Fractal - VA (Dynamic Wicks)This indicator, which we’ve developed as the Frectal - VA (Multi-Timeframe Visual Analytics), is designed for traders who utilize multi-timeframe analysis but want to keep their main chart clean of overlapping candles.
It functions as a Projected Dashboard, pulling price action from a higher timeframe (HTF) and rendering it as a set of dynamic, solid objects in the right-hand margin of your chart.
Core Philosophy
The "Frectal - VA" is built on the principle of Nested Structure. In professional trading, the "Value Area" or the "Fractal" of a higher timeframe often dictates the trend of the lower timeframe. By projecting these candles into the future (the right side of the chart), you can monitor HTF trend shifts, volatility, and candle closes without the HTF candles obscuring your current "live" price action.
Key Components
Decoupled Visualization: Unlike standard MTF indicators that overlay large boxes behind your current bars, this indicator creates a side-by-side comparison in the chart's whitespace.
Real-Time Data Streaming: It doesn't just show historical candles; the "lead" candle in the dashboard updates with every tick of the current price, showing you exactly how the higher timeframe candle is forming.
Dynamic Color Sync: The body, border, and wick of each projected candle are linked. If a 1-hour candle flips from bullish to bearish on a 5-minute chart, the entire dashboard object changes color instantly.
Customizable Offset: You control the "Drop" (Vertical Offset) and the "Margin" (Horizontal Offset). This allows you to tuck the indicator into a corner of your screen as a heads-up display (HUD).
Strategic Use Cases
Trend Confirmation: If you are trading a 1-minute "scalp" but the 15-minute dashboard shows a solid, large-bodied bearish candle, you are alerted to trade with the HTF momentum.
Volatility Monitoring: By observing the size of the wicks in the dashboard, you can see if the higher timeframe is experiencing "rejection" at certain levels, even if your local timeframe looks like a steady trend.
Visual Backtesting: Because it maintains a queue of the last
X
candles, you can see the immediate history of the HTF structure (e.g., a "Morning Star" pattern or "Engulfing" candles) at a glance.
Technical Specifications
Pine Script Version: v6 (latest standard).
Drawing Engine: Uses box and line arrays for high-performance rendering that doesn't lag the UI.
Memory Management: Automatically deletes old objects to stay within TradingView’s script limits, ensuring stability during long trading sessions.
趨勢分析
7 - 16 Trend Reversal CountThe indicator operates by counting consecutive price movements and is primarily divided into two main phases:
Phase 1: Counts to 9
Buy Setup (Downtrend): Completed when there are nine consecutive candles where the current bar's close is lower than the close four bars prior.
Sell Setup (Uptrend): Completed when there are nine consecutive candles where the current bar's close is higher than the close four bars prior.
The appearance of the number 9 suggests a short-term trend reversal is likely.
Phase 2: Counts to 13
This phase begins after a setup is completed and aims to find the point of total trend exhaustion.
A count of 13 is considered a powerful signal of an imminent, significant trend reversal.
Y'all know what it is.
Weekly Trend Eligibility PanelWeekly Trend Eligibility Panel
Weekly Trend Eligibility Panel is a read-only, context-first indicator designed to answer a simple but critical question:
“Is this stock structurally ready right now — or is the timing wrong?”
Many traders focus on what stock to watch. This tool focuses on when conditions are aligned.
What this indicator does
Evaluates a weekly-first set of trend and quality conditions
Summarizes results in a single, easy-to-read panel
Helps distinguish between:
Strong stocks at the wrong time, and
Stocks where multiple structural conditions are aligned
The panel reports:
Eligibility status (Eligible / Not Eligible)
How many conditions passed (all are required for eligibility)
A brief failure summary when conditions are not met
Optional tags showing which criteria are in effect
What makes it unique
Unlike traditional indicators that plot signals or overlays on price, this script acts as an eligibility checkpoint:
No entries, exits, or buy/sell signals
No performance claims or predictions
No need to interpret multiple lines or oscillators
Instead, it consolidates several weekly-based structural checks into a single decision-support panel, making it easier to avoid forcing trades when conditions are incomplete.
This is especially useful when a stock looks “right” fundamentally or technically, but broader trend, structure, or participation conditions are not yet aligned.
Important notes
Indicator only — no trade execution
Educational and informational use only
All calculations use confirmed bar data
Weekly data is requested with lookahead disabled
Results vary by symbol, timeframe, and settings
Intended use
Use this tool as a watchlist filter or timing aid, alongside your own analysis and risk management process — not as a standalone decision system.
Abde/Thomas Tages-Hoch/Tief + Session Hoch/Tief High Low From the Day
Session High Low from the Day
Is a Indictor for Scalping Timeframe 1 min
Multi-Timeframe Moving Average Tracker
Tracks user-defined higher timeframe moving averages on a 1-min chart (maybe higher?).
Useful to see where current price is in relation to a higher timeframe (e.g., 5-min, 1-hr) moving average like the 50 period. This allows the trader to determine size position risk based on personal rules (e.g., price below the 1-hr 40p EMA is high risk for lower price, so position size needs to be lightened, etc).
The higher timeframe moving average is live and plotted on the lower chart as a line (user-defined type and color) with the timeframe and period noted. It will move as the period closes (i.e., 5-min period closes every 5 minutes, 1-hr period closes every 60 minutes, etc.).
Directional Movement Index + MTF TableHey guys, just sharing a modified DMI-ADX indicator. The main addition is the Multi-Timeframe functionality, which helps filter out noise by showing higher TF trends. Credits to TradingView for the original source code. Hope you find it useful!
Playbook Regime &Setups PublicPlaybook (Public) is a market-structure and regime framework designed for intraday traders who want clearer context before taking discretionary entries. It classifies conditions as UP / DOWN / RANGE using EMA alignment and trend strength, then highlights breakout and pullback readiness in the direction of the active regime. A simple confidence score and session context are included to help filter lower-quality conditions. Market regime + setup readiness (breakout/pullback) with confidence & session context.
How to use
Start with the Regime (UP/DOWN/RANGE). Prioritize trades aligned with the regime.
Use Ready / Setup status as a qualification layer, not a standalone entry system.
Use Confidence as a filter (higher confidence = stronger trend alignment / separation).
If enabled, VWAP bias can be used as an additional directional filter.
Notes / limitations
Intended for intraday charts and liquid markets.
Signals are evaluated on bar close.
This script is a framework for context and qualification only. It is not financial advice.
True FVGsThis script highlights 3-candle Fair Value Gaps (FVGs) on your chart, showing areas where price moved quickly and left potential gaps in market structure. Bullish FVGs are shown with green boxes and suggest possible support, while bearish FVGs are shown with red boxes and suggest possible resistance. It also includes doji candles—very small-bodied candles that indicate indecision—so these patterns are not missed. The script displays the most recent 5 FVGs, making it easy to spot recent potential areas where price may react.
