Deadband Hysteresis Filter [BackQuant]Deadband Hysteresis Filter
What this is
This tool builds a “debounced” price baseline that ignores small fluctuations and only reacts when price meaningfully departs from its recent path. It uses a deadband to define how much deviation matters and a hysteresis scheme to avoid rapid flip-flops around the decision boundary. The baseline’s slope provides a simple trend cue, used to color candles and to trigger up and down alerts.
Why deadband and hysteresis help
They filter micro noise so the baseline does not react to every tiny tick.
They stabilize state changes. Hysteresis means the rule to start moving is stricter than the rule to keep holding, which reduces whipsaw.
They produce a stepped, readable path that advances during sustained moves and stays flat during chop.
How it works (conceptual)
At each bar the script maintains a running baseline dbhf and compares it to the input price p .
Compute a base threshold baseTau using the selected mode (ATR, Percent, Ticks, or Points).
Build an enter band tauEnter = baseTau × Enter Mult and an exit band tauExit = baseTau × Exit Mult where typically Exit Mult < Enter Mult .
Let diff = p − dbhf .
If diff > +tauEnter , raise the baseline by response × (diff − tauEnter) .
If diff < −tauEnter , lower the baseline by response × (diff + tauEnter) .
Otherwise, hold the prior value.
Trend state is derived from slope: dbhf > dbhf → up trend, dbhf < dbhf → down trend.
Inputs and what they control
Threshold mode
ATR — baseTau = ATR(atrLen) × atrMult . Adapts to volatility. Useful when regimes change.
Percent — baseTau = |price| × pctThresh% . Scale-free across symbols of different prices.
Ticks — baseTau = syminfo.mintick × tickThresh . Good for futures where tick size matters.
Points — baseTau = ptsThresh . Fixed distance in price units.
Band multipliers and response
Enter Mult — outer band. Price must travel at least this far from the baseline before an update occurs. Larger values reject more noise but increase lag.
Exit Mult — inner band for hysteresis. Keep this smaller than Enter Mult to create a hold zone that resists small re-entries.
Response — step size when outside the enter band. Higher response tracks faster; lower response is smoother.
UI settings
Show Filtered Price — plots the baseline on price.
Paint candles — colors bars by the filtered slope using your long/short colors.
How it can be used
Trend qualifier — take entries only in the direction of the baseline slope and skip trades against it.
Debounced crossovers — use the baseline as a stabilized surrogate for price in moving-average or channel crossover rules.
Trailing logic — trail stops a small distance beyond the baseline so small pullbacks do not eject the trade.
Session aware filtering — widen Enter Mult or switch to ATR mode for volatile sessions; tighten in quiet sessions.
Parameter interactions and tuning
Enter Mult vs Response — both govern sensitivity. If you see too many flips, increase Enter Mult or reduce Response. If turns feel late, do the opposite.
Exit Mult — widening the gap between Enter and Exit expands the hold zone and reduces oscillation around the threshold.
Mode choice — ATR adapts automatically; Percent keeps behavior consistent across instruments; Ticks or Points are useful when you think in fixed increments.
Timeframe coupling — on higher timeframes you can often lower Enter Mult or raise Response because raw noise is already reduced.
Concrete starter recipes
General purpose — ATR mode, atrLen=14 , atrMult=1.0–1.5 , Enter=1.0 , Exit=0.5 , Response=0.20 . Balanced noise rejection and lag.
Choppy range filter — ATR mode, increase atrMult to 2.0, keep Response≈0.15 . Stronger suppression of micro-moves.
Fast intraday — Percent mode, pctThresh=0.1–0.3 , Enter=1.0 , Exit=0.4–0.6 , Response=0.30–0.40 . Quicker turns for scalping.
Futures ticks — Ticks mode, set tickThresh to a few spreads beyond typical noise; start with Enter=1.0 , Exit=0.5 , Response=0.25 .
Strengths
Clear, explainable logic with an explicit noise budget.
Multiple threshold modes so the same tool fits equities, futures, and crypto.
Built-in hysteresis that reduces flip-flop near the boundary.
Slope-based coloring and alerts that make state changes obvious in real time.
Limitations and notes
All filters add lag. Larger thresholds and smaller response trade faster reaction for fewer false turns.
Fixed Points or Ticks can under- or over-filter when volatility regime shifts. ATR adapts, but will also expand bands during spikes.
On extremely choppy symbols, even a well tuned band will step frequently. Widen Enter Mult or reduce Response if needed.
This is a chart study. It does not include commissions, slippage, funding, or gap risks.
Alerts
DBHF Up Slope — baseline turns from down to up on the latest bar.
DBHF Down Slope — baseline turns from up to down on the latest bar.
Implementation details worth knowing
Initialization sets the baseline to the first observed price to avoid a cold-start jump.
Slope is evaluated bar-to-bar. The up and down alerts check for a change of slope rather than raw price crossings.
Candle colors and the baseline plot share the same long/short palette with transparency applied to the line.
Practical workflow
Pick a mode that matches how you think about distance. ATR for volatility aware, Percent for scale-free, Ticks or Points for fixed increments.
Tune Enter Mult until the number of flips feels appropriate for your timeframe.
Set Exit Mult clearly below Enter Mult to create a real hold zone.
Adjust Response last to control “how fast” the baseline chases price once it decides to move.
Final thoughts
Deadband plus hysteresis gives you a principled way to “only care when it matters.” With a sensible threshold and response, the filter yields a stable, low-chop trend cue you can use directly for bias or plug into your own entries, exits, and risk rules.
"Trailing stop" için komut dosyalarını ara
VWAP Price ChannelVWAP Price Channel cuts the crust off of a traditional price channel (Donchian Channel) by anchoring VWAPs at the highs and lows. By doing this, the flat levels, characteristic of traditional Donchian Channels, are no more!
Author's Note: This indicator is formed with no inherent use, and serves solely as a thought experiment.
> Concept
I would be hesitant to call this a "predictive" indicator, however the behavior of it would suggest it could be considered at least partially predictive
Essentially, the Anchored VWAPs creates something from otherwise nothing.
While the DC upper or lower values are staying flat, the VWAPs improvise based on price and volume to project a level that may be a better representation of where future highs or lows may settle.
Visually, this looks like we have cut off the corners of the Donchian Channel.
Note: Notice how we are calculating values before the corners are realized.
> Implementation
While this is only a concept indicator, The specific application I've gone with for this, is a sort of supertrend-ish display (A Trend Flipping Trailing Stop Loss).
The script uses basic logic to create a trend direction, and then displays the Anchored VWAPs as a form of trailing stop loss.
While "In Trend", the script fills in the area between the VWAP and Price in the direction of trend.
When new highs or lows are made while in trend, the opposite VWAP will start to generate at the new highs or lows. These happen on every new high or low, so they are not indicating the trend shift, but could be interpreted as breakout levels for the current trend direction in order for continuation.
Note: All values are drawn live, but when using higher timeframes, there is a natural calculation discrepancy when using live data vs. historical.
> Technicals
In this script, I'm simply detecting new highs or lows from the DC and using those as the anchor frequency on the built-in VWAP function.
So each time a new high or low is made based on DC, the VWAP function re-anchors to the high or low of the candle.
Past that, I have implemented some logic in order to account for a common occurrence I faced during development.
Frequently, the price would outpace the anchored VWAP, so we would end up with the VWAP being further from price than the actual DC upper or lower.
Due to this, what I have ended up with was a third value which, rather than switching between raw VWAP values and DC values, it adjusts the value based on the change in the VWAP value.
This can be simply thought of as a "Start + Change" type of setup.
By doing this, I can use the change values from the actual anchored VWAP, and under normal conditions, this will also be the true VWAP value.
However, situationally, I am able to update the start value which we're applying the VWAP change to.
In other words, when these situations happen, the VWAP change is added to the new (closer to price) DC value.
The specific trend logic being used is nothing fancy at all, we are simply checking if a new high or low is created and setting the trend in that direction.
This is in line with some traditional DC Strategies.
To those who made it here,
Just remember:
The chart may be ugly, but it's the fastest analysis of the data you can get.
Nicer displays often come at the hidden cost of latency.
You have to shoot your shot to make it.
Choose 2: Fast, Clean, Useful
Enjoy!
Kitti-Playbook ATR Study R0
Date : Aug 22 2025
Kitti-Playbook ATR Study R0
This is used to study the operation of the ATR Trailing Stop on the Long side, starting from the calculation of True Range.
1) Studying True Range Calculation
1.1) Specify the Bar graph you want to analyze for True Range.
Enable "Show Selected Price Bar" to locate the desired bar.
1.2) Enable/disable "Display True Range" in the Settings.
True Range is calculated as:
TR = Max (|H - L|, |H - Cp|, |Cp - L|)
• Show True Range:
Each color on the bar represents the maximum range value selected:
◦ |H - L| = Green
◦ |H - Cp| = Yellow
◦ |Cp - L| = Blue
• Show True Range on Selected Price Bar:
An arrow points to the range, and its color represents the maximum value chosen:
◦ |H - L| = Green
◦ |H - Cp| = Yellow
◦ |Cp - L| = Blue
• Show True Range Information Table:
Displays the actual values of |H - L|, |H - Cp|, and |Cp - L| from the selected bar.
