**를 기준으로 포지션을 구축하지만,
만약 그 순간의 가격이 ATH 대비 설정값 이상(예: 약 –72.5% 이상 하락한 상황) 이라면
→ 자산의 300% 규모로 첫 포지션을 진입하도록 설계되어 있습니다.
이 규칙은 다음과 같이 동작합니다.
첫 진입이 1차 드로우다운 구간에서 발생하든,
첫 진입이 2차 드로우다운 구간에서 발생하든,
현재 하락폭이 설정된 기준 이상(예: –72.5% 이상) 이라면
→ “이 정도 하락이면 첫 진입부터 더 공격적으로 들어간다”는 의미로 300% 규모로 진입
그 이하의 하락폭이라면
→ 첫 진입은 100% 규모로 제한
즉, 전략은 다음 두 가지 모드로 동작합니다.
일반적인 상황의 첫 진입: 자산의 100%
심각한 드로우다운 구간에서의 첫 진입: 자산의 300%
이 특수 규칙은 깊은 하락에서는 공격적으로, 평소에는 상대적으로 보수적으로 진입하도록 설계된 것입니다.
3. 전략 동작 구조
3-1. 매수 조건
차트 상 High 기준으로 ATH를 추적합니다.
각 바마다 해당 ATH에서의 하락률을 계산합니다.
사용자가 설정한 두 개의 드로우다운 구간(예시):
1차 구간: 예를 들어 ATH – 50%
2차 구간: 예를 들어 ATH – 72.5%
각 구간에 대해 다음과 같은 조건을 확인합니다.
“이번 ATH 구간에서 아직 해당 구간 매수를 한 적이 없는 상태”이고,
현재 바의 저가(Low)가 해당 구간 가격 이하를 찍는 순간
→ 해당 바에서 매수 조건 충족으로 간주
실제 주문은:
해당 구간 가격에 맞춰 롱 포지션 진입(리밋/시장가 기반 시뮬레이션) 으로 처리됩니다.
3-2. ATH 갱신과 진입 기회 리셋
차트 상에서 새로운 고점(High)이 기존 ATH를 넘어서는 순간,
ATH가 갱신되고,
1차 / 2차 진입 여부를 나타내는 내부 플래그가 초기화됩니다.
이를 통해, 시장이 새로운 고점을 돌파해 나갈 때마다,
해당 구간에서 다시 한 번씩 1차·2차 드로우다운 진입 기회를 갖게 됩니다.
4. 포지션 사이징 및 레버리지
4-1. 계좌 자산(Equity) 기준 포지션 크기 결정
전략은 현재 계좌 자산을 다음과 같이 정의하여 사용합니다.
현재 자산 = 초기 자본 + 실현 손익 + 미실현 손익
각 진입 구간에서의 포지션 가치는 다음과 같이 결정됩니다.
1차 진입 구간:
“자산의 몇 %를 사용할지”를 설정값으로 입력
설정된 퍼센트를 계좌 자산에 곱한 뒤,
다시 전략 내 레버리지 배수(Leverage) 를 곱하여 실제 포지션 가치를 계산
2차 진입 구간:
동일한 방식으로, 독립된 퍼센트 설정값을 사용
즉, 포지션 가치는 다음과 같이 계산됩니다.
포지션 가치 = 현재 자산 × (해당 구간 설정 % / 100) × 레버리지 배수
그리고 이를 해당 구간의 진입 가격으로 나누어 실제 수량(토큰 단위) 를 산출합니다.
4-2. 첫 포지션의 예외 처리 (100% / 300%)
첫 포지션에 대해서는 위의 일반적인 퍼센트 설정 대신,
다음과 같은 고정 비율이 사용됩니다.
기본: 자산의 100% 규모로 첫 포지션 진입
단, 진입 시점의 ATH 대비 하락률이 설정값 이상(예: –72.5% 이상) 일 경우
→ 자산의 300% 규모로 첫 포지션 진입
이때 역시 다음 공식을 사용합니다.
포지션 가치 = 현재 자산 × (100% 또는 300%) × 레버리지
그리고 이를 가격으로 나누어 실제 진입 수량을 계산합니다.
이 규칙은:
첫 진입이 1차 구간이든 2차 구간이든 동일하게 적용되며,
“충분히 깊은 하락 구간에서는 첫 진입부터 더 크게,
평소에는 비교적 보수적으로” 라는 운용 철학을 반영합니다.
4-3. 실레버리지(Real Leverage)의 추적
전략은 각 바 단위로 다음을 추적합니다.
