Volume Aggregated Spot & Futures -- Crypto (by plyst & more)📊 Volume Aggregated Spot & Futures - Enhanced Edition
🎯 Overview
Advanced volume aggregation indicator that combines spot and perpetual futures volume across the top 10 cryptocurrency exchanges. This enhanced version builds upon the original work by @HALDRO Project with optimized calculations and expanded functionality.
✨ Key Features
- 📈 Real-time aggregated volume from 10 major exchanges (Binance, Bybit, OKX, Coinbase, Bitget, KuCoin, Kraken, MEXC, Gate.io, HTX)
- 🔄 Multiple visualization modes: Volume, Delta, Cumulative Delta, Spot vs Perp analysis, Liquidations, OBV, and MFI
- 💱 Multi-currency support: Display volume in COIN, USD, or EUR
- 🎨 Clean, single-color bar chart showing total cumulative volume
- 📊 Multiple calculation methods: SUM, AVG, MEDIAN, VARIANCE
- 🎯 Separate spot (USDT, USD, USDC, etc.) and perpetual futures (.P contracts) tracking
🔧 Technical Improvements
✓ Corrected MFI formula for accurate money flow calculations
✓ Optimized volume aggregation logic with proper NA handling
✓ Support for 10 exchanges (up from 9)
✓ Streamlined codebase for better performance
✓ Updated perpetual contract naming conventions (.P format)
📖 Usage
Perfect for analyzing total market volume, identifying liquidation events, tracking buyer/seller pressure through delta analysis, and understanding the spot vs futures market dynamics.
🙏 Credits
Original concept and framework by @HALDRO Project. This version includes mathematical corrections, code optimizations, and expanded exchange support.
⚠️ Note
Aggregated volume is calculated from external exchange data using request.security(). Ensure your plan supports the necessary security calls for optimal performance.
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Round Number Analyzer v3Round Number Analyzer v3 is an indicator designed to analyze how price interacts with round number levels (levels spaced at fixed intervals in points or pips).
The indicator does not generate entry/exit signals, but provides detailed statistics to better understand market dynamics around these key levels.
✨ Key Features
Cross Counting: detects every time the price crosses a round number level (up = Long, down = Short).
Continuations & Reversals: classifies each cross as:
Continuation: the move continues in the same direction as the previous sequence.
Reversal: the move changes direction compared to the previous sequence.
Sequence Classification (L1…L5+): each level is labelled based on its position within the consecutive cross sequence:
L1 = first level of the sequence,
L2 = second consecutive,
…
L5+ = fifth or higher.
Comprehensive Stats Table (top right corner):
Total crosses (Long, Short, Totals).
Total continuations + breakdown by L1…L5+.
Total reversals + breakdown by L1…L5+.
Percentages calculated against the proper denominator, displayed directly inside the cells next to the absolute values.
Date range of analysis (user-defined).
Customizable Step: Works in both points and pips, making the indicator suitable for indices and forex.
⚙️ Main Inputs
Start date / End date → sets the analysis period.
Step mode → Points or Pips.
Step value → distance between round levels.
Pip size → pip size (default = 0.0001, typical for forex).
📈 How to Interpret
A high continuation percentage after L1–L2 suggests the market tends to extend multiple times beyond the first breakout levels.
Higher reversal percentages at advanced levels (L4–L5+) may signal trend exhaustion.
The analysis helps estimate the probability of continuation or reversal depending on how many consecutive levels have already been crossed.
🔎 Practical Applications
Support for breakout or mean-reversion strategies.
Comparative analysis across different markets (e.g. indices vs forex) or different time periods.
📝 Notes
The indicator is timeframe-robust, as it accounts for multiple steps within the same candle, ensuring results do not depend on the selected timeframe (except for TradingView’s historical data limits).
It does not provide automatic trading signals, but serves as a quantitative analysis tool to refine your strategies.
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Round Number Analyzer v3 è un indicatore pensato per analizzare come il prezzo interagisce con i livelli di round number (livelli a distanza fissa in punti o pips).
L’indicatore non genera segnali di ingresso/uscita, ma fornisce statistiche dettagliate utili per comprendere la dinamica del mercato attorno a questi livelli.
✨ Funzionalità principali
Conteggio dei Cross: rileva ogni volta che il prezzo attraversa un livello round (verso l’alto = Long, verso il basso = Short).
Continuations & Reversals: classifica ogni attraversamento come:
Continuation: il movimento prosegue nella stessa direzione della sequenza precedente.
Reversal: il movimento inverte la direzione rispetto alla sequenza precedente.
Classificazione per sequenza (L1…L5+): ogni livello è etichettato in base alla sua posizione nella sequenza di cross consecutivi:
L1 = primo livello della sequenza,
L2 = secondo consecutivo,
…
L5+ = quinto o superiore.
Statistiche complete in tabella (in alto a destra):
Cross totali (Long, Short, Totals).
Continuations totali + breakdown per L1…L5+.
Reversals totali + breakdown per L1…L5+.
Percentuali calcolate sul denominatore corretto, mostrate direttamente dentro le celle accanto ai valori assoluti.
Date range di analisi (impostabile dall’utente).
Step personalizzabile: puoi lavorare sia in punti che in pips, così l’indicatore è adatto sia per indici che per forex.
⚙️ Input principali
Start date / End date → imposta l’intervallo temporale di analisi.
Step mode → punti o pips.
Step value → ampiezza tra i livelli round.
Pip size → dimensione del pip (default = 0.0001, tipico per il forex).
📈 Come interpretarlo
Una percentuale di continuation molto alta dopo L1–L2 indica che il mercato tende a proseguire più volte oltre i primi livelli di breakout.
Percentuali di reversal più elevate nei livelli avanzati (L4–L5+) possono suggerire esaurimento della spinta.
L’analisi permette di stimare la probabilità che un movimento in corso continui o si inverta in base a quanti livelli sono già stati attraversati consecutivamente.
🔎 Applicazioni pratiche
Supporto per strategie di breakout o mean reversion.
Analisi comparativa tra mercati (es. indici vs forex) o tra periodi temporali diversi.
📝 Note
L’indicatore è timeframe-robust: il conteggio tiene conto di multipli step dentro la stessa candela, così i risultati non dipendono dal timeframe scelto (salvo i limiti di caricamento storico di TradingView).
Non fornisce segnali operativi automatici, ma è un tool di analisi quantitativa per affinare le proprie strategie.
Volume Based Sampling [BackQuant]Volume Based Sampling
What this does
This indicator converts the usual time-based stream of candles into an event-based stream of “synthetic” bars that are created only when enough trading activity has occurred . You choose the activity definition:
Volume bars : create a new synthetic bar whenever the cumulative number of shares/contracts traded reaches a threshold.
Dollar bars : create a new synthetic bar whenever the cumulative traded dollar value (price × volume) reaches a threshold.
The script then keeps an internal ledger of these synthetic opens, highs, lows, closes, and volumes, and can display them as candles, plot a moving average calculated over the synthetic closes, mark each time a new sample is formed, and optionally overlay the native time-bars for comparison.
Why event-based sampling matters
Markets do not release information on a clock: activity clusters during news, opens/closes, and liquidity shocks. Event-based bars normalize for that heteroskedastic arrival of information: during active periods you get more bars (finer resolution); during quiet periods you get fewer bars (coarser resolution). Research shows this can reduce microstructure pathologies and produce series that are closer to i.i.d. and more suitable for statistical modeling and ML. In particular:
Volume and dollar bars are a common event-time alternative to time bars in quantitative research and are discussed extensively in Advances in Financial Machine Learning (AFML). These bars aim to homogenize information flow by sampling on traded size or value rather than elapsed seconds.
The Volume Clock perspective models market activity in “volume time,” showing that many intraday phenomena (volatility, liquidity shocks) are better explained when time is measured by traded volume instead of seconds.
Related market microstructure work on flow toxicity and liquidity highlights that the risk dealers face is tied to information intensity of order flow, again arguing for activity-based clocks.
How the indicator works (plain English)
Choose your bucket type
Volume : accumulate volume until it meets a threshold.
Dollar Bars : accumulate close × volume until it meets a dollar threshold.
Pick the threshold rule
Dynamic threshold : by default, the script computes a rolling statistic (mean or median) of recent activity to set the next bucket size. This adapts bar size to changing conditions (e.g., busier sessions produce more frequent synthetic bars).
Fixed threshold : optionally override with a constant target (e.g., exactly 100,000 contracts per synthetic bar, or $5,000,000 per dollar bar).
Build the synthetic bar
While a bucket fills, the script tracks:
o_s: first price of the bucket (synthetic open)
h_s: running maximum price (synthetic high)
l_s: running minimum price (synthetic low)
c_s: last price seen (synthetic close)
v_s: cumulative native volume inside the bucket
d_samples: number of native bars consumed to complete the bucket (a proxy for “how fast” the threshold filled)
Emit a new sample
Once the bucket meets/exceeds the threshold, a new synthetic bar is finalized and stored. If overflow occurs (e.g., a single native bar pushes you past the threshold by a lot), the code will emit multiple synthetic samples to account for the extra activity.
Maintain a rolling history efficiently
A ring buffer can overwrite the oldest samples when you hit your Max Stored Samples cap, keeping memory usage stable.
Compute synthetic-space statistics
The script computes an SMA over the last N synthetic closes and basic descriptors like average bars per synthetic sample, mean and standard deviation of synthetic returns, and more. These are all in event time , not clock time.
Inputs and options you will actually use
Data Settings
Sampling Method : Volume or Dollar Bars.
Rolling Lookback : window used to estimate the dynamic threshold from recent activity.
Filter : Mean or Median for the dynamic threshold. Median is more robust to spikes.
Use Fixed? / Fixed Threshold : override dynamic sizing with a constant target.
Max Stored Samples : cap on synthetic history to keep performance snappy.
Use Ring Buffer : turn on to recycle storage when at capacity.
Indicator Settings
SMA over last N samples : moving average in synthetic space . Because its index is sample count, not minutes, it adapts naturally: more updates in busy regimes, fewer in quiet regimes.
Visuals
Show Synthetic Bars : plot the synthetic OHLC candles.
Candle Color Mode :
Green/Red: directional close vs open
Volume Intensity: opacity scales with synthetic size
Neutral: single color
Adaptive: graded by how large the bucket was relative to threshold
Mark new samples : drop a small marker whenever a new synthetic bar prints.
Comparison & Research
Show Time Bars : overlay the native time-based candles to visually compare how the two sampling schemes differ.
How to read it, step by step
Turn on “Synthetic Bars” and optionally overlay “Time Bars.” You will see that during high-activity bursts, synthetic bars print much faster than time bars.