2) Studying Average True Range (ATR)
2.1) Set the ATR Length in Settings.
Default value: ATR Length = 14
2.2) Enable/disable "Display Average True Range (RMA)" in Settings:
• Show ATR
• Show ATR Length from Selected Price Bar
(An arrow will point backward equal to the ATR Length)
3) Studying ATR Trailing
3.1) Set the ATR Multiplier in Settings.
Default value: ATR Multiply = 3
3.2) Enable/disable "Display ATR Trailing" in Settings:
• Show High Line
• Show ATR Bands
• Show ATR Trailing
4) Studying ATR Trailing Exit
(Occurs when the Close price crosses below the ATR Trailing line)
Enable/disable "Display ATR Trailing" in Settings:
• Show Close Line
• Show Exit Points
(Exit points are marked by an orange diamond symbol above the price bar)
Smart Impulse Exhaustion Finder (ATR + ADX Filter)📌 Purpose
This indicator detects potential exhaustion of strong bullish or bearish impulses at fresh swing highs/lows by combining multiple price action and volatility-based filters.
🧠 How It Works
A signal is triggered only when all core conditions are satisfied:
1. Swing High/Low Detection
Current high (or low) must be the highest (or lowest) over the last Extremum Lookback bars (default: 50).
This ensures the move is significant relative to recent price action.
2. Impulse Confirmation
Price must extend by at least 1 × ATR from the previous swing point.
This filters out minor fluctuations.
3. Exhaustion Conditions (at least 2 out of 3 must be met)
RSI Extreme: RSI > Overbought Level (default: 80) for bearish signals, RSI < Oversold Level (default: 20) for bullish signals.
Volume Spike: Volume > SMA(Volume, Volume SMA Length) × Volume Spike Multiplier.
Candle Wick Rejection: Upper wick ≥ Wick Threshold % for bearish setups, Lower wick ≥ Wick Threshold % for bullish setups.
4. Trend Filter
ADX > ADX Threshold ensures the market is trending and filters out sideways conditions.
5. Candle Body Filter
Candle body must be ≥ Body Size ATR Factor × ATR.
This avoids weak signals from small candles or doji formations.
📈 How to Use
Bearish Signal:
Appears at fresh swing highs with exhaustion conditions met. Useful for tightening stops, taking partial profits, or counter-trend shorts.
Bullish Signal:
Appears at fresh swing lows with exhaustion conditions met. Useful for trailing stops, profit-taking, or counter-trend longs.
Recommended Timeframes: Works best on 1h, 4h, and Daily charts.
Markets: Crypto, Forex, Stocks — wherever volatility and trends are present.
⚙️ Inputs
RSI Length / Overbought / Oversold
Volume SMA Length & Volume Spike Multiplier
Wick Threshold %
Extremum Lookback (bars for highs/lows)
ADX Length & Threshold
Body Size ATR Factor
⚠️ Disclaimer
This script is for educational purposes only and does not constitute financial advice.
Always test thoroughly and apply proper risk management before live trading.
💡 Tip: Combine this tool with your own market context and confluence factors for higher probability setups.
Price Exhaustion Envelope [BackQuant]Price Exhaustion Envelope
Visual preview of the bands:
What it is
The Price Exhaustion Envelope (PEE) is a multi‑factor overextension detector wrapped inside a dynamic envelope framework. It measures how “tired” a move is by blending price stretch, volume surges, momentum and acceleration, plus optional RSI divergence. The result is a composite exhaustion score that drives both on‑chart signals and the adaptive width of three optional envelope bands around a smoothed baseline. When the score spikes above or below your chosen threshold, the script can flag exhaustion, paint candles, tint the background and fire alerts.
How it works under the hood
Exhaustion score
Price component: distance of close from its mean in standard deviation units.
Volume component: normalized volume pressure that highlights unusual participation.
Momentum component: rate of change and acceleration of price, scaled by their own volatility.
RSI divergence (optional): bullish and bearish divergences gently push the score lower or higher.
Mode control: choose Price, Volume, Momentum or Composite. Composite averages the main pieces for a balanced view.
Energy scale (0 to 100)
The composite score is pushed through a logistic transform to create an “energy” value. High energy (above 70 to 80) signals a move that may be running hot, while very low energy (below 20 to 30) points to exhaustion on the downside.
Envelope engine
Baseline: EMA of price over the main lookback length.
Width: base width is standard deviation times a multiplier.
Type selector:
• Static keeps the width fixed.
• Dynamic expands width in proportion to the absolute exhaustion score.
• Adaptive links width to the energy reading so bands breathe with market “heat.”
Smoothing: a short EMA on the width reduces jitter and keeps bands pleasant to trade around.
Band architecture
You can toggle up to three symmetric bands on each side of the baseline. They default to 1.0, 1.6 and 2.2 multiples of the smoothed width. Soft transparent fills create a layered thermograph of extension. The outermost band often maps to true blow‑off extremes.
On‑chart elements
Baseline line that flips color in real time depending on where price sits.
Up to three upper and lower bands with progressive opacity.
Triangle markers at fresh exhaustion triggers.
Tiny warning glyphs at extreme upper or lower breaches.
Optional bar coloring to visually tag exhausted candles.
Background halo when energy > 80 or < 20 for instant context.
A compact info table showing State, Score, Energy, Momentum score and where price sits inside the envelope (percent).
How to use it in trading
Mean reversion plays
When price pierces the outer band and an exhaustion marker prints, look for reversal candles or lower‑timeframe confirmation to fade the move back toward the baseline.
For conservative entries, wait for the composite score to roll back under the threshold or for energy to drop from extreme to neutral.
Set stops just beyond the extreme levels (use extreme_upper and extreme_lower as natural invalidation points). Targets can be the baseline or the opposite inner band.
Trend continuation with smart pullbacks
In strong trends, the first tag of Band 1 or Band 2 against the dominant direction often offers low‑risk continuation entries. Use energy readings: if energy is low on a pullback during an uptrend, a bounce is more likely.
Combine with RSI divergence: hidden bullish divergence near a lower band in an uptrend can be a powerful confirmation.
Breakout filtering
A breakout that occurs while the composite score is still moderate (not exhausted) has a higher chance of follow‑through. Skip signals when energy is already above 80 and price is punching the outer band, as the move may be late.
Watch env_position (Envelope %) in the table. Breakouts near 40 to 60 percent of the envelope are “healthy,” while those at 95 percent are stretched.
Scaling out and risk control
Use exhaustion alerts to trim positions into strength or weakness.
Trail stops just outside Band 2 or Band 3 to stay in trends while letting the envelope expand in volatile phases.
Multi‑timeframe confluence
Run the script on a higher timeframe to locate exhaustion context, then drill down to a lower timeframe for entries.
Opposite signals across timeframes (daily exhaustion vs. 5‑minute breakout) warn you to reduce size or tighten management.
Key inputs to experiment with
Lookback Period: larger values smooth the score and envelope, ideal for swing trading. Shorter values make it reactive for scalps.
Exhaustion Threshold: raise above 2.0 in choppy assets to cut noise, drop to 1.5 for smooth FX pairs.
Envelope Type: Dynamic is great for crypto spikes, Adaptive shines in stocks where volume and volatility wave together.
RSI Divergence: turn off if you prefer a pure price/volume model or if divergence floods the score in your asset.
Alert set included
Fresh upper exhaustion
Fresh lower exhaustion
Extreme upper breach
Extreme lower breach
RSI bearish divergence
RSI bullish divergence
Hook these to TradingView notifications so you get pinged the moment a move hits exhaustion.
Best practices
Always pair exhaustion signals with structure. Support and resistance, liquidity pools and session opens matter.
Avoid blindly shorting every upper signal in a roaring bull market. Let the envelope type help you filter.
Use the table to sanity‑check: a very high score but mid‑range env_position means the band may still be wide enough to absorb more movement.
Backtest threshold combinations on your instrument. Different tickers carry different volatility fingerprints.
Final note
Price Exhaustion Envelope is a flexible framework, not a turnkey system. It excels as a context layer that tells you when the crowd is pressing too hard or when a move still has fuel. Combine it with sound execution tactics, risk limits and market awareness. Trade safe and let the envelope breathe with the market.
TrendShift [MOT]📈 TrendShift – Multi-Factor Momentum & Trend Signal Suite
TrendShift is a precision-built momentum and confluence tool designed to highlight directional shifts in price action. It combines EMA slope structure, oscillator confirmation, volume behavior, and dynamic SL/TP logic into one cohesive system. Whether you're trading with the trend or catching reversals, TrendShift provides data-backed clarity and visual confidence — and it’s available free to the public.
🔍 Core Signal Logic
Buy (🟢 Long) and Sell (🔴 Short) signals are triggered when multiple conditions align within a set bar window (default: 5 bars):
Stochastic RSI K/D cross
RSI crosses above 20 (long) or below 80 (short)
Stochastic RSI breaks 20 (long) or 80 (short)
Volume exceeds 20-bar average
🧭 Visual Trend Dashboard – Signal Table
A real-time on-chart dashboard displays:
EMA Trend: Bullish / Bearish / Mixed (based on 4 EMA slopes)
Stoch RSI: Oversold / Overbought / Neutral
RSI: Exact value with zone label
Volume: Above or Below average
Dashboard theme and position are fully customizable.