PSAR Laboratory [DAFE]PSAR Laboratory : The Ultimate Adaptive Trailing Stop & Reversal Engine
23 Advanced Algorithms. Adaptive Acceleration. Smart Flip Logic. Parabolic SAR Reimagined.
█ PHILOSOPHY: WELCOME TO THE LABORATORY
The standard Parabolic SAR, created by the legendary J. Welles Wilder Jr., is a tool of beautiful simplicity. But in today's complex, algorithm-driven markets, its simplicity is its fatal flaw. Its fixed acceleration and rigid flip logic cause it to fail precisely when you need it most: it whipsaws in choppy conditions and gives back too much profit in strong trends.
The PSAR Laboratory was not created to be just another PSAR. It was engineered to be the definitive evolution of Wilder's original concept. This is not an indicator; it is a powerful, interactive research environment. It is a sandbox where you, the trader, can move beyond the static "one-size-fits-all" approach and forge a PSAR that is perfectly adapted to your specific market, timeframe, and trading style.
We have deconstructed the very DNA of the Parabolic SAR and rebuilt it from the ground up, infusing it with modern quantitative techniques. The result is an institutional-grade suite of 23 distinct, mathematically diverse algorithms that dynamically control every aspect of the PSAR's behavior.
█ WHAT MAKES THIS A "LABORATORY"? THE CORE INNOVATIONS
This tool stands in a class of its own. It is a collection of what could be 23 separate indicators, all seamlessly integrated into one powerful engine.
The 23 Algorithm Engine: This is the heart of the Laboratory. Instead of one rigid formula, you have a library of 23 unique mathematical engines at your command. These algorithms are not simple tweaks; they are complete re-imaginings of how the PSAR should behave, based on concepts from information theory, digital signal processing, fractal geometry, and institutional analysis.
Truly Adaptive Acceleration (AF): The standard PSAR's "gas pedal" (the AF) is dumb; it accelerates at a fixed rate. Our algorithms make it intelligent. The AF can now speed up in clean, trending environments to lock in profits, and automatically slow down in choppy, chaotic conditions to avoid whipsaws.
Advanced Flip Confirmation Logic: Say goodbye to noise-driven flips. You are no longer at the mercy of a single wick touching the SAR. The Laboratory provides multiple layers of flip confirmation, including requiring a bar close beyond the SAR, a volume spike to validate the reversal, or even a multi-bar confirmation .
Comprehensive Noise Filtering Core: In a revolutionary step, you can apply one of over 30 advanced signal processing filters directly to the SAR output itself. From ultra-low-lag filters like the Hull MA and DAFE Spectral Laguerre to adaptive filters like KAMA and FRAMA , you can surgically remove noise while preserving the responsiveness of the core signal.
Integrated Performance Engine: How do you know which of the 23 algorithms is best for your market? You test it. The built-in Performance Dashboard is a comprehensive backtesting and analytics engine that tracks every trade, providing real-time data on Win Rate, Profit Factor, Max Drawdown, and more. It allows you to scientifically validate your chosen configuration.
█ A GUIDED TOUR OF THE ALGORITHMS: 23 PATHS TO AN EDGE
b]These 23 algorithms are not simple settings; they are distinct mathematical philosophies for how a Parabolic SAR should adapt to the market. They are grouped into three primary categories: those that adapt the Acceleration Factor (AF) , those that enhance the Extreme Point (EP) detection, and those that redefine the Flip Logic .
CATEGORY A: ACCELERATION FACTOR (AF) ADAPTATION
These algorithms dynamically change the "gas pedal" of the PSAR.
1. Volatility-Scaled AF
Core Concept: Treats volatility as market friction. The PSAR should be more forgiving in high-volatility environments.
How It Works: It calculates a Volatility Ratio by comparing the short-term ATR to the long-term ATR. If current volatility is high (ratio > 1), it reduces the AF Step. If volatility is low (ratio < 1), it increases the AF Step to trail tighter.
Ideal Use Case: The best all-rounder. Excellent for any market, especially those with clear shifts between high and low volatility regimes (like indices and crypto).
2. Efficiency Ratio (ER) AF
Core Concept: The PSAR should accelerate aggressively in clean, efficient trends and slow down dramatically in choppy, inefficient markets.
How It Works: It uses Kaufman's Efficiency Ratio (ER), which measures the net directional movement versus the total price movement. A high ER (near 1.0) signifies a pure trend, triggering a high AF multiplier. A low ER (near 0.0) signifies chop, triggering a low AF multiplier.
Ideal Use Case: Markets that alternate between strong trends and sideways chop. It is exceptionally good at surviving ranging periods.
3. Shannon Entropy AF
Core Concept: Uses Information Theory to measure market disorder. The PSAR should be conservative in chaos and aggressive in order.
How It Works: It calculates the Shannon Entropy of recent price changes. High entropy means the market is unpredictable ("chaotic"), causing the AF to slow down. Low entropy means the market is organized and trending, causing the AF to speed up.
Ideal Use Case: Advanced traders looking for a mathematically pure way to distinguish between a tradable trend and random noise.
4. Fractal Dimension (FD) AF
Core Concept: Measures the "jaggedness" or complexity of the price path. A smooth path is a trend; a jagged, space-filling path is chop.
How It Works: It calculates the Fractal Dimension of the price series. An FD near 1.0 is a smooth line (high AF). An FD near 1.5 is a random walk (low AF).
Ideal Use Case: Visually identifying the moment a smooth trend begins to break down into chaotic, unpredictable movement.
5. ADX-Gated AF
Core Concept: Uses the classic ADX indicator to confirm the presence of a trend before allowing the PSAR to accelerate.
How It Works: If the ADX value is above a "Strong" threshold (e.g., 25), the AF accelerates normally. If the ADX is below a "Weak" threshold (e.g., 15), the AF is "frozen" and will not increase, preventing the SAR from tightening up in a non-trending market.
Ideal Use Case: For classic trend-following purists who trust the ADX as their primary regime filter.
6. Kalman AF Estimator
Core Concept: A sophisticated signal processing algorithm that predicts the "true" optimal AF by filtering out price "noise."
How It Works: It treats the PSAR's AF as a state to be estimated. It makes a prediction, then corrects it based on how far the actual price deviates. It's like a GPS constantly refining its position. The "Process Noise" input controls how fast it thinks the AF can change, while "Measurement Noise" controls how much it trusts the price data.
Ideal Use Case: Smooth, high-inertia markets like commodities or major forex pairs. It creates an incredibly smooth and responsive AF.
7. Volume-Momentum AF
Core Concept: A trend's acceleration is only valid if confirmed by both volume and price momentum.
How It Works: The AF will only increase if a new Extreme Point is made on above-average volume AND the Rate of Change (ROC) of the price is aligned with the trend's direction.
Ideal Use Case: Any market with reliable volume data (stocks, futures, crypto). It's excellent for filtering out low-conviction moves.
8. Garman-Klass (GK) AF
Core Concept: Uses a more advanced, statistically efficient measure of volatility (Garman-Klass, which uses OHLC data) to adapt the AF.
How It Works: It modulates the AF based on whether the current GK volatility is higher or lower than its historical average. Unlike the standard Volatility-Scaled algo, it tends to slow down more in high volatility and speed up less in low volatility, making it more conservative.
