Inverse VIX / Custom Inverse Line🎯 Main Idea
This indicator creates a line that moves opposite to the VIX (Volatility Index) — or any symbol you choose.
When VIX rises (fear increases), → this line goes down.
When VIX falls (market calm), → this line goes up.
It helps you visually understand market sentiment — calm periods (bullish) vs fear periods (bearish).
⚙️ Input Settings
Setting Description
Symbol to invert The symbol to invert. Default is CBOE:VIX.
Inverse mode The method used to invert the values. There are 3 options:
① Negate Simply flips the sign (multiplies by -1). Very straightforward.
② Reciprocal Uses the mathematical inverse (1 ÷ value). High values become smaller, and vice versa.
③ Inverse Normalized The most useful mode 🔥 — normalizes values between 0–100 and flips them, similar to an RSI.
Normalization lookback How many bars to use for normalization (default 252 = roughly one trading year).
Smoothing (SMA) Number of bars for smoothing (makes the line smoother).
Use log for reciprocal Uses logarithmic scaling to stabilize big swings.
Plot color / width Customize the line’s color and thickness.
Show original source If enabled, shows the original VIX line for comparison.
📈 How It Works
The script fetches the close price of the VIX (or your chosen symbol).
It applies the selected inversion method.
The inverted line is plotted on the chart.
In “Inverse Normalized” mode:
The range is 0–100.
Values above 75 = high optimism (market often overheated).
Values below 25 = high fear (potential buying opportunity).
A middle line at 50 marks neutral sentiment.
⚠️ Alerts
The indicator includes two default alerts when using “Inverse Normalized” mode:
🔔 Above 75: Market showing strong optimism (potential top or correction zone).
🔔 Below 25: Market showing fear (potential bottom or buy signal).
🧠 How to Use It
Use it on daily or weekly charts for clearer signals.
Compare it with SPX or NASDAQ:
When the Inverse VIX line rises, markets often go up.
When it falls, markets usually drop or consolidate.
Combine it with other indicators (e.g., RSI, MACD) for confirmation.
Tìm kiếm tập lệnh với "汇丰股票25"
MNQ TopStep 50K | Ultra Quality v3.0MNQ TopStep 50K | Ultra Quality v3.0 - Publish Summary
📊 Overview
A professional-grade trading indicator designed specifically for MNQ futures traders using TopStep funded accounts. Combines 7 technical confirmations with 5 advanced safety filters to deliver high-quality trade signals while managing drawdown risk.
🎯 Key Features
Core Signal System
7-Point Confirmation: VWAP, EMA crossovers, 15-min HTF trend, MACD, RSI, ADX, and Volume
Signal Grading: Each signal is rated A+ through D based on 7 quality factors
Quality Threshold: Adjustable minimum grade requirement (A+, A, B, C, D)
Advanced Safety Filters (Customizable)
Mean Reversion Filter - Prevents chasing extended moves beyond VWAP bands
ATR Spike Filter - Avoids trading during extreme volatility events
EMA Spacing Filter - Ensures proper trend separation (optional)
Momentum Filter - Requires consecutive directional bars (optional)
Multi-Timeframe Confirmation - Aligns with 15-min trend (optional)
TopStep Risk Management
Real-time drawdown tracking
Position sizing calculator based on remaining cushion
Daily loss limit monitoring
Consecutive loss protection
Max trades per day limiter
Visual Components
VWAP with 1σ, 2σ, 3σ bands
EMA 9/21 with cloud fill
15-min EMA 50 for HTF trend
Comprehensive metrics dashboard
Risk management panel
Filter status panel
Detailed trade labels with entry, stops, and targets
⚙️ Default Settings (Balanced for Regular Signals)
Technical Indicators
Fast EMA: 9 | Slow EMA: 21 | HTF EMA: 50 (15-min)
MACD: 10/22/9
RSI: 14 period | Thresholds: 52 (buy) / 48 (sell)
ADX: 14 period | Minimum: 20
ATR: 14 period | Stop: 2x | TP1: 2x | TP2: 3x
Volume: 1.2x average required
Session Settings
