Lightning Session LevelsLightning Session Levels (LSL) draws clean, non-repainting levels for the major market sessions and a compact HUD in the top-right corner. It’s built to be lightweight, readable, and “set-and-forget” for intraday traders.
What it shows
Session High/Low and Open/Close levels for:
ASIA (00:00–08:00 UTC)
EUROPE (07:00–16:00 UTC)
US (13:30–20:00 UTC)
OVERNIGHT (20:00–24:00 UTC)
HUD panel:
Current active session
Countdown to the next US session (auto-calculated from UTC)
How it works (non-repainting)
Levels are anchored at session close. Each line is created once on the confirmed closing bar of the session (x2 = session end).
Optional Extend Right keeps the level projecting forward without changing the anchor (no “drifting”).
All drawings are pinned to the right price scale for stable reading.
Inputs
Show HUD — toggle the top-right panel.
Show Levels — master switch for drawing levels.
Draw High/Low — H/L session levels.
Draw Open/Close — O/C session levels.
Extend Right — extend all session lines to the future.
Keep N past sessions per market — FIFO limit per session group (default 12).
ASIA / EUROPE / US / OVERNIGHT — enable/disable specific sessions.
Style & palette
Consistent “Lightning” colors:
ASIA = Cyan, EUROPE = Violet, US = Amber, OVERNIGHT = Teal
Labels are always size: Normal for readability.
HUD uses a dark, subtle two-tone background to stay out of the way.
Recommended use
Timeframes: intraday (1m → 4h).
On 1D and higher, TradingView’s session-window time() filters won’t match intraday windows, so levels won’t plot (by design).
Markets: crypto, indices, FX, equities — any symbol where intraday session context helps.
Notes & limitations
Fixed UTC windows. The US window is set to 13:30–20:00 UTC. Daylight-saving shifts (DST) are not auto-adjusted; if you need region-specific DST behavior, treat this as a consistent UTC model.
The HUD timer counts down to the next US open from the current UTC clock.
Draw limits are capped (500 lines, 500 labels) for performance and stability.
Quick start
Add Lightning Session Levels to your chart.
Toggle Draw High/Low and/or Draw Open/Close.
Turn on Extend Right if you want the levels to project forward.
Enable only the sessions you care about (e.g., just EUROPE and US).
Use Keep N past sessions to control clutter (e.g., 6–12).
Disclaimer
This tool is for educational/informational purposes only and is not financial advice. Past session behavior does not guarantee future results. Always manage risk.
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Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent 🎭
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent ⚡
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2σ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trend—enters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent 💧
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR)
Signal Logic: Breakout anticipation—enters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent 📊
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ε)% of the time
Explores randomly ε% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal → outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (▲): Long signal confirmed
Red triangle (▼): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with ► marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (█████ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5× ATR)
Take-profit 1 (2.0× ATR)
Take-profit 2 (3.5× ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models)
✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint
⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Adaptive EMA CrossoverIndicator Name: Adaptive EMA Crossover
Description:
The Adaptive EMA Crossover is a sleek, visual tool designed to help traders identify trend direction and potential entry/exit points with clarity. By employing two Exponential Moving Averages (EMAs) with dynamic coloring, it cuts through the noise of the chart, allowing you to focus on high-probability signals.
🔍 Key Features:
Dual EMA System: Utilizes a fast and a slow EMA to gauge market momentum. The default settings are 12 (fast) and 21 (slow) periods, which can be fully customized.
Adaptive Visuals: Both EMAs change color simultaneously to reflect the dominant trend.
🟢 Bright Turquoise: Indicates an Uptrend (Fast EMA >= Slow EMA).
🔴 Bright Pink: Indicates a Downtrend (Fast EMA < Slow EMA).
Clear Crossover Signals: Prominent dots directly on the chart mark the exact moment a crossover occurs.
Turquoise Dot: A Bullish Crossover signal (Fast EMA crosses above Slow EMA).
Pink Dot: A Bearish Crossover signal (Fast EMA crosses below Slow EMA).
Integrated Alerts: Never miss a trading opportunity! Built-in alert conditions notify you instantly for both bullish and bearish crossovers.
🎯 How to Use:
Trend Identification: The primary colors of the EMAs give an immediate sense of the trend. Trade in the direction of the trend for higher-probability setups.
Signal Confirmation: Use the crossover dots as potential triggers for entry or exit. A turquoise dot in a rising market can signal a buy opportunity, while a pink dot in a falling market can signal a sell or short opportunity.
Combination with Other Tools: For best results, combine this indicator with other forms of analysis like support/resistance levels or volume confirmation to filter out false signals.
⚙️ Inputs:
EMA Small: Period for the faster-moving average (default: 12).
EMA Big: Period for the slower-moving average (default: 21).
This is my first published indicator. I welcome all feedback and suggestions for improvement! Happy Trading!
ICT Sessions Ranges [SwissAlgo]ICT Session Ranges - ICT Liquidity Zones & Market Structure
OVERVIEW
This indicator identifies and visualizes key intraday trading sessions and liquidity zones based on Inner Circle Trader (ICT) methodology (AM, NY Lunch Raid, PM Session, London Raid). It tracks 'higher high' and 'lower low' price levels during specific time periods that may represent areas where market participants have placed orders (liquidity).
PURPOSE
The indicator helps traders observe:
Session-based price ranges during different market hours
Opening range gaps between market close and next day's open
Potential areas where liquidity may be concentrated and trigger price action
SESSIONS TRACKED
1. London Session (02:00-05:00 ET): Tracks price range during early London trading hours
2. AM Session (09:30-12:00 ET): Tracks price range during the morning New York session
3. NY Lunch Session (12:00-13:30 ET): Tracks price range during typical low-volume lunch period
4. PM Session (13:30-16:00 ET): Tracks price range during the afternoon New York session
CALCULATIONS
Session High/Low: The highest high and lowest low recorded during each active session period
Opening Range Gap: Calculated as the difference between the previous day's 16:00 close and the current day's 09:30 open
Gap Mitigation: A gap is considered mitigated when the price reaches 50% of the gap range
All times are based on America/New_York timezone (ET)
BACKGROUND INDICATORS
NY Trading Hours (09:30-16:00 ET): Optional gray background overlay
Asian Session (20:00-23:59 ET): Optional purple background overlay
VISUAL ELEMENTS
Horizontal lines mark session highs and lows
Subtle background boxes highlight each session range
Labels identify each session type
Orange shaded boxes indicate unmitigated opening range gaps
Dotted line at 50% gap level shows mitigation threshold
FEATURES
Toggle visibility for each session independently
Customizable colors for each session type
Automatic removal of mitigated gaps
All drawing objects use transparent backgrounds for chart clarity
ICT CONCEPTS
This tool relates to concepts discussed by Inner Circle Trader regarding liquidity pools, session-based analysis, and gap theory. The indicator assumes that session highs and lows may represent areas where liquidity is concentrated, and that opening range gaps may attract price until mitigated.
USAGE NOTES
Best used on intraday timeframes (1-15 minute charts)
All sessions are calculated based on actual price movement during specified time periods
Historical session data is preserved as new sessions develop
Gap detection only triggers at 09:30 ET market open
DISCLAIMER
This indicator is for educational and informational purposes only. It displays historical price levels and time-based calculations. Past performance of price levels is not indicative of future results. The identification of "liquidity zones" is a theoretical concept and does not guarantee that orders exist at these levels or that prices will react to them. Trading involves substantial risk of loss. Users should conduct their own analysis and risk assessment before making any trading decisions.
TIME ZONE
Set your timezone to: America/New_York (UTC-5)
Aquantprice: Institutional Structure MatrixSETUP GUIDE
Open TradingView
Go to Indicators
Search: Aquantprice: Institutional Structure Matrix
Click Add to Chart
Customize:
Min Buy = 10, Min Sell = 7
Show only PP, R1, S1, TC, BC
Set Decimals = 5 (Forex) or 8 (Crypto)
USE CASES & TRADING STRATEGIES
1. CPR Confluence Trading (Most Popular)
Rule: Enter when ≥3 timeframes show Buy ≥10/15 or Sell ≥7/13
text Example:
Daily: 12/15 Buy
Weekly: 11/15 Buy
Monthly: 10/15 Buy
→ **STRONG LONG BIAS**
Enter on pullback to nearest **S1 or L3**
2. Hot Zone Scalping (Forex & Indices)
Rule: Trade only when price is in Hot Zone (closest 2 levels)
text Hot: S1-PP → Expect bounce or breakout
Action:
- Buy at S1 if Buy Count ↑
- Sell at PP if Sell Count ↑
3. Institutional Reversal Setup
Rule: Price at H3/L3 + Reversal Condition
text Scenario:
Price touches **Monthly L3**
L3 in **Hot Zone**
Buy Count = 13/15
→ **High-Probability Reversal Long**
4. CPR Width Filter (Avoid Choppy Markets)
Rule: Trade only if CPR Label = "Strong Trend"
text CPR Size < 0.25 → Trending
CPR Size > 0.75 → Sideways (Avoid)
5. Multi-Timeframe Bias Dashboard
Use "Buy" and "Sell" columns as a sentiment meter
TimeframeBuySellBiasDaily123BullishWeekly89BearishMonthly112Bullish
→ Wait for alignment before entering
HOW TO READ THE TABLE
Column Meaning Time frame D, W, M, 3M, 6M, 12MOpen Price Current session open PP, TC, BC, etc. Pivot levels (color-coded if in Hot Zone) Buy X/15 conditions met (≥10 = Strong Buy)Sell X/13 conditions met (≥7 = Strong Sell)CPR Size Histogram + Label (Trend vs Range)Zone Hot: PP-S1, Med: S2-L3, etc. + PP Distance
PRO TIPS
Best on 5M–1H charts for entries
Use with volume or order flow for confirmation
Set alerts on Buy ≥12/15 or Sell ≥10/13
Hide unused levels to reduce clutter
Combine with AQuantPrice Dashboard (Small TF) for full system
IDEAL MARKETS
Forex (EURUSD, GBPUSD, USDJPY)
Indices (NAS100, SPX500, DAX)
Crypto (BTC, ETH – use 6–8 decimals)
Commodities (Gold, Oil)
🚀 **NEW INDICATOR ALERT**
**Aquantprice: Institutional Structure Matrix**
The **ALL-IN-ONE CPR Dashboard** used by smart money traders.
✅ **6 Timeframes in 1 Table** (Daily → Yearly)
✅ **15 Buy + 13 Sell Conditions** (Institutional Logic)
✅ **Hot Zones, CPR Width, PP Distance**
✅ **Fully Customizable – Show/Hide Any Level**
✅ **Real-Time Zone Detection** (Hot, Med, Low)
✅ **Precision up to 8 Decimals**
**No more switching charts. No more confusion.**
See **where institutions are positioned** — instantly.
👉 **Add to Chart Now**: Search **"Aquantprice: Institutional Structure Matrix"**
🔥 **Free Access | Pro-Level Insights**
*By AQuant – Trusted by 10,000+ Traders*
#CPR #PivotTrading #SmartMoney #TradingView
FINAL TAGLINE
"See What Institutions See — Before They Move."
Aquantprice: Institutional Structure Matrix
Your Edge. One Dashboard.
Range Trading StrategyOVERVIEW
The Range Trading Strategy is a systematic trading approach that identifies price ranges
from higher timeframe candles or trading sessions, tracks pivot points, and generates
trading signals when range extremes are mitigated and confirmed by pivot levels.
CORE CONCEPT
The strategy is based on the principle that when a candle (or session) closes within the
range of the previous candle (or session), that previous candle becomes a "range" with
identifiable high and low extremes. When price breaks through these extremes, it creates
trading opportunities that are confirmed by pivot levels.
RANGE DETECTION MODES
1. HTF (Higher Timeframe) Mode:
Automatically selects a higher timeframe based on the current chart timeframe
Uses request.security() to fetch HTF candle data
Range is created when an HTF candle closes within the previous HTF candle's range
The previous HTF candle's high and low become the range extremes
2. Sessions Mode:
- Divides the trading day into 4 sessions (UTC):
* Session 1: 00:00 - 06:00 (6 hours)
* Session 2: 06:00 - 12:00 (6 hours)
* Session 3: 12:00 - 20:00 (8 hours)
* Session 4: 20:00 - 00:00 (4 hours, spans midnight)
- Tracks high, low, and close for each session
- Range is created when a session closes within the previous session's range
- The previous session's high and low become the range extremes
PIVOT DETECTION
Pivots are detected based on candle color changes (bullish/bearish transitions):
1. Pivot Low:
Created when a bullish candle appears after a bearish candle
Pivot low = minimum of the current candle's low and previous candle's low
The pivot bar is the actual bar where the low was formed (current or previous bar)
2. Pivot High:
Created when a bearish candle appears after a bullish candle
Pivot high = maximum of the current candle's high and previous candle's high
The pivot bar is the actual bar where the high was formed (current or previous bar)
IMPORTANT: There is always only ONE active pivot high and ONE active pivot low at any
given time. When a new pivot is created, it replaces the previous one.
RANGE CREATION
A range is created when:
(HTF Mode) An HTF candle closes within the previous HTF candle's range AND a new HTF
candle has just started
(Sessions Mode) A session closes within the previous session's range AND a new session
has just started
Or Range Can Be Created when the Extreme of Another Range Gets Mitigated and We Have a Pivot low Just Above the Range Low or Pivot High just Below the Range High
Range Properties:
rangeHigh: The high extreme of the range
rangeLow: The low extreme of the range
highStartTime: The timestamp when the range high was actually formed (found by looping
backwards through bars)
lowStartTime: The timestamp when the range low was actually formed (found by looping
backwards through bars)
highMitigated / lowMitigated: Flags tracking whether each extreme has been broken
isSpecial: Flag indicating if this is a "special range" (see Special Ranges section)
RANGE MITIGATION
A range extreme is considered "mitigated" when price interacts with it:
High is mitigated when: high >= rangeHigh (any interaction at or above the level)
Low is mitigated when: low <= rangeLow (any interaction at or below the level)
Mitigation can happen:
At the moment of range creation (if price is already beyond the extreme)
At any point after range creation when price touches the extreme
SIGNAL GENERATION
1. Pending Signals:
When a range extreme is mitigated, a pending signal is created:
a) BEARISH Pending Signal:
- Triggered when: rangeHigh is mitigated
- Confirmation Level: Current pivotLow
- Signal is confirmed when: close < pivotLow
- Stop Loss: Current pivotHigh (at time of confirmation)
- Entry: Short position
Signal Confirmation
b) BULLISH Pending Signal:
- Triggered when: rangeLow is mitigated
- Confirmation Level: Current pivotHigh
- Signal is confirmed when: close > pivotHigh
- Stop Loss: Current pivotLow (at time of confirmation)
- Entry: Long position
IMPORTANT: There is only ever ONE pending bearish signal and ONE pending bullish signal
at any given time. When a new pending signal is created, it replaces the previous one
of the same type.