바가 시작할 때의 기존 포지션 크기
해당 바에서 새로 진입한 수량
이를 바탕으로, 진입이 발생한 시점에 다음을 계산합니다.
실제 레버리지 = (포지션 가치 / 현재 자산)
그리고 차트 상에 예를 들어:
Lev 2.53x 와 같은 형식의 레이블로 표시합니다.
이를 통해, 매수 시점마다 실제 계좌 레버리지가 어느 정도였는지를 직관적으로 확인할 수 있습니다.
5. 시각화 및 모니터링 요소
5-1. 차트 상 시각 요소
전략은 차트 위에 다음과 같은 정보를 직접 표시합니다.
ATH 라인
High 기준으로 계산된 역대 최고가를 주황색 선으로 표시
평단가(평균 진입가) 라인
현재 보유 포지션이 있을 때,
해당 포지션의 평균 진입가를 노란색 선으로 표시
추정 청산가(고정형 청산가) 라인
포지션 수량이 변화하는 시점을 감지하여,
당시의 평단가와 실제 레버리지를 이용해 근사적인 청산가를 계산
이를 빨간색 선으로 차트에 고정 표시
포지션이 없거나 레버리지가 1배 이하인 경우에는 청산가 라인을 제거
매수 마커 및 레이블
1차/2차 매수 조건이 충족될 때마다 해당 지점에 매수 마커를 표시
"Buy XX% @ 가격", "Lev XXx" 형태의 라벨로
진입 비율과 당시 레버리지를 함께 시각화
레이블의 위치는 설정에서 선택 가능:
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
5-2. 우측 상단 정보 테이블
차트 우측 상단에는 현재 계좌·포지션 상태를 요약한 정보 테이블이 표시됩니다.
대표적으로 다음 항목들이 포함됩니다.
Pos Qty (Token)
현재 보유 중인 포지션 수량(토큰 기준, 절대값 기준)
Pos Value (USDT)
현재 포지션의 시장 가치 (수량 × 현재 가격)
Leverage (Now)
현재 실레버리지 (포지션 가치 / 현재 자산)
DD from ATH (%)
현재 가격 기준, 최근 ATH에서의 하락률(%)
Avg Entry
현재 포지션의 평균 진입 가격
PnL (%)
현재 포지션 기준 미실현 손익률(%)
Max DD (Equity %)
전략 전체 기간 동안 기록된 계좌 기준 최대 손실(MDD, Max Drawdown)
Last Entry Price
가장 최근에 포지션을 추가로 진입한 직후의 평균 진입 가격
Last Entry Lev
위 “Last Entry Price” 시점에서의 실레버리지
Liq Price (Fixed)
위에서 설명한 고정형 추정 청산가
Return from Start (%)
전략 시작 시점(초기 자본) 대비 현재 계좌 자산의 총 수익률(%)
이 테이블을 통해 사용자는:
현재 계좌와 포지션의 상태
리스크 수준
누적 성과
를 직관적으로 파악할 수 있습니다.
6. 시간 필터 및 라벨 옵션
6-1. 전략 동작 기간 설정
전략은 옵션으로 특정 기간에만 전략을 동작시키는 시간 필터를 제공합니다.
“Use Date Range” 옵션을 활성화하면:
시작 시각과 종료 시각을 지정하여
해당 구간에 한해서만 매매가 발생하도록 제한
옵션을 비활성화하면:
전략은 전체 차트 구간에서 자유롭게 동작
6-2. 진입 라벨 위치 설정
사용자는 매수/레버리지 라벨의 위치를 선택할 수 있습니다.
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
이를 통해 개인 취향 및 차트 가독성에 맞추어
시각화 방식을 유연하게 조정할 수 있습니다.
7. 활용 대상 및 사용 예시
본 전략은 다음과 같은 목적에 적합합니다.
현물 또는 선물 롱 포지션 기준 장기·스윙 관점 추매 전략 백테스트
“고점 대비 하락률”을 기준으로 한 규칙 기반 운용 아이디어 검증
레버리지 사용 시
계좌 레버리지·청산가·MDD를 동시에 모니터링하고자 하는 경우
특정 자산에 대해
“새로운 고점이 형성될 때마다
일정한 규칙으로 깊은 조정 구간에서만 분할 진입하고자 할 때”
실거래에 그대로 적용하기보다는,
전략 아이디어 검증 및 리스크 프로파일 분석,
자신의 성향에 맞는 파라미터 탐색 용도로 사용하는 것을 권장합니다.