Ideal Use Case: Traders who want a volatility-adaptive model that is more focused on risk reduction during volatile periods.
9. RSI-Modulated AF
Core Concept: The RSI can identify points of potential trend exhaustion or strong momentum.
How It Works: If a trend is bullish but the RSI enters the "Overbought" zone, the AF slows down, anticipating a pullback. Conversely, if the RSI is in the strong momentum mid-range (40-60), the AF is boosted to trail more aggressively.
Ideal Use Case: Mean-reversion traders or those who want to automatically loosen their trail stop near potential exhaustion points.
10. Bollinger Squeeze AF
Core Concept: A Bollinger Band Squeeze signals a period of volatility compression, often preceding an explosive breakout.
How It Works: When the algorithm detects that the Bollinger Band Width is in a "Squeeze" (below a certain historical percentile), it boosts the AF in anticipation of a fast move, allowing the PSAR to catch the breakout quickly.
Ideal Use Case: Breakout traders. This algorithm primes the PSAR to be maximally responsive right at the moment a breakout is most likely.
11. Keltner Adaptive AF
Core Concept: Keltner Channels provide a robust measure of a trend's "normal" volatility channel.
How It Works: When price is trading strongly outside the Keltner Channel, it's considered a powerful trend, and the AF is boosted. When price falls back inside the channel, it's considered a consolidation or pullback, and the AF is slowed down.
Ideal Use Case: Trend followers who use channel breakouts as their primary confirmation.
12. Choppiness-Gated AF
Core Concept: Uses the Choppiness Index to quantify whether the market is trending or consolidating.
How It Works: If the Choppiness Index is below the "Trend" threshold (e.g., 38.2), the AF is boosted. If it's above the "Range" threshold (e.g., 61.8), the AF is significantly reduced.
Ideal Use Case: A more responsive alternative to the ADX-Gated algorithm for distinguishing between trending and ranging markets.
13. VIDYA-Style AF
Core Concept: Uses a Chande Momentum Oscillator (CMO) to create a variable-speed acceleration factor.
How It Works: The absolute value of the CMO is used to create a dynamic smoothing constant. Strong momentum (high absolute CMO) results in a faster, more responsive AF. Weak momentum results in a slower, smoother AF.
Ideal Use Case: Momentum traders who want their trailing stop's speed directly tied to the momentum of the price itself.
14. Hilbert Cycle AF
Core Concept: Uses Ehlers' Hilbert Transform to extract the dominant cycle period of the market and synchronizes the PSAR with it.
How It Works: It dynamically adjusts the AF based on the detected cycle period (shorter cycles = faster AF) and can also modulate it based on the current phase within that cycle (e.g., accelerate faster near cycle tops/bottoms).
Ideal Use Case: Markets with clear cyclical behavior, like commodities and some forex pairs.
CATEGORY B: EXTREME POINT (EP) ENHANCEMENT
These algorithms make the detection of new highs/lows more intelligent.
15. Volume-Weighted EP
Core Concept: A new high or low is more significant if it occurs on high volume.
How It Works: It can be configured to only accept a new EP if the volume on that bar is above average. It can also "weight" the EP by volume, pushing it further out on high-volume bars.
Ideal Use Case: Filtering out weak, low-conviction price probes in markets with reliable volume.
16. Wavelet Filtered EP
Core Concept: Uses wavelet decomposition (a signal processing technique) to separate the underlying trend from high-frequency noise.
How It Works: It calculates a smoothed, wavelet-filtered version of the price. A new EP is only registered if the actual high/low significantly exceeds this smoothed baseline, effectively ignoring minor noise spikes.
Ideal Use Case: Noisy markets where small, insignificant wicks can cause the AF to accelerate prematurely.
17. ATR-Validated EP
Core Concept: A new EP should represent a meaningful move, not just a one-tick poke.
How It Works: It requires a new high/low to exceed the previous EP by a minimum amount, defined as a multiple of the current ATR. This ensures only volatility-significant advances are counted.
Ideal Use Case: A simple, robust way to filter out "noise" EPs and slow down the AF's acceleration in choppy conditions.
18. Statistical EP Filter
Core Concept: A new EP is only valid if the price change that created it is statistically significant.
How It Works: It calculates the Z-Score of the bar's price change relative to recent history. A new EP is only accepted if its Z-Score exceeds a certain threshold (e.g., 1.5 sigma), meaning it was an unusually strong move.
Ideal Use Case: For quantitative traders who want to ensure their trailing stop only tightens in response to statistically meaningful price action.
CATEGORY C: FLIP LOGIC & CONFIRMATION
These algorithms change the very rules of when and why the PSAR reverses.
19. Dual-PSAR Gate
Core Concept: Uses two PSARs—one fast and one slow—to confirm a reversal.
How It Works: A flip signal for the main PSAR is only considered valid if both the fast (sensitive) PSAR and the slow (structural) PSAR have flipped. This acts as a powerful trend filter.
Ideal Use Case: An excellent method for reducing whipsaws. It forces the PSAR to wait for both short-term and longer-term momentum to align before signaling a reversal.
20. MTF Coherence PSAR
Core Concept: Do not flip against the higher timeframe macro trend.
How It Works: It pulls PSAR data from two higher timeframes. A flip is only allowed if the new direction does not contradict the trend on at least one (or both) of those higher timeframes. It also boosts the AF when all timeframes are aligned.
Ideal Use Case: The ultimate tool for multi-timeframe traders who want to ensure their entries and exits are in sync with the bigger picture.
21. Momentum-Gated Flip
Core Concept: A reversal is only valid if it is supported by a significant surge of momentum.
How It Works: A price cross of the SAR is not enough. The script also requires the Rate of Change (ROC) to exceed a certain threshold for a set number of bars, confirming that there is real force behind the reversal.
Ideal Use Case: Filtering out weak, drifting reversals and only taking signals that are initiated with explosive power.
22. Close-Only PSAR
Core Concept: Wicks are noise; the bar's close is the final decision.
How It Works: This algorithm modifies the flip logic to ignore wicks. A flip only occurs if one or more bars close beyond the SAR line.
Ideal Use Case: One of the most effective and simple ways to reduce false signals from volatile wicks. A fantastic default choice for any trader.
23. Ultimate PSAR Consensus
Core Concept: The highest conviction signal comes from the agreement of multiple, diverse mathematical models.
How It Works: This is the capstone algorithm. It runs a "vote" between a selection of the top-performing algorithms (e.g., Volatility-Scaled, Efficiency Ratio, Dual-PSAR). A flip is only signaled if a majority consensus is reached. It can even weight the votes based on each algorithm's recent performance.
Ideal Use Case: For traders who want the absolute highest level of confirmation and are willing to accept fewer, but more robust, signals.
█ PART II: THE NOISE FILTERING CORE - The Shield
This is a revolutionary feature that allows you to apply a second layer of signal processing directly to the SAR line itself, surgically removing noise before the flip logic is even considered.
FILTER CATEGORIES
Basic Filters (SMA, EMA, WMA, RMA): The classic moving averages. They provide basic smoothing but introduce significant lag. Best used for educational purposes.