Default: 9:30 AM - 11:30 AM ET (adjustable)
Avoids first 15 minutes after market open
Customizable trading hours
Safety Filters (Default Configuration)
✅ Mean Reversion: Enabled (2.5σ max from VWAP)
✅ ATR Spike: Enabled (2.0x threshold)
❌ EMA Spacing: Disabled (can enable for quality)
❌ Momentum: Disabled (can enable for quality)
❌ MTF Confirmation: Disabled (can enable for quality)
Risk Controls
Minimum Signal Quality: C (adjustable to A+ for fewer/better signals)
Min Bars Between Signals: 10
Max Trades Per Day: 5
Stop After Consecutive Losses: 2
📈 Expected Performance
With Default Settings:
Signals per week: 10-15 trades
Estimated win rate: 55-60%
Risk-Reward: 1:2 (TP1) and 1:3 (TP2)
With Aggressive Settings (Min Quality = D, All Filters Off):
Signals per week: 20-25 trades
Estimated win rate: 50-55%
With Conservative Settings (Min Quality = A, All Filters On):
Signals per week: 3-5 trades
Estimated win rate: 65-70%
🚀 How to Use
Basic Setup:
Add indicator to MNQ 5-minute chart
Adjust TopStep account settings in inputs
Set your risk per trade percentage (default: 0.5%)
Configure trading session hours
Set minimum signal quality (Start with C for balanced results)
Signal Interpretation:
Green Triangle (BUY): Long signal - all confirmations aligned
Red Triangle (SELL): Short signal - all confirmations aligned
Label Details: Shows entry, stop loss, take profit levels, position size, and signal grade
Signal Grade: A+ = Elite (6-7 points) | A = Strong (5) | B = Good (4) | C = Fair (3)
Dashboard Monitoring:
Top Right: Technical metrics and market conditions
Top Left: Filter status (which filters are passing/blocking)
Bottom Right: TopStep risk metrics and position sizing
⚡ Customization Tips
For More Signals:
Lower "Minimum Signal Quality" to D
Decrease ADX threshold to 18-20
Lower RSI thresholds to 50/50
Reduce Volume multiplier to 1.1x
Disable additional filters
For Higher Quality (Fewer Signals):
Raise "Minimum Signal Quality" to A or A+
Increase ADX threshold to 25-30
Enable all 5 advanced filters
Tighten VWAP distance to 2.0σ
Increase momentum requirement to 3-4 bars
For TopStep Compliance:
Adjust "Max Total Drawdown" and "Daily Loss Limit" to match your account
Update "Already Used Drawdown" daily
Monitor the Risk Panel for cushion remaining
Use recommended contract sizing
🛡️ Risk Disclaimer
IMPORTANT: This indicator is for educational and informational purposes only.
Past performance does not guarantee future results
All trading involves substantial risk of loss
Use proper risk management and position sizing
Test thoroughly in paper trading before live use
The indicator does not guarantee profitable trades
Adjust settings based on your risk tolerance and trading style
Always comply with your broker's and TopStep's rules
MNQ TopStep 50K | Ultra Quality v3.0MNQ TopStep 50K | Ultra Quality v3.0 - Publish Summary📊 OverviewA professional-grade trading indicator designed specifically for MNQ futures traders using TopStep funded accounts. Combines 7 technical confirmations with 5 advanced safety filters to deliver high-quality trade signals while managing drawdown risk.🎯 Key FeaturesCore Signal System
7-Point Confirmation: VWAP, EMA crossovers, 15-min HTF trend, MACD, RSI, ADX, and Volume
Signal Grading: Each signal is rated A+ through D based on 7 quality factors
Quality Threshold: Adjustable minimum grade requirement (A+, A, B, C, D)
Advanced Safety Filters (Customizable)
Mean Reversion Filter - Prevents chasing extended moves beyond VWAP bands
ATR Spike Filter - Avoids trading during extreme volatility events
EMA Spacing Filter - Ensures proper trend separation (optional)
Momentum Filter - Requires consecutive directional bars (optional)
Multi-Timeframe Confirmation - Aligns with 15-min trend (optional)
TopStep Risk Management
Real-time drawdown tracking
Position sizing calculator based on remaining cushion