Watch the synthetic SMA . Crosses in synthetic space can be more meaningful because each update represents a roughly comparable amount of traded information.
Use the “Avg Bars per Sample” in the info table as a regime signal. Falling average bars per sample means activity is clustering, often coincident with higher realized volatility.
Try Dollar Bars when price varies a lot but share count does not; they normalize by dollar risk taken in each sample. Volume Bars are ideal when share count is a better proxy for information flow in your instrument.
Quant finance background and citations
Event time vs. clock time : Easley, López de Prado, and O’Hara advocate measuring intraday phenomena on a volume clock to better align sampling with information arrival. This framing helps explain volatility bursts and liquidity droughts and motivates volume-based bars.
Flow toxicity and dealer risk : The same authors show how adverse selection risk changes with the intensity and informativeness of order flow, further supporting activity-based clocks for modeling and risk management.
AFML framework : In Advances in Financial Machine Learning , event-driven bars such as volume, dollar, and imbalance bars are presented as superior sampling units for many ML tasks, yielding more stationary features and fewer microstructure distortions than fixed time bars. ( Alpaca )
Practical use cases
1) Regime-aware moving averages
The synthetic SMA in event time is not fooled by quiet periods: if nothing of consequence trades, it barely updates. This can make trend filters less sensitive to calendar drift and more sensitive to true participation.
2) Breakout logic on “equal-information” samples
The script exposes simple alerts such as breakout above/below the synthetic SMA . Because each bar approximates a constant amount of activity, breakouts are conditioned on comparable informational mass, not arbitrary time buckets.
3) Volatility-adaptive backtests
If you use synthetic bars as your base data stream, most signal rules become self-paced : entry and exit opportunities accelerate in fast markets and slow down in quiet regimes, which often improves the realism of slippage and fill modeling in research pipelines (pair this indicator with strategy code downstream).
4) Regime diagnostics
Avg Bars per Sample trending down: activity is dense; expect larger realized ranges.
Return StdDev (synthetic) rising: noise or trend acceleration in event time; re-tune risk.
Interpreting the info panel
Method : your sampling choice and current threshold.
Total Samples : how many synthetic bars have been formed.
Current Vol/Dollar : how much of the next bucket is already filled.
Bars in Bucket : native bars consumed so far in the current bucket.
Avg Bars/Sample : lower means higher trading intensity.
Avg Return / Return StdDev : return stats computed over synthetic closes .
Research directions you can build from here
Imbalance and run bars
Extend beyond pure volume or dollar thresholds to imbalance bars that trigger on directional order flow imbalance (e.g., buy volume minus sell volume), as discussed in the AFML ecosystem. These often further homogenize distributional properties used in ML. alpaca.markets
Volume-time indicators
Re-compute classical indicators (RSI, MACD, Bollinger) on the synthetic stream. The premise is that signals are updated by traded information , not seconds, which may stabilize indicator behavior in heteroskedastic regimes.
Liquidity and toxicity overlays
Combine synthetic bars with proxies of flow toxicity to anticipate spread widening or volatility clustering. For instance, tag synthetic bars that surpass multiples of the threshold and test whether subsequent realized volatility is elevated.
Dollar-risk parity sampling for portfolios
Use dollar bars to align samples across assets by notional risk, enabling cleaner cross-asset features and comparability in multi-asset models (e.g., correlation studies, regime clustering). AFML discusses the benefits of event-driven sampling for cross-sectional ML feature engineering.
Microstructure feature set
Compute duration in native bars per synthetic sample , range per sample , and volume multiple of threshold as inputs to state classifiers or regime HMMs . These features are inherently activity-aware and often predictive of short-horizon volatility and trend persistence per the event-time literature. ( Alpaca )
Tips for clean usage
Start with dynamic thresholds using Median over a sensible lookback to avoid outlier distortion, then move to Fixed thresholds when you know your instrument’s typical activity scale.
Compare time bars vs synthetic bars side by side to develop intuition for how your market “breathes” in activity time.
Keep Max Stored Samples reasonable for performance; the ring buffer avoids memory creep while preserving a rolling window of research-grade data.
SuperTrend Optimizer Remastered[CHE] SuperTrend Optimizer Remastered — Grid-ranked SuperTrend with additive or multiplicative scoring
Summary
This indicator evaluates a fixed grid of one hundred and two SuperTrend parameter pairs and ranks them by a simple flip-to-flip return model. It auto-selects the currently best-scoring combination and renders its SuperTrend in real time, with optional gradient coloring for faster visual parsing. The original concept is by KioseffTrading Thanks a lot for it.
For years I wanted to shorten the roughly two thousand three hundred seventy-one lines; I have now reduced the core to about three hundred eighty lines without triggering script errors. The simplification is generalizable to other indicators. A multiplicative return mode was added alongside the existing additive aggregation, enabling different rankings and often more realistic compounding behavior.
Motivation: Why this design?
SuperTrend is sensitive to its factor and period. Picking a single pair statically can underperform across regimes. This design sweeps a compact parameter grid around user-defined lower bounds, measures flip-to-flip outcomes, and promotes the combination with the strongest cumulative return. The approach keeps the visual footprint familiar while removing manual trial-and-error. The multiplicative mode captures compounding effects; the additive mode remains available for linear aggregation.
Originally (by KioseffTrading)
Very long script (~2,371 lines), monolithic structure.
SuperTrend optimization with additive (cumulative percentage-sum) scoring only.
Heavier use of repetitive code; limited modularity and fewer UI conveniences.
No explicit multiplicative compounding option; rankings did not reflect sequence-sensitive equity growth.
Now (remastered by CHE)
Compact core (~380 lines) with the same functional intent, no compile errors.
Adds multiplicative (compounding) scoring alongside additive, changing rankings to reflect real equity paths and penalize drawdown sequences.
Fixed 34×3 grid sweep, live ranking, gradient-based bar/wick/line visuals, top-table display, and an optional override plot.
Cleaner arrays/state handling, last-bar table updates, and reusable simplification pattern that can be applied to other indicators.
What’s different vs. standard approaches?
Baseline: A single SuperTrend with hand-picked inputs.
Architecture differences:
Fixed grid of thirty-four factor offsets across three ATR offsets.
Per-combination flip-to-flip backtest with additive or multiplicative aggregation.
Live ranking with optional “Best” or “Worst” table output.
Gradient bar, wick, and line coloring driven by consecutive trend counts.
Optional override plot to force a specific SuperTrend independent of ranking.
Practical effect: Charts show the currently best-scoring SuperTrend, not a static choice, plus an on-chart table of top performers for transparency.
How it works (technical)
For each parameter pair, the script computes SuperTrend value and direction. It monitors direction transitions and treats a change from up to down as a long entry and the reverse as an exit, measuring the move between entry and exit using close prices. Results are aggregated per pair either by summing percentage changes or by compounding return factors and then converting to percent for comparison. On the last bar, open trades are included as unrealized contributions to ranking. The best combination’s line is plotted, with separate styling for up and down regimes. Consecutive regime counts are normalized within a rolling window and mapped to gradients for bars, wicks, and lines. A two-column table reports the best or worst performers, with an optional row describing the parameter sweep.
Parameter Guide
Factor (Lower Bound) — Starting SuperTrend factor; the grid adds offsets between zero and three point three. Default three point zero. Higher raises distance to price and reduces flips.
ATR Period (Lower Bound) — Starting ATR length; the grid adds zero, one, and two. Default ten. Longer reduces noise at the cost of responsiveness.
Best vs Worst — Ranks by top or bottom cumulative return. Default Best. Use Worst for stress tests.
Calculation Mode — Additive sums percents; Multiplicative compounds returns. Multiplicative is closer to equity growth and can change the leaderboard.
Show in Table — “Top Three” or “All”. Fewer rows keep charts clean.
Show “Parameters Tested” Label — Displays the effective sweep ranges for auditability.
Plot Override SuperTrend — If enabled, the override factor and ATR are plotted instead of the ranked winner.
Override Factor / ATR Period — Values used when override is on.
Light Mode (for Table) — Adjusts table colors for bright charts.
Gradient/Coloring controls — Toggles for gradient bars and wick coloring, window length for normalization, gamma for contrast, and transparency settings. Use these to emphasize or tone down visual intensity.
Table Position and Text Size — Places the table and sets typography.
Reading & Interpretation
The auto SuperTrend plots one line for up regimes and one for down regimes. Color intensity reflects consecutive trend persistence within the chosen window. A small square at the bottom encodes the same gradient as a compact status channel. Optional wick coloring uses the same gradient for maximum contrast. The performance table lists parameter pairs and their cumulative return under the chosen aggregation; positive values are tinted with the up color, negative with the down color. “Long” labels mark flips that open a long in the simplified model.
Practical Workflows & Combinations
Trend following: Use the auto line as your primary bias. Enter on flips aligned with structure such as higher highs and higher lows. Filter with higher-timeframe trend or volatility contraction.
Exits/Stops: Consider conservative exits when color intensity fades or when the opposite line is approached. Aggressive traders can trail near the plotted line.
Override mode: When you want stability across instruments, enable override and standardize factor and ATR; keep the table visible for sanity checks.
Multi-asset/Multi-TF: Defaults travel well on liquid instruments and intraday to daily timeframes. Heavier assets may prefer larger lower bounds or multiplicative mode.
Behavior, Constraints & Performance
Repaint/confirmation: Signals are based on SuperTrend direction; confirmation is best assessed on closed bars to avoid mid-bar oscillation. No higher-timeframe requests are used.
Resources: One hundred and two SuperTrend evaluations per bar, arrays for state, and a last-bar table render. This is efficient for the grid size but avoid stacking many instances.
Known limits: The flip model ignores costs, slippage, and short exposure. Rapid whipsaws can degrade both aggregation modes. Gradients are cosmetic and do not change logic.
Sensible Defaults & Quick Tuning
Start with the provided lower bounds and “Top Three” table.
Too many flips → raise the lower bound factor or period.
Too sluggish → lower the bounds or switch to additive mode.
Rankings feel unstable → prefer multiplicative mode and extend the normalization window.
Visuals too strong → increase gradient transparency or disable wick coloring.
What this indicator is—and isn’t
This is a parameter-sweep and visualization layer for SuperTrend selection. It is not a complete trading system, not predictive, and does not include position sizing, transaction costs, or risk management. Combine with market structure, higher-timeframe context, and explicit risk controls.
Attribution and refactor note: The original work is by KioseffTrading. The script has been refactored from approximately two thousand three hundred seventy-one lines to about three hundred eighty core lines, retaining behavior without compiler errors. The general simplification pattern is reusable for other indicators.