8. 한계 및 유의사항
백테스트 결과는 미래 성과를 보장하지 않습니다.
과거 데이터에 기반한 시뮬레이션일 뿐이며,
실제 시장에서는
유동성
슬리피지
수수료 체계
강제청산 규칙
등 다양한 변수가 존재합니다.
청산가는 단순화된 공식에 따른 추정치입니다.
거래소별 실제 청산 규칙, 유지 증거금, 수수료, 펀딩비 등은
본 전략의 계산과 다를 수 있으며,
청산가 추정 라인은 참고용 지표일 뿐입니다.
레버리지 및 진입 비율 설정에 따라 손실 폭이 매우 커질 수 있습니다.
특히 **“첫 포지션 300% 진입”**과 같이 매우 공격적인 설정은
시장 급락 시 계좌 손실과 청산 리스크를 크게 증가시킬 수 있으므로
신중한 검토가 필요합니다.
실거래 연동 시에는 별도의 리스크 관리가 필수입니다.
개별 손절 기준
포지션 상한선
전체 포트폴리오 내 비중 관리 등
본 전략 외부에서 추가적인 안전장치가 필요합니다.
9. 결론
ATH Drawdown Re-Buy Long Only 전략은 단순한 “저가 매수”를 넘어서,
ATH 기준으로 드로우다운을 구조적으로 활용하고,
첫 포지션에 대한 **특수 규칙(100% / 300%)**을 적용하며,
레버리지·청산가·MDD·수익률을 통합적으로 시각화함으로써,
하락 구간에서의 규칙 기반 롱 포지션 구축과
리스크 모니터링을 동시에 지원하는 전략입니다.
사용자는 본 전략을 통해:
자신의 시장 관점과 리스크 허용 범위에 맞는
드로우다운 구간
진입 비율
레버리지 설정
다양한 시나리오에 대한 백테스트와 분석
을 수행할 수 있습니다.
다시 한 번 강조하지만,
본 전략은 연구·학습·백테스트를 위한 도구이며,
실제 투자 판단과 책임은 전적으로 사용자 본인에게 있습니다.
/ENG Version.
This script is designed to use historical drawdown data and automatically enter positions when a predefined percentage drop from the all-time high occurs, using a predefined percentage of your account equity.
You can use leverage, and default parameter values are provided out of the box (you can freely change them to suit your style).
In addition to the two main entry levels, you can add more entry conditions and custom entry percentages – just ask ChatGPT to modify the script.
For actual/live usage, please turn OFF the KillSwitch function and turn ON the Bar Magnifier feature.
ATH Drawdown Re-Buy Long Only Strategy
1. Strategy Overview
The ATH Drawdown Re-Buy Long Only strategy is an automatic re-buy (Long Only) system that builds long positions step-by-step at specific drawdown levels, based on the asset’s all-time high (ATH) and its subsequent drawdown.
This strategy is designed with the following goals:
Systematic scaled buying and leverage usage during sharp correction periods
Clear, rule-based entry logic using drawdowns from ATH
Real-time visualization of:
Average entry price
Leverage
Estimated liquidation price
Account MDD (Max Drawdown)
Return / performance
This allows traders to intuitively monitor both risk and position status.
※ This strategy is provided for educational, research, and backtesting purposes only.
It does not constitute investment advice and does not guarantee any profits.
2. Core Concepts
2-1. Drawdown from ATH (All-Time High)
On the chart, the strategy always tracks the highest high as the ATH.
Whenever a new high is made, ATH is updated, and based on that ATH the following are calculated:
How many percent the current bar’s Low is below the ATH
How many percent the current bar’s Close is below the ATH
Using these, the strategy executes buys at two predefined drawdown zones:
1st entry zone: When price drops X% from ATH
2nd entry zone: When price drops Y% from ATH
Each zone is allowed to trigger only once per ATH cycle.
When a new ATH is created, the “1st / 2nd entry possible” flags are reset, and new opportunities open up for that ATH leg.
2-2. Special Rule for the First Position (100% / 300%)
A key feature of this strategy is the special rule for the very first position.
When the strategy currently holds no position and is about to open the first long position:
Under normal conditions, it builds the position using 100% of account equity.
However, if at that moment the price has dropped by at least a predefined threshold from ATH (e.g. around –72.5% or more),
→ the strategy will open the first position using 300% of account equity.