Daily loss limit monitoring
Consecutive loss protection
Max trades per day limiter
Visual Components
VWAP with 1σ, 2σ, 3σ bands
EMA 9/21 with cloud fill
15-min EMA 50 for HTF trend
Comprehensive metrics dashboard
Risk management panel
Filter status panel
Detailed trade labels with entry, stops, and targets
⚙️ Default Settings (Balanced for Regular Signals)Technical Indicators
Fast EMA: 9 | Slow EMA: 21 | HTF EMA: 50 (15-min)
MACD: 10/22/9
RSI: 14 period | Thresholds: 52 (buy) / 48 (sell)
ADX: 14 period | Minimum: 20
ATR: 14 period | Stop: 2x | TP1: 2x | TP2: 3x
Volume: 1.2x average required
Session Settings
Default: 9:30 AM - 11:30 AM ET (adjustable)
Avoids first 15 minutes after market open
Customizable trading hours
Safety Filters (Default Configuration)
✅ Mean Reversion: Enabled (2.5σ max from VWAP)
✅ ATR Spike: Enabled (2.0x threshold)
❌ EMA Spacing: Disabled (can enable for quality)
❌ Momentum: Disabled (can enable for quality)
❌ MTF Confirmation: Disabled (can enable for quality)
Risk Controls
Minimum Signal Quality: C (adjustable to A+ for fewer/better signals)
Min Bars Between Signals: 10
Max Trades Per Day: 5
Stop After Consecutive Losses: 2
📈 Expected PerformanceWith Default Settings:
Signals per week: 10-15 trades
Estimated win rate: 55-60%
Risk-Reward: 1:2 (TP1) and 1:3 (TP2)
With Aggressive Settings (Min Quality = D, All Filters Off):
Signals per week: 20-25 trades
Estimated win rate: 50-55%
With Conservative Settings (Min Quality = A, All Filters On):
Signals per week: 3-5 trades
Estimated win rate: 65-70%
🚀 How to UseBasic Setup:
Add indicator to MNQ 5-minute chart
Adjust TopStep account settings in inputs
Set your risk per trade percentage (default: 0.5%)
Configure trading session hours
Set minimum signal quality (Start with C for balanced results)
Signal Interpretation:
Green Triangle (BUY): Long signal - all confirmations aligned
Red Triangle (SELL): Short signal - all confirmations aligned
Label Details: Shows entry, stop loss, take profit levels, position size, and signal grade
Signal Grade: A+ = Elite (6-7 points) | A = Strong (5) | B = Good (4) | C = Fair (3)
Dashboard Monitoring:
Top Right: Technical metrics and market conditions
Top Left: Filter status (which filters are passing/blocking)
Bottom Right: TopStep risk metrics and position sizing
⚡ Customization TipsFor More Signals:
Lower "Minimum Signal Quality" to D
Decrease ADX threshold to 18-20
Lower RSI thresholds to 50/50
Reduce Volume multiplier to 1.1x
Disable additional filters
For Higher Quality (Fewer Signals):
Raise "Minimum Signal Quality" to A or A+
Increase ADX threshold to 25-30
Enable all 5 advanced filters
Tighten VWAP distance to 2.0σ
Increase momentum requirement to 3-4 bars
For TopStep Compliance:
Adjust "Max Total Drawdown" and "Daily Loss Limit" to match your account
Update "Already Used Drawdown" daily
Monitor the Risk Panel for cushion remaining
Use recommended contract sizing
🛡️ Risk DisclaimerIMPORTANT: This indicator is for educational and informational purposes only.
Past performance does not guarantee future results
All trading involves substantial risk of loss
Use proper risk management and position sizing
Test thoroughly in paper trading before live use
The indicator does not guarantee profitable trades
Adjust settings based on your risk tolerance and trading style
Always comply with your broker's and TopStep's rules
GEX Options Flow Pro 100% free
INTRODUCTION
This script is designed to visualize advanced options-derived metrics and levels on TradingView charts, including Gamma Exposure (GEX) walls, gamma flip points, vanna levels, delta-neutral prices (DEX), max pain, implied moves, and more. It overlays dynamic lines, labels, boxes, and an info table to highlight potential support, resistance, volatility regimes, and flow dynamics based on options data.