Metadata
Name/Tag: SuperTrend Optimizer Remastered
Pine version: v6
Overlay or separate pane: true (overlay)
Core idea/principle: Grid-based SuperTrend selection by cumulative flip returns with additive or multiplicative aggregation.
Primary outputs/signals: Auto-selected SuperTrend up and down lines, optional override lines, gradient bar and wick colors, “Long” labels, performance table.
Inputs with defaults: See Parameter Guide above.
Metrics/functions used: SuperTrend, ATR, arrays, barstate checks, windowed normalization, gamma-based contrast adjustment, table API, gradient utilities.
Special techniques: Fixed grid sweep, compounding vs linear aggregation, last-bar UI updates, gradient encoding of persistence.
Performance/constraints: One hundred and two SuperTrend calls, arrays of length one hundred and two, label budget, last-bar table updates, no higher-timeframe requests.
Recommended use-cases/workflows: Trend bias selection, quick parameter audits, override standardization across assets.
Compatibility/assets/timeframes: Standard OHLC charts across intraday to daily; liquid instruments recommended.
Limitations/risks: Costs and slippage omitted; mid-bar instability possible; not suitable for synthetic chart types.
Debug/diagnostics: Ranking table, optional tested-range label; internal counters for consecutive trends.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
Historical VolatilityHistorical Volatility Indicator with Custom Trading Sessions
Overview
This indicator calculates **annualized Historical Volatility (HV)** using logarithmic returns and standard deviation. Unlike standard HV indicators, this version allows you to **customize trading sessions and holidays** for different markets, ensuring accurate volatility calculations for options pricing and risk management.
Key Features
✅ Custom Trading Sessions - Define multiple trading sessions per day with precise start/end times
✅ Multiple Markets Support - Pre-configured for US, Russian, European, and crypto markets
✅ Clearing Periods Handling - Account for intraday clearing breaks
✅ Flexible Calendar - Set trading days per year for different countries
✅ All Timeframes - Works correctly on intraday, daily, weekly, and monthly charts
✅ Info Table - Optional display showing calculation parameters
How It Works
The indicator uses the classical volatility formula:
σ_annual = σ_period × √(periods per year)
Where:
- σ_period = Standard deviation of logarithmic returns over the specified period
- Periods per year = Calculated based on actual trading time (not calendar time)
Calculation Method
1. Computes log returns: ln(close / close )
2. Calculates standard deviation over the lookback period
3. Annualizes using the square root rule with accurate period count
4. Displays as percentage
Settings
Calculation
- Period (default: 10) - Lookback period for volatility calculation
Trading Schedule
- Trading Days Per Year (default: 252) - Number of actual trading days
- USA: 252
- Russia: 247-250
- Europe: 250-253
- Crypto (24/7): 365
- Trading Sessions - Define trading hours in format: `hh:mm:ss-hh:mm:ss, hh:mm:ss-hh:mm:ss`
Display
- Show Info Table - Shows calculation parameters in real-time
Market Presets
United States (NYSE/NASDAQ)
Trading Sessions: 09:30:00-16:00:00
Trading Days Per Year: 252
Trading Minutes Per Day: 390
Russia (MOEX)
Trading Sessions: 10:00:00-14:00:00, 14:05:00-18:40:00
Trading Days Per Year: 248
Trading Minutes Per Day: 515
Europe (LSE)
Trading Sessions: 08:00:00-16:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Germany (XETRA)
Trading Sessions: 09:00:00-17:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Cryptocurrency (24/7)
Trading Sessions: 00:00:00-23:59:59
Trading Days Per Year: 365
Trading Minutes Per Day: 1440
Use Cases
Options Trading
- Compare HV vs IV - Historical volatility compared to implied volatility helps identify mispriced options
- Volatility mean reversion - Identify when volatility is unusually high or low
- Straddle/strangle selection - Choose optimal strikes based on historical movement
Risk Management
- Position sizing - Adjust position size based on current volatility
- Stop-loss placement - Set stops based on expected price movement
- Portfolio volatility - Monitor individual asset volatility contribution
Market Analysis
- Regime identification - Detect transitions between low and high volatility environments
- Cross-market comparison - Compare volatility across different assets and markets
Why Accurate Trading Hours Matter
Standard HV indicators assume 24-hour trading or use simplified day counts, leading to significant errors in annualized volatility:
- 5-minute chart error : Can be off by 50%+ if using wrong period count
- Options pricing impact : Even 2-3% HV error affects option values substantially
- Intraday vs overnight : Correctly excludes non-trading periods
This indicator ensures your HV calculations match the methodology used in professional options pricing models.
Technical Notes
- Uses actual trading minutes, not calendar days
- Handles multiple clearing periods within a single trading day
- Properly scales volatility across all timeframes
- Logarithmic returns for more accurate volatility measurement
- Compatible with Pine Script v6
Author Notes: This indicator was designed specifically for options traders who need precise volatility measurements across different global markets. The customizable trading sessions ensure your HV calculations align with actual market hours and industry-standard options pricing models.
Best MA Finder: Sharpe/Sortino ScannerThis script, Best MA Finder: Sharpe/Sortino Scanner, is a tool designed to identify the moving average (SMA or EMA) that best acts as a dynamic trend threshold on a chart, based on risk-adjusted historical performance. It scans a wide range of MA lengths (SMA or EMA) and selects the one whose simple price vs MA crossover delivered the strongest results using either the Sharpe ratio or the Sortino ratio. Reading it is intuitive: when price spent time above the selected MA, conditions were on average more favorable in the backtest; below, less favorable. It is a trend and risk gauge, not an overbought or oversold signal.
What it does:
- Runs individual long-only crossover backtests for many MA lengths across short to very long horizons.
- For each length, measures the total number of trades, the annualized Sharpe ratio, and the annualized Sortino ratio.
- Uses the chosen metric value (Sharpe or Sortino) as the score to rank candidates.
- Applies a minimum trade filter to discard statistically weak results.
- Optionally applies a local stability filter to prefer a length that also outperforms its close neighbors by at least a small margin.
- Selects the optimal MA and displays it on the chart with a concise summary table.
How to use it:
- Choose MA type: SMA or EMA.
- Choose the metric: Sharpe or Sortino.
- Set the minimum trade count to filter out weak samples.
- Select the risk-free mode:
Auto: uses a short-term risk-free rate for USD-priced symbols when available.
Manual: you provide a risk-free ticker.
None: no risk-free rate.
- Optionally enable stability controls: neighbor radius and epsilon.
- Toggle the on-chart summary table as needed.
On-chart output:
- The selected optimal MA is plotted.
- The optional table shows MA length, number of trades, chosen metric value annualized, and the annual risk-free rate used.
Key features:
- Risk-adjusted optimization via Sharpe or Sortino for fair, comparable assessment.
- Broad MA scan with SMA and EMA support.
- Optional stability filter to avoid one-off spikes.
- Clear and auditable presentation directly on the chart.
Use cases:
- Traders who want a defensible, data-driven trend threshold without manual trial and error.
- Swing and trend-following workflows across timeframes and asset classes.
- Quick SMA vs EMA comparisons using risk-adjusted results.
Limitations:
- Not a full trading strategy with position sizing, costs, funding, slippage, or stops.
- Long-only, one position at a time.
- Discrete set of MA lengths, not a continuous optimizer.
- Requires sufficient price history and, if used, a reliable risk-free series.
This script is open-source and built from original logic. It does not replicate closed-source scripts or reuse significant external components.
Multi Momentum 10/21/42/63 — Histogram + 2xSMAMY MM INDICATOR INDIRED BY KARADI
It averages four rate-of-change snapshots of price, all anchored at today’s close.
If “Show as %” is on, the value is multiplied by 100.
Each term is a simple momentum/ROC over a different lookback.
Combining 10, 21, 42, 63 bars blends short, medium, and intermediate horizons into one number.
Positive MM → average upward pressure across those horizons; negative MM → average downward pressure.
Why those lengths?
They roughly stack into ~2× progression (10→21≈2×10, 21→42=2×21, 63≈1.5×42). That creates a “multi-scale” momentum that’s less noisy than a single fast ROC but more responsive than a long ROC alone.
How to read the panel
Gray histogram = raw Multi-Momentum value each bar.
SMA Fast/Slow lines (defaults 12 & 26 over the MM values) = smoothing of the histogram to show the trend of momentum itself.
Typical signals
Zero-line context:
Above 0 → bullish momentum regime on average.
Below 0 → bearish regime.
Crosses of SMA Fast & Slow: momentum trend shifts (fast above slow = improving momentum; fast below slow = deteriorating).
Histogram vs SMA lines: widening distance suggests strengthening momentum; narrowing suggests momentum is fading.
Divergences: price makes a new high/low but MM doesn’t → potential exhaustion.
Compared to a classic ROC
A single ROC(20) is very sensitive to that one window.
MM averages several windows, smoothing idiosyncrasies (e.g., a one-off spike 21 bars ago) and reducing “lookback luck.”
Settings & customization
Lookbacks (10/21/42/63): you can tweak for your asset/timeframe; the idea is to mix short→medium horizons.
Percent vs raw ratio: percent is easier to compare across symbols.
SMA lengths: shorter = more reactive but choppier; longer = smoother but slower.
Practical tips
Use regime + signal: trade longs primarily when MM>0 and fast SMA>slow SMA; consider shorts when MM<0 and fast
Irrationality Index by CRYPTO_ADA_BTC"The market can be irrational longer than you can stay solvent" ~ John Maynard Keynes
This indicator, the Irrationality Index, measures how far the current market price has deviated from a smoothed estimate of its "fair value," normalized for recent volatility. It provides traders with a visual sense of when the market may be behaving irrationally, without giving direct buy or sell signals.
How it works:
1. Fair Value Calculation
The indicator estimates a "fair value" for the asset using a combination of a long-term EMA (exponential moving average) and a linear regression trend over a configurable period. This fair value serves as a smoothed baseline for price, balancing trend-following and mean-reversion.
2. Volatility-Adjusted Z-Score
The deviation between price and fair value is measured in standard deviations of recent log returns:
Z = (log(price) - log(fairValue)) / volatility
This standardization accounts for different volatility environments, allowing comparison across assets.
3. Irrationality Score (0–100)
The Z-score is transformed using a logistic mapping into a 0–100 scale:
- 50 → price near fair value (rational zone)
- >75 → high irrationality, price stretched above fair value
- >90 → extreme irrationality, unsustainable extremes
- <25 → high irrationality, price stretched below fair value
- <10 → extreme bearish irrationality
4. Price vs Fair Value (% deviation)
The indicator plots the percentage difference between price and fair value:
pctDiff = (price - fairValue) / fairValue * 100
- Positive values → Percentage above fair value (optimistic / overvalued)
- Negative values → Percentage below fair value (pessimistic / undervalued)
Visuals:
- Irrationality (%) Line (0–100) shows irrationality level.