Low-Lag Filters (DEMA, TEMA, Hull MA, ZLEMA): A family of filters designed to reduce the lag inherent in basic moving averages. The Hull MA is a standout, offering a superb balance of smoothness and responsiveness.
Adaptive Filters (KAMA, VIDYA, FRAMA): These are "smart" filters. They automatically adjust their smoothing level based on market conditions. They will be very smooth in choppy markets and become highly responsive in trending markets.
Advanced DSP & DAFE Filters: This is the pinnacle of signal processing.
Ehlers Filters (SuperSmoother, 2-Pole, 3-Pole): Based on the work of John Ehlers, these use digital signal processing techniques to remove high-frequency noise with minimal lag.
Gaussian & ALMA: These use a bell-curve weighting, giving the most importance to recent data in a smooth, non-linear fashion.
DAFE Spectral Laguerre: A proprietary, non-linear filter that uses a feedback loop and adapts its "gamma" based on volatility, providing exceptional tracking in all market conditions.
How to Choose a Filter
Start with "None": First, find an algorithm you like with no filtering to understand its raw behavior.
Introduce Low Lag: If you are getting too many whipsaws from noise, apply a short-length Hull MA (e.g., 5-8). This is often the best solution.
Go Adaptive: If your market has very distinct trend/chop regimes, try an Adaptive KAMA .
Maximum Purity: For the smoothest possible output with excellent responsiveness, use the DAFE Spectral Laguerre or Ehlers SuperSmoother .
█ THE VISUAL EXPERIENCE: DATA AS ART
The PSAR Laboratory is not just functional; it is beautiful. The visualization engine is designed to provide you with an intuitive, at-a-glance understanding of the market's state.
Algorithm-Specific Theming: Each of the 23 algorithms comes with its own unique, professionally designed color palette. This not only provides visual variety but allows you to instantly recognize which engine is active.
Dynamic Glow Effects: For many algorithms, the PSAR dots will emit a soft "glow." The brightness and color of this glow are not random; they are tied to a key metric of the active algorithm (e.g., trend strength, volatility, consensus), providing a subtle, visual cue about the health of the trend.
Adaptive Volatility Bands: Certain algorithms will display dynamic bands around the PSAR. These are not standard deviation bands; their width is controlled by the specific logic of the active algorithm, showing you a visual representation of the market's expected range or energy level.
Secondary Reference Lines: For algorithms like the Dual-PSAR or MTF Coherence, a secondary line will be plotted on the chart, giving you a clear visual of the underlying data (e.g., the slow PSAR, the HTF trend) that is driving the decision-making process.
█ THE MASTER DASHBOARD: YOUR MISSION CONTROL
The comprehensive dashboard is your unified command center for analysis and performance tracking.
Engine Status: See the currently selected Algorithm, the active Noise Filter, the Trend direction, and a real-time progress bar of the current Acceleration Factor (AF).
Algorithm-Specific Metrics: This is the most powerful section. It displays the key real-time data from the currently active algorithm. If you're using "Shannon Entropy," you'll see the Entropy score. If you're using "ADX-Gated," you'll see the ADX value. This gives you a direct, quantitative look under the hood.
Performance Readout: When enabled, this section provides a full breakdown of your backtesting results, including Win Rate, Profit Factor, Net P&L, Max Drawdown, and your current trade status.
█ DEVELOPMENT PHILOSOPHY
The PSAR Laboratory was born from a deep respect for Wilder's original work and a relentless desire to push it into the 21st century. We believe that in modern markets, static tools are obsolete. The future of trading lies in adaptation. This indicator is for the serious trader, the tinkerer, the scientist—the individual who is not content with a black box, but who seeks to understand, test, and refine their edge with surgical precision. It is a tool for forging, not just following.
The PSAR Laboratory is designed to be the ultimate tool for that evolution, allowing you to discover and codify the rules that truly fit you.
█ DISCLAIMER AND BEST PRACTICES
THIS IS A TOOL, NOT A STRATEGY: This indicator provides a sophisticated trailing stop and reversal signal. It must be integrated into a complete trading plan that includes risk management, position sizing, and your own contextual analysis.
TEST, DON'T GUESS: The power of this tool is its adaptability. Use the Performance Dashboard to rigorously test different algorithms and settings on your chosen asset and timeframe. Find what works, and build your strategy around that data.
START SIMPLE: Begin with the "Volatility-Scaled AF" algorithm, as it is a powerful and intuitive all-rounder. Once you are comfortable, begin experimenting with other engines.
RISK MANAGEMENT IS PARAMOUNT: All trading involves substantial risk. The backtesting results are hypothetical and do not account for slippage or psychological factors. Never risk more capital than you are prepared to lose.
"I don't think traders can follow rules for very long unless they reflect their own trading style. Eventually, a breaking point is reached and the trader has to quit or change, or find a new set of rules he can follow. This seems to be part of the process of evolution and growth of a trader."
— Ed Seykota, Market Wizard
Taking you to school. - Dskyz, Trade with Volume. Trade with Density. Trade with DAFE
Luminous Market Flux [Pineify]Luminous Market Flux - Dynamic Volatility Channel with Breakout Detection
The Luminous Market Flux indicator is a sophisticated volatility-based trading tool that combines dynamic channel analysis with breakout detection and squeeze identification. This indicator helps traders visualize market conditions by creating an adaptive envelope around price action, highlighting periods of compression (low volatility) and expansion (high volatility) while generating actionable buy and sell signals at key breakout moments.
Key Features
Dynamic volatility channel that adapts to changing market conditions using ATR-based calculations
Visual squeeze detection system that warns traders when volatility is contracting
Automatic breakout signal generation for both bullish and bearish scenarios
Luminous gradient fill that provides instant visual feedback on price position within the channel
Bar coloring feature that highlights strong volatility breakouts
Built-in alert conditions for automated trading notifications
How It Works
The indicator operates on three core calculation layers:
1. Baseline Calculation (Central Tendency)
The foundation uses a Running Moving Average (RMA) of the closing price over the specified Flux Length period. RMA was specifically chosen over SMA or EMA because it provides smoother trend detection similar to how RSI and ATR calculations work, reducing noise while maintaining responsiveness to genuine price movements.
2. Volatility Measurement
The channel width is determined by the Average True Range (ATR) multiplied by the Flux Expansion Factor. ATR captures the true volatility of the market by accounting for gaps and limit moves, making the channel responsive to actual market conditions rather than just closing price variations.
3. Squeeze Detection Logic
The indicator compares the current channel width against a 100-period simple moving average of historical channel widths. When the current range falls below 80% of this average, a squeeze condition is identified, signaling that volatility is compressing and a significant move may be imminent.
Trading Ideas and Insights
Breakout Trading: Enter long positions when price breaks above the upper flux channel with a BUY signal, and short positions when price breaks below the lower channel with a SELL signal. These breakouts indicate strong momentum in the direction of the move.
Squeeze Anticipation: When squeeze circles appear at the top of the chart, prepare for a potential explosive move. Squeezes often precede significant breakouts as the market coils before releasing energy in one direction.