These visualizations aim to help users understand how options market structure might influence price action, such as areas of potential stability (positive GEX) or volatility (negative GEX). All data is user-provided via pasted strings, as Pine Script cannot fetch external options data directly due to platform limitations (detailed below).
The script is open-source under TradingView's terms, allowing study, modification, and improvement. It draws inspiration from standard options Greeks and exposure metrics (e.g., gamma, vanna, charm) discussed in financial literature like Black-Scholes models and dealer positioning analyses. No external code is copied; all logic is original or based on mathematical formulas.
Disclaimer: This is an educational tool only. It does not provide investment advice, trading signals, or guarantees of performance. Past data is not indicative of future results. Use at your own risk, and combine with your own analysis. Not intended for qualified investors only.
How the Options Levels Are Calculated
Levels are not computed in Pine Script—they rely on pre-calculated values from external tools (e.g., Python scripts using libraries like yfinance for options chains). Here's how they're typically derived externally before pasting into the script:
Fetching Options Data: Retrieve options chain for a ticker: strikes, open interest (OI), volume, implied volatility (IV), expirations (e.g., shortest: 0-7 DTE, short: 7-14 DTE, medium: ~30 DTE, long: ~90 DTE). Get current price and 5-day history for context.
Gamma Walls (Put/Call Walls): Compute gamma for each option using Black-Scholes: gamma = N'(d1) / (S * σ * √T) where S = spot price, K = strike, T = time to expiration (years), σ = IV, N'(d1) = normal PDF. Aggregate GEX at strikes: GEX = sign * gamma * OI * 100 * S^2 * 0.01 (per 1% move, with sign based on dealer positioning: typically short calls/puts = negative GEX). Put Wall: Highest absolute GEX put strike below S (support via dealer buying on dips). Call Wall: Highest absolute GEX call strike above S (resistance via dealer selling on rallies). Secondary/Tertiary: Next highest levels. Historical walls track tier-1 levels over 5 days.
Gamma Flip: Net GEX profile across prices: Sum GEX for all options at hypothetical spots. Flip point: Interpolated price where net GEX changes sign (stable above, volatile below).
Vanna Levels: Vanna = -N'(d1) * d2 / σ. Weighted by OI; highest positive/negative strikes.
DEX (Delta-Neutral Price): Net dealer delta: Sum (delta * OI * 100 * sign), with delta from Black-Scholes. DEX: Price where net delta = 0 (interpolated).
Max Pain: Strike minimizing total intrinsic value for all options holders.
Skew: 25-delta skew: IV difference between 25-delta put and call (interpolated).
Net GEX/Delta: Total signed GEX/delta at current S.
Implied Move: ATM IV * √(DTE/365) for 1σ range.
C/P Ratio: (Call OI + volume) / (Put OI + volume).
Smart Stop Loss: Below lowest support (e.g., Put Wall, gamma flip), buffered by IV * √(DTE/30).
Other Metrics: IV: ATM average. 5-day metrics: Avg volume, high/low.
External tools handle dealer assumptions (e.g., short calls/puts) and scaling (per % move).
Effect as Support and Resistance in Technical Trading
Options levels reflect dealer hedging dynamics:
Put Wall (Gamma Support): High put GEX creates buying pressure on dips (dealers hedge short puts by buying stock). Use for long entries, bounces, or stops below.
Call Wall (Gamma Resistance): High call GEX leads to selling on rallies. Good for trims, shorts, or reversals.
Gamma Flip: Pivot for volatility—above: dampened moves (positive GEX, mean reversion); below: amplified trends (negative GEX, momentum).
Vanna Levels: Sensitivity to IV changes; crosses may signal vol shifts.
DEX: Dealer delta neutral—bullish if price below with positive delta.
Max Pain: Price magnet minimizing option payouts.
Implied Move/Confidence Bands: Expected ranges (1σ/2σ/3σ); breakouts suggest extremes.