📐 Trend Structure with EMA Slope Logic
Plots four EMAs (21, 50, 100, 200) color-coded by slope:
Green = Rising
Red = Falling
These feed into the dashboard's EMA Trend display.
🎯 Optional Take Profit / Stop Loss Zones
When enabled, SL/TP lines plot automatically on valid signals:
Fixed-distance targets (e.g., 10pt TP, 5pt SL)
Auto-remove on TP or SL hit
Separate lines for long vs. short trades
Fully customizable styling
🔁 Trailing Stop Filter (Internal Logic)
A custom ATR-based trailing stop helps validate directional strength:
ATR period
HHV window
ATR multiplier
Used internally — not plotted — to confirm trend progression before entry.
⚙️ Customizable Parameters
Every core component is user-configurable:
EMA periods: 21 / 50 / 100 / 200
ATR trailing logic: period, HHV, multiplier
Oscillator settings: Stoch RSI & RSI
Volume length
SL/TP toggles and point values
Bar clustering window
Dashboard theme and location
🔔 Alerts Included
BUY Signal Triggered
SELL Signal Triggered
Compatible with webhook automation or mobile push notifications.
⚠️ Disclaimer
This tool is for educational purposes only and is not financial advice. Trading involves risk — always do your own research and consult a licensed professional before making trading decisions.
Chandelier Exit Oscillator [LuxAlgo]The Chandelier Exit Oscillator is a technical analysis tool that provides insights into potential trend reversals, momentum shifts, and trend continuation patterns, helping traders pinpoint optimal exit points for both long and short positions.
By calculating trailing stop levels based on a multiple of the Average True Range (ATR), the oscillator visually indicates when prices move above or below these critical stop levels.
This script uniquely combines the Chandelier Exit indicator with an oscillator format, equipping traders with a versatile tool that leverages ATR-based levels for enhanced trend analysis.
🔶 USAGE
Displaying the Chandelier Exit as an oscillator allows traders to gauge trend momentum and strength, recognize potential reversals, and refine their market insights.
The Timeframe option specifies the timeframe used for calculations, enabling multi-timeframe analysis and allowing traders to align the indicator’s signals with broader or narrower market trends.
The Chandelier Exit Oscillator allows users to select between a Regular or Normalized oscillator type. The Regular option displays raw oscillator values, while the Normalized version smooths values and scales them from 0 to 100.
The Chandelier Exit Overlay allows users to enable or disable the display of Chandelier Exit levels directly on the price chart. When enabled, this overlay plots trailing stop levels for both long and short positions, helping traders visually monitor potential exit points and trend boundaries alongside the price action.
The Trend-based Bar Color feature allows users to color the bars on the price chart according to the current trend direction. This visual differentiation aids in quicker decision-making and provides a clearer understanding of market dynamics.
🔶 SETTINGS
🔹 Chandelier Exit Settings
Timeframe: Sets the timeframe for calculations, allowing multi-timeframe analysis.
ATR Length: Defines the number of bars used for calculating the Average True Range (ATR), which helps in setting Chandelier Exit levels.
ATR Multiplier: Adjusts the sensitivity of the Chandelier Exit lines based on the ATR. Higher values make the indicator more conservative, while lower values make it more responsive.
🔹 Chandelier Exit Oscillator
Chandelier Exit Oscillator: Allows users to choose between a Regular or Normalized oscillator type. The Regular option displays raw oscillator values, while the Normalized version smooths values and scales them from 0 to 100.
Oscillator Smoothing: Controls the level of smoothing applied to the oscillator. Higher smoothing values filter out minor fluctuations.
🔹 Chandelier Exit Overlay
Chandelier Exit Overlay: Enables or disables the display of Chandelier Exit levels directly on the price chart.
Trend-based Bar Colors: Allows users to color bars based on trend direction, enhancing the visual analysis of market direction.
🔶 RELATED SCRIPTS
Market-Structure-Oscillator
Long-Leg Doji Breakout StrategyThe Long-Leg Doji Breakout Strategy is a sophisticated technical analysis approach that capitalizes on market psychology and price action patterns.
Core Concept: The strategy identifies Long-Leg Doji candlestick patterns, which represent periods of extreme market indecision where buyers and sellers are in equilibrium. These patterns often precede significant price movements as the market resolves this indecision.
Pattern Recognition: The algorithm uses strict mathematical criteria to identify authentic Long-Leg Doji patterns. It requires the candle body to be extremely small (≤0.1% of the total range) while having long wicks on both sides (at least 2x the body size). An ATR filter ensures the pattern is significant relative to recent volatility.
Trading Logic: Once a Long-Leg Doji is identified, the strategy enters a "waiting mode," monitoring for a breakout above the doji's high (long signal) or below its low (short signal). This confirmation approach reduces false signals by ensuring the market has chosen a direction.
Risk Management: The strategy allocates 10% of equity per trade and uses a simple moving average crossover for exits. Visual indicators help traders understand the pattern identification and trade execution process.
Psychological Foundation: The strategy exploits the natural market cycle where uncertainty (represented by the doji) gives way to conviction (the breakout), creating high-probability trading opportunities.
The strength of this approach lies in its ability to identify moments when market sentiment shifts from confusion to clarity, providing traders with well-defined entry and exit points while maintaining proper risk management protocols.
How It Works
The strategy operates on a simple yet powerful principle: identify periods of market indecision, then trade the subsequent breakout when the market chooses direction.
Step 1: Pattern Detection
The algorithm scans for Long-Leg Doji candles, which have three key characteristics:
Tiny body (open and close prices nearly equal)
Long upper wick (significant rejection of higher prices)
Long lower wick (significant rejection of lower prices)
Step 2: Confirmation Wait
Once a doji is detected, the strategy doesn't immediately trade. Instead, it marks the high and low of that candle and waits for a definitive breakout.
Step 3: Trade Execution
Long Entry: When price closes above the doji's high
Short Entry: When price closes below the doji's low
Step 4: Exit Strategy
Positions are closed when price crosses back through a 20-period moving average, indicating potential trend reversal.
Market Psychology Behind It
A Long-Leg Doji represents a battlefield between bulls and bears that ends in a stalemate. The long wicks show that both sides tried to push price in their favor but failed. This creates a coiled spring effect - when one side finally gains control, the move can be explosive as trapped traders rush to exit and momentum traders jump aboard.
Key Parameters
Doji Body Threshold (0.1%): Ensures the body is truly small relative to the candle's range
Wick Ratio (2.0): Both wicks must be at least twice the body size
ATR Filter: Uses Average True Range to ensure the pattern is significant in current market conditions
Position Size: 10% of equity per trade for balanced risk management
Pros:
High Probability Setups: Doji patterns at key levels often lead to significant moves as they represent genuine shifts in market sentiment.
Clear Rules: Objective criteria for entry and exit eliminate emotional decision-making and provide consistent execution.
Risk Management: Built-in position sizing and exit rules help protect capital during losing trades.
Market Neutral: Works equally well for long and short positions, adapting to market direction rather than fighting it.
Visual Confirmation: The strategy provides clear visual cues, making it easy to understand when patterns are forming and trades are triggered.
Cons:
False Breakouts: In choppy or ranging markets, price may break the doji levels only to quickly reverse, creating whipsaws.
Patience Required: Traders must wait for both pattern formation and breakout confirmation, which can test discipline during active market periods.
Simple Exit Logic: The moving average exit may be too simplistic, potentially cutting profits short during strong trends or holding losers too long during reversals.
Volatility Dependent: The strategy relies on sufficient volatility to create meaningful doji patterns - it may underperform in extremely quiet markets.
Lagging Entries: Waiting for breakout confirmation means missing the very beginning of moves, reducing potential profit margins.
Best Market Conditions
The strategy performs optimally during periods of moderate volatility when markets are making genuine directional decisions rather than just random noise. It works particularly well around key support/resistance levels where the market's indecision is most meaningful.
Optimization Considerations
Consider combining with additional confluence factors like volume analysis, support/resistance levels, or other technical indicators to improve signal quality. The exit strategy could also be enhanced with trailing stops or multiple profit targets to better capture extended moves while protecting gains.
Best for Index option,
Enjoy !!
Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
Strategy Builder With IndicatorsThis strategy script is designed for traders who enjoy building systems using multiple indicators.
Please note: This script does not include any built-in indicators. Instead, it works by referencing the plot outputs of the indicators you’ve already added to your chart.
For example, if you add a MACD and an ATR indicator to your chart, you can assign their plot values as inputs in the settings panel of this strategy.
• MACD as a trigger
• ATR as a filter
How Filters Work
Filters check whether certain conditions are met before a trade can be opened. For instance, if you set a filter like ATR > 30, then no trade will be executed unless that condition is true — even if the trigger fires.
All filters are linked, meaning every active filter must be satisfied for a trade to occur.