Trend Confirmation: Use the bar coloring feature to confirm trend strength. Colored bars indicate that price is trading outside the volatility envelope, suggesting strong directional momentum.
Mean Reversion: When price is within the channel (no bar coloring), the gradient fill helps identify whether price is closer to the upper or lower boundary, potentially useful for mean-reversion strategies.
How Multiple Indicators Work Together
This indicator integrates several technical concepts into a cohesive system:
The RMA baseline provides the trend anchor, while the ATR-based envelope adapts to volatility conditions. These two components work together to create a channel that expands during volatile periods and contracts during quiet markets. The squeeze detection layer adds a third dimension by comparing current volatility to historical norms, alerting traders when the market is unusually quiet.
The visual elements reinforce this analysis: the gradient fill shows price position within the channel at a glance, bar coloring confirms breakout strength, and shape markers provide discrete entry signals. This multi-layered approach ensures traders receive consistent information across different visualization methods.
Unique Aspects
The "Luminous" visual design uses color gradients that dynamically shift based on price position, creating an intuitive heat-map effect within the channel
Unlike traditional Bollinger Bands that use standard deviation, this indicator uses ATR for volatility measurement, making it more responsive to actual price range movements
The squeeze detection compares current volatility to a longer-term average (100 periods), providing context-aware compression signals rather than arbitrary thresholds
Signal generation uses proper state tracking to ensure breakout signals only fire on the initial breakout, not on every bar during an extended move
How to Use
Add the indicator to your chart. It will overlay directly on price with the volatility channel visible.
Watch for BUY labels appearing below bars when price breaks above the upper channel - these indicate bullish breakout opportunities.
Watch for SELL labels appearing above bars when price breaks below the lower channel - these indicate bearish breakout opportunities.
Monitor for small circles at the top of the chart indicating squeeze conditions - prepare for potential breakouts when these appear.
Use the colored bars as confirmation of breakout strength - green bars confirm bullish momentum, red bars confirm bearish momentum.
Set up alerts using the built-in alert conditions to receive notifications for buy signals, sell signals, and squeeze warnings.
Customization
Flux Length (default: 20): Controls the lookback period for both the baseline and ATR calculations. Lower values create more responsive but noisier channels; higher values create smoother but slower-reacting channels.
Flux Expansion Factor (default: 2.0): Multiplier for the ATR value that determines channel width. Higher values create wider channels with fewer signals; lower values create tighter channels with more frequent signals.
Smooth Signal : Toggle for signal smoothing preference.
Bullish Energy : Customize the color for bullish breakouts and upper channel highlights.
Bearish Energy : Customize the color for bearish breakouts and lower channel highlights.
Compression/Neutral : Customize the color for squeeze indicators and neutral channel states.
Conclusion
The Luminous Market Flux indicator provides traders with a comprehensive volatility analysis tool that combines channel-based trend detection, squeeze identification, and breakout signaling into a single, visually intuitive package. By using ATR-based volatility measurement and RMA smoothing, the indicator adapts to changing market conditions while filtering out noise. Whether you are a breakout trader looking for momentum entries or a swing trader waiting for volatility expansion after compression periods, this indicator offers the visual clarity and signal precision needed to make informed trading decisions.
XAUUSD: Ultimate Sniper v6.0 [Order Flow & Macro]This indicator is a comprehensive trading system designed specifically for XAUUSD (Gold). It moves away from lagging indicators by combining real-time Macro-Economic sentiment, Regression Analysis, and Institutional Order Flow logic into a single professional interface.
### Core Strategy & Features: 1. Macro Correlation Filter: Gold has a strong inverse correlation with the USD (DXY) and Treasury Yields (US10Y). This script monitors them in the background. If DXY/US10Y are Bullish, Gold Buy signals are filtered out to prevent trading against the trend. 2. Linear Regression Channel: Defines the "Fair Value" of price. We only look for reversal trades when price hits the extreme Upper or Lower bands. 3. Order Flow Pressure (New): Analyzes the internal structure of each candle (Wick vs Body). A signal is only confirmed if the "Buying Pressure" or "Selling Pressure" within the candle supports the move (e.g. >50%). 4. RSI Divergence: Automatically spots Bullish and Bearish divergences to identify momentum exhaustion.
### ⚙️ Recommended Settings / Best Practices To get the best results, adjust the settings based on your trading style:
🏎️ SCALPING (1min - 5min Charts) * Goal: Quick entries, smaller targets, higher frequency. * DXY/US10Y Timeframe: Set to "15" or "30" (Reacts faster to macro changes). * Regression Length: 50 or 80 (Adapts to short-term trends). * RSI Length: 9 or 14.
🛡️ INTRADAY (15min - 1h Charts) - * Goal: Balanced trading, capturing the daily range. * DXY/US10Y Timeframe: Set to "60" (1 Hour). * Regression Length: 100 (Standard setting). * RSI Length: 14.
🦅 SWING TRADING (4h - Daily Charts) * Goal: Catching major trend reversals. * DXY/US10Y Timeframe: Set to "240" (4 Hours) or "D" (Daily). * Regression Length: 200 (Long-term trend baseline). * Channel Width: Increase to 2.5 or 3.0.
### How to Trade: - BUY Signal: Valid when the Dashboard shows "BEARISH" DXY/US10Y and the Live Pressure is "BUYERS". - SELL Signal: Valid when the Dashboard shows "BULLISH" DXY/US10Y and the Live Pressure is "SELLERS". - Risk Management: The script automatically calculates ATR-based Stop Loss (SL) and Take Profit (TP) levels.
Impulse Trend Levels [BOSWaves]Impulse Trend Levels - Momentum-Adaptive Trend Detection with Impulse-Driven Confidence Bands
Overview
Impulse Trend Levels is a momentum-aware trend identification system that tracks directional price movement through adaptive confidence bands, where band width dynamically adjusts based on impulse strength and freshness to reflect real-time conviction in the current trend direction.
Instead of relying on fixed moving average crossovers or static band multipliers, trend state, band positioning, and zone thickness are determined through impulse detection patterns, exponential decay modeling, and volatility-normalized momentum measurement.
This creates dynamic trend boundaries that reflect actual momentum intensity rather than arbitrary technical levels - contracting during fresh impulse conditions when trend conviction is high, expanding during impulse decay periods when directional confidence weakens, and incorporating momentum freshness calculations to reveal whether trends are accelerating or deteriorating.
Price is therefore evaluated relative to bands that adapt to momentum state rather than conventional static thresholds.
Conceptual Framework
Impulse Trend Levels is founded on the principle that meaningful trend signals emerge when price momentum intensity reaches significant thresholds relative to recent volatility rather than when price simply crosses moving averages.
Traditional trend-following methods identify directional changes through price-indicator crossovers, which often ignore the underlying momentum dynamics and conviction levels that sustain those moves. This framework replaces static-threshold logic with impulse-driven band construction informed by actual momentum strength and decay characteristics.
Three core principles guide the design:
Trend direction should be determined by volatility-normalized momentum breaches, not simple price crossovers alone.
