Fractal ZigZag with Retest & Filters By WiselyWealthIndicator ; Fractal ZigZag with Retest & Filters
Introduction
Welcome to the comprehensive guide for the 'Fractal ZigZag with Retest & Filters' indicator. This custom-built Pine Script indicator is an advanced technical analysis tool designed explicitly for the PulseWire platform. At its core, the primary objective of this script is to provide traders with high-probability entry signals by systematically filtering out market noise, avoiding false breakouts, and ensuring alignment with the overarching macroeconomic trend.
Many retail traders fall into the trap of entering positions during sudden, volatile price spikes, only to suffer heavy drawdowns when the market naturally pulls back. This script mitigates that risk by enforcing a strict, rules-based approach: identifying structural shifts, confirming the initial breakout, and mathematically demanding a pullback (or "retest") before issuing a final trading signal. Additionally, it features built-in alert conditions, making it perfectly suited for algorithmic traders who wish to automate their strategies via Webhooks, Telegram bots, or MT5 API integrations.
Technical Mechanism
The mechanical operation of this script is multi-layered, relying on a confluence of structural mapping, trend filtering, and volatility-based retest calculations. Here is a detailed, step-by-step technical breakdown of how the script detects and generates its buy and sell signals:
Mapping Market Structure with Williams Fractals:The foundation of the script relies on identifying key swing highs and swing lows using Williams Fractals. By default, the indicator evaluates a 5-bar lookback and look-forward period to pinpoint these structural pivots. Once a valid upward or downward fractal is identified, the script connects them using a dynamic ZigZag line. This creates an unambiguous visual map of the market's underlying structure, cleanly displaying the sequence of higher highs or lower lows.
Initial Breakout Identification: The indicator actively monitors the current closing price in relation to the most recently confirmed fractal levels. A raw bullish breakout is registered the moment a candle closes definitively above the last established fractal high. Conversely, a raw bearish breakout is noted when the closing price drops below the most recent fractal low. To prevent redundant alerts, the script locks the current trend state upon a successful breakout.
The ATR-Based Retest Engine: This is the most sophisticated aspect of the indicator. When "Enable Retest Mode" is activated, the script refuses to issue an immediate entry signal at the exact moment of the breakout. Instead, it uses the Average True Range (ATR) over a 14-period lookback to measure current market volatility. For a bullish setup, it calculates a "Retest Target" by subtracting a user-defined ATR multiplier (default 1.0) from the breakout close price. It then starts a countdown timer, allowing a maximum number of candles (default 3) for the price to drop back down and touch this target. If the pullback is successful within the time limit, the raw buy signal is triggered. If the time expires without a retest, the setup is safely invalidated.
Macro Trend Filtering: Before finalizing any signal, the script consults a 200-period Exponential Moving Average (EMA). If the trend filter is enabled, a buy signal is entirely suppressed unless the closing price is strictly above the EMA200. Sell signals similarly require the price to remain below the EMA200. Users can also force the script into a "Buy Only" or "Sell Only" mode to align with their long-term directional bias.
How to Use and Best Practices
To extract maximum profitability and accuracy from this script, traders must apply the correct settings and deploy it in appropriate market environments.
Recommended Settings and Configuration:
Conservative Swing Trading: Ensure the EMA200 Trend Filter remains enabled to keep you on the side of institutional momentum. You may also want to increase the Fractal Periods from 5 to 7 or 9. This filters out minor price fluctuations and forces the script to base its breakouts on major structural swing points.
Retest Calibration for Volatility:** The default ATR multiplier is 1.0, and the wait limit is 3 candles. If you are trading on lower timeframes (e.g., 5-minute or 15-minute charts), breakouts can take slightly longer to retest. Consider increasing the "Max Candles to wait" to 5 or 6. For highly volatile assets, increasing the ATR Multiplier to 1.5 can help you secure a deeper, more favorable pullback entry.
Directional Lock: If higher timeframe analysis dictates a strong bull market, use the "Trade Direction" setting to restrict signals to "Buy Only," eliminating counter-trend noise during minor market corrections.
Suitable Markets and Timeframes:
Forex and Indices: This indicator performs exceptionally well on major Forex pairs (EUR/USD, GBP/JPY) and Global Indices (US30, NAS100) on the 1-Hour and 4-Hour timeframes. These assets heavily respect market structure, and liquidity grabs (retests) are highly common after structural breakouts.
Cryptocurrency: Bitcoin and Ethereum on the 15-minute to 1-Hour charts are excellent candidates, provided you adjust the ATR multiplier to account for crypto's volatile, whipsaw movements.
Markets to Avoid: Avoid using this script in heavily consolidated, range-bound, or sideways markets. Breakout and trend-continuation logic inherently struggles during prolonged periods of low volatility, where price chops indiscriminately around the 200 EMA without clear directional follow-through. Indicator
Poor trend[ALT_analyst]Poor trend
ATTENTION: This script is STRICTLY for market environment recognition (Regime Filter). It does NOT provide entry signals or trading recommendations.
■Overview
This indicator, "Poor trend ", is an administrative filter designed not to search for entry signals, but to logically validate and enforce the decision to "take no position."
In directional trading, significant drawdowns occur during low-quality, trendless environments. This script continuously quantifies market stagnation across five independent modules. By mathematically demonstrating the degradation of a directional edge, it provides an objective baseline to suppress unnecessary entries and avoid whipsaw losses.
■Mathematical Proof of Edge Degradation in "Poor Trends"
The mathematical edge of a directional strategy is governed by the Expected Value equation:
Expected Value = (Win Probability * Average Win) - (Loss Probability * Average Loss)
For directional trading (trend-following or breakout), a "Poor Trend" mathematically degrades this equation. When market action exhibits low volatility, restricted ranges, and low liquidity, the probability of a directional breakout (Win Probability) decreases. Simultaneously, the shrinking ATR compresses the potential profit margin (Average Win). As the Average Win approaches transaction costs (spread/commission) and the Win Probability drops, the Expected Value strictly converges toward a negative figure. This script objectively flags the exact parameters where this mathematical degradation occurs.
5 Danger Detection Modules (Calculation Logic & Output Examples)
The script evaluates five independent conditions to calculate a total "Danger Score" (0 to 5).
1. Lack of Trend (ADX)
Calculation Logic:
is_low_adx = adx < adx_threshold (Default: 20)
Why this calculation: The Average Directional Index (ADX) measures absolute trend strength. A value below 20 statistically demonstrates that price action is dominated by noise rather than a directional vector, lowering the Win Probability.
Actual Output Example: If the current ADX value is 15.5, the logic evaluates 15.5 < 20. This returns true (Boolean), adding 1 to the Danger Score.
2. Low Volume (SMA)
Calculation Logic:
is_low_vol = sma(volume, 20) < sma(volume, 50)
Why this calculation: Compares short-term versus long-term volume averages. A drop in short-term volume detects liquidity withdrawal from the market, mathematically increasing slippage risks and transaction costs.
Actual Output Example: If the 20-period SMA volume is 1,200 and the 50-period SMA is 1,500, the logic evaluates 1200 < 1500. This returns true, adding 1 to the Danger Score.
3. Volatility Shrinking (Z-Score)
Calculation Logic:
width_z = (st_width - width_mean) / width_std < 0.0
Why this calculation: Standardizes the current ATR band width against its 50-period history using a Z-score. A negative Z-score proves statistical volatility compression, severely limiting the Average Win potential.
Actual Output Example: If the current band width is 10, the 50-period mean is 15, and the standard deviation is 5. The Z-score is (10 - 15) / 5 = -1.0. Since -1.0 < 0.0, it returns true, adding 1 to the Danger Score.
4. Unstable Direction (Whipsaw)
Calculation Logic: flip_count >= whip_threshold (Default: 3)
Why this calculation: Counts how many times the Supertrend direction has flipped over the last 20 periods. Frequent flips empirically prove directional instability and high whipsaw risk.
Actual Output Example: If the Supertrend has changed direction 4 times within the last 20 bars, the logic evaluates 4 >= 3. This returns true, adding 1 to the Danger Score.
5. Price Stuck (Trapped Inside Bands)
Calculation Logic:
is_trapped = (high < upperBand) and (low > lowerBand)
Why this calculation: Confirms both the high and low of the current candle are completely confined within the ATR boundaries. This proves zero momentum exists to break statistical limits.
Actual Output Example: If the Upper Band is 110, Lower Band is 90, Candle High is 105, and Candle Low is 95. The logic evaluates (105 < 110) and (95 > 90). Both are true, returning true, adding 1 to the Danger Score.
■Visual & UI Specifications
Danger Ribbon: The space between the Normal and Inverse lines fills with color based on the Danger Score (1: Yellow to 5: Dark Red). A score of 0 ("PEACE") renders the ribbon fully transparent.
Sparse Labels: To eliminate chart clutter, status labels ("WAIT", "STOP", "MAX DANGER") are strictly plotted only on the exact bar where the Danger Score increases or resets to 0.
Dashboard Table: A real-time matrix at the bottom right displays the precise binary status ("DETECTED" or "CLEAR") of all 5 modules, providing instantaneous administrative clarity on market conditions.
■Operating Policy
When the Danger Score is active (Ribbon is colored, modules are DETECTED), the statistical Expected Value for directional trading is compromised. Utilize this indicator strictly as an objective administrative filter to halt new entries and justify capital preservation.
Disclaimer
The information and scripts provided in this publication are for educational and informational purposes only. They do not constitute financial, investment, or trading advice. Trading in financial markets involves a high degree of risk, and you may lose some or all of your capital. Past performance is not necessarily indicative of future results. The author assumes no responsibility or liability for any trading losses incurred as a result of using this script. Please conduct your own due diligence and make trading decisions at your own risk.
Indicator
Reversal Scalper 2.0- Adib NooraniReversal Scalper - Smoothed Stoch & ATR Trend Filter
Hey everyone, I originally put this script together to help me scalp XAUUSD and Indian equities on lower timeframes, specifically to solve a problem I was having with standard momentum oscillators.