- Background Colors: Yellow= high bullish irrationality, Green= extreme bullish irrationality, Orange= high bearish irrationality, Red= extreme bearish irrationality.
- Price - FairValue (%) plot: price deviation vs fair value (%), Colored green above 0 and red below 0.
- Label: display actual price, estimated fair value, and Z-score for the latest bar.
- Alerts: configurable thresholds for high and extreme irrationality.
How to read it:
- 50 → Market trading near fair value.
- >75 / >90 → Price may be irrationally high; risk of pullback increases.
- <25 / <10 → Price may be irrationally low; potential rebound zones, but trends can continue.
- Price - FairValue (%) plot → visual guide for % price stretch relative to fair value.
Notes / Warnings:
- Measures relative deviation, not fundamental value!
- High irrationality scores do not automatically indicate trades; markets can remain can be irrational longer than you can stay solvent .
- Best used with other tools: momentum, volume, divergence, and multi-timeframe analysis.
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner
What it is
This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter.
Why pairs at all?
Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean.
Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments.
This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade.
How it works (plain English)
Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both.
Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence.
Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down.
Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.”
Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print:
LONG = long chart symbol / short pair symbol,
SHORT = short chart symbol / long pair symbol,
EXIT = mean reversion into the exit zone or correlation failure.
Core concepts (the three pillars)
Spread Method Your definition of “distance” between the two series.
Guidance:
Log Spread: Focuses on proportional differences; robust when prices live on different scales.
Price Ratio: Classic relative value; good when you care about “X per Y.”
Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays.
Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs).
Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence.
Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context.
What you’ll see on the chart
Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off.
Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean.
Normalized spread (yellow) for a quick “shape read” of recent divergence swings.
Signal markers :
LONG (green label) when Z < –Entry and corr OK,
SHORT (red label) when Z > +Entry and corr OK,
EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor.
Background tint for active state (faint green for long-spread stance, faint red for short-spread stance).
The two built-in dashboards
Statistics Table (top-right)
Pair Symbol Your chosen partner.
Correlation Live value vs. your minimum.
Z-Score How stretched the spread is now.
Current / Pair Prices Real-time anchors.
Signal State NEUTRAL / LONG / SHORT.
Price Ratio Context for ratio-style setups.
Analysis Table (bottom-right)
Avg Correlation Typical co-movement level over your window.
Max |Z| The recent extremes of dislocation.
Spread Volatility How “lively” the spread has been.
Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”).
Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z).
Signals logic (plain English)
Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair.
Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair.
Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted).
A quick, repeatable workflow
1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?”
2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.).
3) Confirm correlation is above your floor no corr, no trade.
4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT .
5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest.
Settings that matter (and why)
Spread Method Defines the “mispricing” you care about.
Correlation Period Longer = steadier regime read, shorter = snappier to regime change.
Z-Score Period The window that defines “normal” for the spread; it sets the yardstick.
Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets.
Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals.
Minimum Correlation The gatekeeper. Raising it favors quality over quantity.
Choosing pairs (practical cheat sheet)
Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens.
Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF.
Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday.
Reading the cues like a pro
Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind.
Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust.
Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it.
Frequently asked (quick answers)
“Long/Short means what exactly?”
LONG = long the chart symbol and short the pair symbol.
SHORT = short the chart symbol and long the pair symbol.
“Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales).
“What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second.
Field notes & patterns
Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions.
Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|.
Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering.
Display controls at a glance
Show Statistics Table Live state & key numbers, top-right.
Show Analysis Table Context/risk read, bottom-right.
Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible.
Show Entry/Exit Signals Turn markers on/off as needed.
Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme.
Alerts (ready to route to your workflow)
Pairs Long Entry Z falls through the long threshold with correlation above minimum.
Pairs Short Entry Z rises through the short threshold with correlation above minimum.
Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor.
Correlation Breakdown Rolling correlation crosses your minimum; relationship caution.
Final notes
The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
BioSwarm Imprinter™BioSwarm Imprinter™ — Agent-Based Consensus for Traders
What it is
BioSwarm Imprinter™ is a non-repainting, agent-based sentiment oscillator. It fuses many short-to-medium lookback “opinions” into one 0–100 consensus line that is easy to read at a glance (50 = neutral, >55 bullish bias, <45 bearish bias). The engine borrows from swarm intelligence: many simple voters (agents) adapt their influence over time based on how well they’ve been predicting price, so the crowd gets smarter as conditions change.
Use it to:
• Detect emerging trends sooner without overreacting to noise.
• Filter mean-reversion vs continuation opportunities.
• Gate entries with a confidence score that reflects both strength and persistence of the move.
• Combine with your execution tools (VWAP/ORB/levels) as a state filter rather than a trade signal by itself.
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Why it’s different
• Swarm learning: Each agent improves or decays its “fitness” depending on whether its vote matched the next bar’s direction. High-fitness agents matter more; weak agents fade.
• Multi-horizon by design: The crowd is composed of fixed, simple lookbacks spread from lenMin to lenMax. You get a blended, robust view instead of a single fragile parameter.
• Two complementary lenses: Each agent evaluates RSI-style balance (via Wilder’s RMA) and momentum (EMA deviation). You decide the weight of each.
• No repaint, no MTF pitfalls: Everything runs on the chart’s timeframe with bar-close confirmation; no request.security() or forward references.
• Actionable UI: A clean consensus line, optional regime background, confidence heat, and triangle markers when thresholds are crossed.
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What you see on the chart
• Consensus line (0–100): Smoothed to your preference; color/area makes bull/bear zones obvious.
• Regime coloring (optional): Light green in bull zone, light red in bear zone; neutral otherwise.
• Confidence heat: A small gauge/number (0–100) that combines distance from neutral and recent persistence.
• Markers (optional): Triangles when consensus crosses up through your bull threshold (e.g., 55) or down through your bear threshold (e.g., 45).
• Info panel (optional): Consensus value, regime, confidence, number of agents, and basic diagnostics.
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How it works (under the hood)
1. Horizon bins: The range is divided into numBins. Each bin has a fixed, simple integer length (crucial for Pine’s safety rules).
2. Per-bin features (computed every bar):
• RSI-style balance using Wilder’s RMA (not ta.rsi()), then mapped to −1…+1.
• Momentum as (close − EMA(L)) / EMA(L) (dimensionless drift).
3. Agent vote: For its assigned bin, an agent forms a weighted score: score = wRSI*RSI_like + wMOM*Momentum. A small dead-band near zero suppresses chop; votes are +1/−1/0.
4. Fitness update (bar close): If the agent’s previous vote agreed with the next bar’s direction, multiply its fitness by learnGain; otherwise by learnPain. Fitness is clamped so it never explodes or dies.
5. Consensus: Weighted average of all votes using fitness as weights → map to 0–100 and smooth with EMA.
Why it doesn’t repaint:
• No future references, no MTF resampling, fitness updates only on confirmed bars.
• All TA primitives (RMA/EMA/deltas) are computed every bar unconditionally.
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Signals & confidence
• Bullish bias: consensus ≥ bullThr (e.g., 55).
• Bearish bias: consensus ≤ bearThr (e.g., 45).
• Confidence (0–100):
• Distance score: how far consensus is from 50.
• Momentum score: how strong the recent change is versus its recent average.
• Combined into a single gate; start filtering entries at ≥60 for higher quality.
Tip: For range sessions, raise thresholds (60/40) and increase smoothing; for momentum sessions, lower smoothing and keep thresholds at 55/45.
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Inputs you’ll actually tune
• Agents & horizons:
• N_agents (e.g., 64–128)
• lenMin / lenMax (e.g., 6–30 intraday, 10–60 swing)
• numBins (e.g., 12–24)
• Weights & smoothing:
• wRSI vs wMOM (e.g., 0.7/0.3 for FX & indices; 0.6/0.4 for crypto)
• deadBand (0.03–0.08)
• consSmooth (3–8)
• Thresholds & hygiene:
• bullThr/bearThr (55/45 default)
• cooldownBars to avoid signal spam
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Playbooks (ready-to-use)
1) Breakout / Trend continuation
• Timeframe: 15m–1h for day/swing.
• Filter: Take longs only when consensus > 55 and confidence ≥ 60.
• Execution: Use your ORB/VWAP/pullback trigger for entry. Trail with swing lows or 1.5×ATR. Exit on a close back under 50 or when a bearish signal prints.
2) Mean reversion (fade)
• When: Sideways days or low-volatility clusters.
• Setup: Increase deadBand and consSmooth.
• Signal: Bearish fades when consensus rolls over below ≈55 but stays above 50; bullish fades when it rolls up above ≈45 but stays below 50.
• Targets: The neutral zone (~50) as the first take-profit.
3) Multi-TF alignment
• Keep BioSwarm on 1H for bias, execute on 5–15m:
• Only take entries in the direction of the 1H consensus.
• Skip counter-bias scalps unless confidence is very low (explicit mean-reversion plan).
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Integrations that work
• DynamoSent Pro+ (macro bias): Only act when macro bias and swarm consensus agree.
• ORB + Session VWAP Pro: Trade London/NY ORB breakouts that retest while consensus >55 (long) or <45 (short).
• Levels/Orderflow: BioSwarm is your “go / no-go”; execution stays with your usual triggers.
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Quick start
1. Drop the indicator on a 1H chart.
2. Start with: N_agents=64, lenMin=6, lenMax=30, numBins=16, deadBand=0.06, consSmooth=5, thresholds 55/45.
3. Trade only when confidence ≥ 60.
4. Add your favorite execution tool (VWAP/levels/OR) for entries & exits.
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Non-repainting & safety notes
• No request.security(); no hidden lookahead.
• Bar-close confirmation for fitness and signals.
• All TA calls are unconditional (no “sometimes called” warnings).
• No series-length inputs to RSI/EMA — we use RMA/EMA formulas that accept fixed simple ints per bin.
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Known limits & tips
• Too many signals? Raise deadBand, increase consSmooth, widen thresholds to 60/40.
• Too few signals? Lower deadBand, reduce consSmooth, narrow thresholds to 53/47.
• Over-fitting risk: Keep learnGain/learnPain modest (e.g., ×1.04 / ×0.96).
• Compute load: Large N_agents × numBins is heavier; scale to your device.
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Example recipes
EURUSD 1H (swing):
lenMin=8, lenMax=34, numBins=16, wRSI=0.7, wMOM=0.3, deadBand=0.06, consSmooth=6, thr=55/45
Buy breakouts when consensus >55 and confidence ≥60; confirm with 5–15m pullback to VWAP or level.