2. Signal Confirmation:
- Bearish: Confirmed when price closes below the pivot low (confirmation level)
- Bullish: Confirmed when price closes above the pivot high (confirmation level)
- Upon confirmation, a trade is entered immediately
- The confirmation line is drawn from the pivot bar to the confirmation bar
TRADE EXECUTION
When a signal is confirmed:
1. Position Management:
- Any existing position in the opposite direction is closed first
- Then the new position is entered
2. Stop Loss:
- Bearish (Short): Stop at pivotHigh
- Bullish (Long): Stop at pivotLow
3. Take Profit:
- Calculated using Risk:Reward Ratio (default 2:1)
- Risk = Distance from entry to stop loss
- Target = Entry ± (Risk × R:R Ratio)
- Can be disabled with "Stop Loss Only" toggle
4. Trade Comments:
- "Range Bear" for short trades
- "Range Bull" for long trades
SPECIAL RANGES
Special ranges are created when:
- A range high is mitigated AND the current pivotHigh is below the range high
- A range low is mitigated AND the current pivotLow is above the range low
In these cases:
- The pivot value is stored in an array (storedPivotHighs or storedPivotLows)
- A "special range" is created with only ONE extreme:
* If pivotHigh < rangeHigh: Creates a range with rangeHigh = pivotLow, rangeLow = na
* If pivotLow > rangeLow: Creates a range with rangeLow = pivotHigh, rangeHigh = na
- Special ranges can generate signals just like normal ranges
- If a special range is mitigated on the creation bar or the next bar, it is removed
entirely without generating signals (prevents false signals)
Special Ranges
REVERSE ON STOP LOSS
When enabled, if a stop loss is hit, the strategy automatically opens a trade in the
opposite direction:
1. Long Stop Loss Hit:
- Detects when: position_size > 0 AND position_size <= 0 AND low <= longStopLoss
- Action: Opens a SHORT position
- Stop Loss: Current pivotHigh
- Trade Comment: "Reverse on Stop"
2. Short Stop Loss Hit:
- Detects when: position_size < 0 AND position_size >= 0 AND high >= shortStopLoss
- Action: Opens a LONG position
- Stop Loss: Current pivotLow
- Trade Comment: "Reverse on Stop"
The reverse trade uses the same R:R ratio and respects the "Stop Loss Only" setting.
VISUAL ELEMENTS
1. Range Lines:
- Drawn from the time when the extreme was formed to the mitigation point (or current
time if not mitigated)
- High lines: Blue (or mitigated color if mitigated)
- Low lines: Red (or mitigated color if mitigated)
- Style: SOLID
- Width: 1
2. Confirmation Lines:
- Drawn when a signal is confirmed
- Extends from the pivot bar to the confirmation bar
- Bearish: Red, solid line
- Bullish: Green, solid line
- Width: 1
- Can be toggled on/off
STRATEGY SETTINGS
1. Range Detection Mode:
- HTF: Uses higher timeframe candles
- Sessions: Uses trading session boundaries
2. Auto HTF:
- Automatically selects HTF based on current chart timeframe
- Can be disabled to use manual HTF selection
3. Risk:Reward Ratio:
- Default: 2.0 (2:1)
- Minimum: 0.5
- Step: 0.5
4. Stop Loss Only:
- When enabled: Trades only have stop loss (no take profit)
- Trades close on stop loss or when opposite signal confirms
5. Reverse on Stop Loss:
- When enabled: Hitting a stop loss opens opposite trade with stop at opposing pivot
6. Max Ranges to Display:
- Limits the number of ranges kept in memory
- Oldest ranges are purged when limit is exceeded
KEY FEATURES
1. Dynamic Pivot Tracking:
- Pivots update on every candle color change
- Always maintains one high and one low pivot
2. Range Lifecycle:
- Ranges are created when price closes within previous range
- Ranges are tracked until mitigated
- Mitigation creates pending signals
- Signals are confirmed by pivot levels
3. Signal Priority:
- Only one pending signal of each type at a time
- New signals replace old ones
- Confirmation happens on close of bar
4. Position Management:
- Closes opposite positions before entering new trades
- Tracks stop loss levels for reverse functionality
- Respects pyramiding = 1 (only one position per direction)
5. Time-Based Drawing:
- Uses time coordinates instead of bar indices for line drawing
- Prevents "too far from current bar" errors
- Lines can extend to any historical point
USAGE NOTES
- Best suited for trending and ranging markets
- Works on any timeframe, but HTF mode adapts automatically
- Sessions mode is ideal for intraday trading
- Pivot detection requires clear candle color changes
- Range detection requires price to close within previous range
- Signals are generated on bar close, not intra-bar
The strategy combines range identification, pivot tracking, and signal confirmation to
create a systematic approach to trading breakouts and reversals based on price structure, past performance does not in any way predict future performance
lower_tfLibrary "lower_tf"
█ OVERVIEW
This library is an enhanced (opinionated) version of the library originally developed by PineCoders contained in lower_tf .
It is a Pine Script® programming tool for advanced lower-timeframe selection and intra-bar analysis.
█ CONCEPTS
Lower Timeframe Analysis
Lower timeframe analysis refers to the analysis of price action and market microstructure using data from timeframes shorter than the current chart period. This technique allows traders and analysts to gain deeper insights into market dynamics, volume distribution, and the price movements occurring within each bar on the chart. In Pine Script®, the request.security_lower_tf() function allows this analysis by accessing intrabar data.
The library provides a comprehensive set of functions for accurate mapping of lower timeframes, dynamic precision control, and optimized historical coverage using request.security_lower_tf().
█ IMPROVEMENTS
The original library implemented ten precision levels. This enhanced version extends that to twelve levels, adding two ultra-high-precision options:
Coverage-Based Precision (Original 5 levels):
1. "Covering most chart bars (least precise)"
2. "Covering some chart bars (less precise)"
3. "Covering fewer chart bars (more precise)"
4. "Covering few chart bars (very precise)"
5. "Covering the least chart bars (most precise)"
Intrabar-Count-Based Precision (Expanded from 5 to 7 levels):
6. "~12 intrabars per chart bar"
7. "~24 intrabars per chart bar"
8. "~50 intrabars per chart bar"
9. "~100 intrabars per chart bar"
10. "~250 intrabars per chart bar"
11. "~500 intrabars per chart bar" ← NEW
12. "~1000 intrabars per chart bar" ← NEW
The key enhancements in this version include:
1. Extended Precision Range: Adds two ultra-high-precision levels (~500 and ~1000 intrabars) for advanced microstructure analysis requiring maximum granularity.
2. Market-Agnostic Implementation: Eliminates the distinction between crypto/forex and traditional markets, removing the mktFactor variable in favor of a unified, predictable approach across all asset classes.
3. Explicit Precision Mapping: Completely refactors the timeframe selection logic using native Pine Script® timeframe properties ( timeframe.isseconds , timeframe.isminutes , timeframe.isdaily , timeframe.isweekly , timeframe.ismonthly ) and explicit multiplier-based lookup tables. The original library used minute-based calculations with market-dependent conditionals that produced inconsistent results. This version provides deterministic, predictable mappings for every chart timeframe, ensuring consistent precision behavior regardless of asset type or market hours.
An example of the differences can be seen side-by-side in the chart below, where the original library is on the left and the enhanced version is on the right:
█ USAGE EXAMPLE
// This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © andre_007
//@version=6
indicator("lower_tf Example")
import andre_007/lower_tf/1 as LTF
import PineCoders/Time/5 as PCtime
//#region ———————————————————— Example code
// ————— Constants
color WHITE = color.white
color GRAY = color.gray
string LTF1 = "Covering most chart bars (least precise)"
string LTF2 = "Covering some chart bars (less precise)"
string LTF3 = "Covering less chart bars (more precise)"
string LTF4 = "Covering few chart bars (very precise)"
string LTF5 = "Covering the least chart bars (most precise)"
string LTF6 = "~12 intrabars per chart bar"
string LTF7 = "~24 intrabars per chart bar"
string LTF8 = "~50 intrabars per chart bar"
string LTF9 = "~100 intrabars per chart bar"
string LTF10 = "~250 intrabars per chart bar"
string LTF11 = "~500 intrabars per chart bar"
string LTF12 = "~1000 intrabars per chart bar"
string TT_LTF = "This selection determines the approximate number of intrabars analyzed per chart bar. Higher numbers of
intrabars produce more granular data at the cost of less historical bar coverage, because the maximum number of
available intrabars is 200K.
\n\nThe first five options set the lower timeframe based on a specified relative level of chart bar coverage.
The last five options set the lower timeframe based on an approximate number of intrabars per chart bar."
string TAB_TXT = "Uses intrabars at the {0} timeframe.\nAvg intrabars per chart bar:
{1,number,#.#}\nChart bars covered: {2} of {3} ({4,number,#.##}%)"
string ERR_TXT = "No intrabar information exists at the {1}{0}{1} timeframe."
// ————— Inputs
string ltfModeInput = input.string(LTF3, "Intrabar precision", options = , tooltip = TT_LTF)
bool showInfoBoxInput = input.bool(true, "Show information box ")
string infoBoxSizeInput = input.string("normal", "Size ", inline = "01", options = )
string infoBoxYPosInput = input.string("bottom", "↕", inline = "01", options = )
string infoBoxXPosInput = input.string("right", "↔", inline = "01", options = )
color infoBoxColorInput = input.color(GRAY, "", inline = "01")
color infoBoxTxtColorInput = input.color(WHITE, "T", inline = "01")
// ————— Calculations
// @variable A "string" representing the lower timeframe for the data request.
// NOTE:
// This line is a good example where using `var` in the declaration can improve a script's performance.
// By using `var` here, the script calls `ltf()` only once, on the dataset's first bar, instead of redundantly
// evaluating unchanging strings on every bar. We only need one evaluation of this function because the selected
// timeframe does not change across bars in this script.
var string ltfString = LTF.ltf(ltfModeInput, LTF1, LTF2, LTF3, LTF4, LTF5, LTF6, LTF7, LTF8, LTF9, LTF10, LTF11, LTF12)
// @variable An array containing all intrabar `close` prices from the `ltfString` timeframe for the current chart bar.
array intrabarCloses = request.security_lower_tf(syminfo.tickerid, ltfString, close)
// Calculate the intrabar stats.
= LTF.ltfStats(intrabarCloses)
int chartBars = bar_index + 1
// ————— Visuals
// Plot the `avgIntrabars` and `intrabars` series in all display locations.
plot(avgIntrabars, "Average intrabars", color.silver, 6)
plot(intrabars, "Intrabars", color.blue, 2)
// Plot the `chartBarsCovered` and `chartBars` values in the Data Window and the script's status line.
plot(chartBarsCovered, "Chart bars covered", display = display.data_window + display.status_line)
plot(chartBars, "Chart bars total", display = display.data_window + display.status_line)
// Information box logic.
if showInfoBoxInput
// @variable A single-cell table that displays intrabar information.
var table infoBox = table.new(infoBoxYPosInput + "_" + infoBoxXPosInput, 1, 1)
// @variable The span of the `ltfString` timeframe formatted as a number of automatically selected time units.
string formattedLtf = PCtime.formattedNoOfPeriods(timeframe.in_seconds(ltfString) * 1000)
// @variable A "string" containing the formatted text to display in the `infoBox`.
string txt = str.format(
TAB_TXT, formattedLtf, avgIntrabars, chartBarsCovered, chartBars, chartBarsCovered / chartBars * 100, "'"
)
// Initialize the `infoBox` cell on the first bar.
if barstate.isfirst
table.cell(
infoBox, 0, 0, txt, text_color = infoBoxTxtColorInput, text_size = infoBoxSizeInput,
bgcolor = infoBoxColorInput
)
// Update the cell's text on the latest bar.
else if barstate.islast
table.cell_set_text(infoBox, 0, 0, txt)
// Raise a runtime error if no intrabar data is available.
if ta.cum(intrabars) == 0 and barstate.islast
runtime.error(str.format(ERR_TXT, ltfString, "'"))
//#endregion
█ EXPORTED FUNCTIONS
ltf(userSelection, choice1, choice2, ...)
Returns the optimal lower timeframe string based on user selection and current chart timeframe. Dynamically calculates precision to balance granularity with historical coverage within the 200K intrabar limit.
ltfStats(intrabarValues)
Analyzes an intrabar array returned by request.security_lower_tf() and returns statistics: number of intrabars in current bar, total chart bars covered, and average intrabars per bar.
█ CREDITS AND LICENSING
Original Concept : PineCoders Team
Original Lower TF Library :
License : Mozilla Public License 2.0
Dynamic Auto FibonacciDynamic Auto Fibonacci - Logarithmic Fib Retracements & Extensions
Overview
Dynamic Auto Fibonacci is an advanced Fibonacci analysis tool that automatically identifies swing highs and lows to plot precise retracement and extension levels on your chart. Unlike traditional manual Fibonacci tools, this indicator dynamically updates as price action evolves, with full support for logarithmic scaling - essential for accurate analysis on long-term charts and high-growth assets.
The indicator features a clean, modern aesthetic with customizable vibrant colors and text-only labels that won't clutter your chart, making it perfect for both intraday scalping and long-term position trading.
Key Features
✅ Automatic Fibonacci Detection - Automatically finds the highest high and lowest low within your selected timeframe
✅ Manual Anchor Point - Click directly on the chart to set a custom low point for your Fibonacci analysis
✅ Logarithmic Scale Support - True logarithmic Fibonacci calculations for accurate levels on log-scale charts
✅ Flexible Display Modes - Show retracements only, extensions only, or both simultaneously
✅ Fully Customizable Levels - Adjust any Fibonacci level value, color, or toggle individual levels on/off
✅ Unified Color Mode - One-click option to change all levels to a single color (perfect for minimalist chart styles)
✅ Clean Modern Design - Text-only labels with vibrant colors and adjustable positioning
✅ 13 Default Levels - Includes 0.0, 0.236, 0.382, 0.5, 0.618, 0.786, 0.886, 1.0, 1.236, 1.414, 1.618, 2.0, and 2.618
How to Use
Quick Start (Automatic Mode)
Add the indicator to your chart
By default, it will automatically find the lowest and highest points over the past 12 months
Fibonacci levels will appear with clean colored text labels positioned to the right of current price
Setting a Custom Anchor Point (Manual Mode)
This is the most powerful feature - drawing from a specific swing low:
Click the Settings icon (gear) on the indicator
Navigate to Fibonacci Settings group
Click inside the "Anchor Start Time" field - this will activate anchor selection mode
Click directly on the candle where you want to set your swing low point on the chart
The indicator will automatically:
Lock that candle as your anchor (swing low)
Find the highest high that occurred after your selected anchor point
Draw Fibonacci retracement and extension levels between those two points
Important: The anchor represents the starting point (0.0 level) of your Fibonacci, and the indicator finds the peak after that point as the 1.0 level.