We all know the main issue with using a regular Stochastic for scalping: it’s great for spotting exhaustion, but when a strong trend kicks in, the oscillator just stays pegged in the overbought or oversold zones. If you try to trade those reversal signals blindly, you just get run over by the trend.
To fix this, I created a mashup that combines a smoothed Stochastic with a custom ATR-based structural trend ribbon. The whole point of combining these two indicators is to use the ATR bands to define the actual market structure, and only take the Stochastic reversal signals when the trend filter confirms that the push is actually exhausted.
How the math works:
First, the bottom oscillator (what I call the Reversal Strength Meter) is based on a standard 8-period Stochastic. But to cut out the erratic noise you usually get on the 1m or 5m charts, I ran it through a 5-period Simple Moving Average. It gives a much cleaner read on momentum.
Second, the background trend filter uses a long-term ATR (100-period, halved) multiplied by a deviation factor (default is 3). The script looks back at recent swing highs and lows to project a volatility channel. I linked this channel to the bar colors so you don't need to look at messy lines on your chart.
How to trade with it:
If the price breaks hard outside the ATR channel, the candles change color (white for a strong push up, black for a strong push down). When you see this, it means the trend is expanding—do not look for reversals, even if the Stochastic is at an extreme.
For Longs: Wait for a strong downward push that turns the candles black. Let the smoothed Stochastic dip below the 20 level. You only enter long when the candles go back to their normal color (showing the structural selling pressure has stopped) AND the stochastic crosses firmly back up above 20.
For Shorts: Wait for a bullish push that turns the candles white. Let the stochastic ride up above 80. Your short trigger is when the candles return to normal and the stochastic crosses back down below 80.
I left the inputs open so you can adjust the Stochastic lengths and the ATR deviation factor depending on what timeframe or asset you are trading. Hope this helps you guys filter out the fake outs. Indicator
Directional PurityDirectional Purity
Rather than a simple standalone strategy, Directional Purity is a professional trend-filtering and directional stability engine designed to supercharge any existing trading strategy. It eliminates the fatal flaw of traditional indicators like ADX—which measure trend strength with significant lag—by equipping your strategy with a zero-lag, mathematically precise gauge of directional purity.
Traditionally, ADX relies on double-smoothed EMAs of directional movements, causing delayed responses to trend breakouts and exhaustion. Directional Purity resolves this by using the mathematical equivalence of Chande's CMO and Kaufman's Efficiency Ratio (ER) as a volatility index to dynamically adapt a 13-period VIDYA (Variable Index Dynamic Average) base.
By utilizing a telescoping sum optimization, this script is fully vectorized (loop-free), ensuring extremely fast execution on any time frame.
Features:
- Live Dashboard: Shows real-time market state (Trending Bullish, Trending Bearish, Ranging) and Trend Purity %.
- Visual Fills: Highlights ranging zones in gray to prevent overtrading.
- Built-in Alerts: Triggers for trend breakouts, entering ranges, and direction shifts.
``` Indicator
Indicator
Market Adaptive Trend [Interakktive]Market Adaptive Trend (MAT) is a diagnostic trend tool that re-tunes its own responsiveness to the live volatility regime — and shows you, in plain English, why it tightened or loosened.
Most "adaptive" trend tools hide their adaptation behind math you cannot audit. MAT does the opposite: it adapts AND it narrates. Every adjustment it makes is shown on the chart, in words, so you can see the reasoning rather than trust a black box.
This is a market-state diagnostic tool, not a signal generator.
█ THE CORE IDEA
A fixed-length moving average has one flaw: it responds the same way in calm markets and violent ones. In a clean trend it lags; in a chop it whipsaws. MAT addresses this by letting the live volatility regime govern how responsive the trend line is — the link most adaptive tools never expose.
MAT continuously measures relative volatility: current ATR divided by its own longer-run average. A reading near 1.00 means volatility is at this market's own baseline; above means more volatile than usual; below means calmer. That single ratio classifies the market into one of three regimes, and each regime changes how the line behaves.
█ THE THREE REGIMES
RIDING (calm) — Volatility below baseline. The line loosens and leans toward its slower estimate, so it rides a clean trend without being shaken out by minor noise.
TIGHTENING (balanced) — Volatility near baseline. The line sits in a balanced blend — neither chasing nor lagging — typical of coiling, pre-expansion conditions.
GUARDED (volatile / stretched) — Volatility above baseline. The line damps its response and becomes slow to flip, and candles tint amber as a caution that conditions are stretched and a flip here is lower-confidence.
█ HOW THE LINE IS BUILT
MAT blends a fast and a slow estimate of price. The blend weight is not fixed — it shifts with the regime above, scaled by an Adaptation Strength input (0 = a fixed blend, 1 = full regime governance). The blended target then drives the visible line through an error-feedback step, so the line moves toward its target proportionally rather than snapping. The calculation uses only confirmed historical data, contains no lookahead, and does not repaint.
█ THE HUD
A compact on-chart panel reports, in plain language:
- Trend — UP / DOWN
- Regime — RIDING / TIGHTENING / GUARDED, with a plain-English volatility descriptor (very calm → below normal → near normal → slightly elevated → high)
- Responsiveness — LOW / MED / HIGH (how reactive the line currently is)
- Read — a one-line summary of the current state
No raw scores are presented as the message — the panel is meant to be read at a glance.
█ HOW TRADERS USE MAT
MAT is designed to provide context, not entries. Common uses:
- Reading whether the current environment favours riding (RIDING) or caution (GUARDED)
- Avoiding low-confidence flips when the regime is GUARDED and conditions are stretched
- Using the regime read as a filter alongside your own entry method
- Framing trend direction with an honest sense of how much to trust it right now
█ SETTINGS OVERVIEW
Adaptive Baseline
- Source, Fast estimate length, Slow estimate length
- Adaptation Strength (how strongly the regime governs responsiveness)
Regime Governor
- Volatility baseline length, ATR length
- Calm threshold (below = RIDING), Volatile threshold (above = GUARDED)
Visual
- Adaptive line, Gradient fill, Edge glow, Color candles, Line width
HUD
- Show HUD, Position, Size
█ DISCLAIMER
This indicator is a market context and diagnostic tool only. It does not generate trade signals, entries, or exits. Past behaviour does not guarantee future price action. Always combine with independent analysis and proper risk management. Indicator
Peak Decoder v1.0Kurzbeschreibung:
Ein hochentwickelter, strukturbasierter Oszillator, der die relative Position des Preises innerhalb seiner aktuellen Handelsspanne entschlüsselt.
Das Tool identifiziert vollautomatisch die mathematischen und visuellen Scheitelpunkte (Peaks & Troughs) in den Extremzonen und filtert kurzfristiges Marktrauschen sowie Fehlausbrüche effektiv heraus.
Hauptfunktionen & Funktionsweise:Drei integrierte Sensitivitäts-Modi:
Über das Einstellungsmenü kann die Reaktivität des Algorithmus fliegend gewechselt werden:
Aggressiv: Extrem schnell, optimiert für das Scalping in kleinsten Zeiteinheiten.
Normal: Die ausgewogene Standard-Einstellung für das klassische Daytrading.
Passiv: Filtert starkes Rauschen heraus, ideal für die übergeordnete Trendbestimmung (HTF).
Intelligenter Bounce- & Wellenfilter: Der Indikator speichert Ausbrüche in den Extremzonen im Zwischenspeicher. Er wartet geduldig, bis eine Bewegung endgültig abgeschlossen ist. Entstehen tiefere Täler oder höhere Hochs innerhalb derselben Phase, wandert das Signal automatisch mit.
Striktes Wechselsystem: Die Logik erzwingt ein sauberes, alternierendes Signalmuster (Top ➔ Bottom ➔ Top). Dadurch werden mehrfache Fehlsignale auf derselben Seite in volatilen Seitwärtsphasen komplett eliminiert.
Präzise visuelle Signale: Bestätigte Wendepunkte werden mit dezenten Kreisen direkt auf der Wellenspitze markiert. Zur besseren Übersicht wird ein fetter Richtungspfeil horizontal (auf 3 Uhr) daneben platziert.
Anwendung im Trading:Der Oszillator dient als hervorragender Filter zur Bestimmung von Premium- (Überkauft) und Discount-Zonen (Überverkauft) im Rahmen von Smart Money Concepts (SMC) oder klassischen Marktstruktur-Strategien.
Rot (Oben): Potenzielle Erschöpfung der Käufer, Vorbereitung für Short-Setups.
Grün (Unten): Potenzielle Erschöpfung der Verkäufer, Vorbereitung für Long-Setups.
Enthält eine voll integrierte Alarm-Schnittstelle (alert()), die pro Bar-Close einmalig auslöst, sobald ein Peak final bestätigt wurde. Indicator
Bull vs Bear Candle CountBull vs Bear Candle Count
Bull vs Bear Candle Count is a market participation and directional bias indicator designed to measure whether buyers or sellers have been dominating recent price action.
Instead of relying on traditional moving averages or oscillators, this indicator simply analyzes the number of bullish and bearish candles over a customizable lookback period to determine whether the market environment is currently Bullish, Bearish, or Balanced. Based on the candle distribution, the indicator calculates net directional pressure and visually highlights shifts in market conditions.
Features:
• Customizable lookback period
• Bullish, Bearish, and Balanced market state detection
• Net Bias histogram for directional strength visualization
• Bull % and Bear % comparison lines
• Adjustable balanced threshold sensitivity
• Optional background highlighting based on market state
• State transition markers for environment changes
• Summary table displaying:
Bull count
Bear count
Doji count
Bull percentage
Current market state
Alerts Included:
• Bullish State Shift
• Bearish State Shift
• Balanced State Shift
Potential use cases:
• Identify directional market pressure
• Filter trades based on overall market environment
• Confirm trend continuation or weakening momentum
• Spot transitions between trending and balanced conditions
• Add confluence to existing strategies and systems
Interpretation:
Bullish
Bullish candles are dominating the selected lookback period
Bearish
Bearish candles are dominating the selected lookback period
Balanced
Bull and bear participation are relatively equal, potentially indicating consolidation or indecision
Bull vs Bear Candle Count is intended as a simple way to visualize market participation and directional behavior without introducing excessive complexity.