Band width must adapt to impulse freshness, reflecting real-time confidence in the current trend.
Momentum decay modeling reveals whether trends are maintaining strength or losing conviction.
This shifts trend analysis from static indicator levels into adaptive, momentum-anchored confidence boundaries.
Theoretical Foundation
The indicator combines exponential moving average smoothing, mean absolute deviation measurement, impulse detection methodology, and exponential decay tracking.
An EMA-based trend baseline provides directional reference, while Mean Absolute Deviation (MAD) offers volatility-normalized scaling for momentum measurement. Impulse detection identifies significant price movements relative to recent volatility, triggering fresh momentum readings that decay exponentially over time. Band multipliers interpolate between tight and wide settings based on calculated impulse freshness.
Four internal systems operate in tandem:
Trend Baseline Engine : Computes EMA-smoothed price levels for directional reference and band anchoring.
Volatility Measurement System : Calculates MAD to provide adaptive scaling that normalizes momentum across varying market conditions.
Impulse Detection Logic : Identifies volatility-normalized price movements exceeding threshold levels, capturing momentum intensity and direction.
Decay-Based Confidence Modeling : Applies exponential decay to impulse readings, converting raw momentum into time-weighted freshness metrics that drive band adaptation.
This design allows trend confidence to reflect actual momentum behavior rather than reacting mechanically to price formations.
How It Works
Impulse Trend Levels evaluates price through a sequence of momentum-aware processes:
Baseline Calculation : EMA smoothing of open and close creates a directional trend reference that filters short-term noise.
Volatility Normalization : MAD calculation over a specified lookback provides dynamic scaling for momentum measurement.
Raw Impulse Detection : Price change over impulse lookback divided by MAD creates volatility-normalized momentum readings.
Threshold-Based Activation : When normalized momentum exceeds threshold (1.0), impulse registers with absolute magnitude and directional sign.
Exponential Decay Application : Between impulse events, stored impulse value decays exponentially via configurable decay rate.
Freshness Conversion : Decaying impulse transforms into freshness metric (0-100%) representing current momentum conviction.
Adaptive Band Construction : Band multiplier interpolates between minimum (fresh) and maximum (stale) settings based on freshness, then scales MAD to determine band width.
Trend State Logic : Price crossing above upper band triggers bullish state; crossing below lower band triggers bearish state; state persists until opposite breach.
Signal Generation : Trend state switches from bearish to bullish produce buy signals; bullish to bearish switches produce sell signals.
Retest Identification : Price touching inner band edge after signal buffer period marks retests, with cooldown periods preventing excessive plotting.
Together, these elements form a continuously updating trend framework anchored in momentum reality.
Interpretation
Impulse Trend Levels should be interpreted as momentum-anchored trend confidence boundaries:
Bullish Trend State (Cyan) : Established when price closes above adaptive upper band, indicating upward momentum breach with associated confidence level.
Bearish Trend State (Magenta) : Established when price closes below adaptive lower band, signaling downward momentum breach with directional conviction.
Trend Cloud : Visual gradient zone displays between outer and inner band edges, with opacity reflecting current trend state and confidence.
Band Width Dynamics : Tighter bands indicate fresh impulse (high confidence), wider bands indicate impulse decay (reduced confidence).
▲ Buy Signals : Green upward triangles mark bullish trend state initiations at crossovers above upper band.
▼ Sell Signals : Red downward triangles mark bearish trend state initiations at crossovers below lower band.
✦ Retest Markers : Small diamonds identify price retouching inner band edge after sufficient buffer period from initial signal.
Retest Extension Lines : Horizontal projections from retest points extend forward, marking potential support/resistance levels.
Colored Candles : Optional bar coloring reflects current trend state for immediate visual reference. Note: The original chart candles must be disabled in chart settings for the trend-colored candles to display properly.
Impulse freshness, band width dynamics, and momentum normalization outweigh isolated price movements.
Signal Logic & Visual Cues
Impulse Trend Levels presents two primary interaction signals:
Buy Signal (▲) : Green label appears when trend state switches from bearish to bullish via upper band crossover, suggesting momentum shift to upside.
Sell Signal (▼) : Red label displays when trend state switches from bullish to bearish via lower band crossunder, indicating momentum shift to downside.
Retest detection provides secondary confirmation when price revisits inner band boundaries after signal buffer cooldown expires.
Alert generation covers trend state switches (long/short), retest occurrences, and impulse freshness decay below 50% threshold for systematic monitoring.
Strategy Integration
Impulse Trend Levels fits within momentum-informed and adaptive trend-following approaches:
Momentum-Confirmed Entries : Use band crossovers as high-probability trend initiation points where volatility-normalized momentum exceeded threshold.
Freshness-Based Position Sizing : Scale exposure based on impulse freshness - larger positions during fresh impulse periods, reduced sizing as impulse decays.
Band-Width Risk Management : Expect wider price ranges when bands expand during decay, tighter ranges when bands contract during fresh impulse.
Retest-Based Re-entry : Use inner band retests as lower-risk entry opportunities within established trends after initial signal cooldown.
Cloud-Aligned Directional Bias : Favor trades aligning with current trend state rather than counter-trend positions.
Multi-Timeframe Momentum Confirmation : Apply higher-timeframe impulse trend state to filter lower-timeframe entry precision.
Technical Implementation Details
Core Engine : EMA-based baseline with MAD volatility measurement
Impulse Model : Volatility-normalized momentum detection with directional sign capture
Decay System : Exponential decay application (0.8-0.99 range) with freshness conversion
Band Construction : Linear interpolation between min/max multipliers scaled by MAD
Visualization : Gradient-filled cloud zones with bar coloring and signal labels
Signal Logic : State-switch detection with retest buffer and cooldown mechanisms
Performance Profile : Optimized for real-time execution across all timeframes
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-trend detection for scalping with responsive impulse settings
15 - 60 min : Intraday momentum tracking with balanced decay characteristics
4H - Daily : Swing-level trend identification with sustained impulse persistence
Suggested Baseline Configuration:
Trend Length : 19
Impulse Lookback : 5
Decay Rate : 0.99
MAD Length : 20
Band Min (Fresh) : 1.5
Band Max (Stale) : 1.9
Signal Buffer Period : 10
Show Trend Cloud : Enabled
Color Bars : Enabled (requires disabling original chart candles in chart settings)
Show Buy/Sell Signals : Enabled
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volatility profile, momentum characteristics, and preferred signal frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Excessive signal noise : Increase Trend Length to demand smoother baseline crossovers or increase Impulse Lookback for less reactive momentum detection.
Missed momentum shifts : Decrease Impulse Lookback to capture shorter-term momentum changes or reduce Decay Rate to allow faster impulse fade.
Bands too tight/wide : Adjust Band Min and Band Max multipliers to modify confidence zone thickness across freshness spectrum.
Impulse decays too quickly : Increase Decay Rate toward 0.99 to sustain impulse readings longer between fresh events.
Impulse decays too slowly : Decrease Decay Rate toward 0.8 for faster momentum fade and more frequent band expansion.