This rule works as follows:
Whether the first entry happens at the 1st drawdown zone or at the 2nd drawdown zone,
If the current drawdown from ATH is at or below the threshold (e.g. –72.5% or worse),
→ the strategy interprets this as “a sufficiently deep crash” and opens the initial position with 300% of equity.
If the drawdown is less severe than the threshold,
→ the first entry is capped at 100% of equity.
So the strategy has two modes for the first entry:
Normal market conditions: 100% of equity
Deep drawdown conditions: 300% of equity
This special rule is intended to be aggressive in extremely deep crashes while staying more conservative in normal corrections.
3. Strategy Logic & Execution
3-1. Entry Conditions
The strategy tracks the ATH using the High price.
For each bar, it calculates the drawdown from ATH.
The user defines two drawdown zones, for example:
1st zone: ATH – 50%
2nd zone: ATH – 72.5%
For each zone, the strategy checks:
If no buy has been executed yet for that zone in the current ATH leg, and
If the current bar’s Low touches or falls below that zone’s price level,
→ That bar is considered to have triggered a buy condition.
Order simulation:
The strategy simulates entering a long position at that zone’s price level
(using a limit/market-like approximation for backtesting).
3-2. ATH Reset & Entry Opportunity Reset
When a new High goes above the previous ATH:
The ATH is updated to this new high.
Internal flags that track whether the 1st and 2nd entries have been used are reset.
This means:
Each time the market makes a new ATH,
The strategy once again has a fresh opportunity to execute 1st and 2nd drawdown entries for that new ATH leg.
4. Position Sizing & Leverage
4-1. Position Size Based on Account Equity
The strategy defines current equity as:
Current Equity = Initial Capital + Realized PnL + Unrealized PnL
For each entry zone, the position value is calculated as follows:
The user inputs:
“What % of equity to use at this zone”
The strategy:
Multiplies current equity by that percentage
Then multiplies by the strategy’s leverage factor
Thus:
Position Value = Current Equity × (Zone % / 100) × Leverage
Finally, this position value is divided by the entry price to determine the actual position size in tokens.
4-2. Exception for the First Position (100% / 300%)
For the very first position (when there is no open position),
the strategy does not use the zone % parameters. Instead, it uses fixed ratios:
Default: Enter the first position with 100% of equity.
If the drawdown from ATH at that moment is greater than or equal to a predefined threshold (e.g. –72.5% or more)
→ Enter the first position with 300% of equity.
The position value is computed as:
Position Value = Current Equity × (100% or 300%) × Leverage
Then it is divided by the entry price to obtain the token quantity.
This rule:
Applies regardless of whether the first entry occurs at the 1st zone or 2nd zone.
Embeds the philosophy:
“In very deep crashes, go much larger on the first entry; otherwise, stay more conservative.”
4-3. Tracking Real Leverage
On each bar, the strategy tracks:
The existing position size at the start of the bar
The newly added size (if any) on that bar
When a new entry occurs, it calculates the real leverage at that moment:
Real Leverage = (Position Value / Current Equity)
This is then displayed on the chart as a label, for example:
Lev 2.53x
This makes it easy to see the actual leverage level at each entry point.
5. Visualization & Monitoring
5-1. On-Chart Visual Elements
The strategy plots the following directly on the chart:
ATH Line
The all-time high (based on High) is plotted as an orange line.
Average Entry Price Line
When a position is open, the average entry price of that position is plotted as a yellow line.
Estimated Liquidation Price (Fixed) Line
The strategy detects when the position size changes.
At each size change, it uses the current average entry price and real leverage to compute an approximate liquidation price.
This “fixed liquidation price” is then plotted as a red line on the chart.
If there is no position, or if leverage is 1x or lower, the liquidation line is removed.
Entry Markers & Labels
When 1st/2nd entry conditions are met, the strategy:
Marks the entry point on the chart.
Displays labels such as "Buy XX% @ Price" and "Lev XXx",
showing both entry percentage and real leverage at that time.