How Triggers Work
Triggers are what actually fire a trade signal — such as a moving average crossover or RSI breaking above a specific level. Unlike filters, triggers are independent. Only one active trigger needs to be true for the trade to execute.
Thanks to its modular structure, this strategy can be used with any indicator of your choice.
⸻
Risk Management Features
In the settings, you’ll find flexible options for:
• Stop Loss (SL)
• Trailing Stop Loss (TSL)
• Multi Take-Profit (TP)
These features enhance trade safety and let you tailor your risk management.
SL types available:
• Tick-based SL
• Percent-based SL
• ATR-based SL
Once you select your preferred SL type, you can fine-tune its distance using the offset field.
Trailing SL allows your stop to follow price as it moves in your favor — helping to lock in profits.
Multi-TP lets you take profits at two different levels, helping you secure gains while leaving room for extended moves.
Breakeven option is also available to automatically move your SL to entry after reaching a profit threshold.
⸻
How to Build a Solid Strategy
Let’s break down a good setup into three key components:
1. Trend Filter
Avoid trading against the trend — that’s like swimming against the current.
Use a filter like:
• Supertrend
• Momentum indicators
• Candlestick bias, etc.
Example: In this case, I used Supertrend and filtered for trades only if the price is above the uptrend line.
2. Trigger Condition
Once we confirm the trend is on our side, we need a trigger to execute at the right moment. This can be:
• RSI cross
• Candlestick patterns
• Trendline breaks
• Moving average crossovers, etc.
Example: I used RSI crossing above 50 as the entry trigger.
3. Risk Management
Even in the right trend at the right time — anything can happen. That’s why you should always define Stop Loss and Take Profit levels.
⸻
And there you have it! Your strategy is ready to backtest, refine, and deploy with alerts for live trading.
Questions or suggestions? Feel free to reach out
QQQ Strategy v2 ESL | easy-peasy-x This is a strategy optimized for QQQ (and SPY) for the 1H timeframe. It significantly outperforms passive buy-and-hold approach. With settings adjustments, it can be used on various assets like stocks and cryptos and various timeframes, although the default out of the box settings favor QQQ 1H.
The strategy uses various triggers to take both long and short trades. These can be adjusted in settings. If you try a different asset, see what combination of triggers works best for you.
Some of the triggers employ LuxAlgo's Ultimate RSI - shoutout to him for great script, check it out here .
Other triggers are based on custom signed standard deviation - basically the idea is to trade Bollinger Bands expansions (long to the upside, short to the downside) and fade or stay out of contractions.
There are three key moving averages in the strategy - LONG MA, SHORT MA, BASIC MA. Long and Short MAs are guides to eyes on the chart and also act as possible trend filters (adjustable in settings). Basic MA acts as guide to eye and a possible trade trigger (adjustable in settings).
There are a few trend filters the strategy can use - moving average, signed standard deviation, ultimate RSI or none. The filters act as an additional condition on triggers, making the strategy take trades only if both triggers and trend filter allows. That way one can filter out trades with unfavorable risk/reward (for instance, don't long if price is under the MA200). Different trade filters can be used for long and short trades.
The strategy employs various stop loss types, the default of which is a trailing %-based stop loss type. ATR-based stop loss is also available. The default 1.5% trailing stop loss is suitable for leveraged trading.
Lastly, the strategy can trigger take profit orders if certain conditions are met, adjustable in settings. Also, it can hold onto winning trades and exit only after stop out (in which case, consecutive triggers to take other positions will be ignored until stop out).
Let me know if you like it and if you use it, what kind of tweaks would you like to see.
With kind regards,
easy-peasy-x
SOXL Trend Surge v3.0.2 – Profit-Only RunnerSOXL Trend Surge v3.0.2 – Profit-Only Runner
This is a trend-following strategy built for leveraged ETFs like SOXL, designed to ride high-momentum waves with minimal interference. Unlike most short-term scalping scripts, this model allows trades to develop over multiple days to even several months, capitalizing on the full power of extended directional moves — all without using a stop-loss.
🔍 How It Works
Entry Logic:
Price is above the 200 EMA (long-term trend confirmation)
Supertrend is bullish (momentum confirmation)
ATR is rising (volatility expansion)
Volume is above its 20-bar average (liquidity filter)
Price is outside a small buffer zone from the 200 EMA (to avoid whipsaws)
Trades are restricted to market hours only (9 AM to 2 PM EST)
Cooldown of 15 bars after each exit to prevent overtrading
Exit Strategy:
Takes partial profit at +2× ATR if held for at least 2 bars
Rides the remaining position with a trailing stop at 1.5× ATR
No hard stop-loss — giving space for volatile pullbacks
⚙️ Strategy Settings
Initial Capital: $500
Risk per Trade: 100% of equity (fully allocated per entry)
Commission: 0.1%
Slippage: 1 tick
Recalculate after order is filled
Fill orders on bar close
Timeframe Optimized For: 45-minute chart
These parameters simulate an aggressive, high-volatility trading model meant for forward-testing compounding potential under realistic trading costs.
✅ What Makes This Unique
No stop-loss = fewer premature exits
Partial profit-taking helps lock in early wins
Trailing logic gives room to ride large multi-week moves
Uses strict filters (volume, ATR, EMA bias) to enter only during high-probability windows
Ideal for leveraged ETF swing or position traders looking to hold longer than the typical intraday or 2–3 day strategies
⚠️ Important Note
This is a high-risk, high-reward strategy meant for educational and testing purposes. Without a stop-loss, trades can experience deep drawdowns that may take weeks or even months to recover. Always test thoroughly and adjust position sizing to suit your risk tolerance. Past results do not guarantee future returns. Backtest range: May 8, 2020 – May 23, 2025
[blackcat] L3 Mean Reversion ATR Stop Loss OVERVIEW
The L3 Mean Reversion ATR Stop Loss indicator is meticulously crafted to empower traders by offering statistically-driven stop-loss levels that adapt seamlessly to evolving market dynamics. By harmoniously blending mean reversion concepts with Advanced True Range (ATR) metrics, it delivers a robust framework for managing risks more effectively. 🌐 The primary objective is to furnish traders with intelligent exit points grounded in both short-term volatility assessments and long-term trend evaluations.
Key highlights encompass:
• Dynamic calculation of Z-scores to evaluate deviations from established means
• Adaptive stop-loss pricing leveraging real-time ATR measurements
• Clear visual cues enabling swift decision-making processes
TECHNICAL ANALYSIS COMPONENTS
📉 Z-SCORE CALCULATION
Measures how many standard deviations an asset's current price lies away from its average
Facilitates identification of extreme conditions indicative of impending reversals
Utilizes simple moving averages and standard deviation computations
📊 STANDARD DEVIATION MEASUREMENT
Quantifies dispersion of closing prices around the mean
Provides insights into underlying price distribution characteristics
Crucial for assessing potential volatility levels accurately
🕵️♂️ ADAPTIVE STOP-LOSS DETECTION
Employs ATR as a proxy for prevailing market volatility
Modulates stop-loss placements dynamically responding to shifting trends
Ensures consistent adherence to predetermined risk management protocols
INDICATOR FUNCTIONALITY
🔢 Core Algorithms
Integrate Smooth Moving Averages (SMAs) alongside standardized deviation formulas
Generate precise Z-scores reflecting true price deviations
Leverage ATR-derived multipliers for fine-grained stop-loss adjustments
🖱️ User Interface Elements
Interactive plots displaying real-time stop-loss markers
Context-sensitive color coding enhancing readability
Background shading indicating proximity to stop-level activations
STRATEGY IMPLEMENTATION
✅ Entry Conditions
Confirm bullish/bearish setups validated through multiple confirmatory signals
Ensure alignment between Z-score readings and broader trend directions
Validate entry decisions considering concurrent market sentiment factors
🚫 Exit Mechanisms
Trigger exits upon hitting predefined ATR-based stop-loss thresholds
Monitor continuous breaches signifying potential trend reversals
Execute partial/total closes contingent upon cumulative loss limits
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines
Period Length: Governs responsiveness versus smoothing trade-offs
ATR Length: Dictates the temporal scope for volatility analysis
Stop Loss ATR Multiplier: Tunes sensitivity towards stop-trigger activations
💬 Customization Recommendations
Commence with baseline defaults; iteratively refine parameters
Evaluate impacts independently prior to combined adjustments
Prioritize minimizing erroneous trigger occurrences first
Sustain balanced risk-reward profiles irrespective of chosen settings
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques
Enforce strict compliance with pre-defined maximum leverage constraints
Mandatorily apply trailing stop-loss orders conforming to script outputs
Allocate positions proportionately relative to available capital reserves
Conduct periodic reviews gauging strategy effectiveness rigorously
⚠️ Potential Pitfalls & Solutions
Address frequent violations arising during heightened volatility phases
Manage false alerts warranting manual interventions judiciously
Prepare contingency plans mitigating margin call possibilities
Continuously assess automated system reliability amidst fluctuating conditions
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics
Assess win percentages consistently across diverse trading instruments
Calculate average profit ratios per successful execution
Measure peak drawdown durations alongside associated magnitudes
Analyze signal generation frequencies revealing hidden patterns
📈 Historical Data Analysis Tools
Maintain comprehensive records capturing every triggered event
Compare realized profits/losses against backtested simulations
Identify recurrent systematic errors demanding corrective actions
Implement iterative refinements bolstering overall efficacy steadily
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges
Unpredictable behaviors emerging within thinly traded markets
Latency issues manifesting during abrupt price fluctuations
Overfitted models yielding suboptimal results post-extensive tuning
Inaccuracies stemming from incomplete or delayed data inputs
💡 Effective Resolution Pathways
Exclude low-liquidity assets prone to erratic movements
Introduce buffer intervals safeguarding major news/event impacts
Limit ongoing optimization attempts preventing model degradation
Verify seamless connectivity ensuring uninterrupted data flows
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
A heartfelt acknowledgment extends to all developers contributing invaluable insights about adaptive stop-loss strategies using statistical measures! ✨
UTSStrategyHelperLibrary "UTSStrategyHelper"
TODO: add library description here
stopLossPrice(sig, atr, factor, isLong)
Calculates the stop loss price using a distance determined by ATR multiplied by a factor. Example for Long trade SL: PRICE - (ATR * factor).