About TrendGenY Indicators
TrendGenY indicators are built from market experience, creative concepts, and a constant pursuit of unique perspectives. Rather than following conventional ideas, the focus is on uncovering alternative insights and viewing market behavior through different angles to bring greater clarity, deeper understanding, and help traders develop a more meaningful edge in the market. Indicator
ES Breakout Toolkit ADX Regime Filter Free=== PART OF THE ES BREAKOUT TOOLKIT ===
This is one of several free, standalone indicators that make up the ES Breakout Toolkit series. Each indicator isolates a single component used in the full ES London Breakout Pro strategy. They are designed to be useful on their own and educational for traders looking to filter trades by market regime using ADX.
=== WHAT THIS INDICATOR DOES ===
The ADX Regime Filter classifies the current market environment into three states: Flat/Choppy, Trending, and Overextended. It does this using the Average Directional Index (ADX) with configurable minimum and maximum thresholds that define a "sweet spot" where the market is trending enough to produce clean breakouts but not so extended that it is likely to reverse or stall.
The indicator plots ADX alongside DI+ and DI- lines, highlights the sweet spot zone between your min and max ADX values, and provides visual markers when ADX enters or exits each regime. DI crossovers are also marked to help identify directional shifts.
=== HOW TO USE IT ===
Apply this indicator to a separate pane below your chart. The shaded zone between the min and max ADX lines represents the regime where trend-following and breakout strategies tend to perform best. When ADX is below the minimum, the market is likely choppy and breakout signals are less reliable. When ADX is above the maximum, the trend may be overextended and new entries carry higher reversal risk.
The dashboard shows the current ADX value, regime classification, DI direction, DI spread, ADX slope, and an overall trade readiness assessment. The DI spread reading helps confirm whether the directional move has conviction — a narrow spread suggests indecision even if ADX is technically in range.
=== KEY FEATURES ===
- Three-state regime classification (Flat, Trending, Overextended)
- Configurable ADX sweet spot zone with visual fill
- DI+/DI- directional lines with crossover markers
- ADX slope tracking (rising vs falling momentum)
- Optional bar coloring by regime and direction
- Background shading by current state
- Dashboard with ADX, regime, direction, DI spread, slope, and trade readiness
- Alerts for regime transitions and DI crossovers
=== WHY ADX BOUNDARIES MATTER ===
Most traders using ADX only set a minimum threshold. However, extremely high ADX readings often indicate that a trend is mature and vulnerable to exhaustion. By defining both a floor and a ceiling, you can focus on the portion of the trend cycle where momentum is building rather than peaking. This indicator makes that concept visual and actionable.
=== ABOUT THE ES BREAKOUT TOOLKIT ===
This indicator is part of a free series that breaks down the building blocks of a London session ES futures breakout strategy. Other free indicators in the series cover session highlighting, consolidation range detection, breakout candle scanning, and momentum close analysis. Each is published separately on my profile.
The full ES London Breakout Pro indicator combines all of these components into a unified strategy with additional proprietary features including advanced risk management, trade qualification, and data tracking. It is available as an invite-only script on my profile. Use the access request instructions on that script's page if you are interested.
=== DISCLAIMER ===
This indicator is provided for educational and informational purposes only. It is NOT financial advice. It does not constitute a recommendation to buy, sell, or hold any financial instrument. Trading futures involves substantial risk of loss and is not suitable for all investors. Past performance of any indicator or strategy is not indicative of future results. Always conduct your own research and consult a qualified financial advisor before making any trading decisions. You are solely responsible for your own trading activity. Indicator
Indicator
Directional Bias Aggregator [JOAT]Directional Bias Aggregator
Introduction
The Directional Bias Aggregator is a sophisticated multi-timeframe bias scoring system designed to measure and aggregate directional conviction across multiple timeframes. This indicator solves the critical problem of conflicting signals across different timeframes by providing a weighted, systematic approach to bias analysis. Understanding the true directional bias requires looking beyond the current timeframe - professional traders always consider the bigger picture, and this tool brings that institutional approach to your trading.
This indicator is built for traders who understand that trends exist on multiple timeframes simultaneously and that the highest probability trades occur when these timeframes align. Whether you're a day trader needing higher timeframe context, a swing trader confirming trend direction, or a position trader assessing long-term bias, this aggregator provides the comprehensive directional intelligence needed to trade with confidence and clarity.
Why This Indicator Exists
Most traders struggle with timeframe analysis - they might see a bullish signal on the 15-minute chart but bearish conditions on the 4-hour, leading to confusion and poor decisions. This indicator addresses that problem by:
Multi-Timeframe Analysis: Evaluates bias across up to four timeframes simultaneously
Weighted Aggregation: Assigns importance to each timeframe based on trading style
Bias Scoring: Provides numerical bias scores (-100 to +100) for objective analysis
Alignment Detection: Identifies when multiple timeframes agree on direction
Trend Integration: Adds trend filter to prevent trading against major moves
Conviction Measurement: Quantifies the strength of directional bias
The aggregator transforms the complex, often subjective process of multi-timeframe analysis into an objective, systematic framework that can be consistently applied.
Core Components Explained
1. Single Timeframe Bias Calculation
Each timeframe's bias is calculated using multiple indicators:
// Single timeframe bias calculation
f_calc_bias(float src_close, float src_high, float src_low) =>
// MA trend component
float ma_fast = ta.ema(src_close, i_ma_fast)
float ma_slow = ta.ema(src_close, i_ma_slow)
float ma_diff = ma_slow != 0 ? (ma_fast - ma_slow) / ma_slow * 100 : 0
float ma_score = math.max(math.min(ma_diff * 10, 100), -100)
// Price position component
float price_pos = 0.0
if src_close > ma_fast and ma_fast > ma_slow
price_pos := 100
else if src_close < ma_fast and ma_fast < ma_slow
price_pos := -100
// ... additional price position logic
// RSI component
float rsi_val = ta.rsi(src_close, i_rsi_len)
float rsi_score = (rsi_val - 50) * 2
// MACD component
float macd_line = ta.ema(src_close, i_macd_fast) - ta.ema(src_close, i_macd_slow)
float macd_signal = ta.ema(macd_line, i_macd_sig)
float macd_hist = macd_line - macd_signal
float atr_val = ta.atr(14)
float macd_score = atr_val > 0 ? (macd_hist > 0 ?
math.min(macd_hist / atr_val * 50, 100) :
math.max(macd_hist / atr_val * 50, -100)) : 0
// Composite score
float composite = ma_score * 0.35 + price_pos * 0.30 + rsi_score * 0.15 + macd_score * 0.20
composite
Bias components:
MA Trend (35% weight): Fast/slow EMA relationship and slope
Price Position (30% weight): Price relative to moving averages
RSI Momentum (15% weight): RSI centered at 50 for directional bias
MACD Histogram (20% weight): Trend acceleration/deceleration
Score Range: -100 (strong bearish) to +100 (strong bullish)
Neutral Zone: Scores between -30 and +30 considered neutral
Each component contributes unique directional information for comprehensive analysis.
2. Multi-Timeframe Data Requests
The indicator requests bias calculations from multiple timeframes:
// Request bias from each timeframe
f_request_bias(string tf) =>
request.security(syminfo.tickerid, tf, f_calc_bias(close, high, low) ,
lookahead=barmerge.lookahead_on)
float bias_tf1 = f_request_bias(i_tf1) // Fastest timeframe
float bias_tf2 = f_request_bias(i_tf2) // Medium timeframe
float bias_tf3 = f_request_bias(i_tf3) // Slow timeframe
float bias_tf4 = f_request_bias(i_tf4) // Slowest timeframe
MTF features:
Configurable Timeframes: User-defined timeframe selection
Confirmed Bars: Uses previous bar to prevent repainting
Lookahead Management: Proper security request handling
Current TF Bias: Also calculates bias on current timeframe
Data Validation: Handles missing or invalid data gracefully
The MTF system ensures you always have the bigger picture context.
3. Weighted Aggregation System
Timeframes are weighted based on their importance:
// Normalize weights
float total_weight = i_w1 + i_w2 + i_w3 + i_w4
float w1_norm = total_weight > 0 ? i_w1 / total_weight : 0.25
float w2_norm = total_weight > 0 ? i_w2 / total_weight : 0.25
float w3_norm = total_weight > 0 ? i_w3 / total_weight : 0.25
float w4_norm = total_weight > 0 ? i_w4 / total_weight : 0.25
// Aggregate bias score
float aggregate_bias = nz(bias_tf1) * w1_norm + nz(bias_tf2) * w2_norm +
nz(bias_tf3) * w3_norm + nz(bias_tf4) * w4_norm
// Smoothed aggregate
float smooth_bias = ta.ema(aggregate_bias, 3)
Weighting features:
Customizable Weights: Assign importance to each timeframe
Automatic Normalization: Ensures weights sum to 100%
Default Weights: Higher weight to slower timeframes (15%, 25%, 30%, 30%)
Smoothing: EMA smoothing for cleaner signals
Flexibility: Adjust weights based on trading style
The aggregation system creates a single, unified bias score from all timeframes.
4. Bias Alignment Analysis
The indicator measures how many timeframes agree on direction:
// Count aligned timeframes
int bullish_count = 0
int bearish_count = 0
if nz(bias_tf1) > i_weak_thresh
bullish_count += 1
else if nz(bias_tf1) < -i_weak_thresh
bearish_count += 1
// Repeat for TF2, TF3, TF4...