The label placement is configurable:
Below Bar
Above Bar
At Price
5-2. Information Table (Top-Right Panel)
In the top-right corner of the chart, the strategy displays a summary table of the current account and position status. It typically includes:
Pos Qty (Token)
Absolute size of the current position (in tokens)
Pos Value (USDT)
Market value of the current position (qty × current price)
Leverage (Now)
Current real leverage (position value / current equity)
DD from ATH (%)
Current drawdown (%) from the latest ATH, based on current price
Avg Entry
Average entry price of the current position
PnL (%)
Unrealized profit/loss (%) of the current position
Max DD (Equity %)
The maximum equity drawdown (MDD) recorded over the entire backtest period
Last Entry Price
Average entry price immediately after the most recent add-on entry
Last Entry Lev
Real leverage at the time of the most recent entry
Liq Price (Fixed)
The fixed estimated liquidation price described above
Return from Start (%)
Total return (%) of equity compared to the initial capital
Through this table, users can quickly grasp:
Current account and position status
Current risk level
Cumulative performance
6. Time Filters & Label Options
6-1. Strategy Date Range Filter
The strategy provides an option to restrict trading to a specific time range.
When “Use Date Range” is enabled:
You can specify start and end timestamps.
The strategy will only execute trades within that range.
When this option is disabled:
The strategy operates over the entire chart history.
6-2. Entry Label Placement
Users can customize where entry/leverage labels are drawn:
Below Bar (Below Bar)
Above Bar (Above Bar)
At the actual price level (At Price)
This allows you to adjust visualization according to personal preference and chart readability.
7. Use Cases & Applications
This strategy is suitable for the following purposes:
Long-term / swing-style re-buy strategies for spot or futures long positions
Testing rule-based strategies that rely on “drawdown from ATH” as a main signal
Monitoring account leverage, liquidation price, and MDD when using leverage
Handling situations where, for a given asset:
“Every time a new ATH is formed,
you want to wait for deep corrections and enter only at specific drawdown zones”
It is generally recommended to use this strategy not as a direct plug-and-play live system, but as a tool for:
Strategy idea validation
Risk profile analysis
Parameter exploration to match your personal risk tolerance and style
8. Limitations & Warnings
Backtest results do not guarantee future performance.
They are based on historical data only.
In live markets, additional factors exist:
Liquidity
Slippage
Fee structures
Exchange-specific liquidation rules
Funding fees, etc.
The liquidation price is only an approximate estimate, derived from a simplified formula.
Actual liquidation rules, maintenance margin requirements, fees, and other details differ by exchange.
The liquidation line should be treated as a reference indicator, not an exact guarantee.
Depending on the configured leverage and entry percentages, losses can be very large.
In particular, extremely aggressive settings such as “first position 300% of equity” can greatly increase the risk of large account drawdowns and liquidation during sharp market crashes.
Use such settings with extreme caution.
For live trading, additional risk management is essential:
Your own stop-loss rules
Maximum position size limits
Portfolio-level exposure controls
And other external safety mechanisms beyond this strategy
9. Conclusion
The ATH Drawdown Re-Buy Long Only strategy goes beyond simple “buy the dip” logic. It:
Systematically utilizes drawdowns from ATH as a structural signal
Applies a special first-position rule (100% / 300%)
Integrates visualization of leverage, liquidation price, MDD, and returns
All of this supports rule-based long position building in drawdown phases and comprehensive risk monitoring.
With this strategy, users can:
Explore different:
Drawdown zones
Entry percentages
Leverage levels
Run various backtests and scenario analyses
Better understand the risk/return profile that fits their own market view and risk tolerance
Once again, this strategy is intended for research, learning, and backtesting only.
All real trading decisions and their consequences are solely the responsibility of the user.
ATR Volatility AlertsOverview:
This is a dynamic alert tool based on the Average True Range (ATR), designed to help traders detect sudden price movements that exceed normal volatility levels. Whether you are trading breakouts or monitoring for abnormal spikes, this indicator visualizes these events on the chart and triggers system alerts when the price move exceeds your specified ATR multiplier.
Key Features:
Fully Customizable ATR Range:
You can adjust the ATR Length (Default: 14) and the Multiplier (Default: 1.5x).
Tip: Increase the multiplier (e.g., to 2.0 or 3.0) to catch only extreme volatility, or lower it for scalping smaller moves.
Visual Chart Signals:
Visual markers appear instantly when a bar's movement exceeds the ATR threshold.
Green Triangle: Indicates an Upward Spike.
Red Triangle: Indicates a Downward Spike.
Flexible System Alerts:
Designed to integrate seamlessly with TradingView's alert system. You can choose from three specific alert directions based on your strategy:
1.Price Spike Up: Triggers only on sharp upward moves.
2.Price Spike Down: Triggers only on sharp downward moves.
3.Bidirectional Volatility Alert: Triggers on BOTH huge pumps and dumps.
How to Set Alerts:
Click the "Create Alert" button in TradingView.
Select ATR Volatility Alerts in the "Condition" dropdown.