Display Modes
Navigate to Display Settings → Display Mode to choose:
Retracements & Extensions (default) - Shows all levels from 0.0 to 2.618
Retracements Only - Shows only 0.0 to 1.0 levels (great for identifying pullback entry zones)
Extensions Only - Shows 1.0+ levels (useful for profit targets and breakout projections)
Customizing Individual Levels
Under Retracement Levels and Extension Levels groups, each level has three controls:
Toggle checkbox - Show/hide the level
Value field - Adjust the exact Fibonacci ratio (e.g., change 0.618 to 0.65 if desired)
Color picker - Set unique colors for each level
Unified Color Override
Perfect for chart screenshots or minimalist aesthetics:
Go to Unified Color Override settings group
Enable "Use Unified Color for All Levels"
Choose your color (defaults to gray)
All lines and text immediately change to that color - individual settings are preserved when you toggle back off
Line & Label Customization
Display Settings group offers:
Line Style: Solid, Dashed, or Dotted
Line Length: Short (10 bars), Medium (50 bars), or Long (extends right infinitely)
Line Width: 1-5 pixels
Label Size: Tiny to Huge
Label Offset: Adjust how many bars to the right labels appear (default: 12)
Show Anchor Line: Display vertical lines at your swing low and swing high points
Settings Overview
Fibonacci Settings:
Retracement Timeframe (default: 12M)
Anchor Start Time (click to select candle)
Use Log Scale Calculation (highly recommended for crypto and growth stocks)
Display Settings:
Display Mode (Retracements & Extensions / Retracements Only / Extensions Only)
Line Style, Length, Width
On-Chart Labels (clean text) or Price Scale Labels (traditional right-side axis)
Label Size and Offset
Unified Color Override:
One-click monochrome mode for all levels
Individual Level Controls:
8 customizable retracement levels (0.0 to 1.0)
5 customizable extension levels (1.236 to 2.618)
Use Cases
📊 Swing Trading - Identify key support/resistance zones for entries and exits
📊 Scalping - Use short-term anchors to find precise intraday reversal levels
📊 Position Trading - Logarithmic calculations essential for multi-year crypto/stock analysis
📊 Options Trading - Extension levels provide excellent profit target zones
📊 Multi-Timeframe Analysis - Set different anchors to compare short-term vs. long-term Fibonacci structures
Tips for Best Results
For cryptocurrency and growth stocks: Always enable "Use Log Scale Calculation" and view your chart in log scale
For precision: Use the manual anchor feature to draw from confirmed swing lows/highs rather than relying on automatic detection
For clean charts: Toggle off levels you don't actively use (e.g., disable 0.786 and 0.886 if you only trade 0.382/0.618)
For screenshots: Enable Unified Color Override and set to grayscale for professional-looking chart exports
Note on Logarithmic Scale
This indicator includes true logarithmic Fibonacci calculations, which are critical when analyzing assets with significant price appreciation. Standard arithmetic Fibonacci tools become increasingly inaccurate on log-scale charts - this indicator solves that problem by calculating levels using logarithmic mathematics when "Use Log Scale Calculation" is enabled.
Disclaimer: This indicator is a tool for technical analysis and does not constitute financial advice. Always perform your own analysis and risk management before making trading decisions.
LibTmFrLibrary "LibTmFr"
This is a utility library for handling timeframes and
multi-timeframe (MTF) analysis in Pine Script. It provides a
collection of functions designed to handle common tasks related
to period detection, session alignment, timeframe construction,
and time calculations, forming a foundation for
MTF indicators.
Key Capabilities:
1. **MTF Period Engine:** The library includes functions for
managing higher-timeframe (HTF) periods.
- **Period Detection (`isNewPeriod`):** Detects the first bar
of a given timeframe. It includes custom logic to handle
multi-month and multi-year intervals where
`timeframe.change()` may not be sufficient.
- **Bar Counting (`sinceNewPeriod`):** Counts the number of
bars that have passed in the current HTF period or
returns the final count for a completed historical period.
2. **Automatic Timeframe Selection:** Offers functions for building
a top-down analysis framework:
- **Automatic HTF (`autoHTF`):** Suggests a higher timeframe
(HTF) for broader context based on the current timeframe.
- **Automatic LTF (`autoLTF`):** Suggests an appropriate lower
timeframe (LTF) for granular intra-bar analysis.
3. **Timeframe Manipulation and Comparison:** Includes tools for
working with timeframe strings:
- **Build & Split (`buildTF`, `splitTF`):** Functions to
programmatically construct valid Pine Script timeframe
strings (e.g., "4H") and parse them back into their
numeric and unit components.
- **Comparison (`isHigherTF`, `isActiveTF`, `isLowerTF`):**
A set of functions to check if a given timeframe is
higher, lower, or the same as the script's active timeframe.
- **Multiple Validation (`isMultipleTF`):** Checks if a
higher timeframe is a practical multiple of the current
timeframe. This is based on the assumption that checking
if recent, completed HTF periods contained more than one
bar is a valid proxy for preventing data gaps.
4. **Timestamp Interpolation:** Contains an `interpTimestamp()`
function that calculates an absolute timestamp by
interpolating at a given percentage across a specified
range of bars (e.g., 50% of the way through the last
20 bars), enabling time calculations at a resolution
finer than the chart's native bars.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
buildTF(quantity, unit)
Builds a Pine Script timeframe string from a numeric quantity and a unit enum.
The resulting string can be used with `request.security()` or `input.timeframe`.
Parameters:
quantity (int) : series int Number to specifie how many `unit` the timeframe spans.
unit (series TFUnit) : series TFUnit The size category for the bars.
Returns: series string A Pine-style timeframe identifier, e.g.
"5S" → 5-seconds bars
"30" → 30-minute bars
"120" → 2-hour bars
"1D" → daily bars
"3M" → 3-month bars
"24M" → 2-year bars
splitTF(tf)
Splits a Pine‑timeframe identifier into numeric quantity and unit (TFUnit).
Parameters:
tf (string) : series string Timeframe string, e.g.
"5S", "30", "120", "1D", "3M", "24M".
Returns:
quantity series int The numeric value of the timeframe (e.g., 15 for "15", 3 for "3M").
unit series TFUnit The unit of the timeframe (e.g., TFUnit.minutes, TFUnit.months).
Notes on strings without a suffix:
• Pure digits are minutes; if divisible by 60, they are treated as hours.
• An "M" suffix is months; if divisible by 12, it is converted to years.
autoHTF(tf)
Picks an appropriate **higher timeframe (HTF)** relative to the selected timeframe.
It steps up along a coarse ladder to produce sensible jumps for top‑down analysis.
Mapping → chosen HTF:
≤ 1 min → 60 (1h) ≈ ×60
≤ 3 min → 180 (3h) ≈ ×60
≤ 5 min → 240 (4h) ≈ ×48
≤ 15 min → D (1 day) ≈ ×26–×32 (regular session 6.5–8 h)
> 15 min → W (1 week) ≈ ×64–×80 for 30m; varies with input
≤ 1 h → W (1 week) ≈ ×32–×40
≤ 4 h → M (1 month) ≈ ×36–×44 (~22 trading days / month)
> 4 h → 3M (3 months) ≈ ×36–×66 (e.g., 12h→×36–×44; 8h→×53–×66)
≤ 1 day → 3M (3 months) ≈ ×60–×66 (~20–22 trading days / month)
> 1 day → 12M (1 year) ≈ ×(252–264)/quantity
≤ 1 week → 12M (1 year) ≈ ×52
> 1 week → 48M (4 years) ≈ ×(208)/quantity
= 1 M → 48M (4 years) ≈ ×48
> 1 M → error ("HTF too big")
any → error ("HTF too big")
Notes:
• Inputs in months or years are restricted: only 1M is allowed; larger months/any years throw.
• Returns a Pine timeframe string usable in `request.security()` and `input.timeframe`.
Parameters:
tf (string) : series string Selected timeframe (e.g., "D", "240", or `timeframe.period`).
Returns: series string Suggested higher timeframe.
autoLTF(tf)
Selects an appropriate **lower timeframe LTF)** for intra‑bar evaluation
based on the selected timeframe. The goal is to keep intra‑bar
loops performant while providing enough granularity.
Mapping → chosen LTF:
≤ 1 min → 1S ≈ ×60
≤ 5 min → 5S ≈ ×60
≤ 15 min → 15S ≈ ×60
≤ 30 min → 30S ≈ ×60
> 30 min → 60S (1m) ≈ ×31–×59 (for 31–59 minute charts)
≤ 1 h → 1 (1m) ≈ ×60
≤ 2 h → 2 (2m) ≈ ×60
≤ 4 h → 5 (5m) ≈ ×48
> 4 h → 15 (15m) ≈ ×24–×48 (e.g., 6h→×24, 8h→×32, 12h→×48)
≤ 1 day → 15 (15m) ≈ ×26–×32 (regular sessions ~6.5–8h)
> 1 day → 60 (60m) ≈ ×(26–32) per day × quantity
≤ 1 week → 60 (60m) ≈ ×32–×40 (≈5 sessions of ~6.5–8h)
> 1 week → 240 (4h) ≈ ×(8–10) per week × quantity
≤ 1 M → 240 (4h) ≈ ×33–×44 (~20–22 sessions × 6.5–8h / 4h)
≤ 3 M → D (1d) ≈ ×(20–22) per month × quantity
> 3 M → W (1w) ≈ ×(4–5) per month × quantity
≤ 1 Y → W (1w) ≈ ×52
> 1 Y → M (1M) ≈ ×12 per year × quantity
Notes:
• Ratios for D/W/M are given as ranges because they depend on
**regular session length** (typically ~6.5–8h, not 24h).
• Returned strings can be used with `request.security()` and `input.timeframe`.
Parameters:
tf (string) : series string Selected timeframe (e.g., "D", "240", or timeframe.period).
Returns: series string Suggested lower TF to use for intra‑bar work.
isNewPeriod(tf, offset)
Returns `true` when a new session-aligned period begins, or on the Nth bar of that period.
Parameters:
tf (string) : series string Target higher timeframe (e.g., "D", "W", "M").
offset (simple int) : simple int 0 → checks for the first bar of the new period.
1+ → checks for the N-th bar of the period.
Returns: series bool `true` if the condition is met.
sinceNewPeriod(tf, offset)
Counts how many bars have passed within a higher timeframe (HTF) period.
For daily, weekly, and monthly resolutions, the period is aligned with the trading session.
Parameters:
tf (string) : series string Target parent timeframe (e.g., "60", "D").
offset (simple int) : simple int 0 → Running count for the current period.
1+ → Finalized count for the Nth most recent *completed* period.
Returns: series int Number of bars.
isHigherTF(tf, main)
Returns `true` when the selected timeframe represents a
higher resolution than the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` > active TF; otherwise `false`.
isActiveTF(tf, main)
Returns `true` when the selected timeframe represents the
exact resolution of the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` == active TF; otherwise `false`.
isLowerTF(tf, main)
Returns `true` when the selected timeframe represents a
lower resolution than the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` < active TF; otherwise `false`.
isMultipleTF(tf)
Returns `true` if the selected timeframe (`tf`) is a practical multiple
of the active skript's timeframe. It verifies this by checking if `tf` is a higher timeframe
that has consistently contained more than one bar of the skript's timeframe in recent periods.
The period detection is session-aware.
Parameters:
tf (string) : series string The higher timeframe to check.
Returns: series bool `true` if `tf` is a practical multiple; otherwise `false`.
interpTimestamp(offStart, offEnd, pct)
Calculates a precise absolute timestamp by interpolating within a bar range based on a percentage.
This version works with RELATIVE bar offsets from the current bar.
Parameters:
offStart (int) : series int The relative offset of the starting bar (e.g., 10 for 10 bars ago).
offEnd (int) : series int The relative offset of the ending bar (e.g., 1 for 1 bar ago). Must be <= offStart.
pct (float) : series float The percentage of the bar range to measure (e.g., 50.5 for 50.5%).
Values are clamped to the range.
Returns: series int The calculated, interpolated absolute Unix timestamp in milliseconds.
Camarilla Pivot Plays (Lite) [BruzX]█ OVERVIEW
This indicator implements the Camarilla Pivot Points levels and a system for suggesting particular plays. It only 3rd, 4th, and 6th levels, as these are the only ones used by the system. It also optionally shows the Central Pivot Range, which is in fact between S2 and R2. In total, there are 12 possible plays, grouped into two groups of six. The algorithm evaluates in real-time which plays fulfil their precondition and shows the candidate plays. The user must then decide if and when to take the play.
█ CREDITS
The Camarilla pivot plays are defined in a strategy developed by Thor Young, and the whole system is explained in his book "A Complete Day Trading System". This description is self-sufficient for effective use.
█ FEATURES
Display the 3rd, 4th and 6th Camarilla pivot levels
Works for stocks, futures, indices, forex and crypto
Automatically switches between RTH and ETH data based on criteria defined by the system.
Option to force RTH/ETH data and force a close price to be used in the calculation.
Preconditions for the plays can be toggled on/off
Works correctly on both RTH and ETH charts
Well-documented options tooltips
Well-documented and high-quality open-source code for those who are interested
█ HOW TO USE
The defaults work well; at a minimum, just add the indicator and watch the plays being called. For US futures, you will probably want to chat the "Timezone for sessions" to New York and the regular session times to 09:30 - 16:00. The following diagram shows its key features.
By default, the indicator draws plays 1 days back; this can be changed up to 20 days. The labels can be shifted left/right using the "label offset" option to avoid overlapping with other labels in this indicator or those of another indicator.
An information box at the top-right of the chart shows:
The data currently in use for the main pivots. This can switch in the pre-market if the H/L range exceeds the previous day's H/L, and if it does, you will see that switch at the time that it happens
Whether the current day's pivots are in a higher or lower range compared to the previous day's.
The width of the pivots compared to the previous day
The current candidate plays fulfilling preconditions. You then need to watch the price action to decide whether to take the play.
The resistance pivots are all drawn in the same colour (red by default), as are the support pivots (green by default). You can change the resistance and support colours, but it is not possible to have different colours for different levels of the same kind.
█ CONCEPTS
The indicator is focused around daily Camarilla pivots and evaluates the preconditions for 12 possible plays: 6 when in a higher range, 6 when in a lower range. The plays are labelled by two letters—the first indicates the range, the second indicates the play—as shown in this diagram:
The pivots can be calculated using only RTH (Regular Trading Hours) data, or ETH (Extended Trading Hours) data, which includes the pre-market and post-market. The indicator implements logic to automatically choose the correct data, based on the rules defined by the strategy. This is user-overridable. With the default options, ETH will be used when the H/L range in the previous day's post-market or current day's pre-market exceeds that of the previous day's regular market. In auto mode, the chosen pivots are considered the main pivots for that day and are the ones used for play evaluation. The "other" pivots can also be shown—"other" here meaning using ETH data when the main pivots use RTH data, and vice versa.
The plays must fulfil a set of preconditions. There are preconditions for valid region and range, price sweeps into levels, correct pivot width, opening position, price action, and whether neutral range plays and premarket plays are enabled. When all the preconditions are fulfilled, the play will be shown as a candidate.