SPY 15m (US session):
lenMin=6, lenMax=24, numBins=12, consSmooth=4, deadBand=0.05
On trend days, stay with longs as long as consensus >55; add on shallow pullbacks.
BTC 1H (24/7):
Increase momentum weight: wRSI=0.6, wMOM=0.4, extend lenMax to ~50. Use dynamic stops (ATR) and partials on strong verticals.
⸻
Final word
BioSwarm is a state engine: it tells you when the market is primed to continue or mean-revert. Pair it with your entries and risk framework to turn that state into trades. If you’d like, I can supply a companion strategy template that consumes the consensus and back-tests the three playbooks (Breakout/Fade/Flip) with standard risk management.
Whale Money Flow DetectorKey Components:
Volume Analysis: Detects unusual volume spikes compared to average
Money Flow Index: Shows buying vs selling pressure
Whale Detection: Identifies large moves with high volume
Cumulative Flow: Tracks net whale activity over time
Visual Signals: Background colors and whale emoji labels
What it detects:
Large volume transactions (configurable multiplier)
Significant price moves with corresponding volume
Buying vs selling pressure from large players
Cumulative whale flow momentum
Customizable Parameters:
Volume MA Length (default: 20)
Whale Volume Multiplier (default: 2.0x)
Money Flow Length (default: 14)
Detection Sensitivity (default: 1.5)
Visual Features:
Green background for whale buying
Red background for whale selling
Whale emoji labels on significant moves
Real-time stats table
Multiple plot lines for different metrics
How to use:
Copy the code to TradingView's Pine Editor
Apply to your chart
Adjust sensitivity settings based on your asset's behavior
Set up alerts for whale buy/sell signals
Dual Best MA Strategy AnalyzerDual Best MA Strategy Analyzer (Lookback Window)
What it does
This indicator scans a range of moving-average lengths and finds the single best MA for long crossovers and the single best MA for short crossunders over a fixed lookback window. It then plots those two “winner” MAs on your chart:
Best Long MA (green): The MA length that would have made the highest total profit using a simple “price crosses above MA → long; exit on cross back below” logic.
Best Short MA (red): The MA length that would have made the highest total profit using “price crosses below MA → short; exit on cross back above.”
You can switch between SMA and EMA, set the min/max length, choose a step size, and define the lookback window used for evaluation.
How it works (brief)
For each candidate MA length between Min MA Length and Max MA Length (stepping by Step Size), the script:
Builds the MA (SMA or EMA).
Simulates a naïve crossover strategy over the last Lookback Window candles:
Long model: enter on crossover, exit on crossunder.
Short model: enter on crossunder, exit on crossover.
Sums simple P&L in price units (no compounding, no fees/slippage).
Picks the best long and best short lengths by total P&L and plots those two MAs.
Note: Long and short are evaluated independently. The script plots MAs only; it doesn’t open positions.
Inputs
Min MA Length / Max MA Length – Bounds for MA search.
Step Size – Spacing between tested lengths (e.g., 10 tests 10, 20, 30…).
Use EMA instead of SMA – Toggle average type.
Lookback Window (candles) – Number of bars used to score each MA. Needs enough history to be meaningful.
What the plots mean
Best Long MA (green): If price crosses above this line (historically), that MA length produced the best long-side results over the lookback.
Best Short MA (red): If price crosses below this line (historically), that MA length produced the best short-side results.
These lines can change over time as new bars enter the lookback window. Think of them as adaptive “what worked best recently” guides, not fixed signals.
Practical tips
Timeframe matters: Run it on the timeframe you trade; the “best” length on 1h won’t match 1m or 1D.
Step size trade-off: Smaller steps = more precision but heavier compute. Larger steps = faster scans, coarser choices.
Use with confirmation: Combine with structure, volume, or volatility filters. This is a single-factor tester.
Normalization: P&L is in raw price units. For cross-symbol comparison, consider using one symbol at a time (or adapt the script to percent P&L).
Limitations & assumptions
No fees, funding, slippage, or position sizing.
Simple “in/out” on the next crossover; no stops/targets/filters.
Results rely on lookback choice and will repaint historically as the “best” length is re-selected with new data (the plot is adaptive, not forward-fixed).
The script tests up to ~101 candidates internally (bounded by your min/max/step).
Good uses
Quickly discover a recently effective MA length for trend following.
Compare SMA vs EMA performance on your market/timeframe.
Build a playbook: note which lengths tend to win in certain regimes (trending vs choppy).
Not included (by design)
Alerts, entries/exits, or a full strategy report. It’s an analyzer/overlay.
If you want alerts, you can add simple conditions like:
ta.crossover(close, plotLongMA) for potential long interest
ta.crossunder(close, plotShortMA) for potential short interest
Changelog / Notes
v1: Initial release. Array-based scanner, SMA/EMA toggle, adaptive long/short best MA plots, user-set lookback.
Disclaimer
This is educational tooling, not financial advice. Test thoroughly and use proper risk management.
Structural Liquidity Signals [BullByte]Structural Liquidity Signals (SFP, FVG, BOS, AVWAP)
Short description
Detects liquidity sweeps (SFPs) at pivots and PD/W levels, highlights the latest FVG, tracks AVWAP stretch, arms percentile extremes, and triggers after confirmed micro BOS.
Full description
What this tool does
Structural Liquidity Signals shows where price likely tapped liquidity (stop clusters), then waits for structure to actually change before it prints a trigger. It spots:
Liquidity sweeps (SFPs) at recent pivots and at prior day/week highs/lows.
The latest Fair Value Gap (FVG) that often “pulls” price or serves as a reaction zone.
How far price is stretched from two VWAP anchors (one from the latest impulse, one from today’s session), scaled by ATR so it adapts to volatility.
A “percentile” extreme of an internal score. At extremes the script “arms” a setup; it only triggers after a small break of structure (BOS) on a closed bar.
Originality and design rationale, why it’s not “just a mashup”
This is not a mashup for its own sake. It’s a purpose-built flow that links where liquidity is likely to rest with how structure actually changes:
- Liquidity location: We focus on areas where stops commonly cluster—recent pivots and prior day/week highs/lows—then detect sweeps (SFPs) when price wicks beyond and closes back inside.
- Displacement context: We track the last Fair Value Gap (FVG) to account for recent inefficiency that often acts as a magnet or reaction zone.
- Stretch measurement: We anchor VWAP to the latest N-bar impulse and to the Daily session, then normalize stretch by ATR to assess dislocation consistently across assets/timeframes.
- Composite exhaustion: We combine stretch, wick skew, and volume surprise, then bend the result with a tanh transform so extremes are bounded and comparable.
- Dynamic extremes and discipline: Rather than triggering on every sweep, we “arm” at statistical extremes via percent-rank and only fire after a confirmed micro Break of Structure (BOS). This separates “interesting” from “actionable.”
Key concepts
SFP (liquidity sweep): A candle briefly trades beyond a level (where stops sit) and closes back inside. We detect these at:
Pivots (recent swing highs/lows confirmed by “left/right” bars).
Prior Day/Week High/Low (PDH/PDL/PWH/PWL).
FVG (Fair Value Gap): A small 3‑bar gap (bar2 high vs bar1 low, or vice versa). The latest gap often acts like a magnet or reaction zone. We track the most recent Up/Down gap and whether price is inside it.
AVWAP stretch: Distance from an Anchored VWAP divided by ATR (volatility). We use:
Impulse AVWAP: resets on each new N‑bar high/low.
Daily AVWAP: resets each new session.
PR (Percentile Rank): Where the current internal score sits versus its own recent history (0..100). We arm shorts at high PR, longs at low PR.
Micro BOS: A small break of the recent high (for longs) or low (for shorts). This is the “go/no‑go” confirmation.
How the parts work together
Find likely liquidity grabs (SFPs) at pivots and PD/W levels.
Add context from the latest FVG and AVWAP stretch (how far price is from “fair”).
Build a bounded score (so different markets/timeframes are comparable) and compute its percentile (PR).
Arm at extremes (high PR → short candidate; low PR → long candidate).
Only print a trigger after a micro BOS, on a closed bar, with spacing/cooldown rules.
What you see on the chart (legend)
Lines:
Teal line = Impulse AVWAP (resets on new N‑bar extreme).
Aqua line = Daily AVWAP (resets each session).
PDH/PDL/PWH/PWL = prior day/week levels (toggle on/off).
Zones:
Greenish box = latest Up FVG; Reddish box = latest Down FVG.
The shading/border changes after price trades back through it.
SFP labels:
SFP‑P = SFP at Pivot (dotted line marks that pivot’s price).
SFP‑L = SFP at Level (at PDH/PDL/PWH/PWL).
Throttle: To reduce clutter, SFPs are rate‑limited per direction.
Triggers:
Triangle up = long trigger after BOS; triangle down = short trigger after BOS.
Optional badge shows direction and PR at the moment of trigger.
Optional Trigger Zone is an ATR‑sized box around the trigger bar’s close (for visualization only).
Background:
Light green/red shading = a long/short setup is “armed” (not a trigger).
Dashboard (Mini/Pro) — what each item means
PR: Percentile of the internal score (0..100). Near 0 = bullish extreme, near 100 = bearish extreme.
Gauge: Text bar that mirrors PR.
State: Idle, Armed Long (with a countdown), or Armed Short.
Cooldown: Bars remaining before a new setup can arm after a trigger.
Bars Since / Last Px: How long since last trigger and its price.
FVG: Whether price is in the latest Up/Down FVG.
Imp/Day VWAP Dist, PD Dist(ATR): Distance from those references in ATR units.
ATR% (Gate), Trend(HTF): Status of optional regime filters (volatility/trend).
How to use it (step‑by‑step)
Keep the Safety toggles ON (default): triggers/visuals on bar‑close, optional confirmed HTF for trend slope.
Choose timeframe:
Intraday (5m–1h) or Swing (1h–4h). On very fast/thin charts, enable Performance mode and raise spacing/cooldown.
Watch the dashboard:
When PR reaches an extreme and an SFP context is present, the background shades (armed).
Wait for the trigger triangle:
It prints only after a micro BOS on a closed bar and after spacing/cooldown checks.
Use the Trigger Zone box as a visual reference only:
This script never tells you to buy/sell. Apply your own plan for entry, stop, and sizing.
Example:
Bullish: Sweep under PDL (SFP‑L) and reclaim; PR in lower tail arms long; BOS up confirms → long trigger on bar close (ATR-sized trigger zone shown).
Bearish: Sweep above PDH/pivot (SFP‑L/P) and reject; PR in upper tail arms short; BOS down confirms → short trigger on bar close (ATR-sized trigger zone shown).