Choose the specific logic you need:
· Select Price Spike Up for bullish monitoring.
· Select Price Spike Down for bearish monitoring.
· Select Bidirectional Volatility Alert to watch for any volatility expansion.
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent 🎭
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent ⚡
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2σ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trend—enters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent 💧
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR)
Signal Logic: Breakout anticipation—enters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent 📊
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ε)% of the time
Explores randomly ε% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal → outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (▲): Long signal confirmed
Red triangle (▼): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with ► marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (█████ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5× ATR)
Take-profit 1 (2.0× ATR)
Take-profit 2 (3.5× ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models)
✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint
⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Checklist Discrezionale USdCHf 2025 Cesar Italiano📘 Indicator Description: Discretionary Checklist with Weighted Scoring and Visual Validation
This advanced Pine Script indicator is built for discretionary traders who want to structure their decision-making without sacrificing flexibility. It provides a customizable checklist that evaluates multiple technical, contextual, and macroeconomic criteria—each with its own weight in the overall score.
🔧 Key Features:
- On-screen visual checklist, with items triggered manually or by automated conditions
- Weighted scoring system, allowing you to prioritize high-impact criteria like market structure, confluence, or macro context
- Setup validation logic: displays a confidence bar or traffic light based on total score
- Optional integration with news zones, sentiment indicators, and risk management modules
- Conditional activation: can trigger alerts or unlock other tools only when the setup meets a minimum quality threshold
🧠 Ideal for:
- Traders who blend technical analysis, macro context, and discretionary judgment
- Prop firm evaluations or capital scaling workflows
- Strategies that require visual control, partial automation, and structured decision-making
Italian
Checklist Discrecional UsdChF 2025 PA📘 Indicator Description: Discretionary Checklist with Weighted Scoring and Visual Validation
This advanced Pine Script indicator is built for discretionary traders who want to structure their decision-making without sacrificing flexibility. It provides a customizable checklist that evaluates multiple technical, contextual, and macroeconomic criteria—each with its own weight in the overall score.
🔧 Key Features:
- On-screen visual checklist, with items triggered manually or by automated conditions
- Weighted scoring system, allowing you to prioritize high-impact criteria like market structure, confluence, or macro context
- Setup validation logic: displays a confidence bar or traffic light based on total score
- Optional integration with news zones, sentiment indicators, and risk management modules
- Conditional activation: can trigger alerts or unlock other tools only when the setup meets a minimum quality threshold
🧠 Ideal for:
- Traders who blend technical analysis, macro context, and discretionary judgment
- Prop firm evaluations or capital scaling workflows
- Strategies that require visual control, partial automation, and structured decision-making
Market Structure Trailing Stop MTF [Inspired by LuxAlgo]# Market Structure Trailing Stop MTF
**OPEN-SOURCE SCRIPT**
*208k+ views on original · Modified for MTF Support*
This indicator is a direct adaptation of the renowned **Market Structure Trailing Stop** by **LuxAlgo** (original script: [Market Structure Trailing Stop ]()). The core logic remains untouched, providing dynamic trailing stops based on market structure breaks (CHoCH/BOS). The **only modification** is the addition of **Multi-Timeframe (MTF) support**, allowing users to apply the trailing stops and structures from **higher timeframes (HTF)** directly on their current chart. This enhances usability for traders analyzing cross-timeframe confluence without switching charts.
**Special thanks to LuxAlgo** for releasing this powerful open-source tool under CC BY-NC-SA 4.0. Your contributions to the TradingView community have inspired countless traders—grateful for the solid foundation!
## 🔶 How the Script Works: A Deep Dive
At its heart, this indicator detects **market structure shifts** (bullish or bearish breaks of swing highs/lows) and uses them to generate **adaptive trailing stops**. These stops trail the price while protecting profits and acting as dynamic support/resistance levels. The MTF enhancement pulls this logic from user-specified higher timeframes, overlaying HTF structures and stops on the lower timeframe chart for seamless multi-timeframe analysis.
### Core Logic (Unchanged from LuxAlgo's Original)
1. **Pivot Detection**:
- Uses `ta.pivothigh()` and `ta.pivotlow()` with a user-defined lookback (`length`) to identify swing highs (PH) and lows (PL).
- Coordinates (price `y` and bar index/time `x`) are stored in persistent variables (`var`) for tracking recent pivots.
2. **Market Structure Detection**:
- **Bullish Structure (BOS/CHoCH)**: Triggers when `close > recent PH` (break above swing high).