█ NOTE FOR FUTURES
Futures don't officially have a pre-market or post-market like equities. Let's take ES on CME as an example. It trades from 18:00 ET Sunday to 17:00 Friday (ET), with a daily pause between 17:00 and 18:00 ET. However, most of the trading activity is done between 09:30 and 16:00, which you can tell from the volume spikes at those times, and this coincides with NYSE/NASDAQ regular hours. So we define a pseudo-pre-market from 18:00 the previous day to 09:30 on the current day, then a pseudo-regular market from 08:30 to 16:00, then a pseudo-post-market from 16:00 to 17:00. The indicator then works exactly the same as with equities—all the options behave the same, just with different session times defined for the pre-, regular, and post-market, with "RTH" meaning just the regular market and "ETH" meaning all three.
█ LIMITATIONS
The pivots are very close to those shown in DAS Trader Pro. They are not to-the-cent exact, but within a few cents. The reasons are:
TradingView provides free real-time data from CBOE One, not full exchange data (you can pay for this though, and it's not expensive), and
the close/high/low are taken from the intraday timeframe you are currently viewing, not daily data—which are very close, but often not exactly the same. For example, the high on the daily timeframe may differ slightly from the daily high you'll see on an intraday timeframe.
Despite these caveats, occasionally large spikes will be seem in one platform and not the other (even with paid data), or the spikes will reach significantly difference prices. Where these spikes create the daily high or low, this can cause significantly different pivots levels. The more traded the stock is, the less the difference tends to be. Highly traded stocks are usually within a few cents (but even they occasionally have large differences in spikes). There is nothing that can be done about this.
The 6th Camarilla level does not have a standard definition and may not match the level shown on other platforms. It does match the definition used by DAS Trader Pro.
Replay mode for stocks does not work correctly. This is due to some important Pine Script variables provided by the TradingView platform and used by the script not being assigned correct values in replay mode. Futures do not use these variables, so they should work in replay mode.
The indicator is an intraday indicator (despite also being able to show weekly and monthly pivots on an intraday chart). It deactivates on a daily timeframe and higher. Sub-minute timeframes are also not supported.
The indicator was developed and tested for US/European stocks, US futures and EURUSD forex and BTCUSD. It should work as intended for stocks and futures in different countries, and for all forex and crypto, but this is tested as much as the security it was developed for.
█ DISCLAIMER
This indicator is provided for information only and should not be used in isolation without a good understand of the system and without considering other factors. You should not take trades using real money based solely on what this indicator says. Any trades you take are entirely at your own risk.
MACD HTF Hardcoded (A/B Presets) + Regimes [CHE] MACD HTF Hardcoded (A/B Presets) + Regimes — Higher-timeframe MACD emulation with acceptance-based regime filter and on-chart diagnostics
Summary
This indicator emulates a higher-timeframe MACD directly on the current chart using two hardcoded preset families and a time-bucket mapping, avoiding cross-timeframe requests. It classifies four MACD regimes and applies an acceptance filter that requires several consecutive bars before a state is considered valid. A small dead-band around zero reduces noise near the axis. An on-chart table reports the active preset, the inferred time bucket, the resolved lengths, and the current regime.
Pine version: v6
Overlay: false
Primary outputs: MACD line, Signal line, Histogram columns, zero line, regime-change alert, info table
Motivation: Why this design?
Cross-timeframe indicators often rely on external timeframe requests, which can introduce repaint paths and added latency. This design provides a deterministic alternative: it maps the current chart’s timeframe to coarse higher-timeframe buckets and uses fixed EMA lengths that approximate those views. The dead-band suppresses flip-flops around zero, and the acceptance counter reduces whipsaw by requiring sustained agreement across bars before acknowledging a regime.
What’s different vs. standard approaches?
Baseline: Classical MACD with user-selected lengths on the same timeframe, or higher-timeframe MACD via cross-timeframe requests.
Architecture differences:
Hardcoded A and B length families with a bucket map derived from the chart timeframe.
No `request.security`; all calculations occur on the current series.
Regime classification from MACD and Histogram sign, gated by an acceptance count and a small zero dead-band.
Diagnostics table for transparency.
Practical effect: The MACD behaves like a slower, higher-timeframe variant without external requests. Regimes switch less often due to the dead-band and acceptance logic, which can improve stability in choppy sessions.
How it works (technical)
The script derives a coarse bucket from the chart timeframe using `timeframe.in_seconds` and maps it to preset-specific EMA lengths. EMAs of the source build MACD and Signal; their difference is the Histogram. Signs of MACD and Histogram define four regimes: strong bull, weak bull, strong bear, and weak bear. A small, user-defined band around zero treats values near the axis as neutral. An acceptance counter checks whether the same regime persisted for a given number of consecutive bars before it is emitted as the filtered regime. A single alert condition fires when the filtered regime changes. The histogram columns change shade based on position relative to zero and whether they are rising or falling. A persistent table object shows preset, bucket tag, resolved lengths, and the filtered regime. No cross-timeframe requests are used, so repaint risk is limited to normal live-bar movement; values stabilize on close.
Parameter Guide
Source — Input series for MACD — Default: Close — Using a smoother source increases stability but adds lag.
Preset — A or B length family — Default: “3,10,16” — Switch to “12,26,9” for the classic family mapped to buckets.
Table Position — Anchor for the info table — Default: Top right — Choose a corner that avoids covering price action.
Table Size — Table text size — Default: Normal — Use small on dense charts, large for presentations.
Dark Mode — Table theme — Default: Enabled — Match your chart background for readability.
Show Table — Toggle diagnostics table — Default: Enabled — Disable for a cleaner pane.
Zero dead-band (epsilon) — Noise gate around zero — Default: Zero — Increase slightly when you see frequent flips near zero.
Acceptance bars (n) — Bars required to confirm a regime — Default: Three — Raise to reduce whipsaw; lower to react faster.
Reading & Interpretation
Histogram columns: Above zero indicates bullish pressure; below zero indicates bearish pressure. Darker shade implies the histogram increased compared with the prior bar; lighter shade implies it decreased.
MACD vs. Signal lines: The spread corresponds to histogram height.
Regimes:
Strong bull: MACD above zero and Histogram above zero.
Weak bull: MACD above zero and Histogram below zero.
Strong bear: MACD below zero and Histogram below zero.
Weak bear: MACD below zero and Histogram above zero.
Table: Inspect active preset, bucket tag, resolved lengths, and the filtered regime number with its description.
Practical Workflows & Combinations
Trend following: Use strong bull to favor long exposure and strong bear to favor short exposure. Use weak states as pullback or transition context. Combine with structure tools such as swing highs and lows or a baseline moving average for confirmation.
Exits and risk: In strong trends, consider exiting partial size on a regime downgrade to a weak state. In choppy sessions, increase the acceptance bars to reduce churn.
Multi-asset / Multi-timeframe: Works on time-based charts across liquid futures, indices, currencies, and large-cap equities. Bucket mapping helps retain a consistent feel when moving from lower to higher timeframes.
Behavior, Constraints & Performance
Repaint/confirmation: No cross-timeframe requests; values can evolve intrabar and settle on close. Alerts follow your TradingView alert timing settings.
Resources: `max_bars_back` is set to five thousand. Very large resolved lengths require sufficient history to seed EMAs; expect a warm-up period on first load or after switching symbols.
Known limits: Dead-band and acceptance can delay recognition at sharp turns. Extremely thin markets or large gaps may still cause brief regime reversals.
Sensible Defaults & Quick Tuning
Start with preset “3,10,16”, dead-band near zero, and acceptance of three bars.
Too many flips near zero: increase the dead-band slightly or raise the acceptance bars.
Too sluggish in clean trends: reduce the acceptance bars by one.
Too sensitive on fast lower timeframes: switch to the “12,26,9” preset family or raise the acceptance bars.
Want less clutter: hide the table and keep the alert.
What this indicator is—and isn’t
This is a visualization and regime layer for MACD using higher-timeframe emulation and stability gates. It is not a complete trading system and does not generate position sizing or risk management. Use it with market structure, execution rules, and protective stops.
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
Opening Range Breakout with Multi-Timeframe Liquidity]═══════════════════════════════════════
OPENING RANGE BREAKOUT WITH MULTI-TIMEFRAME LIQUIDITY
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A professional Opening Range Breakout (ORB) indicator enhanced with multi-timeframe liquidity detection, trading session visualization, volume analysis, and trend confirmation tools. Designed for intraday trading with comprehensive alert system.
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WHAT THIS INDICATOR DOES
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This indicator combines multiple trading concepts:
- Opening Range Breakout (ORB) - Customizable time period detection with automatic high/low identification
- Multi-Timeframe Liquidity - HTF (Higher Timeframe) and LTF (Lower Timeframe) key level detection
- Trading Sessions - Tokyo, London, New York, and Sydney session visualization
- Volume Analysis - Volume spike detection and strength measurement
- Multi-Timeframe Confirmation - Trend bias from higher timeframes
- EMA Integration - Trend filter and dynamic support/resistance
- Smart Alerts - Quality-filtered breakout notifications
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HOW IT WORKS
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OPENING RANGE BREAKOUT (ORB):
Concept:
The Opening Range is a period at the start of a trading session where price establishes an initial high and low. Breakouts beyond this range often indicate the direction of the day's trend.
Detection Method:
- Default: 15-minute opening range (configurable)
- Custom Range: Set specific session times with timezone support
- Automatically identifies ORH (Opening Range High) and ORL (Opening Range Low)
- Tracks ORB mid-point for reference
Range Establishment:
1. Session starts (or custom time begins)
2. Tracks highest high and lowest low during the period
3. Range confirmed at end of opening period
4. Levels extend throughout the session
Breakout Detection:
- Bullish Breakout: Close above ORH
- Bearish Breakout: Close below ORL
- Mid-point acts as bias indicator
Visual Display:
- Shaded box during range formation
- Horizontal lines for ORH, ORL, and mid-point
- Labels showing level values
- Color-coded fills based on selected method
Fill Color Methods:
1. Session Comparison:
- Green: Current OR mid > Previous OR mid
- Red: Current OR mid < Previous OR mid
- Gray: Equal or first session
- Shows day-over-day momentum
2. Breakout Direction (Recommended):
- Green: Price currently above ORH (bullish breakout)
- Red: Price currently below ORL (bearish breakout)
- Gray: Price inside range (no breakout)
- Real-time breakout status
MULTI-TIMEFRAME LIQUIDITY:
Two-Tier System for comprehensive level identification:
HTF (Higher Timeframe) Key Liquidity:
- Default: 4H timeframe (configurable to Daily, Weekly)
- Identifies major institutional levels
- Uses pivot detection with adjustable parameters
- Suitable for swing highs/lows where large orders rest
LTF (Lower Timeframe) Key Liquidity:
- Default: 1H timeframe (configurable)
- Provides precision entry/exit levels
- Finer granularity for intraday trading
- Captures minor swing points
Calculation Method:
- Pivot high/low detection algorithm
- Configurable left bars (lookback) and right bars (confirmation)
- Timeframe multiplier for accurate multi-timeframe detection
- Automatic level extension
Mitigation System:
- Tracks when levels are swept (broken)
- Configurable mitigation type: Wick or Close-based
- Option to remove or show mitigated levels
- Display limit prevents chart clutter
Asset-Specific Optimization:
The indicator includes quick reference settings for different assets:
- Major Forex (EUR/USD, GBP/USD): Default settings optimal
- Crypto (BTC/ETH): Left=12, Right=4, Display=7
- Gold: HTF=1D, Left=20
TRADING SESSIONS:
Four Major Sessions with Full Customization:
Tokyo Session:
- Default: 04:00-13:00 UTC+4
- Asian trading hours
- Often sets daily range
London Session:
- Default: 11:00-20:00 UTC+4
- Highest liquidity period
- Major institutional activity
New York Session:
- Default: 16:00-01:00 UTC+4
- US market hours
- High-impact news events
Sydney Session:
- Default: 01:00-10:00 UTC+4
- Earliest Asian activity
- Lower volatility
Session Features:
- Shaded background boxes
- Session name labels
- Optional open/close lines
- Session high/low tracking with colored lines
- Each session has independent color settings
- Fully customizable times and timezones
VOLUME ANALYSIS:
Volume-Based Trade Confirmation:
Volume MA:
- Configurable period (default: 20)
- Establishes average volume baseline
- Used for spike detection
Volume Spike Detection:
- Identifies when volume exceeds MA * multiplier
- Default: 1.5x average volume
- Confirms breakout strength
Volume Strength Measurement:
- Calculates current volume as percentage of average
- Shows relative volume intensity
- Used in alert quality filtering
High Volume Bars:
- Identifies bars above 50th percentile
- Additional confirmation layer
- Indicates institutional participation
MULTI-TIMEFRAME CONFIRMATION:
Trend Bias from Higher Timeframes:
HTF 1 (Trend):
- Default: 1H timeframe
- Uses EMA to determine intermediate trend
- Compares current timeframe EMA to HTF EMA
HTF 2 (Bias):
- Default: 4H timeframe
- Uses 50 EMA for longer-term bias
- Confirms overall market direction
Bias Classifications:
- Bullish Bias: HTF close > HTF 50 EMA AND Current EMA > HTF1 EMA
- Bearish Bias: HTF close < HTF 50 EMA AND Current EMA < HTF1 EMA
- Neutral Bias: Mixed signals between timeframes
EMA Stack Analysis:
- Compares EMA alignment across timeframes
- +1: Bullish stack (lower TF EMA > higher TF EMA)
- -1: Bearish stack (lower TF EMA < higher TF EMA)
- 0: Neutral/crossed
Usage:
- Filters false breakouts
- Confirms trend direction
- Improves trade quality
EMA INTEGRATION:
Dynamic EMA for Trend Reference:
Features:
- Configurable period (default: 20)
- Customizable color and width
- Acts as dynamic support/resistance
- Trend filter for ORB trades
Application:
- Above EMA: Favor long breakouts
- Below EMA: Favor short breakouts
- EMA cross: Potential trend change
- Distance from EMA: Momentum gauge
SMART ALERT SYSTEM:
Quality-Filtered Breakout Notifications:
Alert Types:
1. Standard ORB Breakout
2. High Quality ORB Breakout
Quality Criteria:
- Volume Confirmation: Volume > 1.2x average
- MTF Confirmation: Bias aligned with breakout direction
Standard Alert:
- Basic breakout detection
- Price crosses ORH or ORL
- Icon: 🚀 (bullish) or 🔻 (bearish)
High Quality Alert:
- Both volume AND MTF confirmed
- Stronger probability setup
- Icon: 🚀⭐ (bullish) or 🔻⭐ (bearish)
Alert Information Includes:
- Alert quality rating
- Breakout level and current price
- Volume strength percentage (if enabled)
- MTF bias status (if enabled)
- Recommended action
One Alert Per Bar:
- Prevents alert spam
- Uses flag system to track sent alerts
- Resets on new ORB session
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HOW TO USE
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OPENING RANGE SETUP:
Basic Configuration:
1. Select time period for opening range (default: 15 minutes)
2. Choose fill color method (Breakout Direction recommended)
3. Enable historical data display if needed
Custom Range (Advanced):