Liquidity Zones: Wall ranges as price magnets.
Smart Stop Loss: Protective level below supports, IV-adjusted.
C/P Ratio & Skew: Sentiment (high C/P = bullish; high skew = put demand).
Net GEX: Positive = low vol strategies (e.g., condors); negative = momentum trades.
Combine with TA (e.g., volume, trends). High activity strengthens effects; alerts on crosses/proximities for awareness.
Limitations of the TradingView Platform for Data Pulling
Pine Script is sandboxed:
No API calls or internet access (can't fetch options data directly).
Limited to chart/symbol data; no real-time chains.
Inputs static per load; manual updates needed.
Caching not persistent across sessions.
This ensures lightweight scripts but requires external data sourcing.
Creative Solution for On-Demand Data Pulling
Users can use external tools (e.g., Python scripts with yfinance) to fetch/compute data on demand. Generate a formatted string (ticker,timestamp|term1_data|term2_data|...), paste into inputs. Tools can process multiple tickers, cache for ~15-30 min, and output strings for quick portfolio scanning. Run locally or via custom setups for near-real-time updates without platform violations.
For convenience, a free bot is available on my website that accepts commands like !gex to generate both current data strings (for all expiration terms) and historical walls data on demand. This allows users to easily obtain fresh or cached data (refreshed every ~30 min) for pasting into the indicator—ideal for scanning portfolios without manual coding.
Script Functionality Breakdown
Inputs: Data strings (current/historical); term selector (Shortest/Short/Medium/Long); toggles (historical walls, GEX profile, secondaries, vanna, table, max pain, DEX, stop loss, implied move, liquidity, bands); colors/styles.
Parsing: Extracts term-specific data; validates ticker match; gets timestamp for freshness.
Drawing: Dynamic lines/labels (width/color by GEX strength); boxes (moves, zones, bands); clears on updates.
Info Table: Dashboard with status (freshness emoji), Greeks (GEX/delta with emojis), vol (IV/skew), levels (distances), flow (C/P, vol vs 5D).
Historical Walls: Displays past tier-1 walls on daily+ timeframes.
Alerts: 20+ conditions (e.g., near/cross walls, GEX sign change, high IV).
Performance: Efficient for real-time; smart label positioning.
Release Notes
Initial release: Full features including multi-term support, enhanced table with emojis/sentiment, dynamic visuals, smart stop loss.
Data String Format: TICKER,TIMESTAMP|TERM1_DATA|TERM2_DATA|TERM3_DATA|TERM4_DATA Where each TERM_DATA = val0,val1,...,val30 (31 floats: current_price, prev_close, call_wall_1, call_wall_1_gex, ..., low_5d). Historical: TICKER|TERM1_HIST|... where TERM_HIST = date:cw,pw;date:cw,pw;...
Feedback welcome in comments. Educational only—not advice.
MA Disparity (乖離率%)このインジケータは、現在の終値と移動平均線(SMAまたはEMA)との**乖離率(かいりりつ)**を%で表示します。
「価格が移動平均線からどれだけ離れているか」を視覚的に把握することで、**過熱感(買われすぎ/売られすぎ)**を判断できます。
設定で期間(例:20日、25日など)を自由に変更可能
SMA/EMAの選択が可能
0%ラインを基準として、プラス側は上方乖離、マイナス側は下方乖離を示します
トレンドの勢い確認、押し目・戻り目の判断にも活用できます
📊 例:
+10%以上 → 短期的な過熱感
-10%以下 → 売られすぎの可能性
---
This indicator displays the disparity ratio (price deviation) between the current close and a moving average (SMA or EMA), expressed in percentage.
It helps visualize how far the price has moved away from its average — a useful signal for identifying overbought or oversold conditions.
Adjustable period (e.g., 20, 25, 50, etc.)
Selectable MA type (SMA or EMA)
0% baseline: positive values = above MA, negative = below MA
Great for spotting trend strength, pullbacks, and reversals
📈 Example:
+10% → potential overbought zone
-10% → potential oversold zone
---
#Kairi #Disparity #MovingAverage #Volume #SMA #EMA #Overbought #Oversold #Japan
8 SMA Bands (Points)The "8 SMA Bands (Points)" indicator creates a set of eight Simple Moving Average (SMA) bands with adjustable offsets, overlaid on a price chart.