- If `resetOn = 'CHoCH'`, resets only on major shifts (Change of Character); otherwise, on all breaks.
- Sets trend state `os = 1` (bullish) and highlights the break with a horizontal line (dashed for CHoCH, dotted for BOS).
- Initializes trailing stop at the local minimum (lowest low since the pivot) using a backward loop: `btm = math.min(low , btm)`.
- **Bearish Structure**: Triggers when `close < recent PL`, mirroring the bullish logic (`os = -1`, local maximum for stop).
- Structure state `ms` tracks the break type (1 for bull, -1 for bear, 0 neutral), resetting based on user settings.
3. **Trailing Stop Calculation**:
- Tracks **trailing max/min**:
- On new bull structure: Reset `max = close`.
- On new bear: Reset `min = close`.
- Otherwise: `max = math.max(close, max)` / `min = math.min(close, min)`.
- **Stop Adjustment** (the "trailing" magic):
- On fresh structure: `ts = btm` (bull) or `top` (bear).
- In ongoing trend: Increment/decrement by a percentage of the max/min change:
- Bull: `ts += (max - max ) * (incr / 100)`
- Bear: `ts += (min - min ) * (incr / 100)`
- This creates a **ratcheting effect**: Stops move favorably with the trend but never against it, converging toward price at a controlled rate.
- **Visuals**:
- Plots `ts` line colored by trend (teal for bull, red for bear).
- Fills area between `close` and `ts` (orange on retracements).
- Draws structure lines from pivot to break point.
4. **Edge Cases**:
- Variables like `ph_cross`/`pl_cross` prevent multiple triggers on the same pivot.
- Neutral state (`ms = 0`) preserves prior `max/min` until a new structure.
### MTF Enhancement (Our Addition)
- **request.security() Integration**:
- Wraps the entire core function `f()` in a security call for each timeframe (`tf1`, `tf2`).
- Returns HTF values (e.g., `ts1`, `os1`, structure times/prices) to the chart's context.
- Uses `lookahead=barmerge.lookahead_off` for accurate historical repainting-free data.
- Structures are drawn using `xloc.bar_time` to align HTF lines precisely on the LTF chart.
- **Multi-Output Handling**:
- Separate plots/fills/lines for each TF (e.g., `plot_ts1`, `plot_ts2`).
- Colors and toggles per TF to distinguish HTF1 (e.g., teal/red) from HTF2 (e.g., blue/maroon).
- **Benefits**: Spot HTF bias on LTF entries, e.g., enter longs only if both TF1 (1H) and TF2 (4H) show bullish `os=1`.
This keeps the script lightweight—**no repainting, max 500 lines**, and fully compatible with LuxAlgo's original behavior when TFs are set to the chart's timeframe.
## 🔶 SETTINGS
### Core Parameters
- **Pivot Lookback** (`length = 14`): Bars left/right for pivot detection. Higher = smoother structures, fewer signals; lower = more noise.
- **Increment Factor %** (`incr = 100`): Speed of stop convergence (0-∞). 100% = full ratchet (mirrors max/min exactly); <100% = slower trail, reduces whipsaws.
- **Reset Stop On** (`'CHoCH'`): `'CHoCH'` = Reset only on major reversals (dashed lines); `'All'` = Reset on every BOS/CHoCH (tighter stops).
### MTF Support
- **Timeframe 1** (`tf1 = ""`): HTF for first set (e.g., "1H"). Empty = current chart.
- **Timeframe 2** (`tf2 = ""`): Second HTF (e.g., "4H"). Enables dual confluence.
### Display Toggles
- **Show Structures** (`true`): Draws horizontal lines for breaks (per TF colors).
- **Show Trailing Stop TF1/TF2** (`true`): Plots the stop line.
- **Show Fill TF1/TF2** (`true`): Area fill between close and stop.
### Candle Coloring (Optional)
- **Color Candles** (`false`): Enables custom `plotcandle` for body/wick/border.
- **Candle Color Based On TF** (`"None"`): `"TF1"`, `"TF2"`, or none. Colors bull trend green, bear red.
- **Candle Colors**: Separate inputs for bull/bear body, wick, border (e.g., solid green body, transparent wick).
### Alerts
- **Enable MS Break Alerts** (`false`): Notifies on structure breaks (bull/bear per TF) **only on bar close** (`barstate.isconfirmed` + `alert.freq_once_per_bar_close`).