Settings guide (with “when to adjust”)
Safety & Stability (defaults ON)
Confirm triggers at bar close, Draw visuals at bar close: Keep ON for clean, stable prints.
Use confirmed HTF values: Applies to HTF trend slope only; keeps it from changing until the HTF bar closes.
Performance mode: Turn ON if your chart is busy or laggy.
Core & Context
ATR Length: Bigger = smoother distances; smaller = more reactive.
Impulse AVWAP Anchor: Larger = fewer resets; smaller = resets more often.
Show Daily AVWAP: ON if you want session context.
Use last FVG in logic: ON to include FVG context in arming/score.
Show PDH/PDL/PWH/PWL: ON to see prior day/week levels that often attract sweeps.
Liquidity & Microstructure
Pivot Left/Right: Higher values = stronger/rarer pivots.
Min Wick Ratio (0..1): Higher = only more pronounced SFP wicks qualify.
BOS length: Larger = stricter BOS; smaller = quicker confirmations.
Signal persistence: Keeps SFP context alive for a few bars to avoid flicker.
Signal Gating
Percent‑Rank Lookback: Larger = more stable extremes; smaller = more reactive extremes.
Arm thresholds (qHi/qLo): Move closer to 0.5 to see more arms; move toward 0/1 to see fewer arms.
TTL, Cooldown, Min bars and Min ATR distance: Space out triggers so you’re not reacting to minor noise.
Regime Filters (optional)
ATR percentile gate: Only allow triggers when volatility is at/above a set percentile.
HTF trend gate: Only allow longs when the HTF slope is up (and shorts when it’s down), above a minimum slope.
Visuals & UX
Only show “important” SFPs: Filters pivot SFPs by Volume Z and |Impulse stretch|.
Trigger badges/history and Max badge count: Control label clutter.
Compact labels: Toggle SFP‑P/L vs full names.
Dashboard mode and position; Dark theme.
Reading PR (the built‑in “oscillator”)
PR ~ 0–10: Potential bullish extreme (long side can arm).
PR ~ 90–100: Potential bearish extreme (short side can arm).
Important: “Armed” ≠ “Enter.” A trigger still needs a micro BOS on a closed bar and spacing/cooldown to pass.
Repainting, confirmations, and HTF notes
By default, prints wait for the bar to close; this reduces repaint‑like effects.
Pivot SFPs only appear after the pivot confirms (after the chosen “right” bars).
PD/W levels come from the prior completed candles and do not change intraday.
If you enable confirmed HTF values, the HTF slope will not change until its higher‑timeframe bar completes (safer but slightly delayed).
Performance tips
If labels/zones clutter or the chart lags:
Turn ON Performance mode.
Hide FVG or the Trigger Zone.
Reduce badge history or turn badge history off.
If price scaling looks compressed:
Keep optional “score”/“PR” plots OFF (they overlay price and can affect scaling).
Alerts (neutral)
Structural Liquidity: LONG TRIGGER
Structural Liquidity: SHORT TRIGGER
These fire when a trigger condition is met on a confirmed bar (with defaults).
Limitations and risk
Not every sweep/extreme reverses; false triggers occur, especially on thin markets and low timeframes.
This indicator does not provide entries, exits, or position sizing—use your own plan and risk control.
Educational/informational only; no financial advice.
License and credits
© BullByte - MPL 2.0. Open‑source for learning and research.
Built from repeated observations of how liquidity runs, imbalance (FVG), and distance from “fair” (AVWAPs) combine, and how a small BOS often marks the moment structure actually shifts.
PolyFilter [BackQuant]PolyFilter
A flexible, low-lag trend filter with three smoothing engines—optimized for clean bias, fewer whipsaws, and clear alerting.
What it does
PolyFilter draws a single “intelligent” baseline that adapts to price while suppressing noise. You choose the engine— Fractional MA , Ehlers 2-Pole Super Smoother , or a Multi-Kernel blend . The line can color itself by slope (trend) or by position vs price (above/below), and you get four ready-made alerts for flips and crosses.
What it plots
PolyFilter line — your smoothed trend baseline (width set by “Line Width”).
Optional candle & background coloring — choose: color by trend slope or by whether price is above/below the filter.
Signal markers — Arrows with L/S when the slope flips or when price crosses the line (if you enable shapes/alerts).
How the three engines differ
Fractional MA (experimental) — A power-law weighting of past bars (heavier focus on the most recent samples without throwing away history). The Adaptation Speed acts like the “fraction” exponent (default 0.618). Lower values lean more on recent bars; higher values spread weight further back.
Ehlers 2-Pole Super Smoother — Classic low-lag IIR smoother that aggressively reduces high-frequency noise while preserving turns. Great default when you want a steady, responsive baseline with minimal parameter fuss.
Multi-Kernel — A 70/30 blend of a Gaussian window and an exponential kernel. The Gaussian contributes smooth structure; the exponential adds a hint of responsiveness. Useful for assets that oscillate but still trend.
Reading the colors
Trend mode (default) — Line & candles turn green while the filter is rising (signal > signal ) and red while it’s falling.
Above/Below mode — Line & candles reflect price’s position relative to the filter: green when price > filter, red when price < filter. This is handy if you treat the filter like a dynamic “fair value” or bias line.
Inputs you’ll actually use
Calculation Settings
Price Source — Default HLC/3. Switch to Close for stricter trend, or HLC3/HL2 to soften single-print spikes.
Filter Length — Window/period for all engines. Shorter = snappier turns; longer = smoother line.
Adaptation Speed — Only affects Fractional MA . Lower it for faster, more local weighting; raise it for smoother, more global weighting.
Filter Type — Pick one of: Fractional MA, Ehlers 2-Pole, Multi-Kernel.
UI & Plotting
Color based off… — Choose Trend (slope) or > or < Close (position vs price).
Long/Short Colors — Customize bull/bear hues to your theme.
Show Filter Line / Paint candles / Color background — Visual toggles for the line, bars, and backdrop.
Line Width — Make the filter stand out (2–3 works well on most charts).
Signals & Alerts
PolyFilter Trend Up — Slope flips upward (the filter crosses above its prior value). Good for early continuation entries or stop-tightening on shorts.
PolyFilter Trend Down — Slope flips downward. Often used to scale out longs or rotate bias.
PolyFilter Above Price — The filter line crosses up through price (filter > price). This can confirm that mean has “caught up” after a pullback.
PolyFilter Below Price — The filter line crosses down through price (filter < price). Useful to confirm momentum loss on bounces.
Quick starts (suggested presets)
Intraday (5–15m, crypto or indices) — Ehlers 2-Pole, Length 55–80. Trend coloring ON, candle paint ON. Look for pullbacks to a rising filter; avoid fading a falling one.
Swing (1H–4H) — Multi-Kernel, Length 80–120. Background color OFF (cleaner), candle paint ON. Add a higher-TF confirmation (e.g., 4H filter rising when you trade 1H).
Range-prone FX — Fractional MA, Length 70–100, Adaptation ~0.55–0.70. Consider Above/Below mode to trade mean reversion to the line with a strict risk cap.
How to use it in practice
Bias line — Trade in the direction of the filter slope; stand aside when it flattens and color chops back and forth.
Dynamic support/resistance — Treat the line as a moving value area. In trends, entries often appear on shallow tags of the line with structure confluence.
Regime switch — When the filter flips and holds color for several bars, tighten stops on the opposing side and look for first pullback in the new color.
Stacking filters — Many users run PolyFilter on the active chart and a slower instance (longer length) on a higher timeframe as a “macro bias” guardrail.
Tuning tips
If you see too many flips, lengthen the filter or switch to Multi-Kernel.
If turns feel late, shorten the filter or try Ehlers 2-Pole for lower lag.
On thin or very noisy symbols, prefer HLC3 as the source and longer lengths.
Performance note: very large lengths increase computation time for the Multi-Kernel and Fractional engines. Start moderate and scale up only if needed.
Summary
PolyFilter gives you a single, trustworthy baseline that you can read at a glance—either as a pure trend line (slope coloring) or as a dynamic “above/below fair value” reference. Pick the engine that matches your market’s personality, set a sensible length, and let the color and alerts guide bias, entries on pullbacks, and risk on reversals.
EMA+RSI Buy/Sell with Fibonacci GuideSingle-Instance EUR/USD & GBP/USD Trend+MACD ATR EA
Purpose:
This EA is designed for automated Forex trading on EUR/USD and GBP/USD. It identifies trend-based trading opportunities, dynamically calculates position sizes based on your available capital and risk percentage, and manages trades with ATR-based stop-loss and take-profit levels, including optional trailing stops.
Key Features:
Auto Pair Selection:
Compares the trend strength of EUR/USD vs GBP/USD using a combination of EMA slopes and MACD direction.
Automatically trades the stronger trending pair.
Trend & Signal Detection:
Uses Fast EMA / Slow EMA crossover for trend direction.
Confirms trend with MACD line vs signal line.
Generates long and short signals only when trend and MACD align.
Dynamic SL/TP:
Stop-loss and take-profit are calculated based on ATR (Average True Range).
Supports optional trailing stops to lock in profits.
Position Sizing:
Automatically calculates micro-lot sizes based on your capital and risk percentage.
Ensures risk per trade does not exceed the defined % of your account equity.
Chart Visualization:
Plots Fast EMA / Slow EMA.
Displays SL and TP levels on the chart.
Shows a label indicating the active pair currently being traded.
Alerts:
Generates alerts for long and short signals.
Can be used with TradingView alerts to notify or trigger webhooks.
Single Strategy Instance:
Fully compatible with Pine Script v6.
Only one strategy instance runs on the chart to prevent “too many strategies” errors.
Small-Cap — Sell Every Spike (Rendon1) Small-Cap — Sell Every Spike v6 — Strict, No Look-Ahead
Educational use only. This is not financial advice or a signal service.
This strategy targets low/ mid-float runners (≤ ~20M) that make parabolic spikes. It shorts qualified spikes and scales out into flushes. Logic is deliberately simple and transparent to avoid curve-fit.
What the strategy does
Detects a parabolic up move using:
Fast ROC over N bars
Big range vs ATR
Volume spike vs SMA
Fresh higher high (no stale spikes)
Enters short at bar close when conditions are met (no same-bar fills).
Manages exits with ATR targets and optional % covers.
Tracks float rotation intraday (manual float input) and blocks trades above a hard limit.
Draws daily spike-high resistance from confirmed daily bars (no repaint / no look-ahead).
Timeframes & market
Designed for 1–5 minute charts.
Intended for US small-caps; turn Premarket on.
Works intraday; avoid illiquid tickers or names with constant halts.
Entry, Exit, Risk (short side)
Entry: parabolic spike (ROC + Range≥ATR×K + Vol≥SMA×K, new HH).