Parameters:
sig (float)
atr (float) : (float): The value of the atr.
factor (float)
isLong (bool) : (bool): The current trade direction.
Returns: (bool): A boolean value.
takeProfitPrice(sig, atr, factor, isLong)
Calculates the take profit price using a distance determined by ATR multiplied by a factor. Example for Long trade TP: PRICE + (ATR * factor). When take profit price is reached usually 50 % of the position is closed and the other 50 % get a trailing stop assigned.
Parameters:
sig (float)
atr (float) : (float): The value of the atr.
factor (float)
isLong (bool) : (bool): The current trade direction.
Returns: (bool): A boolean value.
trailingStopPrice(initialStopPrice, atr, factor, priceSource, isLong)
Calculates a trailing stop price using a distance determined by ATR multiplied by a factor. It takes an initial price and follows the price closely if it changes in a favourable way.
Parameters:
initialStopPrice (float) : (float): The initial stop price which, for consistency also should be ATR * factor behind price: e.g. Long trade: PRICE - (ATR * factor)
atr (float) : (float): The value of the atr. Ideally the ATR value at trade open is taken and used for subsequent calculations.
factor (float)
priceSource (float) : (float): The current price.
isLong (bool) : (bool): The current trade direction.
Returns: (bool): A boolean value.
hasGreaterPositionSize(positionSize)
Determines if the strategy's position size has grown since the last bar.
Parameters:
positionSize (float) : (float): The size of the position.
Returns: (bool): A boolean value.
hasSmallerPositionSize(positionSize)
Determines if the strategy's position size has decreased since the last bar.
Parameters:
positionSize (float) : (float): The size of the position.
Returns: (bool): A boolean value.
hasUnchangedPositionSize(positionSize)
Determines if the strategy's position size has changed since the last bar.
Parameters:
positionSize (float) : (float): The size of the position.
Returns: (bool): A boolean value.
exporthasLongPosition(positionSize)
Determines if the strategy has an open long position.
Parameters:
positionSize (float) : (float): The size of the position.
Returns: (bool): A boolean value.
hasShortPosition(positionSize)
Determines if the strategy has an open short position.
Parameters:
positionSize (float) : (float): The size of the position.
Returns: (bool): A boolean value.
hasAnyPosition(positionSize)
Determines if the strategy has any open position, regardless of short or long.
Parameters:
positionSize (float) : (float): The size of the position.
Returns: (bool): A boolean value.
hasSignal(value)
Determines if the given argument contains a valid value (means not 'na').
Parameters:
value (float) : (float): The actual value.
Returns: (bool): A boolean value.
[blackcat] L3 Smart Money FlowCOMPREHENSIVE ANALYSIS OF THE L3 SMART MONEY FLOW INDICATOR
🌐 OVERVIEW:
The L3 Smart Money Flow indicator represents a sophisticated multi-dimensional analytics tool combining traditional momentum measurements with advanced institutional investor tracking capabilities. It's particularly effective at identifying large-scale capital movement dynamics that often precede significant price shifts.
Core Objectives:
• Detect subtle but meaningful price action anomalies indicating major player involvement
• Provide clear entry/exit markers based on multiple validated criteria
• Offer risk-managed positioning strategies suitable for various account sizes
• Maintain operational efficiency even during high volatility regimes
THEORETICAL BACKDROP AND METHODOLOGY
🎓 Conceptual Foundation Principles:
Utilizes Time-Varying Moving Averages (TVMA) responding adaptively to changing market states
Implements Extended Smoothing Algorithm (XSA) providing enhanced filtration characteristics
Employs asymmetric weight distribution favoring recent price observations over historical ones
→ Analyzes price-weighted closing prices incorporating volume influence indirectly
← Applies Asymmetric Local Maximum (ALMA) filters generating institution-specific trends
⟸ Combines multiple temporal perspectives producing robust directional assessments
✓ Calculates normalized momentum ratios comparing current state against extended range extremes
✗ Filters out insignificant fluctuations via double-stage verification process
⤾ Generates actionable alerts upon exceeding predefined significance boundaries
CONFIGURABLE PARAMETERS IN DEPTH
⚙️ Input Customization Options Detailed Explanation:
Temporal Resolution Control:
→ TVMA Length Setting:
Minimum value constraint ensuring mathematical validity
Higher numbers increase smoothing effect reducing reaction velocity
Lower intervals enhance responsiveness potentially increasing noise exposure
Validation Threshold Definition:
↓ Bull-Bear Boundary Level:
Establishes fundamental acceptance/rejection zones
Typically set near extreme values reflecting rare occurrence probability
Can be adjusted per instrument liquidity profiles if necessary
ADVANCED ALGORITHMIC PROCEDURES BREAKDOWN
💻 Internal Operation Architecture:
Base Calculations Infrastructure:
☑ Raw Data Preparation and Normalization
☐ High/Low/Closing Aggregation Processes
☒ Range Estimation Algorithms
Intermediate Transform Engine:
📈 Momentum Ratio Computation Workflow
↔ First Pass XSA Application Details
➖ Second Stage Refinement Mechanics
Final Output Synthesis Framework:
➢ Composite Reading Compilation Logic
➣ Validation Status Determination Process
➤ Alert Trigger Decision Making Structure
INTERACTIVE VISUAL INTERFACE COMPONENTS
🎨 User Experience Interface Elements:
🔵 Plotting Series Hierarchy:
→ Primary FundFlow Signal: White trace marking core oscillator progression
↑ Secondary Confirmation Overlay: Orange/Yellow highlighting validation status
🟥 Risk/Reward Boundaries: Aqua line delineating strategic areas requiring attention
🏷️ Interactive Marker System:
✔ "BUY": Green upward-pointing labels denoting confirmed long entries
❌ "SELL": Red downward-facing badges signaling short setups
PRACTICAL APPLICATION STRATEGY GUIDE
📋 Operational Deployment Instructions:
Strategic Planning Initiatives:
• Define precise profit targets considering realistic reward/risk scenarios
→ Set maximum acceptable loss thresholds protecting available resources adequately
↓ Develop contingency plans addressing unexpected adverse developments promptly
Live Trading Engagement Protocols:
→ Maintaining vigilant monitoring of label placement activities continuously
↓ Tracking order fill success rates across implemented grids regularly
↑ Evaluating system effectiveness compared alternative methodologies periodically
Performance Optimization Techniques:
✔ Implement incremental improvements iteratively throughout lifecycle
❌ Eliminate ineffective component variations systematically
⟹ Ensure proportional growth capability matching user needs appropriately
EFFICIENCY ENHANCEMENT APPROACHES
🚀 Ongoing Development Strategy:
Resource Management Focus Areas:
→ Minimizing redundant computation cycles through intelligent caching mechanisms
↓ Leveraging parallel processing capabilities where feasible efficiently
↑ Optimizing storage access patterns improving response times substantially
Scalability Consideration Factors:
✔ Adapting to varying account sizes/market capitalizations seamlessly
❌ Preventing bottlenecks limiting concurrent operation capacity
⟹ Ensuring balanced growth capability matching evolving requirements accurately
Maintenance Routine Establishment:
✓ Regular codebase updates incorporation keeping functionality current
↓ Periodic performance audits conducting verifying continued effectiveness
↑ Documentation refinement updating explaining any material modifications made
SYSTEMATIC RISK CONTROL MECHANISMS
🛡️ Comprehensive Protection Systems:
Position Sizing Governance:
∅ Never exceed predetermined exposure limitations strictly observed
± Scale entries proportionally according to available resources carefully
× Include slippage allowances within planning stages realistically
Emergency Response Procedures:
↩ Well-defined exit strategies including trailing stops activation logic
🌀 Contingency plan formulation covering worst-case scenario contingencies
⇄ Recovery procedure documentation outlining restoration steps methodically
WebhookGeneratorLibrary "WebhookGenerator"
Generates Json objects for webhook messages.
GenerateOT(license_id, symbol, action, order_type, trade_type, size, price, tp, sl, risk, trailPrice, trailOffset)
CreateOrderTicket: Establishes a order ticket.