Here’s a breakdown:
Purpose: It tracks price trends using multiple SMAs of varying lengths (default 25, 50, 100, 200, 400, 800, 1600 periods) and adds upper and lower bands around each SMA based on point offsets, helping identify potential support, resistance, and trend strength.
Key Components:
SMAs: Eight SMAs are calculated using closing prices with lengths ranging from 25 to 1600 periods. Each SMA is plotted with a distinct color and line thickness (e.g., MA 1 is blue, MA 8 is white with thicker lines).
Bands: For each SMA, upper and lower bands are created by adding or subtracting a point-based offset (suggestions are to use default Murray Math based numbers e.g., 0.305176 for MA 1, 39.062528 for MA 8) multiplied by a global multiplier (default 1.0). These offsets define the band width and are customizable.
Customization: Users can adjust SMA lengths, offset points, colors, and the global multiplier via input settings grouped by each MA.
Visuals: SMAs are plotted as solid lines with increasing thickness for longer periods (e.g., MA 6–8 use thicker lines or circles).
Bands are plotted as semi-transparent lines matching the SMA color, with longer-term bands (MA 6–7) using a different style for emphasis.
Usage: The indicator helps traders visualize trend direction (upward if price is above most SMAs, downward if below) and potential reversal zones where price interacts with band boundaries.
The flattening or crossing of bands can signal momentum shifts. The coming together of multiple envelope tops/bottoms can signal reversal zones of various degrees based on how many envelopes come together. More envelopes converging mean a more significant top or bottom.
This indicator is particularly useful for identifying multi-timeframe trends and volatility zones on assets like Gold Futures, with flexibility to fine-tune based on market conditions.
SuperScript Filtered (Stable)🔎 What This Indicator Does
The indicator is a trend and momentum filter.
It looks at multiple well-known technical tools (T3 moving averages, RSI, TSI, and EMA trend) and assigns a score to the current market condition.
• If most tools are bullish → score goes up.
• If most tools are bearish → score goes down.
• Only when the score is very strong (above +75 or below -75), it prints a Buy or Sell signal.
This helps traders focus only on high-probability setups instead of reacting to every small wiggle in price.
________________________________________
⚙️ How It Works
1. T3 Trend Check
o Compares a fast and slow T3 moving average.
o If the fast T3 is above the slow T3 → bullish signal.
o If it’s below → bearish signal.
2. RSI Check
o Uses the Relative Strength Index.
o If RSI is above 50 → bullish momentum.
o If RSI is below 50 → bearish momentum.
3. TSI Check
o Uses the True Strength Index.
o If TSI is above its signal line → bullish momentum.
o If TSI is below → bearish momentum.
4. EMA Trend Check
o Looks at two exponential moving averages (fast and slow).
o If price is above both → bullish.
o If price is below both → bearish.
5. Score System
o Each condition contributes +25 (bullish) or -25 (bearish).
o The total score can range from -100 to +100.
o Score ≥ +75 → Strong Buy
o Score ≤ -75 → Strong Sell
6. Signal Filtering
o Only one buy is allowed until a sell appears (and vice versa).
o A minimum bar gap is enforced between signals to avoid clutter.
________________________________________
📊 How It Appears on the Chart
• Green “BUY” label below candles → when multiple signals agree and the market is strongly bullish.
• Red “SELL” label above candles → when multiple signals agree and the market is strongly bearish.
• Background softly shaded green or red → highlights bullish or bearish conditions.
No messy tables, no clutter — just clear trend-based entries.
________________________________________
🎯 How Traders Can Use It
This indicator is designed to help traders by:
1. Filtering Noise
o Instead of reacting to every small crossover or RSI blip, it waits until at least 3–4 conditions agree.
o This avoids entering weak trades.
2. Identifying Strong Trend Shifts
o When a Buy or Sell arrow appears, it usually signals a shift in momentum that can lead to a larger move.