// Alignment score (0-4)
int alignment_score = math.max(bullish_count, bearish_count)
// Alignment direction
int alignment_direction = bullish_count > bearish_count ? 1 :
bearish_count > bullish_count ? -1 : 0
// Perfect alignment check
bool perfect_bullish = bullish_count == 4
bool perfect_bearish = bearish_count == 4
Alignment features:
Alignment Score: Number of timeframes agreeing (0-4)
Alignment Direction: Overall consensus direction
Perfect Alignment: All timeframes agree (strongest signal)
Weak Threshold: Minimum bias for alignment (default 30)
Mixed Signals: When timeframes disagree (lower confidence)
Higher alignment scores indicate higher probability setups.
5. Trend Filter Integration
An optional trend filter prevents trading against major moves:
// Trend filter
float trend_ma = ta.ema(close, i_trend_ma)
bool above_trend = close > trend_ma
bool below_trend = close < trend_ma
float trend_distance = trend_ma != 0 ? (close - trend_ma) / trend_ma * 100 : 0
// Trend-adjusted bias
float trend_adjusted_bias = smooth_bias
if i_use_trend
if above_trend and smooth_bias > 0
trend_adjusted_bias := smooth_bias * (1 + i_trend_weight)
else if below_trend and smooth_bias < 0
trend_adjusted_bias := smooth_bias * (1 + i_trend_weight)
else if above_trend and smooth_bias < 0
trend_adjusted_bias := smooth_bias * (1 - i_trend_weight * 0.5)
else if below_trend and smooth_bias > 0
trend_adjusted_bias := smooth_bias * (1 - i_trend_weight * 0.5)
Trend filter features:
Trend MA: Long-term moving average (default 200)
Trend Weight: Bonus for trading with trend (default 20%)
Penalty System: Reduces bias when trading against trend
Trend Distance: Measures how far price is from trend
Optional: Can be disabled for counter-trend strategies
The trend filter adds an extra layer of confirmation for directional bias.
6. Conviction and Consistency Metrics
The indicator measures the strength and stability of bias:
// Confluence quality
float confluence_quality = (float(alignment_score) / 4.0) *
(math.abs(smooth_bias) / 100.0) * 100
// Bias conviction score
float conviction_score = 0.0
conviction_score += float(alignment_score) * 15 // Max 60
conviction_score += math.abs(smooth_bias) * 0.3 // Max 30
if i_use_trend
if (above_trend and smooth_bias > 0) or (below_trend and smooth_bias < 0)
conviction_score += 10 // Trend alignment bonus
conviction_score := math.min(conviction_score, 100)
// Bias consistency
var int bias_consistency_counter = 0
if smooth_bias > i_weak_thresh and smooth_bias > i_weak_thresh
bias_consistency_counter := math.min(bias_consistency_counter + 1, 20)
else if smooth_bias < -i_weak_thresh and smooth_bias < -i_weak_thresh
bias_consistency_counter := math.min(bias_consistency_counter + 1, 20)
else
bias_consistency_counter := math.max(bias_consistency_counter - 1, 0)
float bias_consistency = float(bias_consistency_counter) / 20.0 * 100
Quality metrics:
Confluence Quality: Combines alignment and strength (0-100%)
Conviction Score: Overall signal strength (0-100)
Bias Consistency: How stable the bias has been (0-100%)
Momentum: Rate of change in bias
Acceleration: Change in bias momentum
These metrics help assess signal reliability and persistence.
Visual Elements
Bias Histogram: Main bias display with gradient coloring
Conviction Ribbon: Visual representation of conviction strength
MTF Breakdown Lines: Individual timeframe bias lines
Alignment Markers: Diamonds for perfect alignment
Momentum Plot: Bias momentum visualization
Background Colors: Regime-based background shading
Dashboard: Comprehensive metrics panel
Glow Effects: Intensity-based visual enhancements
The dashboard displays:
1. Individual timeframe biases and weights
2. Aggregate bias and trend-adjusted bias
3. Alignment score and direction
4. Confluence quality percentage
5. Conviction score and consistency
6. Bias momentum and acceleration
7. Trend filter status and distance
8. Signal strength and recommendations
Input Parameters
Timeframe Settings:
Timeframe 1-4: Individual timeframes for analysis
Default: 15m, 60m, 240m, Daily
Flexible: Can be any valid timeframe combination
Weighting Settings:
TF1-TF4 Weights: Individual importance weights
Default: 15%, 25%, 30%, 30% (favoring slower timeframes)
Total: Automatically normalized to 100%
Calculation Settings:
Fast/Slow MA: Bias calculation periods (default: 8/21)
RSI Period: Momentum oscillator (default: 14)
MACD Settings: Fast/Slow/Signal (default: 12/26/9)
Threshold Settings:
Strong Bias Threshold: Strong signal level (default: 60)
Weak Bias Threshold: Minimum bias for alignment (default: 30)
Trend Weight: Bonus for trend alignment (default: 20%)
How to Use This Indicator
Step 1: Analyze Individual Timeframes
Check the dashboard to see bias on each timeframe. Look for consistency - if most timeframes show the same direction, confidence is higher.
Step 2: Check Aggregate Bias
The aggregate bias provides a unified directional score. Values above 60 indicate strong bullish bias, below -60 indicate strong bearish bias.
Step 3: Verify Alignment
Higher alignment scores (3-4 timeframes) offer the highest probability setups. Perfect alignment (4/4) often precedes strong moves.
Step 4: Assess Conviction
High conviction scores (>75%) indicate strong, consistent bias. Low conviction (<50%) suggests uncertainty - wait for clarity.
Step 5: Consider Trend Filter
If enabled, ensure bias aligns with the major trend. Trading against the trend reduces conviction and increases risk.
Step 6: Monitor Momentum
Accelerating bias in the direction of alignment suggests the move is gaining strength. Decelerating bias warns of potential reversals.
Best Practices
Perfect alignment (4/4) provides the highest probability setups
Higher timeframe bias should generally override lower timeframe signals
Increasing conviction scores suggest strengthening trends
Divergence between timeframes often precedes reversals
Use the trend filter unless you're specifically trading counter-trend setups
Bias consistency is key - look for stable, persistent bias
Sudden changes in aggregate bias often signal regime shifts
Combine with price action for optimal entry timing
Adjust timeframe weights based on your trading style
Keep a bias journal to track how different instruments behave
Trading Applications
Trend Following:
Enter when bias > 60 on at least 3 timeframes
Add to positions as conviction increases
Stay in trades as long as bias remains aligned
Exit when bias weakens or reverses on slower timeframes
Mean Reversion:
Look for extreme bias (>80 or <-80) on faster timeframes
Enter when faster timeframe bias opposes slower timeframe
Target mean reversion to neutral bias levels
Quick exits - don't fight the longer-term bias
Breakout Trading:
Wait for bias alignment across all timeframes
Enter on breakouts with supporting bias momentum
Use wider stops due to potential volatility
Scale out as bias reaches extreme levels
Strategy Integration
This indicator enhances any trading system:
Use as a directional filter for existing strategies
Import aggregate bias for trend confirmation
Use alignment score as signal strength filter
Apply conviction scoring for position sizing
Integrate trend filter for additional safety
Export individual timeframe biases for custom logic
Technical Implementation
Built with Pine Script v6 featuring:
Multi-timeframe bias calculation with proper security requests
Weighted aggregation system with automatic normalization
Advanced alignment detection with perfect alignment alerts
Trend filter integration with adjustable weighting
Conviction and consistency scoring systems
Momentum and acceleration analysis
Comprehensive visualization with multi-layer effects
Real-time dashboard with 12 key metrics
Alert conditions for all major bias events
Export functions for strategy integration
The code uses confirmed bars and proper lookahead management to prevent repainting.
Originality Statement
This indicator is original in its comprehensive approach to multi-timeframe bias aggregation and scoring. While individual components (moving averages, RSI, MACD) are established tools, this indicator is justified because:
It synthesizes bias analysis across multiple timeframes into a unified scoring system
The weighted aggregation allows customization based on trading style and preferences
Alignment detection provides objective measures of timeframe consensus
The conviction scoring system quantifies signal strength and reliability
Trend filter integration adds an extra layer of confirmation
Consistency analysis identifies stable, persistent bias versus noisy fluctuations
The dashboard presents complex multi-timeframe analysis in an accessible format
Export functions enable integration with any trading system
Each timeframe contributes unique context: faster timeframes show immediate bias, slower timeframes show established trends
The indicator solves the real problem of conflicting signals across timeframes through systematic aggregation
The indicator's value lies in transforming the complex, often confusing world of multi-timeframe analysis into a clear, objective system that traders can use to make informed decisions with confidence.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Multi-timeframe analysis is a tool for understanding market context, not a prediction system.
Bias can change suddenly due to news events, economic data, or changes in market structure. Past bias patterns do not guarantee future behavior. The indicator's signals are mathematical calculations based on historical patterns and should be used in conjunction with other forms of analysis.
Always use proper risk management, including stop losses and position sizing appropriate for your account and risk tolerance. Strong bias alignment does not guarantee success - markets can remain irrational longer than you can remain solvent.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
Indicator
Strategic Trend FilterStrategic Trend Filter (STF) | MisinkoMaster
Strategic Trend Filter is a structurally weighted trend confirmation overlay designed to identify high-quality directional environments while filtering out low-volatility noise and weak structural movement.
Rather than relying on traditional moving averages, STF constructs a dynamically weighted equilibrium level derived from multiple price components and structural factors. It then validates trend conditions only when price displacement is supported by sufficient volatility expansion.
The result is a disciplined trend filter that emphasizes structural strength over simple price crossing behavior.
Core Philosophy
Many trend tools respond primarily to price direction. STF goes further by incorporating:
• Structural correlation behavior
• Statistical dispersion
• Rate-of-change magnitude
• Price range positioning
• Volatility confirmation
This multi-factor structure allows the filter to respond only when price movement demonstrates internal coherence and sufficient expansion.
In short, STF is designed to confirm quality trends, not just directional movement.