1. Enable Custom Range toggle
2. Set specific session time (e.g., 0930-0945)
3. Select appropriate timezone
4. Useful for specific market opens (NYSE, LSE, etc.)
LIQUIDITY LEVELS SETUP:
Quick Configuration by Asset:
- Forex: Use default settings (Left=15, Right=5)
- Crypto: Set Left=12, Right=4, Display=7
- Gold: Set HTF=1D, Left=20
HTF Liquidity:
- Purpose: Major support/resistance levels
- Recommended: 4H for day trading, 1D for swing trading
- Use as profit targets or reversal zones
LTF Liquidity:
- Purpose: Entry/exit refinement
- Recommended: 1H for day trading, 4H for swing trading
- Use for position management
Mitigation Settings:
- Wick-based: More sensitive (default)
- Close-based: More conservative
- Remove or Show mitigated levels based on preference
TRADING SESSIONS SETUP:
Enable/Disable Sessions:
- Master toggle for all sessions
- Individual session controls
- Show/hide session names
Session High/Low Lines:
- Enable to see session extremes
- Each session has custom colors
- Useful for range trading
Customization:
- Adjust session times for your broker
- Set timezone to match your location
- Customize colors for visibility
VOLUME ANALYSIS SETUP:
Enable Volume Analysis:
1. Toggle on Volume Analysis
2. Set MA length (20 recommended)
3. Adjust spike multiplier (1.5 typical)
Usage:
- Confirm breakouts with volume
- Identify climactic moves
- Filter false signals
MULTI-TIMEFRAME SETUP:
HTF Selection:
- HTF 1 (Trend): 1H for day trading, 4H for swing
- HTF 2 (Bias): 4H for day trading, 1D for swing
Interpretation:
- Trade only with bias alignment
- Neutral bias: Be cautious
- Bias changes: Potential reversals
EMA SETUP:
Configuration:
- Period: 20 for responsive, 50 for smoother
- Color: Choose contrasting color
- Width: 1-2 for visibility
Usage:
- Filter trades: Long above, Short below
- Dynamic support/resistance reference
- Trend confirmation
ALERT SETUP:
TradingView Alert Creation:
1. Enable alerts in indicator settings
2. Enable ORB Breakout Alerts
3. Right-click chart → Add Alert
4. Select this indicator
5. Choose "Any alert() function call"
6. Configure delivery method (mobile, email, webhook)
Alert Filtering:
- All alerts include quality rating
- High Quality alerts = Volume + MTF confirmed
- Standard alerts = Basic breakout only
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TRADING STRATEGIES
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CLASSIC ORB STRATEGY:
Setup:
1. Wait for opening range to complete
2. Price breaks and closes above ORH or below ORL
3. Volume > average (if enabled)
4. MTF bias aligned (if enabled)
Entry:
- Bullish: Buy on break above ORH
- Bearish: Sell on break below ORL
- Consider retest entries for better risk/reward
Stop Loss:
- Bullish: Below ORL or range mid-point
- Bearish: Above ORH or range mid-point
- Adjust based on volatility
Targets:
- Initial: Range width extension (ORH + range width)
- Secondary: HTF liquidity levels
- Final: Session high/low or major support/resistance
ORB + LIQUIDITY CONFLUENCE:
Enhanced Setup:
1. Opening range established
2. HTF liquidity level near or beyond ORH/ORL
3. Breakout occurs with volume
4. Price targets the liquidity level
Entry:
- Enter on ORB breakout
- Target the HTF liquidity level
- Use LTF liquidity for position management
Management:
- Partial profits at ORB + range width
- Move stop to breakeven at LTF liquidity
- Final exit at HTF liquidity sweep
ORB REJECTION STRATEGY (Counter-Trend):
Setup:
1. Price breaks above ORH or below ORL
2. Weak volume (below average)
3. MTF bias opposite to breakout
4. Price closes back inside range
Entry:
- Failed bullish break: Short below ORH
- Failed bearish break: Long above ORL
Stop Loss:
- Beyond the failed breakout level
- Or beyond session extreme
Target:
- Opposite end of opening range
- Range mid-point for partial profit
SESSION-BASED ORB TRADING:
Tokyo Session:
- Typically narrower ranges
- Good for range trading
- Wait for London open breakout
London Session:
- Highest volume and volatility
- Strong ORB setups
- Major liquidity sweeps common
New York Session:
- Strong trending moves
- News-driven volatility
- Good for momentum trades
Sydney Session:
- Quieter conditions
- Suitable for range strategies
- Sets up Tokyo session
EMA-FILTERED ORB:
Rules:
- Only take bullish breaks if price > EMA
- Only take bearish breaks if price < EMA
- Ignore counter-trend breaks
Benefits:
- Reduces false signals
- Aligns with larger trend
- Improves win rate
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CONFIGURATION GUIDE
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OPENING RANGE SETTINGS:
Time Period:
- 15 min: Standard for most markets
- 30 min: Wider range, fewer breakouts
- 60 min: For slower markets or swing trades
Custom Range:
- Use for specific market opens
- NYSE: 0930-1000 EST
- LSE: 0800-0830 GMT
- Set timezone to match exchange
Historical Display:
- Enable: See all previous session data
- Disable: Cleaner chart, current session only
LIQUIDITY SETTINGS:
Left Bars (5-30):
- Lower: More frequent, sensitive levels
- Higher: Fewer, more significant levels
- Recommended: 15 for most markets
Right Bars (1-25):
- Confirmation period
- Higher: More reliable, less frequent
- Recommended: 5 for balance
Display Limit (1-20):
- Number of active levels shown
- Higher: More context, busier chart
- Recommended: 7 for clarity
Extension Options:
- Short: Levels visible near formation
- Current: Extended to current bar (recommended)
- Max: Extended indefinitely
VOLUME SETTINGS:
MA Length (5-50):
- Shorter: More responsive to spikes
- Longer: Smoother baseline
- Recommended: 20 for balance
Spike Multiplier (1.0-3.0):
- Lower: More sensitive spike detection
- Higher: Only extreme spikes
- Recommended: 1.5 for day trading
MULTI-TIMEFRAME SETTINGS:
HTF 1 (Trend):
- 5m chart: Use 15m or 1H
- 15m chart: Use 1H or 4H
- 1H chart: Use 4H or 1D
HTF 2 (Bias):
- One level higher than HTF 1
- Provides longer-term context
- Don't use same as HTF 1
EMA SETTINGS:
Length:
- 20: Responsive, more signals
- 50: Smoother, stronger filter
- 200: Long-term trend only
Style:
- Choose contrasting color
- Width 1-2 for visibility
- Match your trading style
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BEST PRACTICES
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Chart Timeframe Selection:
- ORB Trading: Use 5m or 15m charts
- Session Review: Use 1H or 4H charts
- Swing Trading: Use 1H or 4H charts
Quality Over Quantity:
- Wait for high-quality alerts (volume + MTF)
- Avoid trading every breakout
- Focus on confluence setups
Risk Management:
- Position size based on range width
- Wider ranges = smaller positions
- Use stop losses always
- Take partial profits at targets
Market Conditions:
- Best results in trending markets
- Reduce position size in choppy conditions
- Consider session overlaps for volatility
- Avoid trading near major news if inexperienced
Continuous Improvement:
- Track win rate by session
- Note which confluence factors work best
- Adjust settings based on market volatility
- Review performance weekly
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PERFORMANCE OPTIMIZATION
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This indicator is optimized with:
- max_bars_back declarations for efficient processing
- Conditional calculations based on enabled features
- Proper memory management for drawing objects
- Minimal recalculation on each bar
Best Practices:
- Disable unused features (sessions, MTF, volume)
- Limit historical display to reduce rendering
- Use appropriate timeframe for your strategy
- Clear old drawing objects periodically
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EDUCATIONAL DISCLAIMER
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This indicator combines established trading concepts:
- Opening Range Breakout theory (price action)
- Liquidity level detection (pivot analysis)
- Session-based trading (time-of-day patterns)
- Volume analysis (confirmation technique)
- Multi-timeframe analysis (trend alignment)
All calculations use standard technical analysis methods:
- Pivot high/low detection algorithms
- Moving averages for trend and volume
- Session time filtering
- Timeframe security functions
The indicator identifies potential trading setups but does not predict future price movements. Success requires proper application within a complete trading strategy including risk management, position sizing, and market context.
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USAGE DISCLAIMER
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This tool is for educational and analytical purposes. Opening Range Breakout trading involves substantial risk. The alert system and quality filters are designed to identify potential setups but do not guarantee profitability. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results. Trading intraday breakouts requires experience and discipline.
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CREDITS & ATTRIBUTION
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ORIGINAL SOURCE:
This indicator builds upon concepts from LuxAlgo's-ORB
Price Action Brooks ProPrice Action Brooks Pro (PABP) - Professional Trading Indicator
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📊 OVERVIEW
Price Action Brooks Pro (PABP) is a professional-grade TradingView indicator developed based on Al Brooks' Price Action trading methodology. It integrates decades of Al Brooks' trading experience and price action analysis techniques into a comprehensive technical analysis tool, helping traders accurately interpret market structure and identify trading opportunities.
• Applicable Markets: Stocks, Futures, Forex, Cryptocurrencies
• Timeframes: 1-minute to Daily (5-minute chart recommended)
• Theoretical Foundation: Al Brooks Price Action Trading Method
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🎯 CORE FEATURES
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1️⃣ INTELLIGENT GAP DETECTION SYSTEM
Automatically identifies and marks three critical types of gaps in the market.
TRADITIONAL GAP
• Detects complete price gaps between bars
• Upward gap: Current bar's low > Previous bar's high
• Downward gap: Current bar's high < Previous bar's low
• Hollow border design - doesn't obscure price action
• Color coding: Upward gaps (light green), Downward gaps (light pink)
• Adjustable border: 1-5 pixel width options
TAIL GAP
• Detects price gaps between bar wicks/shadows
• Analyzes across 3 bars for precision
• Identifies hidden market structure
BODY GAP
• Focuses only on gaps between bar bodies (open/close)
• Filters out wick noise
• Disabled by default, enable as needed
Trading Significance:
• Gaps signal strong momentum
• Gap fills provide trading opportunities
• Consecutive gaps indicate trend continuation
✓ Independent alert system for all gap types
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2️⃣ RTH BAR COUNT (Trading Session Counter)
Intelligent counting system designed for US stock intraday trading.
FEATURES
• RTH Only Display: Regular Trading Hours (09:30-15:00 EST)
• 5-Minute Chart Optimized: Displays every 3 bars (15-minute intervals)
• Daily Auto-Reset: Counting starts from 1 each trading day
SMART COLOR CODING
• 🔴 Red (Bars 18 & 48): Critical turning moments (1.5h & 4h)
• 🔵 Sky Blue (Multiples of 12): Hourly markers (12, 24, 36...)
• 🟢 Light Green (Bar 6): Half-hour marker (30 minutes)
• ⚫ Gray (Others): Regular 15-minute interval markers
Al Brooks Time Theory:
• Bar 18 (90 min): First 90 minutes determine daily trend
• Bar 48 (4 hours): Important afternoon turning point
• Hourly markers: Track institutional trading rhythm
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3️⃣ FOUR-LINE EMA SYSTEM
Professional-grade configurable moving average system.
DEFAULT CONFIGURATION
• EMA 20: Short-term trend (Al Brooks' most important MA)
• EMA 50: Medium-short term reference
• EMA 100: Medium-long term confirmation
• EMA 200: Long-term trend and bull/bear dividing line
FLEXIBLE CUSTOMIZATION
Each EMA can be independently configured:
• On/Off toggle
• Data source selection (close/high/low/open, etc.)
• Custom period length
• Offset adjustment
• Color and transparency
COLOR SCHEME
• EMA 20: Dark brown, opaque (most important)
• EMA 50/100/200: Blue-purple gradient, 70% transparent
TRADING APPLICATIONS
• Bullish Alignment: Price > 20 > 50 > 100 > 200
• Bearish Alignment: 200 > 100 > 50 > 20 > Price
• EMA Confluence: All within <1% = major move precursor
Al Brooks Quote:
"The EMA 20 is the most important moving average. Almost all trading decisions should reference it."
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4️⃣ PREVIOUS VALUES (Key Prior Price Levels)
Automatically marks important price levels that often act as support/resistance.
THREE INDEPENDENT CONFIGURATIONS
Each group configurable for:
• Timeframe (1D/60min/15min, etc.)
• Price source (close/high/low/open/CurrentOpen, etc.)
• Line style and color
• Display duration (Today/TimeFrame/All)
SMART OPEN PRICE LABELS ⭐
• Auto-displays "Open" label when CurrentOpen selected
• Label color matches line color
• Customizable label size
TYPICAL SETUP
• 1st Line: Previous close (Support/Resistance)
• 2nd Line: Previous high (Breakout target)
• 3rd Line: Previous low (Support level)
Al Brooks Magnet Price Theory:
• Previous open: Price frequently tests opening price
• Previous high/low: Strongest support/resistance
• Breakout confirmation: Breaking prior levels = trend continuation
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5️⃣ INSIDE & OUTSIDE BAR PATTERN RECOGNITION
Automatically detects core candlestick patterns from Al Brooks' theory.
ii PATTERN (Consecutive Inside Bars)
• Current bar contained within previous bar
• Two or more consecutive
• Labels: ii, iii, iiii (auto-accumulates)
• High-probability breakout setup
• Stop loss: Outside both bars
Trading Significance:
"Inside bars are one of the most reliable breakout setups, especially three or more consecutive inside bars." - Al Brooks
OO PATTERN (Consecutive Outside Bars)
• Current bar engulfs previous bar
• Two or more consecutive
• Labels: oo, ooo (auto-accumulates)
• Indicates indecision or volatility increase
ioi PATTERN (Inside-Outside-Inside)
• Three-bar combination: Inside → Outside → Inside
• Auto-detected and labeled
• Tug-of-war pattern
• Breakout direction often very strong
SMART LABEL SYSTEM
• Auto-accumulation counting
• Dynamic label updates
• Customizable size and color
• Positioned above bars
✓ Independent alerts for all patterns
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💡 USE CASES
INTRADAY TRADING
✓ Bar Count (timing rhythm)
✓ Traditional Gap (strong signals)
✓ EMA 20 + 50 (quick trend)
✓ ii/ioi Patterns (breakout points)
SWING TRADING
✓ Previous Values (key levels)
✓ EMA 20 + 50 + 100 (trend analysis)
✓ Gaps (trend confirmation)
✓ iii Patterns (entry timing)
TREND FOLLOWING
✓ All four EMAs (alignment analysis)
✓ Gaps (continuation signals)
✓ Previous Values (targets)
BREAKOUT TRADING
✓ iii Pattern (high-reliability setup)
✓ Previous Values (targets)
✓ EMA 20 (trend direction)
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🎨 DESIGN FEATURES
PROFESSIONAL COLOR SCHEME
• Gaps: Hollow borders + light colors
• Bar Count: Smart multi-color coding
• EMAs: Gradient colors + transparency hierarchy
• Previous Values: Customizable + smart labels
CLEAR VISUAL HIERARCHY
• Important elements: Opaque (EMA 20, bar count)
• Reference elements: Semi-transparent (other EMAs, gaps)
• Hollow design: Doesn't obscure price action
USER-FRIENDLY INTERFACE
• Clear functional grouping
• Inline layout saves space
• All colors and sizes customizable
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📚 AL BROOKS THEORY CORE
READING PRICE ACTION
"Don't try to predict the market, read what the market is telling you."