Optional confirmations (OFF by default to “sell every spike”): upper-wick and VWAP cross-down.
Stop: ATR stop above entry (default 1.2× ATR).
Targets: TP1 = 1.0× ATR, TP2 = 2.0× ATR + optional 10/20/30% covers.
Safety: skip trades if RVOL is low or Float Rotation exceeds your limit (default warn 5×, hard 7×).
Inputs (Balanced defaults)
Price band: $2–$10
Float Shares: set per ticker (from Finviz).
RVOL(50) ≥ 1.5×
ROC(5) ≥ 1.0%, Range ≥ 1.6× ATR, Vol ≥ 1.8× SMA
Cooldown: 10 bars; Max trades/day: 6
Optional: Require wick (≥35%) and/or Require VWAP cross-down.
Presets suggestion:
• Balanced (defaults above)
• Safer: wick+VWAP ON, Range≥1.8×, trades/day 3–4
• Micro-float (<5M): ROC 1.4–1.8%, Range≥1.9–2.2×, Vol≥2.2×, RVOL≥2.0, wick 40–50%
No look-ahead / repaint notes
Daily spike-highs use request.security(..., lookahead_off) and shifted → only closed daily bars.
Orders arm next bar after entry; entries execute at bar close.
VWAP/ATR/ROC/Vol/RVOL are computed on the chart timeframe (no HTF peeking).
How to use
Build a watchlist: Float <20M, RelVol >2, Today +20% (Finviz).
Open 1–5m chart, enter Float Shares for the ticker.
Start with Balanced, flip to Safer on halty/SSR names or repeated VWAP reclaims.
Scale out into flushes; respect the stop and rotation guard.
Limitations & risk
Backtests on small-caps can be optimistic due to slippage, spreads, halts, SSR, and limited premarket data. Always use conservative sizing. Low-float stocks can squeeze violently.
Alerts
Parabolic UP (candidate short)
SHORT Armed (conditions met; entry at bar close)
Liquidity Void Detector (Zeiierman)█ Overview
Liquidity Void Detector (Zeiierman) is an oscillator highlighting inefficient price displacements under low participation. It measures the most recent price move (standardized return) and amplifies it only when volume is below its own trend.
Positive readings ⇒ strong up-move on low volume → potential Buy-Side Imbalance (void below) that often refills.
Negative readings ⇒ strong down-move on low volume → potential Sell-Side Imbalance (void above) that often refills.
This tool provides a quantitative “void” proxy: when price travels far with unusually thin volume, the move is flagged as likely inefficient and prone to mean-reversion/mitigation.
█ How It Works
⚪ Volume Shock (Participation Filter)
Each bar, volume is compared to a rolling baseline. This is then z-scored.
// Volume Shock calculation
volTrend = ta.sma(volume, L)
vs = (volume > 0 and volTrend > 0) ? math.log(volume) - math.log(volTrend) : na
vsZ = zScore(vs, vzLen) // z-scored volume shock
lowVS = (vsZ <= vzThr) // low-volume condition
Bars with VolShock Z ≤ threshold are treated as low-volume (thin).
⚪ Prior Return Extremeness
The 1-bar log return is computed and z-scored.
// Prior return extremeness
r1 = math.log(close / close )
retZ = zScore(r1, rLen) // z-scored prior return
This shows whether the latest move is unusually large relative to recent history.
⚪ Void Oscillator
The oscillator is:
// Oscillator construction
weight = lowVS ? 1.0 : fadeNoLow
osc = retZ * weight
where Weight = 1 when volume is low, otherwise fades toward a user-set factor (0–1).
Osc > 0: up-move emphasized under low volume ⇒ Buy-Side Imbalance.
Osc < 0: down-move emphasized under low volume ⇒ Sell-Side Imbalance.
█ Why Use It
⚪ Targets Inefficient Moves
By filtering for low participation, the oscillator focuses on moves most likely driven by thin books/noise trading, which are statistically more likely to retrace.
⚪ Simple, Robust Logic
No need for tick data or order-book depth. It derives a practical void proxy from OHLCV, making it portable across assets and timeframes.
⚪ Complements Price-Action Tools
Use alongside FVG/imbalance zones, key levels, and volume profile to prioritize voids that carry the highest reversal probability.
█ How to Use
Sell-Side Imbalance = aggressive sell move (price goes down on low volume) → expect price to move up to fill it.
Buy-Side Imbalance = aggressive buy move (price goes up on low volume) → expect price to move down to fill it.
█ Settings
Volume Baseline Length — Bars for the volume trend used in VolShock. Larger = smoother baseline, fewer low-volume flags.
Vol Shock Z-Score Lookback — Bars to standardize VolShock; larger = smoother, fewer extremes.
Low-Volume Threshold (VolShock Z ≤) — Defines “thin participation.” Typical: −0.5 to −1.0.
Return Z-Score Lookback — Bars to standardize the 1-bar log return; larger = smoother “extremeness” measure.
Fade When Volume Not Low (0–1) — Weight applied when volume is not low. 0.00 = ignore non-low-volume bars entirely. 1.00 = treat volume condition as irrelevant (pure return extremeness).
Upper Threshold (Osc ≥) — Trigger for Sell-Side Imbalance (void below).
Lower Threshold (Osc ≤) — Trigger for Buy-Side Imbalance (void above).
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
8MA Compass — HTF map + GC/DC cues8MA Compass provides a clean trend context by combining strict 4-of-4 confluence (Current TF vs Higher TF) with SMA200 repainting on Golden/Death Cross (GC/DC).
What it shows
4-of-4 background (context): compares EMA10, EMA20, SMA50, SMA200 on the Current TF against the same four MAs on the Higher TF (HTF).
All 4 above their HTF values → bullish background.
All 4 below their HTF values → bearish background.
SMA200 color on GC/DC (Current TF):
Last signal is DC and price below SMA200 → SMA200 turns red.
Price above SMA200 but the last signal is DC (no GC afterward) → SMA200 stays base color.
Last signal is GC and price above SMA200 → SMA200 turns green #089981.
Why “8MA” ? The 4-of-4 logic uses 8 moving averages in total: 4 on the Current TF and 4 on the HTF (EMA10/20 and SMA50/200 on both frames). HTF EMAs are used in calculations but are not plotted by default—hence the name 8MA Compass.
Auto HTF mapping
Current 1H → HTF 4H
Current 4H → HTF 1D
Current 1D → HTF 1W
All other timeframes: HTF defaults to Current TF (4-of-4 will typically be neutral).
Manual mode: choose any HTF. If Manual HTF equals Current TF, HTF SMAs are hidden to avoid overlap.
Settings
1. Display
Show CURRENT TF — plot EMA10/20, SMA50/200 on Current TF.
Show HARD TF — plot SMA50/200 on HTF (hidden if HTF == Current TF).
HTF mode — Auto / Manual, with Hard TF (Manual) selector.
2. Filter
Show base background (4-of-4) — enable/disable confluence shading.
Epsilon (in ticks) — small tolerance in Cur vs HTF comparisons to reduce flicker.
3. Golden/Death
Color SMA200 on GC/DC (Cur TF) — repaint SMA200 on GC/DC per rules above (enabled by default).
Alerts
GC/DC (Current TF, SMA50/200): Golden Cross / Death Cross (on bar close).
EMA10/20 (Current TF): “Bull regime ON” / “Bear regime ON” on crossovers.
Optional HTF GC/DC alerts (SMA50/200 on chosen HTF).
Visual details
HTF SMA50/200 are drawn first; Current TF lines are drawn on top for clarity.
SMA200 (Current TF) is drawn last (and slightly thicker) to remain readable.
HTF EMAs are used in 4-of-4 logic but not plotted by design.
Usage
1. Use the 4-of-4 background as inter-timeframe momentum context.
2. Use SMA200 color to gauge long-term regime confirmation:
Prefer longs when last GC and price holds above SMA200 (#089981 line).
Avoid longs when last DC and price is below SMA200 (red line).
Disclaimer : For educational purposes only. Not financial advice. Trading involves risk.
Confluence Engine Confluence Engine is a practical, non-repainting decision aid that scores market conditions from −100…+100 by combining six proven modules: Trend, Momentum, Volatility, Volume, Structure, and an HTF confirmation. It’s designed for crypto, forex, indices, and stocks, and it fires entries only on confirmed bar closes.
What’s inside
Trend: EMA 20/50/200 alignment plus a Supertrend/KAMA toggle (you choose the baseline).
Momentum: RSI + MACD with confirmed-pivot divergence detection.
Volatility: ATR% and Bollinger Band width vs its average to favor expansion over chop.
Volume: OBV-style cumulative flow slope + volume surge vs SMA×multiplier.
Market Structure: Confirmed pivots, BOS (break of structure) and CHOCH (change of character).
HTF Filter: Closed higher-timeframe context via request.security(..., barmerge.gaps_on, barmerge.lookahead_off).
Why it does not repaint
Signals are computed and plotted on closed bars only.
Pivots/divergences use confirmed pivot points (no forward look).
HTF series are fetched with lookahead_off and use the last closed HTF bar in realtime.
No future bar references are used for entries or alerts.
How to use (3 steps)
Pick a timeframe pair: use a 4–6× HTF multiplier (5m→30m, 15m→1h, 1h→4h, 4h→1D, 1D→1W).
Trade with the HTF: take longs only when the HTF filter is bullish; shorts only when bearish.
Prefer expansion: act when BB width > its average and ATR% is elevated; skip most signals in compression.
Suggested presets (start here)
Crypto (BTC/ETH): 15m→1h, 1h→4h. stLen=10, stMult=3.0, bbLen=20, surgeMul=1.8–2.2, thresholds +40 / −40 (intraday can try +35 / −35).
Forex majors: 15m→1h, 1h→4h. stLen=10–14, stMult=2.5–3.0, surgeMul=1.5–1.8, thresholds +35 / −35 (swing: +45 / −45).
US equities (liquid): 5m→30m/1h, 15m→1h/2h. stMult=3.0–3.5, surgeMul=1.6–2.0, thresholds +45 / −45 to reduce chop.
Indices (ES/NQ): 5m→30m, 15m→1h. Defaults are fine; start at +40 / −40.
Gold/Oil: 15m→1h, 1h→4h. Thresholds +35 / −35, surgeMul=1.6–1.9.
Inputs (plain English)
Use Supertrend (off = KAMA): choose the trend baseline.
EMA Fast/Mid/Slow: 20/50/200 by default for classic stack.
RSI/MACD + divergence pivots: momentum and exhaustion context.
ATR Length & BB Length: volatility regime detection.
Volume SMA & Surge Multiplier: defines “meaningful” volume spikes.