Parameters:
license_id (string) : Provide your license index
symbol (string) : Symbol on which to execute the trade
action (string) : Execution method of the trade : "MRKT" or "PENDING"
order_type (string) : Direction type of the order: "BUY" or "SELL"
trade_type (string) : Is it a "SPREAD" trade or a "SINGLE" symbol execution?
size (float) : Size of the trade, in units
price (float) : If the order is pending you must specify the execution price
tp (float) : (Optional) Take profit of the order
sl (float) : (Optional) Stop loss of the order
risk (float) : Percent to risk for the trade, if size not specified
trailPrice (float) : (Optional) Price at which trailing stop is starting
trailOffset (float) : (Optional) Amount to trail by
Returns: Return Order string
Directional Movement Index (DMI) + AlertsThis is a Study with associated visual indicators and Bullish/Bearish Alerts for Directional Movement (DMI). It consists of an Average Directional Index (ADX), Plus Directional Indicator (+DI) and Minus Directional Indicator (-DI).
Published by J. Welles Wilder in 1978 for use with currencies and commodities which are typically more volatile than stocks and have stronger trends.
Development Notes
---------------------------
This indicator, and most of the descriptions below, were derived largely from the TradingView reference manual. Feedback and suggestions for improvement are more than welcome, as well are recommended Input settings and best practices for use.
tradingview.com/chart/?solution=43000502250
Strategy Description
---------------------------
ADX defines whether or not there is a trend present; +DI and -DI compliment the ADX by taking direction into account. An ADX above 25 indicates a strong trend, and a Bullish alert is subsequently triggered when +DI is above -DI and a Bearish alert when -DI is above +DI.
Note that the Bullish or Bearish crossover alert will only trigger if ADX is simultaneously above 25 during the crossover event. If ADX later rises to 25 and +DI is still greater than -DI, or -DI greater than +DI, then a delayed alert will not trigger by design.
Basic Use
---------------------------
Acceptable DMI values are up to the trader's interpretation and may change depending on the financial instrument being examined. Recommend not changing any default values without being first familiar with their purpose and impact on the indicator at large.
Confidence in price action and trend is higher when two or more indicators are in agreement -- therefore we recommend not using this indicator by itself to determine entry or exit trade opportunities.
Recommend also choosing 'Once Per Bar Close' when creating alerts.
Inputs
---------------------------
ADX Smoothing - the time period to be used in calculating the ADX which has a smoothing component (14 is the Default).
DI Length - the time period to be used in calculating the DI (14 is the Default).
Key Level - any trade with the ADX above the key level is a strong indicator that it is trending (23 to 25 is the suggested setting).
Sensitivity - an incremental variable to test whether the past n candles are in the same bullish or bearish state before triggering a delayed crossover alert (3 is the Default). Filter out some noise and reduces active alerts.
Show ADX Option - two visual styles are provided for user preference, a visible ADX line or a background overlay (green or red when ADX is above the key level, for bullish or bearish, and gray when below).
Color Candles - an option to transpose the bullish and bearish crossovers to the main candle bars. Can be turned off in the Style Tab by deselecting 'Bar Colors'. Dark blue is bullish, dark purple is bearish, and the black inner color is neutral. Note that the outer red and green border will still be distinguished by whether each individual candle is bearish or bullish during the specified timeframe.
Indicator Visuals
---------------------------
Bullish or Bearish plot based on DMI strategy (ADX and +/-DI values).
Visual cues are intended to improve analysis and decrease interpretation time during trading, as well as to aid in understanding the purpose of this study and how its inclusion can benefit a comprehensive trading strategy.
Trend Strength
---------------------------
To analyze trend strength, the focus should be on the ADX line and not the +DI or -DI lines. An ADX reading above 25 indicates a strong trend, while a reading below 20 indicates a weak or non-existent trend. A reading between those two values would be considered indeterminable. Though what is truly a strong trend or a weak trend depends on the financial instrument being examined; historical analysis can assist in determining appropriate values.
Bullish DI Cross
---------------------------
1. ADX must be over 25 (strong trend) (value is determined by the trader)
2. +DI cross above -DI
3. Set Stop Loss at the current day's low (any +DI cross-backs below -DI should be ignored)
4. Set trailing stop if ADX strengthens (i.e., signal rises)
Bearish DI Cross
---------------------------
1. ADX must be over 25 (strong trend) (value is determined by the trader)
2. -DI cross above +DI
3. Set Stop Loss at the current day's high (any -DI cross-backs below +DI should be ignored)
4. Set trailing stop if ADX strengthens (i.e., signal rises)
Disclaimer
---------------------------
This post and the script are not intended to provide any financial advice. Trade at your own risk.
No known repainting.
Version 1.1
-------------------------
- Added multi-timeframe resolution using PineCoders secure security function to eliminate repainting.
- Cleaned up option for selecting ADX view; and added a colored line as a choice, based on same bullish, bearish, or neutral colors as the background.
- Added exit crossover indicator to aid in an overall strategy development. This ability pairs better with my CHOP Zone Entry Strategy which relies on DMI Exits. Note that exit conditions don't employ the sensitivity variable. Green labels are for Bullish exits and red are for Bearish.
-- Exit condition is triggered if in an active Bullish or Bearish position and ADX drops below 25, Or if either the -DI crosses above +DI (for previously Bullish) or +DI crosses above -DI (for previously Bearish).
- Added reverse position determination. Triggers when a Bullish entry occurs on the same candle as a Bearish exit, or vice versa. Green labels are for Bullish reverses and red are for Bearish.
- Added selectable option to choose visible labels -- Bearish, Bullish, Both, Exits, Reverses, or All.
-- Note that a reverse label will only show if the opposing entry and exit labels are set to show, otherwise the reverse will revert to the appropriate entry or exit on the chart.
- Added alerts to account for new conditions.
-- Note that alerts for crossovers, exits, and reverses will only be triggered if the associated labels are selected to be shown (i.e., what you choose to see on the chart is what you will be alerted to).
Version 1.2
-------------------------
- Changed exit condition to be decided on by whether ADX is below 25 and on a +/-DI crossover. Versus being either or. The previous version had too many false triggers. This variety can now show multiple Bullish or Bearish alerts before an Exit condition too. I'm tempted to simply make this condition based on ADX, and not DI … thoughts? See lines 138 and 139.
- Updated the Background view to have deeper shades of colors dependent upon the ADX trend strength.
- Added an Oscillator view for the ADX and momentum computations to color the histogram by trend. DI lines are hidden.
-- If ADX is Bullish, then the oscillator is colored light green in an uptrend and dark green in a downtrend; if Bearish, then its light red in an uptrend and dark redin a downtrend; if adx is below key level, then it is light gray in a downtrend and dark grey in the uptrend.
- Added option to Hide ADX in case only the Directional lines are desired. This could be useful if you would like to have the ADX oscillator in one panel and +/-DI crossovers in another.
- Added a Columnar view for the ADX. DI lines are hidden. This view is really simple and compact, with the trend strength still easily understood. Colors are the same as for the oscillator -- the deeper the shade of green or red, then the higher the ADX trend strength level.
- Added a Trend Strength label.
ADX Trend Strength Trade (Y/N) Setup Types
0 to 10 = Barely Breathing N N/A
10 to 20 = Weak Trend Y Range/Pre-Breakout
20 to 30 = Potentially Starting to Trend Y Early Stage Trend
30 to 50 = Strong Trend Y Ride the Wave
50 to 75 = Very Strong Trend N Exhaustion
75 to 100 = Extremely Strong Trend N N/A
Version 1.3
-------------------------
Updated to Pine Script v5 to resolve errors from the deprecated v4 version.
This is a reissue of a previously published script that was hidden due to a v4 compatibility issue.
'https://www.tradingview.com/script/9OoEHrv5-Directional-Movement-Index-DMI-Alerts/'
[blackcat] L3 Ichimoku FusionCOMPREHENSIVE ANALYSIS OF THE L3 ICHIMOKU FUSION INDICATOR
🌐 Overview:
The L3 Ichimoku Fusion is a sophisticated multi-layered technical analysis tool integrating classic Japanese market forecasting techniques with enhanced dynamic elements designed specifically for identifying potential turning points in financial instruments' pricing action.
Key Purpose:
To provide traders with an intuitive yet powerful framework combining established ichimoku principles while incorporating additional validation checkpoints derived from cross-timeframe convergence studies.