PABP converts core concepts into visual tools:
• Trend Assessment: EMA system
• Time Rhythm: Bar Count
• Market Structure: Gap analysis
• Trade Setups: Inside/Outside Bars
• Support/Resistance: Previous Values
PROBABILITY THINKING
• ii pattern: Medium probability
• iii pattern: High probability
• iii + EMA 20 support: Very high probability
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⚙️ TECHNICAL SPECIFICATIONS
• Pine Script Version: v6
• Maximum Objects: 500 lines, 500 labels, 500 boxes
• Alert Functions: 8 independent alerts
• Supported Timeframes: All (5-min recommended for Bar Count)
• Compatibility: All TradingView plans, Mobile & Desktop
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🚀 RECOMMENDED INITIAL SETTINGS
GAPS
• Traditional Gap: ✓
• Tail Gap: ✓
• Border Width: 2
BAR COUNT
• Use Bar Count: ✓
• Label Size: Normal
EMA
• EMA 20: ✓
• EMA 50: ✓
• EMA 100: ✓
• EMA 200: ✓
PREVIOUS VALUES
• 1st: close (Previous close)
• 2nd: high (Previous high)
• 3rd: low (Previous low)
INSIDE & OUTSIDE BAR
• All patterns: ✓
• Label Size: Large
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🌟 WHY CHOOSE PABP?
✅ Solid Theoretical Foundation
Based on Al Brooks' decades of trading experience
✅ Complete Professional Features
Systematizes complex price action analysis
✅ Highly Customizable
Every feature adjustable to personal style
✅ Excellent Performance
Optimized code ensures smooth experience
✅ Continuous Updates
Constantly improving based on feedback
✅ Suitable for All Levels
Benefits beginners to professionals
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📖 RECOMMENDED LEARNING
Al Brooks Books:
• "Trading Price Action Trends"
• "Trading Price Action Trading Ranges"
• "Trading Price Action Reversals"
Learning Path:
1. Understand basic candlestick patterns
2. Learn EMA applications
3. Master market structure analysis
4. Develop trading system
5. Continuous practice and optimization
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⚠️ RISK DISCLOSURE
IMPORTANT NOTICE:
• For educational and informational purposes only
• Does not constitute investment advice
• Past performance doesn't guarantee future results
• Trading involves risk and may result in capital loss
• Trade according to your risk tolerance
• Test thoroughly in demo account first
RESPONSIBLE TRADING:
• Always use stop losses
• Control position sizes reasonably
• Don't overtrade
• Continuous learning and improvement
• Keep trading journal
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📜 COPYRIGHT
Price Action Brooks Pro (PABP)
Author: © JimmC98
License: Mozilla Public License 2.0
Pine Script Version: v6
Acknowledgments:
Thanks to Dr. Al Brooks for his contributions to price action trading. This indicator is developed based on his theories.
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Experience professional-grade price action analysis now!
"The best traders read price action, not indicators. But when indicators help you read price action better, use them." - Al Brooks
NOVA Breakout Signals v2.2 (TF M30)A clean, rules-based breakout signal tool for 30-minute charts.
It detects Dow swing breakouts and filters them with RSI, MACD and Volume so you only see the higher-quality entries. The script does not place trades and does not calculate SL/TP – it only prints clear LONG/SHORT labels at the entry price.
⸻
How it works
1. Timeframe enforcement – Signals are generated only on M30. On other timeframes the script shows a notice and stays silent.
2. Breakout engine (Dow swings) – The last confirmed swing high/low (pivots) is tracked.
• Breakout Up: bar closes above the last swing high by a small buffer.
• Breakout Down: bar closes below the last swing low by a small buffer.
3. Quality filters (all must be true):
• RSI (default length 30):
• Long: RSI > threshold and rising.
• Short: RSI < threshold and falling.
• MACD (12/26/9):
• Long: histogram > 0 and line > signal.
• Short: histogram < 0 and line < signal.
• Volume: current volume > SMA(volume, 20) × multiplier.
4. Debounce / anti-spam
• Cooldown of 4 hours (8 M30 bars) after any signal.
• Minimum price distance from the previous signal to avoid clustered labels.
Signals appear once the bar closes (barstate.isconfirmed). No swing lines are drawn to keep the chart clean; only entry labels are shown.
⸻
Inputs (key)
• RSI length & thresholds for Long/Short confirmation.
• MACD uses 12/26/9 (fixed).
• Volume multiplier (relative to SMA 20).
• Breakout buffer %, Cooldown hours, Min distance %.
• Show labels (on/off).
⸻
Usage tips
• Start with gold/major FX/indices on M30; use “Once per bar close” if you attach alerts.
• Increase the breakout buffer and volume multiplier in choppy markets.
• Tighten RSI thresholds (e.g., 55/45) if you want fewer but stronger signals.
⸻
Notes & limitations
• Pivots confirm after a few bars by definition; signals themselves are printed only on confirmed bar close and do not repaint once shown.
• This is a signal indicator, not investment advice. Always manage risk.
Smart MACD Volume Trader# Smart MACD Volume Trader
## Overview
Smart MACD Volume Trader is an enhanced momentum indicator that combines the classic MACD (Moving Average Convergence Divergence) oscillator with an intelligent high-volume filter. This combination significantly reduces false signals by ensuring that trading signals are only generated when price momentum is confirmed by substantial volume activity.
The indicator supports over 24 different instruments including major and exotic forex pairs, precious metals (gold and silver), energy commodities (crude oil, natural gas), and industrial metals (copper). For forex and commodity traders, the indicator automatically maps to CME and COMEX futures contracts to provide accurate institutional-grade volume data.
## Originality and Core Concept
Traditional MACD indicators generate signals based solely on price momentum, which can result in numerous false signals during low-activity periods or ranging markets. This indicator addresses this critical weakness by introducing a volume confirmation layer with automatic institutional volume integration.
**What makes this approach original:**
- Signals are triggered only when MACD crossovers coincide with elevated volume activity
- Implements a lookback mechanism to detect volume spikes within recent bars
- Automatically detects and maps 24+ forex pairs and commodities to their corresponding CME and COMEX futures contracts
- Provides real institutional volume data for forex pairs where spot volume is unreliable
- Combines two independent market dimensions (price momentum and volume) into a single, actionable signal
- Includes intelligent asset detection that works across multiple exchanges and ticker formats
**The underlying principle:** Volume validates price movement. When institutional money enters the market, it creates volume signatures. By requiring high volume confirmation and using actual institutional volume data from futures markets, this indicator filters out weak price movements and focuses on trades backed by genuine market participation. The automatic futures mapping ensures that forex and commodity traders always have access to the most accurate volume data available, without manual configuration.
## How It Works
### MACD Component
The indicator calculates MACD using standard methodology:
1. **Fast EMA (default: 12 periods)** - Tracks short-term price momentum
2. **Slow EMA (default: 26 periods)** - Tracks longer-term price momentum
3. **MACD Line** - Difference between Fast EMA and Slow EMA
4. **Signal Line (default: 9-period SMA)** - Smoothed average of MACD line
**Crossover signals:**
- **Bullish:** MACD line crosses above Signal line (momentum turning positive)
- **Bearish:** MACD line crosses below Signal line (momentum turning negative)
### Volume Filter Component
The volume filter adds an essential confirmation layer:
1. **Volume Moving Average** - Calculates exponential MA of volume (default: 20 periods)
2. **High Volume Threshold** - Multiplies MA by ratio (default: 2.0x or 200%)
3. **Volume Detection** - Identifies bars where current volume exceeds threshold
4. **Lookback Period** - Checks if high volume occurred in recent bars (default: 5 bars)
**Signal logic:**
- Buy/Sell signals only trigger when BOTH conditions are met:
- MACD crossover/crossunder occurs
- High volume detected within lookback period
### Automatic CME Futures Integration
For forex traders, spot FX volume data can be unreliable or non-existent. This indicator solves this problem by automatically detecting forex pairs and mapping them to corresponding CME futures contracts with real institutional volume data.
**Supported Major Forex Pairs (7):**
- EURUSD → CME:6E1! (Euro FX Futures)
- GBPUSD → CME:6B1! (British Pound Futures)
- AUDUSD → CME:6A1! (Australian Dollar Futures)
- USDJPY → CME:6J1! (Japanese Yen Futures)
- USDCAD → CME:6C1! (Canadian Dollar Futures)
- USDCHF → CME:6S1! (Swiss Franc Futures)
- NZDUSD → CME:6N1! (New Zealand Dollar Futures)
**Supported Exotic Forex Pairs (4):**
- USDMXN → CME:6M1! (Mexican Peso Futures)
- USDRUB → CME:6R1! (Russian Ruble Futures)
- USDBRL → CME:6L1! (Brazilian Real Futures)
- USDZAR → CME:6Z1! (South African Rand Futures)
**Supported Cross Pairs (6):**
- EURJPY → CME:6E1! (Uses Euro Futures)
- GBPJPY → CME:6B1! (Uses British Pound Futures)
- EURGBP → CME:6E1! (Uses Euro Futures)
- AUDJPY → CME:6A1! (Uses Australian Dollar Futures)
- EURAUD → CME:6E1! (Uses Euro Futures)
- GBPAUD → CME:6B1! (Uses British Pound Futures)
**Supported Precious Metals (2):**
- Gold (XAUUSD, GOLD) → COMEX:GC1! (Gold Futures)
- Silver (XAGUSD, SILVER) → COMEX:SI1! (Silver Futures)
**Supported Energy Commodities (3):**
- WTI Crude Oil (USOIL, WTIUSD) → NYMEX:CL1! (Crude Oil Futures)
- Brent Oil (UKOIL) → NYMEX:BZ1! (Brent Crude Futures)
- Natural Gas (NATGAS) → NYMEX:NG1! (Natural Gas Futures)
**Supported Industrial Metals (1):**
- Copper (COPPER) → COMEX:HG1! (Copper Futures)
**How the automatic detection works:**
The indicator intelligently identifies the asset type by analyzing:
1. Exchange name (FX, OANDA, TVC, COMEX, NYMEX, etc.)
2. Currency pair pattern (6-letter codes like EURUSD, GBPUSD)
3. Commodity identifiers (XAU for gold, XAG for silver, OIL for crude)
When a supported instrument is detected, the indicator automatically switches to the corresponding futures contract for volume analysis. For stocks, cryptocurrencies, and other assets, the indicator uses the native volume data from the current chart.
**Visual feedback:**
An information table appears in the top-right corner of the MACD pane showing:
- Current chart symbol
- Exchange name
- Currency pair or asset name
- Volume source being used (highlighted in orange for futures, yellow for native volume)
- Current high volume status
This provides complete transparency about which data source the indicator is using for its volume analysis.
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. The indicator displays in a separate pane (MACD) and overlay (signals/volume bars)
3. Default settings work well for most assets, but can be customized
### Signal Interpretation
### Visual Signals
**Visual Signals:**
- **Green "BUY" label** - Bullish MACD crossover confirmed by high volume
- **Red "SELL" label** - Bearish MACD crossunder confirmed by high volume
- **Green/Red candles** - Highlight bars with volume exceeding the threshold
- **Light green/red background** - Emphasizes signal bars on the chart
**Information Table:**
A detailed information table appears in the top-right corner of the MACD pane, providing real-time transparency about the indicator's operation:
- **Chart:** Current symbol being analyzed
- **Exchange:** The exchange or data feed being used
- **Pair:** The currency pair or asset name extracted from the ticker
- **Volume From:** The actual symbol used for volume analysis
- Orange color indicates CME or COMEX futures are being used (automatic institutional volume)
- Yellow color indicates native volume from the chart symbol is being used
- Hover tooltip shows whether automatic futures mapping is active
- **High Volume:** Current status showing YES (green) when volume exceeds threshold, NO (gray) otherwise
This table ensures complete transparency and allows you to verify that the correct volume source is being used for your analysis.
**Volume Analysis:**
- Gray histogram bars = Normal volume
- Red histogram bars = High volume (exceeds threshold)
- Green line = Volume moving average baseline
**MACD Analysis:**
- Blue line = MACD line (momentum indicator)
- Orange line = Signal line (trend confirmation)
- Gray dotted line = Zero line (bullish above, bearish below)
### Parameter Customization
**MACD Parameters:**
- Adjust Fast/Slow EMA lengths for different sensitivities
- Shorter periods = More signals, faster response
- Longer periods = Fewer signals, less noise
**Volume Parameters:**
- **Volume MA Period:** Higher values smooth volume analysis
- **High Volume Ratio:** Lower values (1.5x) = More signals; Higher values (3.0x) = Fewer, stronger signals
- **Volume Lookback Bars:** Controls how recent the volume spike must be
**Direction Filters:**
- **Only Buy Signals:** Enables long-only strategy mode
- **Only Sell Signals:** Enables short-only strategy mode
### Alert Configuration
The indicator includes three alert types:
1. **Buy Signal Alert** - Triggers when bullish signal appears
2. **Sell Signal Alert** - Triggers when bearish signal appears
3. **High Volume Alert** - Triggers when volume exceeds threshold
To set up alerts:
1. Click the indicator name → "Add alert on Smart MACD Volume Trader"
2. Select desired alert condition
3. Configure notification method (popup, email, webhook, etc.)
## Trading Strategy Guidelines
### Best Practices
**Recommended markets:**
- Liquid stocks (large-cap, high daily volume)
- Major forex pairs (EURUSD, GBPUSD, USDJPY, AUDUSD, USDCAD, USDCHF, NZDUSD)
- Exotic forex pairs (USDMXN, USDRUB, USDBRL, USDZAR)
- Cross pairs (EURJPY, GBPJPY, EURGBP, AUDJPY, EURAUD, GBPAUD)
- Precious metals (Gold, Silver with automatic COMEX futures mapping)
- Energy commodities (Crude Oil, Natural Gas with automatic NYMEX futures mapping)
- Industrial metals (Copper with automatic COMEX futures mapping)
- Major cryptocurrency pairs
- Index futures and ETFs
**Timeframe recommendations:**
- **Day trading:** 5-minute to 15-minute charts
- **Swing trading:** 1-hour to 4-hour charts
- **Position trading:** Daily charts
**Risk management:**
- Use signals as entry confirmation, not standalone strategy
- Combine with support/resistance levels
- Consider overall market trend direction
- Always use stop-loss orders
### Strategy Examples
**Trend Following Strategy:**
1. Identify overall trend using higher timeframe (e.g., daily chart)
2. Trade only in trend direction
3. Use "Only Buy" filter in uptrends, "Only Sell" in downtrends
4. Enter on signal, exit on opposite signal or at resistance/support
**Volume Breakout Strategy:**
1. Wait for consolidation period (low volume, tight MACD range)
2. Enter when signal appears with high volume (confirms breakout)
3. Target previous swing highs/lows
4. Stop loss below/above recent consolidation
**Forex Scalping Strategy (with automatic CME futures):**
1. The indicator automatically detects forex pairs and uses CME futures volume
2. Trade during active sessions only (use session filter)
3. Focus on quick profits (10-20 pips)
4. Exit at opposite signal or profit target
**Commodities Trading Strategy (Gold, Silver, Oil):**
1. The indicator automatically maps to COMEX and NYMEX futures contracts
2. Trade during high-liquidity sessions (overlap of major markets)
3. Use the high volume confirmation to identify institutional entry points
4. Combine with key support and resistance levels for entries
5. Monitor the information table to confirm futures volume is being used (orange color)
6. Exit on opposite MACD signal or at predefined profit targets
## Why This Combination Works
### The Volume Advantage
Studies consistently show that price movements accompanied by high volume are more likely to continue, while low-volume movements often reverse. This indicator leverages this principle by requiring volume confirmation.