3. Reducing Overtrading
o By limiting signals, traders won’t be tempted to jump in and out unnecessarily.
4. Trade Confirmation
o Traders can use the signals as confirmation for their own setups.
o Example: If your strategy says “go long” and the indicator also shows a strong Buy, that trade has more conviction.
5. Alert Automation
o Built-in alerts mean you don’t have to watch the chart all day.
o You’ll be notified only when a strong signal appears.
________________________________________
⚡ When It Helps the Most
• Works best in trending markets (bullish or bearish).
• Very useful on higher timeframes (1h, 4h, daily) for swing trading.
• Can also work on lower timeframes (5m, 15m) if combined with higher timeframe trend filtering.
________________________________________
👉 In short
This indicator is a signal filter + trend detector. It combines four powerful tools into one scoring system, and only tells you to act when the odds are stacked in your favor.
________________________________________
Bollinger Bands with 4 Moving AveragesCombines Bollinger Bands (BB) with up to four optional Moving Averages (MA) to read volatility, trend direction, and dynamic support–resistance in one overlay.
How It Works
BB: basis = MA(length, type) with standard deviation mult. upper = basis + dev, lower = basis − dev.
MA1–MA4: additional averages you can toggle (default only MA4/200 enabled).
Key Features
Flexible basis MA type for BB: SMA / EMA / RMA (Wilder) / WMA / VWMA.
Four optional MAs with independent length, color, and width (defaults: 7, 25, 99, 200; only 200 on by default).
Offset to shift BB for visual testing.
Overlay on price with shaded band between Upper–Lower.
Inputs & Defaults
BB Length = 20, StdDev = 2.0, Source = close.
Basis MA Type = SMA.
MA4 active (200), MA1–MA3 off (7/25/99 ready).
Offset = 0.
Practical Use
Use BB for volatility context: squeeze → potential breakout; expansion → strong trend.
Treat Basis / Upper / Lower as dynamic levels:
Pullbacks to Basis often become decision zones in trends.
Upper/Lower touches = relative extremes.
Add MA4(200) for primary bias; enable MA1–MA3 for finer timing.
Typical behavior:
Price > MA200 and rising basis → bullish bias; watch pullbacks to basis/MA25-like zones.
Price < MA200 and falling basis → bearish bias; watch rejections at basis/MAs.
Common Signals (not financial advice)
Breakout + BB expansion confirms momentum.
Squeeze + basis break can preface volatility expansion.
Confluence: Lower touch + fast MA in uptrends → mean-reversion setups; inverse for downtrends.
Notes
MA1–MA4 are SMA in the code; BB basis follows the selected MA type.
Test across timeframes; tune length and mult to the asset.
Disclaimer
Visual tool only. Combine with risk management, multi-timeframe confirmation, and a tested plan.
Irrationality Index by CRYPTO_ADA_BTC"The market can be irrational longer than you can stay solvent" ~ John Maynard Keynes
This indicator, the Irrationality Index, measures how far the current market price has deviated from a smoothed estimate of its "fair value," normalized for recent volatility. It provides traders with a visual sense of when the market may be behaving irrationally, without giving direct buy or sell signals.
How it works:
1. Fair Value Calculation
The indicator estimates a "fair value" for the asset using a combination of a long-term EMA (exponential moving average) and a linear regression trend over a configurable period. This fair value serves as a smoothed baseline for price, balancing trend-following and mean-reversion.
2. Volatility-Adjusted Z-Score
The deviation between price and fair value is measured in standard deviations of recent log returns:
Z = (log(price) - log(fairValue)) / volatility
This standardization accounts for different volatility environments, allowing comparison across assets.
3. Irrationality Score (0–100)
The Z-score is transformed using a logistic mapping into a 0–100 scale:
- 50 → price near fair value (rational zone)
- >75 → high irrationality, price stretched above fair value
- >90 → extreme irrationality, unsustainable extremes
- <25 → high irrationality, price stretched below fair value
- <10 → extreme bearish irrationality
4. Price vs Fair Value (% deviation)
The indicator plots the percentage difference between price and fair value:
pctDiff = (price - fairValue) / fairValue * 100
- Positive values → Percentage above fair value (optimistic / overvalued)
- Negative values → Percentage below fair value (pessimistic / undervalued)
Visuals:
- Irrationality (%) Line (0–100) shows irrationality level.