- **Enable Stop Hit Alerts** (`false`): Triggers on stop breaches (long/short per TF), using `ta.crossunder/crossover`.
### Colors
- **TF1 Colors**: Bullish (teal), Bearish (red), Retracement (orange).
- **TF2 Colors**: Bullish (blue), Bearish (maroon), Retracement (orange).
- **Area Transparency** (`80`): Fill opacity (0-100).
## 🔶 USAGE
Trailing stops shine in **trend-following strategies**:
- **Entries**: Use structure breaks as signals (e.g., long on bullish BOS from HTF1).
- **Exits**: Trail stops for profit-locking; alert on hits for automation.
- **Confluence**: Overlay HTF1 (e.g., 1H) for bias, HTF2 (e.g., Daily) for major levels—enter LTF only on alignment.
- **Risk Management**: Lower `incr` avoids early stops in chop; reset on `'All'` for aggressive trailing.
! (i.imgur.com)
*HTF1 shows bullish structure (teal line), trailing stop ratchets up—long entry confirmed on LTF pullback.*
! (i.imgur.com)
*TF1 (blue) bearish, TF2 (red) neutral—avoid shorts until alignment.*
! (i.imgur.com)
*Colored based on TF1 trend: Green bodies on bull `os=1`.*
Pro Tip: Test on demo—pair with LuxAlgo's other tools like Smart Money Concepts for full structure ecosystem.
## 🔶 DETAILS: Mathematical Breakdown
On bullish break:
- Local min: `btm = ta.lowest(n - ph_x)` (optimized loop equivalent).
- Stop init: `ts = btm`.
- Update: `Δmax = max - max `, `ts_new = ts + Δmax * (incr/100)`.
Bearish mirrors with `Δmin` (negative, so decrements `ts`).
In MTF: HTF `time` aligns lines via `line.new(htf_time, level, current_time, level, xloc.bar_time)`.
No logs/math libs needed—pure Pine v5 efficiency.
## Disclaimer
This is for educational purposes. Not financial advice. Backtest thoroughly. Original by LuxAlgo—modify at your risk. See TradingView's (www.tradingview.com). Licensed under CC BY-NC-SA 4.0 (attribution to LuxAlgo required).
CCI + MACD Signal MTF (2nd-cross)This custom indicator combines the Commodity Channel Index (CCI) and the MACD to generate trading signals.
Basic signals (dots):
A green dot is plotted when CCI is above +100 and MACD is positive.
A red dot is plotted when CCI is below –100 and MACD is negative.
These dots help visualize momentum alignment between the two indicators.
Second-cross signals (text + alert):
The indicator also tracks cycles of the CCI.
When CCI first moves above +100 and later falls back below +100, this is counted as one completed cycle.
The next time CCI crosses back above +100 (the second cross), if MACD is still positive, a “BUY” label is plotted and a buy alert is triggered.
Conversely, when CCI first moves below –100 and later rises back above –100, that is one completed cycle.
The next time CCI crosses back below –100 (the second cross), if MACD is negative, a “SELL” label is plotted and a sell alert is triggered.
Alerts:
Alerts are only fired on the second-cross events (BUY or SELL), making them rarer but potentially more reliable than the basic dot conditions.
Timeframe flexibility:
Both the CCI and the MACD can be calculated on custom timeframes independently of the chart’s timeframe.
CCI + MACD Signal MTF (2nd-cross)This custom indicator combines the Commodity Channel Index (CCI) and the MACD to generate trading signals.
Basic signals (dots):
A green dot is plotted when CCI is above +100 and MACD is positive.
A red dot is plotted when CCI is below –100 and MACD is negative.
These dots help visualize momentum alignment between the two indicators.
Second-cross signals (text + alert):
The indicator also tracks cycles of the CCI.
When CCI first moves above +100 and later falls back below +100, this is counted as one completed cycle.
The next time CCI crosses back above +100 (the second cross), if MACD is still positive, a “BUY” label is plotted and a buy alert is triggered.
Conversely, when CCI first moves below –100 and later rises back above –100, that is one completed cycle.
The next time CCI crosses back below –100 (the second cross), if MACD is negative, a “SELL” label is plotted and a sell alert is triggered.
Alerts:
Alerts are only fired on the second-cross events (BUY or SELL), making them rarer but potentially more reliable than the basic dot conditions.
Timeframe flexibility:
Both the CCI and the MACD can be calculated on custom timeframes independently of the chart’s timeframe.






