**Key benefits:**
1. **Reduced False Signals:** Eliminates MACD whipsaws during low-volume consolidation
2. **Confirmation Bias:** Two independent indicators (price momentum + volume) agreeing
3. **Institutional Alignment:** High volume often indicates institutional participation
4. **Trend Validation:** Volume confirms that price momentum has "conviction"
### Statistical Edge
By combining two uncorrelated signals (MACD crossovers and volume spikes), the indicator creates a higher-probability setup than either signal alone. The lookback mechanism ensures signals aren't missed if volume spike slightly precedes the MACD cross.
## Supported Exchanges and Automatic Detection
The indicator includes intelligent asset detection that works across multiple exchanges and ticker formats:
**Forex Exchanges (Automatic CME Mapping):**
- FX (TradingView forex feed)
- OANDA
- FXCM
- SAXO
- FOREXCOM
- PEPPERSTONE
- EASYMARKETS
- FX_IDC
**Commodity Exchanges (Automatic COMEX/NYMEX Mapping):**
- TVC (TradingView commodity feed)
- COMEX (directly)
- NYMEX (directly)
- ICEUS
**Other Asset Classes (Native Volume):**
- Stock exchanges (NASDAQ, NYSE, AMEX, etc.)
- Cryptocurrency exchanges (BINANCE, COINBASE, KRAKEN, etc.)
- Index providers (SP, DJ, etc.)
The detection algorithm analyzes three factors:
1. Exchange prefix in the ticker symbol
2. Pattern matching for currency pairs (6-letter codes)
3. Commodity identifiers in the symbol name
This ensures accurate automatic detection regardless of which data feed or exchange you use for charting. The information table in the top-right corner always displays which volume source is being used, providing complete transparency.
## Technical Details
**Calculations:**
- MACD Fast MA: EMA(close, fastLength)
- MACD Slow MA: EMA(close, slowLength)
- MACD Line: Fast MA - Slow MA
- Signal Line: SMA(MACD Line, signalLength)
- Volume MA: Exponential MA of volume
- High Volume: Current volume >= Volume MA × Ratio
**Signal logic:**
```
Buy Signal = (MACD crosses above Signal) AND (High volume in last N bars)
Sell Signal = (MACD crosses below Signal) AND (High volume in last N bars)
```
## Parameters Reference
| Parameter | Default | Description |
|-----------|---------|-------------|
| Volume Symbol | Blank | Manual override for volume source (leave blank for automatic detection) |
| Use CME Futures | False | Legacy option (automatic detection is now built-in) |
| Alert Session | 1530-2200 | Active session time range for alerts |
| Timezone | UTC+1 | Timezone for alert sessions |
| Volume MA Period | 20 | Number of periods for volume moving average |
| High Volume Ratio | 2.0 | Volume threshold multiplier (2.0 = 200% of average) |
| Volume Lookback | 5 | Number of bars to check for high volume confirmation |
| MACD Fast Length | 12 | Fast EMA period for MACD calculation |
| MACD Slow Length | 26 | Slow EMA period for MACD calculation |
| MACD Signal Length | 9 | Signal line SMA period |
| Only Buy | False | Filter to show only bullish signals |
| Only Sell | False | Filter to show only bearish signals |
| Show Signals | True | Display buy and sell labels on chart |
## Optimization Tips
**For volatile markets (crypto, small caps):**
- Increase High Volume Ratio to 2.5-3.0
- Reduce Volume Lookback to 3-4 bars
- Consider faster MACD settings (8, 17, 9)
**For stable markets (large-cap stocks, bonds):**
- Decrease High Volume Ratio to 1.5-1.8
- Increase Volume MA Period to 30-50
- Use standard MACD settings
**For forex (with automatic CME futures):**
- The indicator automatically uses CME futures when forex pairs are detected
- Set appropriate trading session based on your timezone
- Use Volume Lookback of 5-7 bars
- Consider session-based alerts only
- Monitor the information table to verify correct futures mapping
**For commodities (Gold, Silver, Oil, Copper):**
- The indicator automatically maps to COMEX and NYMEX futures
- Increase High Volume Ratio to 2.0-2.5 for metals
- Use slightly higher Volume MA Period (25-30) for smoother analysis
- Trade during active market hours for best volume data
- The information table will show the futures contract being used (orange highlight)
## Limitations and Considerations
**What this indicator does NOT do:**
- Does not predict future price direction
- Does not guarantee profitable trades
- Does not replace proper risk management
- Does not work well in extremely low-volume conditions
**Market conditions to avoid:**
- Pre-market and after-hours sessions (low volume)
- Major news events (volatile, unpredictable volume)
- Holidays and low-liquidity periods
- Extremely low float stocks
## Conclusion
Smart MACD Volume Trader represents a significant evolution of the traditional MACD indicator by combining volume confirmation with automatic institutional volume integration. This dual-confirmation approach significantly improves signal quality by filtering out low-conviction price movements and ensuring traders work with accurate volume data.
The indicator's automatic detection and mapping system supports over 24 instruments across forex, commodities, and metals markets. By intelligently switching to CME and COMEX futures contracts when appropriate, the indicator provides forex and commodity traders with the same quality of volume data that stock traders naturally have access to.
This indicator is particularly valuable for traders who want to:
- Align their entries with institutional money flow
- Avoid getting trapped in false breakouts
- Trade forex pairs with reliable volume data
- Access accurate volume information for gold, silver, and energy commodities
- Combine momentum and volume analysis in a single, streamlined tool
Whether you are day trading stocks, swing trading forex pairs, or positioning in commodities markets, this indicator provides a robust framework for identifying high-probability momentum trades backed by genuine institutional participation. The automatic futures mapping works seamlessly across all supported instruments, requiring no manual configuration or expertise in futures markets.
---
## Support and Updates
This indicator is actively maintained and updated based on user feedback and market conditions. For questions about implementation or custom modifications, please use the comments section below.
**Disclaimer:** This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management before trading.
Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
TASC 2025.11 The Points and Line Chart█ OVERVIEW
This script implements the Points and Line Chart described by Mohamed Ashraf Mahfouz and Mohamed Meregy in the November 2025 edition of the TASC Traders' Tips , "Efficient Display of Irregular Time Series”. This novel chart type interprets regular time series chart data to create an irregular time series chart.
█ CONCEPTS
When formatting data for display on a price chart, there are two main categorizations of chart types: regular time series (RTS) and irregular time series (ITS).
RTS charts, such as a typical candlestick chart, collect data over a specified amount of time and display it at one point. A one-minute candle, for example, represents the entirety of price movements within the minute that it represents.
ITS charts display data only after certain conditions are met. Since they do not plot at a consistent time period, they are called “irregular”.
Typically, ITS charts, such as Point and Figure (P&F) and Renko charts, focus on price change, plotting only when a certain threshold of change occurs.
The Points and Line (P&L) chart operates similarly to a P&F chart, using price change to determine when to plot points. However, instead of plotting the price in points, the P&L chart (by default) plots the closing price from RTS data. In other words, the P&L chart plots its points at the actual RTS close, as opposed to (price) intervals based on point size. This approach creates an ITS while still maintaining a reference to the RTS data, allowing us to gain a better understanding of time while consolidating the chart into an ITS format.
█ USAGE
Because the P&L chart forms bars based on price action instead of time, it displays displays significantly more history than a typical RTS chart. With this view, we are able to more easily spot support and resistance levels, which we could use when looking to place trades.
In the chart below, we can see over 13 years of data consolidated into one single view.
To view specific chart details, hover over each point of the chart to see a list of information.
In addition to providing a compact view of price movement over larger periods, this new chart type helps make classic chart patterns easier to interpret. When considering breakouts, the closing price provides a clearer representation of the actual breakout, as opposed to point size plots which are limited.
Because P&L is a new charting type, this script still requires a standard RTS chart for proper calculations. However, the main price chart is not intended for interpretation alongside the P&L chart; users can hide the main price series to keep the chart clean.
█ DISPLAYS
This indicator creates two displays: the "Price Display" and the "Data Display".
With the "Price display" setting, users can choose between showing a line or OHLC candles for the P&L drawing. The line display shows the close price of the P&L chart. In the candle display, the close price remains the same, while the open, high, and low values depend on the price action between points.
With the "Data display" setting, users can enable the display of a histogram that shows either the total volume or days/bars between the points in the P&L chart. For example, a reading of 12 days would indicate that the time since the last point was 12 days.
Note: The "Days" setting actually shows the number of chart bars elapsed between P&L points. The displayed value represents days only if the chart uses the "1D" timeframe.
The "Overlay P&L on chart" input controls whether the P&L line or candles appear on the main chart pane or in a separate pane.
Users can deactivate either display by selecting "None" from the corresponding input.
Technical Note: Due to drawing limitations, this indicator has the following display limits:
The line display can show data to 10,000 P&L points.
The candle display and tooltips show data for up to 500 points.
The histograms show data for up to 3,333 points.
█ INPUTS
Reversal Amount: The number of points/steps required to determine a reversal.
Scale size Method: The method used to filter price movements. By default, the P&L chart uses the same scaling method as the P&F chart. Optionally, this scaling method can be changed to use ATR or Percent.
P&L Method: The prices to plot and use for filtering:
“Close” plots the closing price and uses it to determine movements.
“High/Low” uses the high price on upside moves and low price on downside moves.
"Point Size" uses the closing price for filtration, but locks the price to plot at point size intervals.
Moving Average Convergence-Divergence (MACD)This script implements the Moving Average Convergence-Divergence (MACD), a popular momentum indicator used in technical analysis to identify trend direction, momentum shifts, and potential buy/sell signals.
🔹 Key Features
1. Inputs & Customization
MACD Lines Toggle: Enable/disable the MACD and signal lines.
Source Price: Defaults to close but can be adjusted (e.g., open, high, low, hl2).
Fast Length (12): The period for the faster-moving EMA.
Slow Length (26): The period for the slower-moving EMA.
Signal Length (9): The smoothing period for the signal line.
2. Calculations
Computes the MACD Line (fast EMA - slow EMA).
Computes the Signal Line (EMA of the MACD line).
Computes the Histogram (difference between MACD and Signal lines).
3. Visual Indicators
Zero Line: A white horizontal line at 0 for reference.
MACD Line: Plotted in green when above the signal line, red when below.
Signal Line: Displayed as a yellow line.
Histogram:
Green bars when MACD > Signal (bullish momentum).
Red bars when MACD < Signal (bearish momentum).
Background Highlights:
Light green on bullish crossovers (MACD crosses above Signal).
Light red on bearish crossunders (MACD crosses below Signal).
4. Alerts
Triggers when:
Bullish Crossover (MACD crosses above Signal).
Bearish Crossunder (MACD crosses below Signal).
🔹 How Traders Use This Indicator
Trend Identification:
MACD above zero → bullish trend.
MACD below zero → bearish trend.
Momentum Signals:
Bullish Crossover (Buy Signal): MACD crosses above Signal.
Bearish Crossunder (Sell Signal): MACD crosses below Signal.
Divergence (Not in this script, but useful):
Price makes higher highs, but MACD makes lower highs → Potential reversal.
🔹 Strengths of This Script
✅ Clean and Efficient Code – Uses Pine Script v6 best practices.
✅ Customizable Inputs – Adjust lengths and source price.
✅ Clear Visuals – Color-coded for easy interpretation.
✅ Built-in Alerts – For automated trading strategies.
Jul 1
Release Notes
This script implements the Moving Average Convergence-Divergence (MACD), a popular momentum indicator used in technical analysis to identify trend direction, momentum shifts, and potential buy/sell signals.
🔹 Key Features
1. Inputs & Customization
MACD Lines Toggle: Enable/disable the MACD and signal lines.
Source Price: Defaults to close but can be adjusted (e.g., open, high, low, hl2).
Fast Length (12): The period for the faster-moving EMA.
Slow Length (26): The period for the slower-moving EMA.
Signal Length (9): The smoothing period for the signal line.
2. Calculations
Computes the MACD Line (fast EMA - slow EMA).
Computes the Signal Line (EMA of the MACD line).
Computes the Histogram (difference between MACD and Signal lines).
3. Visual Indicators
Zero Line: A white horizontal line at 0 for reference.
MACD Line: Plotted in green when above the signal line, red when below.
Signal Line: Displayed as a yellow line.
Histogram:
Green bars when MACD > Signal (bullish momentum).
Red bars when MACD < Signal (bearish momentum).
Background Highlights:
Light green on bullish crossovers (MACD crosses above Signal).
Light red on bearish crossunders (MACD crosses below Signal).
4. Alerts
Triggers when:
Bullish Crossover (MACD crosses above Signal).
Bearish Crossunder (MACD crosses below Signal).
🔹 How Traders Use This Indicator
Trend Identification:
MACD above zero → bullish trend.
MACD below zero → bearish trend.
Momentum Signals:
Bullish Crossover (Buy Signal): MACD crosses above Signal.
Bearish Crossunder (Sell Signal): MACD crosses below Signal.
Divergence (Not in this script, but useful):
Price makes higher highs, but MACD makes lower highs → Potential reversal.
🔹 Strengths of This Script
✅ Clean and Efficient Code – Uses Pine Script v6 best practices.
✅ Customizable Inputs – Adjust lengths and source price.
✅ Clear Visuals – Color-coded for easy interpretation.
✅ Built-in Alerts – For automated trading strategies.
Chart Fusion Line SND Detection by TitikSona🧭 Overview
Fusion Line Momentum Analyzer is a momentum visualization tool that introduces a unified model of oscillator fusion.
It blends Fast and Slow Stochastics with RSI into one adaptive curve, designed to eliminate conflicting signals between different momentum sources.
Instead of reading three separate oscillators, the Fusion Line provides a consolidated view of strength and exhaustion zones in a single framework.
This approach helps analysts detect aligned momentum shifts with greater clarity and less noise, without repainting or lagging methods.
⚙️ Core Concept
Traditional oscillators often provide conflicting readings when volatility changes.
To solve this, the Fusion Line averages three normalized components:
Fast Stochastic (12,3,3) — reacts quickly to short-term momentum spikes.
Slow Stochastic (100,8,8) — filters long-term momentum context.