THEORETICAL FOUNDATION EXPLAINED
🎓 Conceptual Background:
:
• Conversion & Base Lines tracking intermediate term averages
• Lagging Span providing delayed feedback mechanism
• Lead Spans projecting future equilibrium states
:
• Adaptive parameter scaling options
• Automated labeling system for critical junctures
• Real-time alert infrastructure enabling immediate response capability
PARAMETER CONFIGURATION GUIDE
⚙️ Input Parameters Explained In Detail:
Regional Setting Selection:**
→ Oriental Configuration: Standardized approach emphasizing slower oscillation cycles
→ Occidental Variation: Optimized settings reducing lag characteristics typical of original methodology
Multiplier Adjustment Functionality:**
↔ Allows fine-graining oscillator responsiveness without altering core relationship dynamics
↕ Enables adaptation to various instrument volatility profiles efficiently
Displacement Value Control:**
↓ Controls lead/lag offset positioning relative to current prices
↑ Provides flexibility in adjusting visual representation alignment preferences
DYNAMIC CALCULATION PROCESSES
💻 Algorithmic Foundation:
:
Utilizes highest/lowest extremes over specified lookback windows
Produces more responsive conversions compared to simple MAs
:
→ Confirms directional bias across multiple independent criteria
← Ensures higher probability outcomes reduce random noise influence
:
♾ Creates persistent annotations documenting significant events
🔄 Handles complex state transitions maintaining historical record integrity
VISUALIZATION COMPONENTS OVERVIEW
🎨 Display Architecture Details:
:
→ Solid colored trendlines representing conversion/base relationships
↑ Fill effect overlay differentiating expansion/compression phases
↔ Offset spans positioned according to calculated displacement values
:
→ Green shading indicates positive configuration scenarios
↘ Red filling highlights negative arrangement situations
⟳ Orange transition areas mark transitional periods requiring caution
:
✔️ LE: Long Entry opportunity confirmed
❌ SE: Short Setup validated
☑ XL/XS: Position closure triggers active
✓ RL/RS: Potential re-entry chances emerging
STRATEGIC APPLICATION FRAMEWORK
📋 Practical Deployment Guidelines:
Initial Integration Phase:
Select appropriate timeframe matching trading horizon preference
Configure input parameters aligning with target asset behavior traits
Test thoroughly under simulated conditions prior to live usage
Active Monitoring Procedures:
• Regular observation of cloud formation evolution
• Tracking label placements against actual price movements
• Noting pattern development leading up to signaled entry/exit moments
Decision Making Process Flowchart:
→ Identify clear breakout/crossover events exceeding confirmation thresholds
← Evaluate contextual factors supporting/rejecting indicated direction
↑ Execute trades only after achieving required number of confirming inputs
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Refinement Strategies:
Calibration Optimization Approach:
→ Start testing with default suggested configurations
↓ Gradually adjust individual components observing outcome changes
↑ Document findings systematically building personalized version profile
Context Adaptability Methods:
➕ Add supplementary indicators enhancing overall reliability
➖ Remove unnecessary complexity layers if causing confusion
✨ Incorporate custom rules adapting to specific security behaviors
Efficiency Improvement Tactics:
🔧 Streamline redundant processing routines where possible
♻️ Leverage shared data streams whenever feasible
⚡ Optimize refresh frequencies balancing update speed vs computational load
RISK MITIGATION PROTOCOLS
🛡️ Safety Measures Implementation Guide:
Position Sizing Principles:
∅ Never exceed preset maximum exposure limits defined by risk tolerance
± Scale positions proportionally per account size/market capitalization
× Include slippage allowances within planning stages accounting for liquidity variations
Validation Requirements Hierarchy:
☐ Verify signals meet minimum number of concurrent validations
⛔ Ignore isolated occurrences lacking adequate evidence backing
▶ Look for convergent evidence strengthening conviction level
Emergency Response Planning:
↩ Establish predefined exit strategies including trailing stops mechanisms
🌀 Plan worst-case scenario responses ahead avoiding panic reactions
⇄ Maintain contingency plans addressing unexpected adverse developments
USER EXPERIENCE ENHANCEMENT FEATURES
🌟 Additional Utility Functions:
Alert System Infrastructure:
→ Automatic notifications delivered directly to user devices
↑ Message content customized explaining triggered condition specifics
↔ Timing optimization ensuring minimal missed opportunities due to latency issues
Historical Review Capability:
→ Ability to analyze past performance retrospectively
↓ Assess effectiveness across varying market regimes objectively
↗ Generate statistics measuring success/failure rates quantitatively
Community Collaboration Support:
↪ Share personal optimizations benefiting wider trader community
↔ Exchange experiences improving collective understanding base
✍️ Provide constructive feedback aiding ongoing refinement process
CONCLUSION AND NEXT STEPS
This comprehensive guide serves as your roadmap toward mastering the capabilities offered by the L3 Ichimoku Fusion indicator effectively. Success relies heavily on disciplined application combined with continuous learning and adjustment processes throughout implementation journey.
Wishing you prosperous trading endeavors! 👋💰
ICT Swiftedge# ICT SwiftEdge: Advanced Market Structure Trading System
**Overview**
ICT SwiftEdge is a powerful trading system built upon the foundation of ICTProTools' ICT Breakers, licensed under the Mozilla Public License 2.0 (mozilla.org). This script has been significantly enhanced by to combine market structure analysis with modern technical indicators and a sleek, AI-inspired statistics dashboard. The goal is to provide traders with a comprehensive tool for identifying high-probability trade setups, managing exits, and tracking performance in a visually intuitive way.
**Credits**
This script is a derivative work based on the original "ICT Breakers" by ICTProTools, used with permission under the Mozilla Public License 2.0. Significant enhancements, including RSI-MA signals, trend filtering, dynamic timeframe adjustments, dual exit strategies, and an AI-style statistics dashboard, were developed by . We express our gratitude to ICTProTools for their foundational work in market structure analysis.
**What It Does**
ICT SwiftEdge integrates multiple trading concepts to help traders identify and manage trades based on market structure and momentum:
- **Market Structure Analysis**: Identifies Break of Structure (BOS) and Market Structure Shift (MSS) patterns, which signal potential trend continuations or reversals. BOS indicates a continuation of the current trend, while MSS highlights a shift in market direction, providing key entry points.
- **RSI-MA Signals**: Generates "BUY" and "SELL" signals when BOS or MSS patterns align with the Relative Strength Index (RSI) smoothed by a Moving Average (RSI-MA). Signals are filtered to occur only when RSI-MA is above 50 (for buys) or below 50 (for sells), ensuring momentum supports the trade direction.
- **Trend Filtering**: Prevents multiple signals in the same trend, ensuring only one buy or sell signal per trend direction, reducing noise and improving trade clarity.
- **Dynamic Timeframe Adjustment**: Automatically adjusts pivot points, RSI, and MA parameters based on the selected chart timeframe (1M to 1D), optimizing performance across different market conditions.
- **Flexible Exit Strategies**: Offers two user-selectable exit methods:
- **Trailing Stop-Loss (TSL)**: Exits trades when price moves against the position by a user-defined distance (in points), locking in profits or limiting losses.
- **RSI-MA Exit**: Exits trades when RSI-MA crosses the 50 level, signaling a potential loss of momentum.
- Users can enable either or both strategies, providing flexibility to adapt to different trading styles.
- **AI-Style Statistics Dashboard**: Displays real-time trade performance metrics in a futuristic, neon-colored interface, including total trades, wins, losses, win/loss ratio, and win percentage. This helps traders evaluate the system's effectiveness without external tools.
**Why This Combination?**
The integration of these components creates a synergistic trading system:
- **BOS/MSS and RSI-MA**: Combining market structure breaks with RSI-MA ensures entries are based on both price action (structure) and momentum (RSI-MA), increasing the likelihood of high-probability trades.
- **Trend Filtering**: By limiting signals to one per trend, the system avoids overtrading and focuses on significant market moves.
- **Dynamic Adjustments**: Timeframe-specific parameters make the system versatile, suitable for scalping (1M, 5M) or swing trading (4H, 1D).
- **Dual Exit Strategies**: TSL protects profits during trending markets, while RSI-MA exits are ideal for range-bound or reversing markets, catering to diverse market conditions.
- **Statistics Dashboard**: Provides immediate feedback on trade performance, enabling data-driven decision-making without manual tracking.
This combination balances technical precision with user-friendly visuals, making it accessible to both novice and experienced traders.
**How to Use**
1. **Add to Chart**: Apply the script to any TradingView chart.
2. **Configure Settings**:
- **Chart Timeframe**: Select your chart's timeframe (1M to 1D) to optimize parameters.
- **Structure Timeframe**: Choose a timeframe for market structure analysis (leave blank for chart timeframe).
- **Exit Strategy**: Enable Trailing Stop-Loss (`useTslExit`), RSI-MA Exit (`useRsiMaExit`), or both. Adjust `tslPoints` for TSL distance.
- **Show Signals/Labels**: Toggle `showSignals` and `showExit` to display "BUY", "SELL", and "EXIT" labels.
- **Dashboard**: Enable `showDashboard` to view trade statistics. Customize colors with `dashboardBgColor` and `dashboardTextColor`.
3. **Trading**:
- Look for "BUY" or "SELL" labels to enter trades when BOS/MSS aligns with RSI-MA.
- Exit trades at "EXIT" labels based on your chosen strategy.
- Monitor the statistics dashboard to track performance (total trades, win/loss ratio, win percentage).
4. **Alerts**: Set up alerts for BOS, MSS, buy, sell, or exit signals using the provided alert conditions.
**License**
This script is licensed under the Mozilla Public License 2.0 (mozilla.org). The source code is available for review and modification under the terms of this license.