Unstable volatility scaling : Increase MAD Length to smooth volatility measurement and reduce sensitivity to short-term spikes.
Too many retest markers : Increase retest cooldown period (55 bars hardcoded) or increase Signal Buffer Period to space out signals.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Trending markets with clear momentum phases and directional persistence
Instruments with consistent volatility characteristics where MAD scaling normalizes effectively
Momentum continuation strategies entering on fresh impulse signals
Trend-following approaches benefiting from adaptive confidence measurement
Reduced Effectiveness:
Choppy, range-bound markets with frequent whipsaw crossovers
Extremely low volatility environments where impulse threshold becomes difficult to breach
News-driven or gapped markets with discontinuous momentum patterns
Mean-reversion dominant conditions where momentum breaches quickly reverse
Consolidation and sideways price action where trend-following methodologies inherently struggle due to lack of sustained directional movement
Integration Guidelines
Confluence : Combine with BOSWaves structure, volume analysis, or traditional trend indicators
Freshness Respect : Trust signals occurring during high impulse freshness periods with contracted bands
Decay Awareness : Reduce position sizing or tighten stops as impulse decays and bands widen
Retest Utilization : Treat inner band retests as continuation confirmation rather than reversal signals
State Discipline : Maintain directional bias aligned with current trend state until opposite band breach occurs
Disclaimer
Impulse Trend Levels is a professional-grade momentum and trend analysis tool. It uses volatility-normalized impulse detection with exponential decay modeling but does not predict future price movements. Results depend on market conditions, volatility characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volume context, and comprehensive risk management.
FxShare - Trend MomentumThis one is just a clean background script. You can use it as an addition to your other indicators or if you just want:
a clean Trend Channel
a calm background
Momentum Strength meter panel.
It is based on our favorite accurate combo ATR, MACD and RSI mix . It has only one outside parameter for channel smoothing - 0-50 range. Use it, break it, improve it..
Supertrend + RSI + EMA + MACD - Fixed Single SignalMomentum trading with signals to add alerts and connect to API for Algo trading
Keltner-Aroon-EFI FlowKeltner-Aroon-EFI Flow (KAE)
KAE Flow is a quantitative composite indicator designed to identify dominant market trends by fusing three distinct dimensions of price action: Volatility, Trend Age, and Volume Pressure.
Unlike standard indicators that rely on a single data point (like a moving average crossover), KAE Flow aggregates three independent logic engines into a single normalized "Flow" score. This score is then smoothed using an Arnaud Legoux Moving Average (ALMA) to filter out noise while retaining responsiveness to genuine trend reversals.
This script operates strictly on the current chart timeframe, ensuring all signals are causal, non-repainting, and reliable for real-time analysis.
1. The Quantitative Engine (How it Works)
The indicator polls three separate components. Each component votes "1" (Bullish), "-1" (Bearish), or "0" (Neutral). These votes are averaged to create the raw signal.
K — Keltner Channels (Volatility Dimension)
Concept: Measures volatility expansion.
Logic: The script calculates Keltner Channels using an EMA center line and ATR bands.
Bullish (+1): Price closes above the Upper Channel.
Bearish (-1): Price closes below the Lower Channel.
This component ensures we only trade when price is breaking out of its expected volatility range.
A — Aroon (Trend Age Dimension)
Concept: Measures the strength and "freshness" of a trend.
Logic: We utilize the Aroon Up and Aroon Down metrics.
Bullish (+1): Aroon Up is greater than Aroon Down AND Aroon Up is > 70.
Bearish (-1): Aroon Down is greater than Aroon Up AND Aroon Down > 70.
This filters out weak or aging trends, ensuring the move has mathematical momentum.
E — Elder’s Force Index (Volume Dimension)
Concept: Measures volume-weighted price change.
Logic: We calculate the raw Force Index (Close - Close ) * Volume and smooth it with an EMA.
Bullish (+1): Smoothed EFI > 0.
Bearish (-1): Smoothed EFI < 0.
This component confirms that price movement is supported by actual volume flow (accumulation/distribution).
2. Signal Processing (ALMA Smoothing)
Raw aggregation can be noisy. The composite score is passed through an ALMA (Arnaud Legoux Moving Average) filter.
Why ALMA? It uses a Gaussian distribution to provide smoothness without the significant lag associated with SMA or EMA. This creates the "Flow" line that resists false flips during choppy consolidation.
3. How to Use
The indicator plots a signal line and dynamically colors the price bars and background to reflect the dominant bias.
Deep Blue (Bullish Flow): The KAE Score is > 0.1. All three engines (or the majority) are aligned bullishly. Traders typically look for long entries or hold existing long positions.
White (Bearish Flow): The KAE Score is < -0.1. The majority of engines detect bearish volatility and volume. Traders typically look for short entries.
Gray (Neutral): The score is between -0.1 and 0.1. The market is in equilibrium or transition. Trend-following strategies should be paused.
4. Configuration
Logic Engine: You can toggle individual components (K, A, or E) on or off to isolate specific market dimensions.
Smoothing: Adjust the ALMA Window and Offset to fine-tune the sensitivity of the signal line.
Lengths: Fully customizable periods for Keltner, Aroon, and EFI to adapt to different asset classes (e.g., Crypto vs. Forex).
Mean-Reversion Strategy (RSI + ATR) v1
Entry: Wait for RSI(10) to cross 35 (bullish) or 65 (bearish)
Stop-loss: 2.5 times current ATR away from entry
Take-profit: 4 times current ATR away from entry
Risk: 2% of account per trade
Skip trades if price moved >5% recently or volume is below average
Risk/Reward: You risk $1 to make $1.60 (1:1.6 ratio)
That's the complete strategy. Simple, rules-based, volatility-adjusted for crypto.
Future Swing [BigBeluga]🔵 OVERVIEW
Future Swing is a swing-based projection tool that estimates the potential size and price target of the next swing move using historical swing behavior.
Instead of predicting direction randomly, it analyzes completed swing legs, measures their percentage moves, and projects a statistically derived swing target into the future.
The indicator combines swing structure, high/low zones, volume context, and a real-time dashboard to help traders anticipate where price may travel next.
🔵 CONCEPTS
Swing Detection — Swing highs and lows are identified using a configurable lookback length.
Swing Percentage Tracking — Each completed swing leg is converted into a percentage move and stored.
Statistical Projection — Future swing size is estimated using Average, Median, or Mode of past swing percentages.
Directional Awareness — Projections adapt automatically based on current swing direction.
🔵 FEATURES
Historical Swing Sampling —
• Uses a user-defined number of completed swings.
• More samples = smoother projection, fewer samples = faster adaptation.
Future Swing Projection —
• Dashed line projects the estimated swing target forward in time.
• Projection distance is visual-only and does not affect calculations.
High/Low Swing Zones —
• Upper and lower swing zones expand using ATR distance.
• Zones visualize potential reaction and rejection areas.
Volume Context per Swing —
• Buy and sell volume are accumulated during each swing leg.
• Delta and total volume are displayed in the dashboard.