Key Features
Multi-factor structural weighting model
Dynamic equilibrium filter instead of traditional moving average
Volatility-confirmed trend validation
Volume-aware filter stabilization
Median-based volatility confirmation
Automatic trend coloring
Optional on-chart long and short labels
Overlay design for direct price interaction
Reduced whipsaws in low-volatility environments
Suitable as a directional bias filter for strategies
How It Works (Conceptual)
The indicator builds a composite equilibrium level using several internal components:
Structural Correlation
Measures how individual price components relate to the composite price structure over the lookback window.
Statistical Dispersion
Standard deviation measurements help evaluate how far price is distributing around equilibrium.
Momentum Magnitude
Absolute rate-of-change calculations measure directional displacement strength.
These components are combined into weighted factors that influence how much each price dimension contributes to the final filter value.
The resulting filter represents a dynamic structural equilibrium rather than a simple average.
Additionally, a volatility confirmation layer compares current true range behavior against its median condition. Trend state changes are validated only when sufficient volatility is present.
Proprietary weighting relationships remain protected in the invite-only implementation.
Trend Logic Explained
Bullish State
Activated when price structure holds above the dynamic filter and volatility confirms expansion. This suggests sustained upward pressure supported by structural alignment.
Bearish State
Activated when price structure remains below the filter and volatility confirms expansion. This indicates organized downside movement rather than random fluctuation.
If volatility contracts or price fails to maintain structural positioning, the filter avoids unnecessary state changes.
Volume Stabilization Mechanism
When volume declines relative to the previous bar, the filter stabilizes temporarily. This reduces sensitivity during participation drops, helping avoid false transitions caused by thin liquidity conditions.
This feature improves robustness in lower-liquidity assets and during session transitions.
Visual Components
Dynamic Filter Line
Represents structural equilibrium and adjusts continuously to price behavior.
Color-Coded Environment
Filter and candles change color to reflect bullish or bearish state.
Shaded Region
A filled zone between price and filter visually highlights directional dominance.
Optional Long / Short Labels
When enabled, transition points are clearly marked on the chart.
Inputs Overview
Lookback Period
Controls the primary structural evaluation window. Higher values create smoother, more stable filters. Lower values increase responsiveness.
Confirmation Length
Defines the volatility median window used for expansion validation.
Allow Labels?
Enables or disables on-chart long and short markers.
Parameter Tuning Guidance
Shorter Lookback
→ Faster adaptation
→ More sensitive to structural shifts
→ Suitable for lower timeframes
Longer Lookback
→ More stable equilibrium
→ Better for swing or position trading
Shorter Confirmation Length
→ Faster volatility confirmation
→ More reactive signals
Longer Confirmation Length
→ Stricter volatility validation
→ Fewer but stronger transitions
Best Use Cases
Directional bias filter for breakout systems
Confirmation layer for momentum strategies
Trend qualification before position scaling
Volatility-aware trade filtering
Multi-timeframe bias alignment
Portfolio-level environment scanning
Strategy Integration Ideas
Use STF to:
• Trade only in the direction of confirmed trend state
• Avoid mean-reversion setups during strong structural expansion
• Filter out low-volatility consolidation phases
• Improve win rate by aligning entries with structural bias
STF performs best when paired with entry triggers such as pullbacks, continuation patterns, or momentum expansions.
Summary
Strategic Trend Filter is a structurally weighted, volatility-confirmed overlay designed to detect organized directional movement while filtering weak or noisy price action.
By combining correlation structure, dispersion metrics, momentum magnitude, and volatility validation, STF delivers a disciplined trend confirmation framework suitable for discretionary traders and systematic strategy developers alike. Indicator
Market Force Oscillator Elite ProMarket Force Oscillator Elite Pro is a single-pane oscillator that combines acceleration, volume-weighted force, trend alignment, divergence logic, and multi-method cycle diagnostics.
How components work together:
- Force engine estimates buy/sell pressure from candle position, relative volume weighting, and optional momentum factor.
- Oscillator core combines acceleration with force and normalizes using robust scale logic (stdev with MAD fallback when stdev is unstable).
- Dynamic levels compute adaptive OB/OS using ATR percent with timeframe-aware auto calibration and a soft-cap transform.
- Trend filter compares LTF and HTF EMA direction before allowing directional signals.
- Signal quality gate combines oscillator magnitude, relative volume, and optional alignment weighting.
- Divergence module uses confirmed pivots with one-shot/cooldown modes.
- Cycle module computes Original Ehlers, Zero-Crossing, Peak-to-Peak, Autocorrelation, and Composite estimates.
What is new/original in this version (from current code):
- Multi-method cycle detector with Composite mode.
- Timeframe-aware ATR auto calibration for dynamic OB/OS behavior.
- ATR soft-cap compression to avoid overly wide bands on higher timeframes.
- Robust oscillator normalization with MAD fallback when stdev becomes outlier-like.
- Oscillator-pane marker anchoring (`location.absolute`) to prevent autoscale distortion from price-anchored shapes.
How to Use quickstart
1. Add the script to chart and start with `Preset = Balanced`.
2. Set `Cycle Detector Mode = Composite` for combined cycle diagnostics.
3. Enable `Show Detected Cycle (data window)` to inspect cycle outputs.
4. Enable advanced settings only if you need to tune quality gates, trend filter, and cooldowns.
5. Configure alerts from the 5 built-in alert conditions after threshold tuning.
Indicator
NeuraCloud - Ichimoku (Purple Kumo) + Alerts (Minimal)NeuraCloud is a clean, modern interpretation of the Ichimoku Cloud, designed to identify trend direction, market structure, and key support/resistance zones at a glance.
The purple cloud (Kumo) acts as a dynamic trend filter:
• Price above the cloud indicates bullish conditions
• Price below the cloud indicates bearish conditions
• Price inside the cloud signals consolidation or uncertainty
NeuraCloud combines the cloud with Tenkan-sen and Kijun-sen to highlight momentum shifts, pullbacks, and trend continuation opportunities. Built-in alerts notify you of price/cloud breaks, momentum crosses, and cloud flips, helping you stay aligned with high-probability market structure.
Ideal for trend traders, swing traders, and multi-timeframe analysis, NeuraCloud keeps charts clean while delivering clear market context.
Indicator
Indicator
Smart RSI Composite [DotGain]Summary
Do you want to know the "True Direction" of the market without getting distracted by noise on a single timeframe?
The Smart RSI Composite simplifies market analysis by aggregating momentum data from 10 different timeframes (5m to 12M) into a single, easy-to-read Histogram.
Instead of looking at 10 separate charts or dots, this indicator calculates the Average RSI of the entire market structure. It answers one simple question: "Is the market predominantly Bullish or Bearish right now?"
⚙️ Core Components and Logic
This indicator works like a consensus mechanism for momentum:
Data Aggregation: It pulls RSI values from 10 customizable slots (Default: 5m, 15m, 1h, 4h, 1D, 1W, 1M, 3M, 6M, 12M). All slots are enabled by default.
Smart Averaging: It calculates the arithmetic mean of all active timeframes. If the 5m chart is bearish but the Monthly chart is bullish, this indicator balances them out to show you the net result.
Histogram Visualization: The result is plotted as a histogram centered around the 50-line (Neutral).
🚦 How to Read the Histogram
The histogram bars indicate the aggregate strength of the trend based on the Average RSI:
🟩 DARK GREEN (Strong Bullish)
Condition: Average RSI > 60.
Meaning: The market is in a strong uptrend across most timeframes. Momentum is firmly on the buyers' side.
🟢 LIGHT GREEN (Weak Bullish)
Condition: Average RSI between 50 and 60.
Meaning: Slight bullish bias. The bulls are in control, but momentum is not yet extreme.
🔴 LIGHT RED (Weak Bearish)
Condition: Average RSI between 40 and 50.
Meaning: Slight bearish bias. The bears are taking control.
🟥 DARK RED (Strong Bearish)
Condition: Average RSI < 40.
Meaning: The market is in a strong downtrend across most timeframes. Momentum is firmly on the sellers' side.
Visual Elements
Center Line (50): This acts as the Zero-Line. Above 50 is bullish, below 50 is bearish.
Zone Lines (30/70): Dashed lines indicate the traditional Overbought/Oversold levels applied to the aggregate average.
Key Benefit
The Smart RSI Composite acts as a powerful Macro Trend Filter .
Pro Tip: Never go long if the Histogram is Dark Red, and avoid shorting when it is Dark Green. Use this tool to align your trades with the overall market momentum.
Have fun :)
Disclaimer
This "Smart RSI Composite" indicator is provided for informational and educational purposes only. It does not, and should not be construed as, financial, investment, or trading advice.
The signals generated by this tool (both "Buy" and "Sell" indications) are the result of a specific set of algorithmic conditions. They are not a direct recommendation to buy or sell any asset. All trading and investing in financial markets involves substantial risk of loss. You can lose all of your invested capital.
Past performance is not indicative of future results. The signals generated may produce false or losing trades. The creator (© DotGain) assumes no liability for any financial losses or damages you may incur as a result of using this indicator.
You are solely responsible for your own trading and investment decisions. Always conduct your own research (DYOR) and consider your personal risk tolerance before making any trades. Indicator
EMA HeatmapEMA Heatmap — Indicator Description
The EMA Order Heatmap is a visual trend-structure tool designed to show whether the market is currently trending bullish, trending bearish, or moving through a neutral consolidation phase. It evaluates the alignment of multiple exponential moving averages (EMAs) at three different structural layers: short-term daily, medium-term daily, and weekly macro trend. This creates a quick and intuitive picture of how well price movement is organized across timeframes.
Each layer of the heatmap is scored from bearish to bullish based on how the EMAs are stacked relative to each other. When EMAs are in a fully bullish configuration, the row displays a bright green or lime color. Fully bearish alignment is shown in red. Yellow tones appear when the EMAs are mixed or compressing, indicating uncertainty, trend exhaustion, or a change in market character. The three rows combined offer a concise view of whether strength or weakness is isolated to one timeframe or broad across the market.