**Compliance with TradingView House Rules**
This publication adheres to TradingView's House Rules and Scripts Publication Rules. It provides a clear, self-contained description of the script's functionality, credits the original author (ICTProTools), and explains the rationale for combining indicators. The script contains no promotional content, offensive language, or proprietary restrictions beyond MPL 2.0.
**Note**
Trading involves risk, and past performance is not indicative of future results. Always backtest and validate the system on your preferred markets and timeframes before live trading.
Enjoy trading with ICT SwiftEdge, and let data-driven insights guide your decisions!
Dskyz (DAFE) Turning Point Indicator - Dskyz (DAFE) Turning Point Indicator — Smart Reversal Signals
Inspired by the intelligent logic of a pervious indicator I saw. This script represents a next-generation reversal detection system—completely re-engineered with cutting-edge filters, adaptive logic, and intelligent dashboards.
The Dskyz (DAFE) Turning Point Indicator
🧠 What Is It?
is designed to identify key market reversal zones with extraordinary accuracy by combining trend direction, volatility confirmation, price action patterns, and smart filtering layers—all visualized in a highly interactive and informative chart overlay.
This isn’t just a signal generator—it’s a decision-making assistant.
⚙️ Inputs & How to Use Them
All input fields are grouped for ease-of-use and explanation:
🔸 Reversal Logic Settings
Source: The price source used for signal generation (default: hlcc4). Can be changed to any standard price formula (open, close, hl2, etc.).
ATR Period: Used for determining volatility and dynamic trailing stop logic.
Supertrend Factor / Period: Calculates directional movement to detect trending vs choppy zones.
Reversal Sensitivity Thresholds: Internal logic filters minor pullbacks from true reversals.
🔸 Filters
Trend Filter: Enables trend-only signals (optional).
Volume Spike Filter: Confirms reversals with significant volume activity.
Volatility Zone Coloring: Visually highlights high-volatility areas to avoid late entries or fakeouts.
Custom High/Low Detection: Smart local top/bottom scanning to reinforce accuracy.
🔸 Visual & Dashboard Options
Signal Labels: Toggle signal labels on the chart.
Color Theme: Choose your visual theme for easier visibility.
Dashboard Toggle: Activate a compact dashboard summarizing strategy health (win rate, drawdown, trend state, volatility).
🧩 Functions Used
ta.supertrend(): Determines trend direction for signal confirmation and filtering.
ta.atr(): Calculates real-time volatility to determine trailing stop exits and visual zones.
ta.rsi() (internally optimized): Helps filter overbought/oversold conditions.
Local High/Low Scanner: Tracks recent pivots using a custom dynamic lookback.
Signal Engine: Consolidates multiple confirmation layers before plotting.
🚀 What Makes It Unique?
Unlike traditional reversal indicators, this one combines:
Multi-factor signal validation: No single indicator makes the call—volume, trend, price action, and volatility all contribute.
Adaptive filtering: The indicator evolves with the market—less noise, smarter signals.
Visual volatility heatmap zones: Avoid entering during uncertainty or manipulation spikes.
Interactive trend dashboard: Immediate insight into the strength and condition of the current market phase.
Highly customizable: Turn features on/off to match your trading style—scalping, swing, or trend-following.
Precision timing: Uses optimized versions of RSI and ATR that adjust automatically with price context.
🧬 Recommended for:
Commodity: Futures, Forex, Crypto
Timeframes: 1m to 1h for active traders. 4h+ for swing trades.
Pair With: Support/resistance zones, Fibonacci levels, and smart money concepts for additional confluence.
🎯 Why It Works
- Traditional reversal signals suffer from lag and noise. This system filters both by:
- Using multi-source confirmation, not just price movement.
-Tracking volatility directly, not assuming static markets.
-Detecting exhaustion, not just divergence.
-Keeping your screen clean, with only the most relevant data shown.
🧾 Credit & Acknowledgement
🧠 Original Concept Inspiration: This project was deeply inspired by the work of Enes_Yetkin_ and their approach to reversal detection. This version expands on the concept with additional technical layers, updated visuals, and real-time adaptability.
📌 Final Thoughts
This is more than a reversal tool. It's a market condition interpreter, entry/exit planner, and risk assistant all in one. Every aspect is engineered to give you an edge—especially when timing means everything.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
Supply & Demand Zones + Order Block (Pro Fusion) - Auto Order Strategy Title:
Smart Supply & Demand Zones + Order Block Auto Strategy with ScalpPro (Buy-Focused)
📄 Strategy Description:
This strategy combines the power of Supply & Demand Zone analysis, Order Block detection, and an enhanced Scalp Pro momentum filter, specifically designed for automated decision-making based on high-volume breakouts.
✅ Key Features:
Auto Entry (Buy Only) Based on Breakouts
Automatically enters a Buy position when the price breaks out of a valid demand zone, confirmed by EMA 50 trend and volume spike.
Order Block Logic
Identifies bullish and bearish order blocks using consecutive candle structures and significant price movement.
Dynamic Stop Loss & Trailing Stop
Implements a trailing stop once price moves in profit, along with static initial stop loss for risk management.
Clear Visual Labels & Alerts
Displays BUY/SELL, Demand/Supply, and Order Block labels directly on the chart. Alerts trigger on valid breakout signals.
Scalp Pro Momentum Filter (Optimized)
Uses a modified MACD-style momentum indicator to confirm trend strength and filter out weak signals.
IU Bigger than range strategyDESCRIPTION
IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals.
USER INPUTS:
Look back Length: Number of candles to calculate the high-low range. Default is 22.
Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3.
Stop Loss Method: Choose between:(Default is "Previous High/Low")
- Previous High/Low
- ATR (Average True Range)
- Swing High/Low
ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14).
ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2).
Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2)
LONG CONDITION:
The current candle’s range (absolute difference between open and close) is greater than the previous range.
The closing price is higher than the opening price (bullish candle).
SHORT CONDITIONS:
The current candle’s range exceeds the previous range.
The closing price is lower than the opening price (bearish candle).
LONG EXIT:
Stop-loss:
- Previous Low
- ATR-based trailing stop
- Recent Swing Low
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
SHORT EXIT:
Stop-loss:
- Previous High
- ATR-based trailing stop
- Recent Swing High
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
ALERTS:
Long Entry Triggered
Short Entry Triggered
WHY IT IS UNIQUE:
This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios.
Multiple stop-loss methods provide flexibility for different trading styles and risk profiles.
The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making.
HOW USERS CAN BENEFIT FROM IT:
Ideal for breakout traders looking to capitalize on momentum-driven price moves.
Provides flexibility to customize stop-loss methods and fine-tune risk management parameters.
Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Supertrend Fixed TP Unified with Time Filter (MSK)Trend Strategy Based on the SuperTrend Indicator
This strategy is based on the use of the adaptive SuperTrend indicator, which takes into account the current market volatility and acts as a dynamic trailing stop. The indicator is visualized on the chart with colors that change depending on the direction of the trade: green indicates an uptrend (long), while red indicates a downtrend (short).
How It Works:
A buy signal (long) is generated when a bar closes above the indicator line.
A sell signal (short) is triggered when a bar closes below the indicator line.
Strategy Settings:
Trading Modes :
Long only : Only long positions are allowed.
Short only : Only short positions are allowed.
Both : Both types of trades are permitted.
Take-Profit :
The strategy supports a simple percentage-based take-profit, allowing you to lock in profits during sharp price movements without waiting for a pullback.
The take-profit level and its value are visualized on the chart. Visualization can be disabled in the settings.
Colored Chart Areas :
Long and short areas on the chart are highlighted with background colors for easier analysis.
Price Level :
You can set a price level in the settings to restrict trade execution:
Long trades are executed only above the specified level.
Short trades are executed only below the specified level.
This mode can be enabled or disabled in the parameters.
________________________________________________________________
Описание стратегии (на русском языке)
Трендовая стратегия на основе индикатора SuperTrend
Стратегия основана на использовании адаптивного индикатора SuperTrend , который учитывает текущую волатильность рынка и играет роль динамического трейлинг-стопа. Индикатор визуализируется на графике цветом, который меняется в зависимости от направления сделки: зелёный цвет указывает на восходящий тренд (лонг), а красный — на нисходящий тренд (шорт).
Принцип работы:
Сигнал на покупку (лонг) генерируется при закрытии бара выше линии индикатора.
Сигнал на продажу (шорт) возникает при закрытии бара ниже линии индикатора.
Настройки стратегии:
Режимы торговли :
Long only : только лонговые позиции.
Short only : только шортовые позиции.
Both : разрешены оба типа сделок.
Тейк-профит :
Стратегия поддерживает простой процентный тейк-профит, что позволяет фиксировать прибыль при резком изменении цены без ожидания отката.
Уровень и значение тейк-профита визуализируются на графике. Визуализацию можно отключить в настройках.
Цветные области графика :
Лонговые и шортовые области графика выделяются цветом фона для удобства анализа.
Уровень цены :
В настройках можно задать уровень цены, который будет ограничивать выполнение сделок:
Лонговые сделки выполняются только выше указанного уровня.
Шортовые сделки выполняются только ниже указанного уровня.
Этот режим можно включать или отключать в параметрах.