Smart Dashboard —
• Displays each stored swing percentage.
• Shows calculated swing projection value.
Flexible Projection Method —
• Average: smooth and balanced.
• Median: filters out extreme outliers.
• Mode: focuses on the most common swing size.
Extendable Zones —
• Swing zones can optionally extend forward indefinitely.
🔵 HOW TO USE
Anticipate Swing Targets — Use the projected swing line as a probabilistic price objective.
Combine with Structure — Align projections with support, resistance, or liquidity zones.
Filter by Volume — Confirm swing quality using delta and total volume metrics.
Adjust Sensitivity — Tune swing length and historical sample size to match timeframe and volatility.
Context, Not Certainty — Use projections as guidance, not fixed take-profit levels.
🔵 CONCLUSION
Future Swing transforms past swing behavior into a forward-looking projection model.
By combining swing structure, statistical aggregation, ATR zones, and volume analysis, it offers traders a structured way to estimate where the next meaningful price move may reach — without relying on fixed targets or subjective assumptions.
Multi-Timeframe EMA Bundle (576/676/144/169/12)A comprehensive EMA (Exponential Moving Average) indicator combining five key moving averages used by professional traders for trend identification and dynamic support/resistance levels.
Included EMAs:
EMA 576 & EMA 676 (Blue) — Long-term trend filters commonly used on lower timeframes to represent higher timeframe structure. Acts as major support/resistance zones.
EMA 144 & EMA 169 (White) — Mid-term trend indicators derived from Fibonacci numbers. When price respects this zone, it often signals strong trend continuation.
EMA 12 (Yellow) — Short-term momentum tracker for entries and exits. Useful for identifying pullback opportunities within the trend.
AI Adaptive Trend Navigator Strategy Echo EditionAI Adaptive Trend Navigator Strategy
This is a professional long-only automated strategy optimized for Taiwan Index Futures (TX). Based on the LuxAlgo clustering framework, this version features advanced logic iteration for institutional-grade backtesting and execution.
1. Realistic Cost Modeling To ensure backtest reliability, this strategy is pre-configured with:
Slippage: 2 ticks (Approx. 400 TWD per side).
Commission: 100 TWD per side.
Total Cost: 500 TWD per side. This provides a rigorous stress test for real-world trading environments.
2. State Consistency & Logic Continuity Optimized the underlying array handling to ensure "State Persistence." This eliminates the logic gaps common in real-time script execution, ensuring that historical signals are 100% consistent with live alerts.
3. Adaptive AI Clustering Utilizes K-means clustering to dynamically select the optimal ATR factors based on current market volatility, allowing the strategy to "evolve" as market regimes shift.
🧠 開發理念：追求實戰一致性的量化策略 本策略旨在為台指期（TX）提供一套具備真實參考價值的自動化系統。
✨ Echo 版核心優化點
數據連續性迭代：修正底層邏輯，確保訊號在即時盤勢中穩定不跳斷。
真實交易成本模擬：預設 2 點滑價 與 單邊 100 TWD 手續費，單邊總成本對標 500 TWD，拒絕虛假神單，挑戰最嚴苛的回測環境。
台指期專屬參數調校：融入針對台灣市場波動特性的預設參數與過濾邏輯。
🛡️ 進階實戰過濾
空間緩衝區 (Buffer Strategy)：價格需有效突破緩衝區才觸發，精準過濾盤整雜訊。
AI 信心評分系統：只有當動能穩定度達標時才會發進場訊號。
冷卻保護機制：有效抑制訊號在洗盤區間過度頻繁跳動。
⚠️ Disclaimer: Backtest results do not guarantee future performance.
Euro Day StrategyThis is a false breakout reversal strategy that fades short-term breakouts when they conflict with longer-term momentum. Here's the detailed breakdown:
Strategy Overview
Type: Counter-trend/Fade strategy disguised as breakout trading
Core Logic: Enter against immediate breakouts when longer-term momentum suggests the move is exhausted.
Strategy Classification
This is a FADE/EXHAUSTION strategy, NOT a breakout-following strategy
Enters against the immediate breakout direction
Bets on mean reversion when short-term price action diverges from longer-term momentum
Works best in ranging/choppy markets where breakouts frequently fail
Will get hurt in strong trending markets where breakouts are genuine
This strategy is designed for intraday mean-reversion trading on instruments that tend to range (likely forex or futures). It requires markets where false breakouts are common and price tends to snap back quickly.
MTF Equals v1.0MTF Equals is a professional-grade tool designed to identify significant price levels across multiple timeframes. It scans the current chart and higher timeframes (HTF) for identical highs and lows ("Equals"), which often act as price magnets or liquidity pools.
Key Features:
Multi-Timeframe Analysis: Automatically detects identical highs and lows on the current chart, as well as M5, M15, M30, H1, H4, and Daily.
NQ Auto-Detection: Specialized logic for Nasdaq (NQ) that automatically determines the ideal starting point for analysis based on volume, efficiency, and price density.
Live Statistics: Displays the number of touches and the bar distance from the first touchpoint directly on the price level.
Smart Cleaning: Levels are automatically removed once they are significantly breached by price, keeping your chart clutter-free.
Advanced Visuals: Fully customizable colors, line styles, and label positioning (e.g., Align to Margin).
How to use:
Perfect for spotting "Equal Highs/Lows" (Liquidity) or confirming institutional support and resistance zones.
AI Adaptive Trend Navigator Echo EditionAI Adaptive Trend Navigator
This is an advanced trend-following system optimized for high-volatility index futures (TX). Built upon the LuxAlgo clustering framework, this version introduces several critical enhancements to meet professional trading standards:
1. State Consistency Iteration Enhanced the underlying logic for dynamic arrays and User-Defined Types (UDTs) to ensure stable "State Persistence." This fix eliminates logic gaps during real-time price fluctuations, ensuring that historical backtests perfectly align with live execution.
2. Adaptive Factor Tuning (K-means) The system simulates dozens of parameter paths in real-time, using K-means clustering to automatically select the optimal factor suited for the current market volatility.
3. Advanced Practical Filters
Dynamic Buffer Strategy: Filters out market noise during consolidation and early session volatility.
Confidence Threshold: Only triggers signals when the AI performance score meets the required quality.
Cooldown Logic: Prevents rapid signal flipping in choppy markets.
🧠 開發理念：將 AI 自適應力帶入台指期實戰 針對台指期（TX）高波動特性開發，透過機器學習演算法動態尋優，解決傳統指標參數固定的滯後性。
✨ Echo 版核心優化點
數據連續性迭代：底層邏輯優化，確保訊號在即時盤勢中穩定不跳斷，回測與實戰高度吻合。
自適應動態尋優：透過 K-means 聚類自動鎖定當前最佳 ATR 因子。
實戰多重濾網：包含空間緩衝區 (Buffer) 與信心門檻，大幅提升訊號品質。
📊 視覺說明
🚀 Rocket: AI confirms trend momentum.
⚡ Lightning: Trend exhaustion or reversal warning.
⚠️ Disclaimer: For educational and technical analysis purposes only.