This indicator is best used as a trend filter before making trading decisions. Traders may find more consistent setups when the majority of the heatmap supports the direction of their trade. Green-dominant conditions suggest a trending bullish environment where long trades can be favored. Red-dominant conditions indicate bearish momentum and stronger potential for short opportunities. When yellow becomes more prominent, the market may be transitioning, ranging, or gearing up for a breakout, making timing more challenging and risk higher.
• Helps quickly identify directional bias
• Highlights when trends strengthen, weaken, or turn
• Provides insight into whether momentum is supported by higher timeframes
• Encourages traders to avoid fighting market structure
It is important to recognize the limitations. EMAs are lagging indicators, so the heatmap may confirm a trend after the initial move is underway, especially during fast reversals. In sideways or low-volume environments, the structure can shift frequently, reducing clarity. This tool does not generate entry or exit signals on its own and should be paired with price action, momentum studies, or support and resistance analysis for precise trade execution.
The EMA Order Heatmap offers a clean and reliable way to stay aligned with the broader market environment and avoid lower-quality trades in indecisive conditions. It supports more disciplined decision-making by helping traders focus on setups that match the prevailing structural trend. Indicator
Hann Window FIR Filter Ribbon [BigBeluga]🔵 OVERVIEW
The Hann Window FIR Filter Ribbon is a trend-following visualization tool based on a family of FIR filters using the Hann window function. It plots a smooth and dynamic ribbon formed by six Hann filters of progressively increasing length. Gradient coloring and filled bands reveal trend direction and compression/expansion behavior. When short-term trend shifts occur (via filter crossover), it automatically anchors visual support/resistance zones at the nearest swing highs or lows.
🔵 CONCEPTS
Hann FIR Filter: A finite impulse response filter that uses a Hann (cosine-based) window for weighting past price values, resulting in a non-lag, ultra-smooth output.
hannFilter(length)=>
var float hann = na // Final filter output
float filt = 0
float coef = 0
for i = 1 to length
weight = 1 - math.cos(2 * math.pi * i / (length + 1))
filt += price * weight
coef += weight
hann := coef != 0 ? filt / coef : na
Ribbon Stack: The indicator plots 6 Hann FIR filters with increasing lengths, creating a smooth "ribbon" that adapts to price shifts and visually encodes volatility.
Gradient Coloring: Line colors and fill opacity between layers are dynamically adjusted based on the distance between the filters, showing momentum expansion or contraction.
Dynamic Swing Zones: When the shortest filter crosses its nearest neighbor, a swing high/low is located, and a triangle-style level is anchored and projected to the right.
Self-Extending Levels: These dynamic levels persist and extend until invalidated or replaced by a new opposite trend break.
🔵 FEATURES
Plots 6 Hann FIR filters with increasing lengths (controlled by Ribbon Size input).
Automatically colors each filter and the fill between them with smooth gradient transitions.
Detects trend shifts via filter crossover and anchors visual resistance (red) or support (green) zones.
Support/resistance zones are triangle-style bands built around recent swing highs/lows.
Levels auto-extend right and adapt in real time until invalidated by price action.
Ribbon responds smoothly to price and shows contraction or expansion behavior clearly.
No lag in crossover detection thanks to FIR architecture.
Adjustable sensitivity via Length and Ribbon Size inputs.
🔵 HOW TO USE
Use the ribbon gradient as a visual trend strength and smooth direction cue.
Watch for crossover of shortest filters as early trend change signals.
Monitor support/resistance zones as potential high-probability reaction points.
Combine with other tools like momentum or volume to confirm trend breaks.
Adjust ribbon thickness and length to suit your trading timeframe and volatility preference.
🔵 CONCLUSION
Hann Window FIR Filter Ribbon blends digital signal processing with trading logic to deliver a visually refined, non-lagging trend tool. The adaptive ribbon offers insight into momentum compression and release, while swing-based levels give structure to potential reversals. Ideal for traders who seek smooth trend detection with intelligent, auto-adaptive zone plotting. Indicator
VIX Filter/RSI/EMA Bias/Cum-TICK w/ Exhaustion Zone DashboardThis all-in-one dashboard gives intraday traders a real-time visual read of market conditions, combining volatility regime, trend bias, momentum exhaustion, and internal strength — all in a fully customizable overlay that won’t clutter your chart.
📉 VIX Market Regime Detector
Identifies "Weak", "Normal", "Volatile", or "Danger" market states based on customizable VIX ranges and symbol (e.g., VXN or VIX).
📊 RSI Momentum Readout
Displays real-time RSI from any selected timeframe or symbol, with adjustable length, OB/OS thresholds, and color-coded exhaustion alerts.
📈 EMA Trend Bias Scanner
Compares fast and slow EMAs to define bullish or bearish bias, using your preferred timeframe, symbol, and EMA lengths — ideal for multi-timeframe setups.
🧠 Cumulative TICK Pressure & Exhaustion Engine
Analyzes internal market strength using cumulative TICK data to classify conditions as:
-Strong / Mild Bullish or Bearish Pressure
-Choppy / No Edge
-⚠️ Exhaustion Zones — when raw TICK values hit extreme highs/lows, a separate highlight box appears in the dashboard, warning of potential turning points
All logic is customizable, including TICK symbol, timeframes, thresholds, and lookback periods.
Scalpers and day traders who want fast, visual insight into market internals, exhaustion, and trend bias. Indicator
Indicator
Trend Gauge [BullByte]Trend Gauge
Summary
A multi-factor trend detection indicator that aggregates EMA alignment, VWMA momentum scaling, volume spikes, ATR breakout strength, higher-timeframe confirmation, ADX-based regime filtering, and RSI pivot-divergence penalty into one normalized trend score. It also provides a confidence meter, a Δ Score momentum histogram, divergence highlights, and a compact, scalable dashboard for at-a-glance status.
________________________________________
## 1. Purpose of the Indicator
Why this was built
Traders often monitor several indicators in parallel - EMAs, volume signals, volatility breakouts, higher-timeframe trends, ADX readings, divergence alerts, etc., which can be cumbersome and sometimes contradictory. The “Trend Gauge” indicator was created to consolidate these complementary checks into a single, normalized score that reflects the prevailing market bias (bullish, bearish, or neutral) and its strength. By combining multiple inputs with an adaptive regime filter, scaling contributions by magnitude, and penalizing weakening signals (divergence), this tool aims to reduce noise, highlight genuine trend opportunities, and warn when momentum fades.
Key Design Goals
Signal Aggregation
Merged trend-following signals (EMA crossover, ATR breakout, higher-timeframe confirmation) and momentum signals (VWMA thrust, volume spikes) into a unified score that reflects directional bias more holistically.
Market Regime Awareness
Implemented an ADX-style filter to distinguish between trending and ranging markets, reducing the influence of trend signals during sideways phases to avoid false breakouts.
Magnitude-Based Scaling
Replaced binary contributions with scaled inputs: VWMA thrust and ATR breakout are weighted relative to recent averages, allowing for more nuanced score adjustments based on signal strength.
Momentum Divergence Penalty
Integrated pivot-based RSI divergence detection to slightly reduce the overall score when early signs of momentum weakening are detected, improving risk-awareness in entries.
Confidence Transparency
Added a live confidence metric that shows what percentage of enabled sub-indicators currently agree with the overall bias, making the scoring system more interpretable.
Momentum Acceleration Visualization
Plotted the change in score (Δ Score) as a histogram bar-to-bar, highlighting whether momentum is increasing, flattening, or reversing, aiding in more timely decision-making.
Compact Informational Dashboard
Presented a clean, scalable dashboard that displays each component’s status, the final score, confidence %, detected regime (Trending/Ranging), and a labeled strength gauge for quick visual assessment.
________________________________________
## 2. Why a Trader Should Use It
Main benefits and use cases
1. Unified View: Rather than juggling multiple windows or panels, this indicator delivers a single score synthesizing diverse signals.
2. Regime Filtering: In ranging markets, trend signals often generate false entries. The ADX-based regime filter automatically down-weights trend-following components, helping you avoid chasing false breakouts.
3. Nuanced Momentum & Volatility: VWMA and ATR breakout contributions are normalized by recent averages, so strong moves register strongly while smaller fluctuations are de-emphasized.
4. Early Warning of Weakening: Pivot-based RSI divergence is detected and used to slightly reduce the score when price/momentum diverges, giving a cautionary signal before a full reversal.
5. Confidence Meter: See at a glance how many sub-indicators align with the aggregated bias (e.g., “80% confidence” means 4 out of 5 components agree ). This transparency avoids black-box decisions.
6. Trend Acceleration/Deceleration View: The Δ Score histogram visualizes whether the aggregated score is rising (accelerating trend) or falling (momentum fading), supplementing the main oscillator.
7. Compact Dashboard: A corner table lists each check’s status (“Bull”, “Bear”, “Flat” or “Disabled”), plus overall Score, Confidence %, Regime, Trend Strength label, and a gauge bar. Users can scale text size (Normal, Small, Tiny) without removing elements, so the full picture remains visible even in compact layouts.
8. Customizable & Transparent: All components can be enabled/disabled and parameterized (lengths, thresholds, weights). The full Pine code is open and well-commented, letting users inspect or adapt the logic.
9. Alert-ready: Built-in alert conditions fire when the score crosses weak thresholds to bullish/bearish or returns to neutral, enabling timely notifications.
________________________________________
## 3. Component Rationale (“Why These Specific Indicators?”)
Each sub-component was chosen because it adds complementary information about trend or momentum:
1. EMA Cross
o Basic trend measure: compares a faster EMA vs. a slower EMA. Quickly reflects trend shifts but by itself can whipsaw in sideways markets.
2. VWMA Momentum
o Volume-weighted moving average change indicates momentum with volume context. By normalizing (dividing by a recent average absolute change), we capture the strength of momentum relative to recent history. This scaling prevents tiny moves from dominating and highlights genuinely strong momentum.
3. Volume Spikes
o Sudden jumps in volume combined with price movement often accompany stronger moves or reversals. A binary detection (+1 for bullish spike, -1 for bearish spike) flags high-conviction bars.