Pivot left/right & “Confirm BOS/CHOCH on Close”: structure strictness.
Enable HTF & Higher Timeframe: confirms the lower timeframe direction.
Thresholds (+long / −short): when the score crosses these, you get signals.
Signals & alerts (IDs preserved)
Entry shapes plot at bar close when the score crosses thresholds.
Alerts you can enable:
CONFLUENCE LONG — long entry signal
CONFLUENCE SHORT — short entry signal
BULLISH BIAS — score turned positive
BEARISH BIAS — score turned negative
Best practices
Focus on signals with HTF agreement and volatility expansion; require volume participation (surge or rising OBV slope) for higher quality.
Raise thresholds (+45/−45 or +50/−50) to reduce whipsaws in choppy sessions.
Lower thresholds (+35/−35) only if you also require volatility/volume filters.
Performance & scope
Works across crypto/FX/equities/indices; no broker data or special feeds required.
No repainting by design; signals/alerts are computed on closed bars.
As with any tool, results vary by regime; always combine with risk management.
Disclosure
This script is for educational purposes only and is not financial advice. Trading involves risk. Test on historical data and paper trade before using live.
LP Sweep / Reclaim & Breakout Grading: Long-onlySignals
1) LP Sweep & Reclaim (mean-reversion entry)
Compute LP bounds from prior-bar window extremes:
lpLL_prev = lowest low of the last N bars (offset 1).
lpHH_prev = highest high of the last N bars (offset 1).
Sweep long trigger: current low dips below lpLL_prev and closes back above it.
Real-time quality grading (A/B/C) for sweep:
Trend filter & slope via EMA(88).
BOS bonus: close > last confirmed swing high.
Body size vs ATR, location above a long EMA, headroom to swing high (penalty if too close), and multi-sweep count bonus.
Sum → score → grade A/B/C; A or B required for sweep entry.
2) Trend Breakout (momentum entry)
Core trigger: close > previous Donchian high (length boLen) + ATR buffer.
Optional filter: close must be above the default EMA.
Breakout grading (A/B/C) in real time combining:
Trend up (price > EMA and EMA rising),
Body/ATR, Gap above breakout level (in ATR),
Volume vs MA,
Upper-wick penalty,
Position-in-Score: headroom to last swing high (penalty if too near) + EMA slope bonus.
Sum → score → A or B required if grading enabled.
Transformer Flux DashboardHere’s a practical guide to what your Transformer Flux Dashboard does and how to use it.
What it is
A compact, two-column trading dashboard + signal pack that blends trend, MACD, and OBV into one view (“Flux Score”) and adds session awareness (pre-sessions and main sessions in Eastern time). It’s designed for regular candles by default and avoids repaint by letting you confirm on bar close.
Core pieces it calculates
Moving Averages
Two MAs: Fast (HMA/EMA) and Slow (HMA/EMA).
You choose length, line width, color, and transparency.
Trend engine (Strict/Lenient)
Uses the relation between Fast/Slow MA and a debounced fast-MA slope filter (slope > ATR×buffer).
Strict: requires fast>slow and slow rising (or the inverse for down).
Lenient: fast>slow or slow rising (or the inverse).
A confirmation window (bars) must hold true before trend flips. That window can be auto-tuned by session (Asia/London/NY) or set globally.
OBV confirmation (optional)
OBV smoothed by SMA; needs to be rising/falling for N bars (also session-aware if you enable presets).
MACD
Standard MACD Fast/Slow/Signal; the dashboard shows Bull ▲, Bear ▼ or Flat based on line vs signal.
Flux Score (top row)
A composite, smoothed gauge from 0–100:
40% Trend, 30% MACD, 30% OBV → EMA(3) smoothed.
Labels: Bullish ≥ 70, Bearish ≤ 30, otherwise Neutral.
Summary line explains why (e.g., “MACD↑, OBV↑, Trend up”).
Sessions & zones (Eastern/NY time)
Recognizes Asia / London / New York main sessions and pre-sessions using your chart’s Eastern time.
Session label (top of chart): text is white; background auto-matches the current session color (or your manual color).
Zone backgrounds (optional): off by default; when on, default transparency ≈ 95% (very light), with separate colors for each session and pre-session. A toggle lets you draw pre-session on top or beneath main sessions.
Signals & markers
Two strength tiers: Strong (Trend + OBV + MACD aligned) and Weak (2 of the 3 agree).
To reduce clutter, markers only appear on direction shifts (from last visible direction to a new one), and you can enforce a minimum bar gap.
Marker style:
Default Icons with LabelUp/LabelDown (tiny).
Colors: strong long = bright white by default; others configurable.
Weak markers are slightly offset from price using ATR so they don’t overlap wicks.
Dashboard (2-column)
Left column = label, right column = value:
Flux Score: numeric + Bullish/Neutral/Bearish tag.
Summary: short reason of the score.
Trend: UP / DOWN / FLAT (cell tinted green/red/gray).
MACD: Bull ▲ / Bear ▼ / Flat (tinted).
Signal: last printed signal + bar age (fresh signals get a lighter tint).
MA: slow MA type/length and up/down arrow.
Sess: current session label (e.g., “Pre-London”, “New York”).
VIX / VXN (optional): shows current value.
Auto tint: based on calm/watch/elevated thresholds (you control levels and colors).
Manual tint: fixed BG color if you prefer consistency.
Params: “P”=trend bars, “O”=OBV bars, mode (Strict/Lenient), and “Candles”.
You can set a global Default Transparency for the dashboard cells.
Key settings to know
Confirm On Close: when on (default), trend/OBV/MACD states use the last confirmed bar; this avoids mid-bar flicker and reduces repaint risk.
Session presets: when enabled, the number of bars required for confirmations tightens/loosens per session (e.g., Asia uses more bars than NY).
Colors & Opacity:
MA lines have their own transparency (default 0 = fully opaque).
Dashboard cells use a single global transparency (default 40%).
Session zones default to very light (95%) and are off by default.
VIX/VXN cells can auto-color by regime or use a manual background.
Markers:
“Icons” vs “Ticks.” Default is Icons with tiny labels up/down.
“Shift only” display reduces noise; you can also set min bar spacing.
How to read it (quick workflow)
Flux Score row: a fast “risk-on/off” gauge.
≥70 with green Trend/MACD cells → higher-conviction long context.
≤30 with red Trend/MACD cells → higher-conviction short context.
Summary explains why the score is what it is.
Signal row: tells you the last official signal and how many bars ago it fired. Fresh signals tint lighter.
MA row: aligns your slow baseline; arrow helps spot slow-turns early.
Sess row + label: know which market is active; behavior and your confirmation bars adapt by session if presets are on.
VIX/VXN (if enabled): extra context for risk regime (values and color band).
Good practices & caveats
It’s confirmation-based to reduce false flips; you’ll get signals slightly later, by design.
All signals are informational; there’s no position management or stops in this build (we removed the stop visuals by request).
If you switch to exotic chart types or extreme resolutions, re-tune lengths and confirmation bars (and potentially disable session presets).
For scalping, consider reducing confirmation bars and OBV smoothing; for higher timeframes, increase them.
Quick customization ideas
Want faster flips? Lower confirmBars and obvBars, increase slope buffer a bit to retain quality.
Want fewer weak signals? Show only strong markers (toggle off weak via colors/visibility or increase min bar gap).
Prefer EMA stacking? Set both Fast/Slow to EMA.
Don’t care about OBV? Turn OBV confirm off; Trend + MACD will drive
Ichimoku Fractal Flow### Ichimoku Fractal Flow (IFF)
By Gurjit Singh
Ichimoku Fractal Flow (IFF) distills the Ichimoku system into a single oscillator by merging fractal echoes of price and cloud dynamics into one flow signal. Instead of static Ichimoku lines, it measures the "flow" between Conversion/Base, Span A/B, price echoes, and cloud echoes. The result is a multidimensional oscillator that reveals hidden rhythm, momentum shifts, and trend bias.
#### 📌 Key Features
1. Fourfold Fusion – The oscillator blends:
* Phase: Tenkan vs. Kijun spread (short vs. medium trend).
* Kumo Phase: Span A vs. Span B spread (cloud thickness).
* Echo: Price vs lagged reflection.
* Cloud Echo: Price vs. projected cloud center.
2. Oscillator Output – A unified flow line oscillating around zero.
3. Dual Calculation Modes – Oscillator can be built using:
* High-Low Midpoint (classic Ichimoku-style averaging).
* Wilder’s RMA (smoother, less noisy averaging averaging).
4. Optional Smoothing – EMA or Wilder’s RMA creates a trend line, enabling MACD-style crossovers.
5. Dynamic Coloring – Bullish/Bearish color shifts for quick bias recognition.
6. Fill Styling – Highlighted regions between oscillator & smoothing line.
7. Zero Line Reference – Acts as a structural pivot (bull vs. bear).
#### 🔑 How to Use
1. Add to Chart: Works across all assets and timeframes.
2. Flow Bias (Zero Line):
* Above 0 → Bullish flow 🐂
* Below 0 → Bearish flow 🐻
3. With Signal Line:
* Oscillator above smoothing line → Possible upward trend shift.
* Oscillator below smoothing line → Possible downward trend shift.
4. Strength:
* Wide separation from smoothing = strong trend.
* Flat, tight clustering = indecision/range.
5. Contextual Edge: Combine signals with Ichimoku Cloud analysis for stronger confluence.
#### ⚙️ Inputs & Options
* Conversion Line (Tenkan, default 9)
* Base Line (Kijun, default 26)
* Leading Span B (default 52)
* Lag/Lead Shift (default 26)
* Oscillator Mode: High-Low Midpoint vs Wilder’s RMA
* Use Smoothing (toggle on/off)
* Signal Smoothing: Wilder/EMA option
* Smoothing Length (default 9)
* Bullish/Bearish Colors + Transparency
#### 💡 Tips
* Wilder’s RMA (both oscillator & smoothing) is gentler, reducing whipsaws in sideways markets.
* High-Low Mid captures pure Ichimoku-style ranges, good for structure-based traders.
* EMA reacts faster than RMA; use if you want early momentum signals.
* Zero-line flips act like momentum pivots—watch them near cloud boundaries.
* Signal line crossovers behave like MACD-style triggers.
* Strongest signals appear when oscillator, signal line, and Ichimoku Cloud all align.
👉 In short: Ichimoku Fractal Flow compresses multi-layered Ichimoku system into a single fractal oscillator that detects flow, pivotal shifts, and momentum with clarity—bridging price, cloud, and echoes into one signal. Where the cloud shows structure, IFF reveals the underlying flow. Together, they offer a fractal lens into market rhythm.