RSI (26) — measures internal strength between buying and selling pressure.
Each is rescaled to a 0–100 range, then averaged into a single curve called the Fusion Line.
A secondary Signal Line (SMA 9) is added to visualize directional confirmation.
This combination aims to preserve responsiveness from the fast components while maintaining structural stability from the slow and RSI layers.
🌈 Features
Unified momentum curve combining stochastic and RSI dynamics.
Automatic bias shading to highlight dominant trend direction.
Real-time percentage strength meter (visual intensity).
Configurable alert triggers on key momentum zones (20/80).
Clean chart display without unnecessary elements or overlays.
📘 Interpretation
Rising Fusion Line → indicates strengthening bullish momentum.
Falling Fusion Line → indicates strengthening bearish pressure.
Fusion values below 20 → potential oversold recovery.
Fusion values above 80 → possible exhaustion or reversal zone.
Mid-zone movement → reflects equilibrium or sideways momentum.
These readings should always be combined with higher timeframe structure or volume confirmation for context.
⚙️ Default Parameters
Fast Stochastic (12,3,3)
Slow Stochastic (100,8,8)
RSI Length (26)
Signal Line Smoothing (9)
All values can be adjusted to adapt to asset volatility or timeframe conditions.
⚠️ Disclaimer
This indicator is a research and visualization tool, not a signal generator.
It does not predict price movement or guarantee performance.
Use for analytical purposes only and combine with your own trading framework.
👨💻 Developer
Created by TitikSona — Research & Fusion Concept Designer
Built using Pine Script v6
Type: Open-source educational script
💬 Short Description
Fusion-based momentum visualization combining Double Stochastic and RSI into one adaptive line for clearer, noise-free momentum analysis.
RSI VWAP v1 [JopAlgo]RSI VWAP v1.1 made stronger by volume-aware!
We know there's nothing new and the original RSI already does an excellent job. We're just working on small, practical improvements – here's our take: The same basic idea, clearer display, and a single, specially developed rolling line: a VWAP of the RSI that incorporates volume (participation) into the calculation.
Do you prefer the pure classic?
You can still use Wilder or Cutler engines –
but the star here is the VW-RSI + rolling line.
This RSI also offers the possibility of illustrating a possible
POC (Point of Control - or the HAL or VAL) level.
However, the indicator does NOT plot any of these levels itself.
We have included an illustration in the chart for this!
We hope this version makes your decision-making easier.
What you’ll see
The RSI line with a 50 midline and optional bands: either static 70/30 or adaptive μ±k·σ of the Rolling Line.
One smoothing concept only: the Rolling Line (light blue) = VWAP of RSI.
Shadow shading between RSI and the Rolling Line (green when RSI > line, red when RSI < line).
A lighter tint only on the parts of that shadow that sit above the upper band or below the lower band (quick overbought/oversold context).
Simple divergence lines drawn from RSI pivots (green for regular bullish, red for regular bearish). No labels, no buy/sell text—kept deliberately clean.
What’s new, and why it helps
VW-RSI engine (default):
RSI can be computed from volume-weighted up/down moves, so momentum reflects how much traded when price moved—not just the direction.
Rolling Line (VWAP of RSI) with pure VWAP adaptation:
Low volume: blends toward a faster VWAP so early, thin starts aren’t missed.
Volume spikes: blends toward a slower VWAP so a single heavy bar doesn’t whip the curve.
You can reveal the Base Rolling (pre-adaptation) line to see exactly how much adaptation is happening.
Adaptive bands (optional):
Instead of fixed 70/30, use mean ± k·stdev of the Rolling Line over a lookback. Levels breathe with the market—useful in strong trends where static bounds stay pinned.
Minimal, readable panel:
One smoothing, one story. The shadow tells you who’s in control; the lighter highlight shows stretch beyond your lines.
How to read it (fast)
Bias: RSI above 50 (and a rising Rolling Line) → bullish bias; below 50 → bearish bias.
Trigger: RSI crossing the Rolling Line with the bias (e.g., above 50 and crossing up).
Stretch: Near/above the upper band, avoid chasing; near/below the lower band, avoid panic—prefer a cross back through the line.
Divergence lines: Use as context, not as standalone signals. They often help you wait for the next cross or avoid late entries into exhaustion.
Settings that actually matter
RSI Engine: VW-RSI (default), Wilder, or Cutler.
Rolling Line Length: the VWAP length on RSI (higher = calmer, lower = earlier).
Adaptive behavior (pure VWAP):
Speed-up on Low Volume → blends toward fast VWAP (factor of your length).
Dampen Spikes (volume z-score) → blends toward slow VWAP.
Fast/Slow Factors → how far those fast/slow variants sit from the base length.
Bands: choose Static 70/30 or Adaptive μ±k·σ (set the lookback and k).
Visuals: show/hide Base Rolling (ref), main shadow, and highlight beyond bands.
Signal gating: optional “ignore first bars” per day/session if you dislike open noise.
Starter presets
Scalp (1–5m): RSI 9–12, Rolling 12–18, FastFactor ~0.5, SlowFactor ~2.0, Adaptive on.
Intraday (15m–1H): RSI 10–14, Rolling 18–26, Bands k = 1.0–1.4.
Swing (4H–1D): RSI 14–20, Rolling 26–40, Bands k = 1.2–1.8, Adaptive on.
Where it shines (and limits)
Best: liquid markets where volume structure matters (majors, indices, large caps).
Works elsewhere: even with imperfect volume, the shadow + bands remain useful.
Limits: very thin/illiquid assets reduce the benefit of volume-weighting—lengthen settings if needed.
Attribution & License
Based on the concept and baseline implementation of the “Relative Strength Index” by TradingView (Pine v6 built-in).
Released as Open-source (MPL-2.0). Please keep the license header and attribution intact.
Disclaimer
For educational purposes only; not financial advice. Markets carry risk. Test first, use clear levels, and manage risk. This project is independent and not affiliated with or endorsed by TradingView.
ICT Killzones & MacrosICT Killzones & Macros (v1.1.5) — configurable ICT session windows + refined “macro” windows with live High/Low levels, optional extensions, next-window previews, and lightweight opening-price lines. Built to be clock-robust, timezone-aware, and performant on intraday charts.
Tip: All times are interpreted in your chosen IANA timezone (default: America/New_York) and auto-handle DST. You can rename, recolor, enable/disable, and retime every window.
What it plots
- Killzones (5) : Asia (19:00–02:00), London (02:00–05:00), NY AM (07:00–09:30), London Close (10:00–12:00), NY PM (13:30–16:00) — full-height boxes with optional header.
- Macros (8) (defaults tailored for common ICT “refined” windows): Asia-1 (18:00–21:00), Asia-2 (21:00–00:00), London-1 (01:00–04:00), AM-1 (09:45–10:15), AM-2 (10:45–11:15), Lunch (12:00–13:00), PM-1 (13:30–14:30), Power Hour (15:10–16:00).
- Live High/Low lines for the current Macro/Killzone window.
- Optional HL extension to the right until price crosses or the trading day rolls (style selectable).
- “Next” previews : earliest upcoming Macro and Killzone header; optional next-window background band.
- Opening Prices (3 lightweight time lines) : defaults 00:00, 08:30, 09:30 with right-edge labels, scoped to a session you choose (auto-cleans at session end).
- Key inputs & styling
- General : Timezone (IANA), “Sessions to show” (per window) to keep only the last N completed windows.
- Header : height (ticks), gap (ticks), fill opacity, border width/style, text size/color, toggle “Next Macro/Killzone” headers.
- Boxes : global fill opacity, global border width/style (used by both Macros & Killzones).
- High/Low : show HL, HL line style, extend on/off + extension style, optional extension labels.
- Opening Prices : enable Time 1/2/3, set HH:MM for each, session window, per-line colors, style (dotted/dashed/solid), width.
- Per-window controls : each Macro/Killzone has Enable, Session (HHMM-HHMM), Label, Fill color.
How to use (quick start)
- Set Timezone to your preference (default America/New_York).
- Toggle on the Macros and Killzones you trade. Adjust session times if needed.
- (Optional) Turn on Extend High/Low to project levels until crossed/day-roll.
- (Optional) Enable Next… headers to see the next upcoming window at a glance.
- (Optional) Configure Opening Prices (00:00 / 08:30 / 09:30 by default) and the session over which they appear.
Behavior & notes
- Time windows are computed by clock, not by guessing bar timestamps, making them robust across brokers and timeframes.
- With HL extension on, the current window’s levels extend until crossed or the end of the trading day (in your timezone). With it off, completed windows keep static HL markers (limited by “Sessions to show”).
- “Sessions to show” applies per Macro/Killzone to automatically prune older windows and keep charts snappy.
- Opening-price lines exist only within the chosen “Opening Prices Session” and are removed when it ends (keeps charts clean).
Defaults (color cues)
Killzones: Asia (blue), London (purple), NY AM (green), London Close (yellow), NY PM (orange).
Macros: neutral greys with Lunch and PM accents out of the box (all customizable).
Performance tips
- Reduce “Sessions to show” if you scroll far back in history.
- Disable “Next…” previews and/or extension labels on very slow machines.
- Narrow the “Opening Prices Session” window to exactly when you need those lines.
Changelog highlights
- v1.1.5 : Internal refinements and stability.
- v1.1.3 : Live High/Low lines for current windows + optional extension.
- v1.1.2 : Added “next Killzone” preview (to match “next Macro”).
- v1.1.0 : Defaults updated (5 KZ, 8 Macros). Removed “snap-to-killzone” behavior.
- v1.0.0 : Independent Macro vs. Killzone rendering; cleaner header logic.
- Known limitations
If your chart warns about drawings, trim “Sessions to show”.
If your broker session times differ from NY hours, adjust the sessions or change the indicator timezone.
Credits & intent
Inspired by ICT timing concepts; provided for education/mark-up, not financial advice.
Built to be flexible so you can mirror your personal playbook and journaling workflow.
Triple SuperTrend + RSI + Fib BBTriple SuperTrend + RSI + Fibonacci Bollinger Bands Strategy
📊 Overview
This advanced trading strategy combines the power of three SuperTrend indicators with RSI confirmation and Fibonacci Bollinger Bands to generate high-probability trade signals. The strategy is designed to capture strong trending moves while filtering out false signals through multi-indicator confluence.
🔧 Core Components
Three SuperTrend Indicators
The strategy uses three SuperTrend indicators with progressively longer periods and multipliers:
SuperTrend 1: 10-period ATR, 1.0 multiplier (fastest, most sensitive)
SuperTrend 2: 11-period ATR, 2.0 multiplier (medium sensitivity)
SuperTrend 3: 12-period ATR, 3.0 multiplier (slowest, most stable)
This layered approach ensures that all three timeframe perspectives align before generating a signal, significantly reducing false entries.
RSI Confirmation (7-period)
The Relative Strength Index acts as a momentum filter:
Long signals require RSI > 50 (bullish momentum)
Short signals require RSI < 50 (bearish momentum)
This prevents entries during weak or divergent price action.
Fibonacci Bollinger Bands (200, 2.618)
Uses a 200-period Simple Moving Average with 2.618 standard deviation bands (Fibonacci ratio). These bands serve dual purposes:
Visual representation of price extremes
Automatic exit trigger when price reaches overextended levels
📈 Entry Logic
LONG Entry (BUY Signal)
A LONG position is opened when ALL of the following conditions are met simultaneously:
All three SuperTrend indicators turn green (bullish)
RSI(7) is above 50
This is the first bar where all conditions align (no repainting)
SHORT Entry (SELL Signal)
A SHORT position is opened when ALL of the following conditions are met simultaneously:
All three SuperTrend indicators turn red (bearish)
RSI(7) is below 50
This is the first bar where all conditions align (no repainting)
🚪 Exit Logic
Positions are automatically closed when ANY of these conditions occur:
SuperTrend Color Change: Any one of the three SuperTrend indicators changes direction
Fibonacci BB Touch: Price reaches or exceeds the upper or lower Fibonacci Bollinger Band (2.618 standard deviations)
This dual-exit approach protects profits by:
Exiting quickly when trend momentum shifts (SuperTrend change)
Taking profits at statistical price extremes (Fib BB touch)
🎨 Visual Features
Signal Arrows
Green Up Arrow (BUY): Appears below the bar when long entry conditions are met
Red Down Arrow (SELL): Appears above the bar when short entry conditions are met
Yellow Down Arrow (EXIT): Appears above the bar when exit conditions are met
Background Coloring
Light Green Tint: All three SuperTrends are bullish (uptrend environment)
Light Red Tint: All three SuperTrends are bearish (downtrend environment)
SuperTrend Lines
Three colored lines plotted with varying opacity:
Solid line (ST1): Most responsive to price changes
Semi-transparent (ST2): Medium-term trend
Most transparent (ST3): Long-term trend structure
Dashboard
Real-time information panel showing:
Individual SuperTrend status (UP/DOWN)
Current RSI value and color-coded status
Current position (LONG/SHORT/FLAT)
Net Profit/Loss
⚙️ Customizable Parameters
SuperTrend Settings
ATR periods for each SuperTrend (default: 10, 11, 12)
Multipliers for each SuperTrend (default: 1.0, 2.0, 3.0)
RSI Settings
RSI length (default: 7)
RSI source (default: close)
Fibonacci Bollinger Bands
BB length (default: 200)
BB multiplier (default: 2.618)
Strategy Options
Enable/disable long trades
Enable/disable short trades
Initial capital
Position sizing
Commission settings
💡 Strategy Philosophy
This strategy is built on the principle of confluence trading - waiting for multiple independent indicators to align before taking a position. By requiring three SuperTrend indicators AND RSI confirmation, the strategy filters out the majority of low-probability setups.
The multi-timeframe SuperTrend approach ensures that short-term, medium-term, and longer-term trends are all in agreement, which typically occurs during strong, sustainable price moves.
The exit strategy is equally important, using both trend-following logic (SuperTrend changes) and mean-reversion logic (Fibonacci BB touches) to adapt to different market conditions.
📊 Best Use Cases
Trending Markets: Works best in markets with clear directional bias
Higher Timeframes: Designed for 15-minute to daily charts
Volatile Assets: SuperTrend indicators excel in assets with clear trends
Swing Trading: Hold times typically range from hours to days
⚠️ Important Notes
No Repainting: All signals are confirmed and will not change on historical bars
One Signal Per Setup: The strategy prevents duplicate signals on consecutive bars
Exit Protection: Always exits before potentially taking an opposite position
Visual Clarity: All three SuperTrend lines are visible simultaneously for transparency
🎯 Recommended Settings
While default parameters are optimized for general use, consider:
Crypto/Volatile Markets: May benefit from slightly higher multipliers
Forex: Default settings work well for major pairs
Stocks: Consider longer BB periods (250-300) for daily charts
Lower Timeframes: Reduce all periods proportionally for scalping
📝 Alerts
Built-in alert conditions for:
BUY signal triggered
SELL signal triggered
EXIT signal triggered
Set up notifications to never miss a trade opportunity!
Disclaimer: This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Always backtest thoroughly and practice proper risk management before live trading.