4. ATR Breakout
o Detects price breaking beyond recent highs/lows by a multiple of ATR. Measures breakout strength by how far beyond the threshold price moves relative to ATR, capped to avoid extreme outliers. This gives a volatility-contextual trend signal.
5. Higher-Timeframe EMA Alignment
o Confirms whether the shorter-term trend aligns with a higher timeframe trend. Uses request.security with lookahead_off to avoid future data. When multiple timeframes agree, confidence in direction increases.
6. ADX Regime Filter (Manual Calculation)
o Computes directional movement (+DM/–DM), smoothes via RMA, computes DI+ and DI–, then a DX and ADX-like value. If ADX ≥ threshold, market is “Trending” and trend components carry full weight; if ADX < threshold, “Ranging” mode applies a configurable weight multiplier (e.g., 0.5) to trend-based contributions, reducing false signals in sideways conditions. Volume spikes remain binary (optional behavior; can be adjusted if desired).
7. RSI Pivot-Divergence Penalty
o Uses ta.pivothigh / ta.pivotlow with a lookback to detect pivot highs/lows on price and corresponding RSI values. When price makes a higher high but RSI makes a lower high (bearish divergence), or price makes a lower low but RSI makes a higher low (bullish divergence), a divergence signal is set. Rather than flipping the trend outright, the indicator subtracts (or adds) a small penalty (configurable) from the aggregated score if it would weaken the current bias. This subtle adjustment warns of weakening momentum without overreacting to noise.
8. Confidence Meter
o Counts how many enabled components currently agree in direction with the aggregated score (i.e., component sign × score sign > 0). Displays this as a percentage. A high percentage indicates strong corroboration; a low percentage warns of mixed signals.
9. Δ Score Momentum View
o Plots the bar-to-bar change in the aggregated score (delta_score = score - score ) as a histogram. When positive, bars are drawn in green above zero; when negative, bars are drawn in red below zero. This reveals acceleration (rising Δ) or deceleration (falling Δ), supplementing the main oscillator.
10. Dashboard
• A table in the indicator pane’s top-right with 11 rows:
1. EMA Cross status
2. VWMA Momentum status
3. Volume Spike status
4. ATR Breakout status
5. Higher-Timeframe Trend status
6. Score (numeric)
7. Confidence %
8. Regime (“Trending” or “Ranging”)
9. Trend Strength label (e.g., “Weak Bullish Trend”, “Strong Bearish Trend”)
10. Gauge bar visually representing score magnitude
• All rows always present; size_opt (Normal, Small, Tiny) only changes text size via text_size, not which elements appear. This ensures full transparency.
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## 4. What Makes This Indicator Stand Out
• Regime-Weighted Multi-Factor Score: Trend and momentum signals are adaptively weighted by market regime (trending vs. ranging) , reducing false signals.
• Magnitude Scaling: VWMA and ATR breakout contributions are normalized by recent average momentum or ATR, giving finer gradation compared to simple ±1.
• Integrated Divergence Penalty: Divergence directly adjusts the aggregated score rather than appearing as a separate subplot; this influences alerts and trend labeling in real time.
• Confidence Meter: Shows the percentage of sub-signals in agreement, providing transparency and preventing blind trust in a single metric.
• Δ Score Histogram Momentum View: A histogram highlights acceleration or deceleration of the aggregated trend score, helping detect shifts early.
• Flexible Dashboard: Always-visible component statuses and summary metrics in one place; text size scaling keeps the full picture available in cramped layouts.
• Lookahead-Safe HTF Confirmation: Uses lookahead_off so no future data is accessed from higher timeframes, avoiding repaint bias.
• Repaint Transparency: Divergence detection uses pivot functions that inherently confirm only after lookback bars; description documents this lag so users understand how and when divergence labels appear.
• Open-Source & Educational: Full, well-commented Pine v6 code is provided; users can learn from its structure: manual ADX computation, conditional plotting with series = show ? value : na, efficient use of table.new in barstate.islast, and grouped inputs with tooltips.
• Compliance-Conscious: All plots have descriptive titles; inputs use clear names; no unnamed generic “Plot” entries; manual ADX uses RMA; all request.security calls use lookahead_off. Code comments mention repaint behavior and limitations.
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## 5. Recommended Timeframes & Tuning
• Any Timeframe: The indicator works on small (e.g., 1m) to large (daily, weekly) timeframes. However:
o On very low timeframes (<1m or tick charts), noise may produce frequent whipsaws. Consider increasing smoothing lengths, disabling certain components (e.g., volume spike if volume data noisy), or using a larger pivot lookback for divergence.
o On higher timeframes (daily, weekly), consider longer lookbacks for ATR breakout or divergence, and set Higher-Timeframe trend appropriately (e.g., 4H HTF when on 5 Min chart).
• Defaults & Experimentation: Default input values are chosen to be balanced for many liquid markets. Users should test with replay or historical analysis on their symbol/timeframe and adjust:
o ADX threshold (e.g., 20–30) based on instrument volatility.
o VWMA and ATR scaling lengths to match average volatility cycles.
o Pivot lookback for divergence: shorter for faster markets, longer for slower ones.
• Combining with Other Analysis: Use in conjunction with price action, support/resistance, candlestick patterns, order flow, or other tools as desired. The aggregated score and alerts can guide attention but should not be the sole decision-factor.
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## 6. How Scoring and Logic Works (Step-by-Step)
1. Compute Sub-Scores
o EMA Cross: Evaluate fast EMA > slow EMA ? +1 : fast EMA < slow EMA ? -1 : 0.
o VWMA Momentum: Calculate vwma = ta.vwma(close, length), then vwma_mom = vwma - vwma . Normalize: divide by recent average absolute momentum (e.g., ta.sma(abs(vwma_mom), lookback)), clip to .
o Volume Spike: Compute vol_SMA = ta.sma(volume, len). If volume > vol_SMA * multiplier AND price moved up ≥ threshold%, assign +1; if moved down ≥ threshold%, assign -1; else 0.
o ATR Breakout: Determine recent high/low over lookback. If close > high + ATR*mult, compute distance = close - (high + ATR*mult), normalize by ATR, cap at a configured maximum. Assign positive contribution. Similarly for bearish breakout below low.
o Higher-Timeframe Trend: Use request.security(..., lookahead=barmerge.lookahead_off) to fetch HTF EMAs; assign +1 or -1 based on alignment.
2. ADX Regime Weighting
o Compute manual ADX: directional movements (+DM, –DM), smoothed via RMA, DI+ and DI–, then DX and ADX via RMA. If ADX ≥ threshold, market is considered “Trending”; otherwise “Ranging.”
o If trending, trend-based contributions (EMA, VWMA, ATR, HTF) use full weight = 1.0. If ranging, use weight = ranging_weight (e.g., 0.5) to down-weight them. Volume spike stays binary ±1 (optional to change if desired).
3. Aggregate Raw Score
o Sum weighted contributions of all enabled components. Count the number of enabled components; if zero, default count = 1 to avoid division by zero.
4. Divergence Penalty
o Detect pivot highs/lows on price and corresponding RSI values, using a lookback. When price and RSI diverge (bearish or bullish divergence), check if current raw score is in the opposing direction:
If bearish divergence (price higher high, RSI lower high) and raw score currently positive, subtract a penalty (e.g., 0.5).
If bullish divergence (price lower low, RSI higher low) and raw score currently negative, add a penalty.
o This reduces score magnitude to reflect weakening momentum, without flipping the trend outright.
5. Normalize and Smooth
o Normalized score = (raw_score / number_of_enabled_components) * 100. This yields a roughly range.
o Optional EMA smoothing of this normalized score to reduce noise.
6. Interpretation
o Sign: >0 = net bullish bias; <0 = net bearish bias; near zero = neutral.
o Magnitude Zones: Compare |score| to thresholds (Weak, Medium, Strong) to label trend strength (e.g., “Weak Bullish Trend”, “Medium Bearish Trend”, “Strong Bullish Trend”).
o Δ Score Histogram: The histogram bars from zero show change from previous bar’s score; positive bars indicate acceleration, negative bars indicate deceleration.
o Confidence: Percentage of sub-indicators aligned with the score’s sign.
o Regime: Indicates whether trend-based signals are fully weighted or down-weighted.
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## 7. Oscillator Plot & Visualization: How to Read It
Main Score Line & Area
The oscillator plots the aggregated score as a line, with colored fill: green above zero for bullish area, red below zero for bearish area. Horizontal reference lines at ±Weak, ±Medium, and ±Strong thresholds mark zones: crossing above +Weak suggests beginning of bullish bias, above +Medium for moderate strength, above +Strong for strong trend; similarly for bearish below negative thresholds.
Δ Score Histogram
If enabled, a histogram shows score - score . When positive, bars appear in green above zero, indicating accelerating bullish momentum; when negative, bars appear in red below zero, indicating decelerating or reversing momentum. The height of each bar reflects the magnitude of change in the aggregated score from the prior bar.
Divergence Highlight Fill
If enabled, when a pivot-based divergence is confirmed:
• Bullish Divergence : fill the area below zero down to –Weak threshold in green, signaling potential reversal from bearish to bullish.
• Bearish Divergence : fill the area above zero up to +Weak threshold in red, signaling potential reversal from bullish to bearish.
These fills appear with a lag equal to pivot lookback (the number of bars needed to confirm the pivot). They do not repaint after confirmation, but users must understand this lag.
Trend Direction Label
When score crosses above or below the Weak threshold, a small label appears near the score line reading “Bullish” or “Bearish.” If the score returns within ±Weak, the label “Neutral” appears. This helps quickly identify shifts at the moment they occur.
Dashboard Panel
In the indicator pane’s top-right, a table shows:
1. EMA Cross status: “Bull”, “Bear”, “Flat”, or “Disabled”
2. VWMA Momentum status: similarly
3. Volume Spike status: “Bull”, “Bear”, “No”, or “Disabled”
4. ATR Breakout status: “Bull”, “Bear”, “No”, or “Disabled”
5. Higher-Timeframe Trend status: “Bull”, “Bear”, “Flat”, or “Disabled”
6. Score: numeric value (rounded)
7. Confidence: e.g., “80%” (colored: green for high, amber for medium, red for low)
8. Regime: “Trending” or “Ranging” (colored accordingly)
9. Trend Strength: textual label based on magnitude (e.g., “Medium Bullish Trend”)
10. Gauge: a bar of blocks representing |score|/100
All rows remain visible at all times; changing Dashboard Size only scales text size (Normal, Small, Tiny).
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## 8. Example Usage (Illustrative Scenario)
Example: BTCUSD 5 Min
1. Setup: Add “Trend Gauge ” to your BTCUSD 5 Min chart. Defaults: EMAs (8/21), VWMA 14 with lookback 3, volume spike settings, ATR breakout 14/5, HTF = 5m (or adjust to 4H if preferred), ADX threshold 25, ranging weight 0.5, divergence RSI length 14 pivot lookback 5, penalty 0.5, smoothing length 3, thresholds Weak=20, Medium=50, Strong=80. Dashboard Size = Small.
2. Trend Onset: At some point, price breaks above recent high by ATR multiple, volume spikes upward, faster EMA crosses above slower EMA, HTF EMA also bullish, and ADX (manual) ≥ threshold → aggregated score rises above +20 (Weak threshold) into +Medium zone. Dashboard shows “Bull” for EMA, VWMA, Vol Spike, ATR, HTF; Score ~+60–+70; Confidence ~100%; Regime “Trending”; Trend Strength “Medium Bullish Trend”; Gauge ~6–7 blocks. Δ Score histogram bars are green and rising, indicating accelerating bullish momentum. Trader notes the alignment.
3. Divergence Warning: Later, price makes a slightly higher high but RSI fails to confirm (lower RSI high). Pivot lookback completes; the indicator highlights a bearish divergence fill above zero and subtracts a small penalty from the score, causing score to stall or retrace slightly. Dashboard still bullish but score dips toward +Weak. This warns the trader to tighten stops or take partial profits.
4. Trend Weakens: Score eventually crosses below +Weak back into neutral; a “Neutral” label appears, and a “Neutral Trend” alert fires if enabled. Trader exits or avoids new long entries. If score subsequently crosses below –Weak, a “Bearish” label and alert occur.
5. Customization: If the trader finds VWMA noise too frequent on this instrument, they may disable VWMA or increase lookback. If ATR breakouts are too rare, adjust ATR length or multiplier. If ADX threshold seems off, tune threshold. All these adjustments are explained in Inputs section.
6. Visualization: The screenshot shows the main score oscillator with colored areas, reference lines at ±20/50/80, Δ Score histogram bars below/above zero, divergence fill highlighting potential reversal, and the dashboard table in the top-right.
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## 9. Inputs Explanation
A concise yet clear summary of inputs helps users understand and adjust:
1. General Settings
• Theme (Dark/Light): Choose background-appropriate colors for the indicator pane.
• Dashboard Size (Normal/Small/Tiny): Scales text size only; all dashboard elements remain visible.
2. Indicator Settings
• Enable EMA Cross: Toggle on/off basic EMA alignment check.
o Fast EMA Length and Slow EMA Length: Periods for EMAs.
• Enable VWMA Momentum: Toggle VWMA momentum check.
o VWMA Length: Period for VWMA.
o VWMA Momentum Lookback: Bars to compare VWMA to measure momentum.
• Enable Volume Spike: Toggle volume spike detection.
o Volume SMA Length: Period to compute average volume.
o Volume Spike Multiplier: How many times above average volume qualifies as spike.
o Min Price Move (%): Minimum percent change in price during spike to qualify as bullish or bearish.
• Enable ATR Breakout: Toggle ATR breakout detection.
o ATR Length: Period for ATR.
o Breakout Lookback: Bars to look back for recent highs/lows.
o ATR Multiplier: Multiplier for breakout threshold.
• Enable Higher Timeframe Trend: Toggle HTF EMA alignment.
o Higher Timeframe: E.g., “5” for 5-minute when on 1-minute chart, or “60” for 5 Min when on 15m, etc. Uses lookahead_off.
• Enable ADX Regime Filter: Toggles regime-based weighting.
o ADX Length: Period for manual ADX calculation.
o ADX Threshold: Value above which market considered trending.
o Ranging Weight Multiplier: Weight applied to trend components when ADX < threshold (e.g., 0.5).
• Scale VWMA Momentum: Toggle normalization of VWMA momentum magnitude.
o VWMA Mom Scale Lookback: Period for average absolute VWMA momentum.
• Scale ATR Breakout Strength: Toggle normalization of breakout distance by ATR.
o ATR Scale Cap: Maximum multiple of ATR used for breakout strength.
• Enable Price-RSI Divergence: Toggle divergence detection.
o RSI Length for Divergence: Period for RSI.
o Pivot Lookback for Divergence: Bars on each side to identify pivot high/low.
o Divergence Penalty: Amount to subtract/add to score when divergence detected (e.g., 0.5).
3. Score Settings
• Smooth Score: Toggle EMA smoothing of normalized score.
• Score Smoothing Length: Period for smoothing EMA.
• Weak Threshold: Absolute score value under which trend is considered weak or neutral.
• Medium Threshold: Score above Weak but below Medium is moderate.
• Strong Threshold: Score above this indicates strong trend.
4. Visualization Settings
• Show Δ Score Histogram: Toggle display of the bar-to-bar change in score as a histogram. Default true.
• Show Divergence Fill: Toggle background fill highlighting confirmed divergences. Default true.
Each input has a tooltip in the code.
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## 10. Limitations, Repaint Notes, and Disclaimers
10.1. Repaint & Lag Considerations
• Pivot-Based Divergence Lag: The divergence detection uses ta.pivothigh / ta.pivotlow with a specified lookback. By design, a pivot is only confirmed after the lookback number of bars. As a result:
o Divergence labels or fills appear with a delay equal to the pivot lookback.
o Once the pivot is confirmed and the divergence is detected, the fill/label does not repaint thereafter, but you must understand and accept this lag.
o Users should not treat divergence highlights as predictive signals without additional confirmation, because they appear after the pivot has fully formed.
• Higher-Timeframe EMA Alignment: Uses request.security(..., lookahead=barmerge.lookahead_off), so no future data from the higher timeframe is used. This avoids lookahead bias and ensures signals are based only on completed higher-timeframe bars.
• No Future Data: All calculations are designed to avoid using future information. For example, manual ADX uses RMA on past data; security calls use lookahead_off.
10.2. Market & Noise Considerations
• In very choppy or low-liquidity markets, some components (e.g., volume spikes or VWMA momentum) may be noisy. Users can disable or adjust those components’ parameters.
• On extremely low timeframes, noise may dominate; consider smoothing lengths or disabling certain features.
• On very high timeframes, pivots and breakouts occur less frequently; adjust lookbacks accordingly to avoid sparse signals.
10.3. Not a Standalone Trading System
• This is an indicator, not a complete trading strategy. It provides signals and context but does not manage entries, exits, position sizing, or risk management.
• Users must combine it with their own analysis, money management, and confirmations (e.g., price patterns, support/resistance, fundamental context).
• No guarantees: past behavior does not guarantee future performance.
10.4. Disclaimers
• Educational Purposes Only: The script is provided as-is for educational and informational purposes. It does not constitute financial, investment, or trading advice.
• Use at Your Own Risk: Trading involves risk of loss. Users should thoroughly test and use proper risk management.
• No Guarantees: The author is not responsible for trading outcomes based on this indicator.
• License: Published under Mozilla Public License 2.0; code is open for viewing and modification under MPL terms.
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## 11. Alerts
• The indicator defines three alert conditions:
1. Bullish Trend: when the aggregated score crosses above the Weak threshold.
2. Bearish Trend: when the score crosses below the negative Weak threshold.
3. Neutral Trend: when the score returns within ±Weak after being outside.
Good luck
– BullByte
Indicator
Indicator
Range Filtered Trend Signals [AlgoAlpha]Introducing the Range Filtered Trend Signals , a cutting-edge trading indicator designed to detect market trends and ranging conditions with high accuracy. This indicator leverages a combination of Kalman filtering and Supertrend analysis to smooth out price fluctuations while maintaining responsiveness to trend shifts. By incorporating volatility-based range filtering, it ensures traders can differentiate between trending and ranging conditions effectively, reducing false signals and enhancing trade decision-making.
:key: Key Features
:white_check_mark: Kalman Filter Smoothing – Minimizes market noise while preserving trend clarity.
:bar_chart: Supertrend Integration – A dynamic trend-following mechanism for spotting reversals.
:fire: Volatility-Based Range Detection – Detects trending vs. ranging conditions with precision.
:art: Color-Coded Trend Signals – Instantly recognize bullish, bearish, and ranging market states.
:gear: Customizable Inputs – Fine-tune Kalman parameters, Supertrend settings, and color themes to match your strategy.
:bell: Alerts for Trend Shifts – Get real-time notifications when market conditions change!
:tools: How to Use
Add the Indicator – Click the star icon to add it to your PulseWire favorites.
Analyze Market Conditions – Observe the color-coded signals and range boundaries to identify trend strength and direction.
Use Alerts for Trade Execution – Set alerts for trend shifts and market conditions to stay ahead without constantly monitoring charts.
:mag: How It Works
The Kalman filter smooths price fluctuations by dynamically adjusting its weighting based on market volatility. It helps remove noise while keeping the signal reactive to trend changes. The Supertrend calculation is then applied to the filtered price data, providing a robust trend-following mechanism. To enhance signal accuracy, a volatility-weighted range filter is incorporated, creating upper and lower boundaries that define trend conditions. When price breaks out of these boundaries, the indicator confirms trend continuation, while signals within the range indicate market consolidation. Traders can leverage this tool to enhance trade timing, filter false breakouts, and identify optimal entry/exit zones. Indicator