- Background Colors: Yellow= high bullish irrationality, Green= extreme bullish irrationality, Orange= high bearish irrationality, Red= extreme bearish irrationality.
- Price - FairValue (%) plot: price deviation vs fair value (%), Colored green above 0 and red below 0.
- Label: display actual price, estimated fair value, and Z-score for the latest bar.
- Alerts: configurable thresholds for high and extreme irrationality.
How to read it:
- 50 → Market trading near fair value.
- >75 / >90 → Price may be irrationally high; risk of pullback increases.
- <25 / <10 → Price may be irrationally low; potential rebound zones, but trends can continue.
- Price - FairValue (%) plot → visual guide for % price stretch relative to fair value.
Notes / Warnings:
- Measures relative deviation, not fundamental value!
- High irrationality scores do not automatically indicate trades; markets can remain can be irrational longer than you can stay solvent .
- Best used with other tools: momentum, volume, divergence, and multi-timeframe analysis.
Grand Master's Candlestick Dominance (ATR Enhanced)### Grand Master's Candlestick Dominance (ATR Enhanced)
**Overview**
Unleash the ancient wisdom of Japanese candlestick charting with a modern twist! This comprehensive Pine Script v5 strategy and indicator scans for over 75 classic and advanced candlestick patterns (bullish, bearish, and neutral), assigning dynamic strength scores (1-10) to each for precise signal filtering. Enhanced with Average True Range (ATR) for volatility-aware body size validation, it dominates the markets by combining timeless pattern recognition with robust confirmation layers. Whether used as a backtestable strategy or visual indicator, it empowers traders to spot high-probability reversals, continuations, and indecision setups with surgical accuracy.
Inspired by Steve Nison's *Japanese Candlestick Charting Techniques*, this tool elevates pattern analysis beyond basics—think Hammers, Engulfing patterns, Morning Stars, and rare gems like Abandoned Baby or Concealing Baby Swallow—all consolidated into intelligent arrays for real-time averaging and prioritization.
**Key Features**
- **Extensive Pattern Library**:
- **Bullish (25+ patterns)**: Hammer (8.0), Bullish Engulfing (10.0), Morning Star (7.0), Three White Soldiers (9.0), Dragonfly Doji (8.0), and more (e.g., Rising Three, Unique Three River Bottom).
- **Bearish (25+ patterns)**: Hanging Man (8.0), Bearish Engulfing (10.0), Evening Star (7.0), Three Black Crows (9.0), Gravestone Doji (8.0), and exotics like Upside Gap Two Crows or Stalled Pattern.
- **Neutral/Indecision (34+ patterns)**: Doji variants (Long-Legged, Four Price), Spinning Tops, Harami Crosses, and multi-bar setups like Upside Tasuki Gap or Advancing Block.
Each pattern includes duration tracking (1-5 bars) and ATR-adjusted body/shadow criteria for relevance in volatile conditions.
- **Smart Confirmation Filters** (All Toggleable):
- **Trend Alignment**: 20-period SMA (customizable) ensures entries align with the prevailing trend; optional higher timeframe (e.g., Daily) MA crossover for multi-timeframe confluence.
- **Support/Resistance (S/R)**: Pivot-based levels with 0.01% tolerance to confirm bounces or breaks.
- **Volume Surge**: 20-period volume MA with 1.5x spike multiplier to validate momentum.
- **ATR Body Sizing**: Filters small bodies (<0.3x ATR) and long bodies (>0.8x ATR) for context-aware pattern reliability.
- **Follow-Through**: Ensures post-pattern confirmation via bullish/bearish closes or closes beyond prior bars.
Minimum average strength (default 7.0) and individual pattern thresholds (5.0) prevent weak signals.
- **Entry & Exit Logic**:
- **Long Entry**: Bullish average strength ≥7.0 (outweighing bearish), uptrend, volume spike, near support, follow-through, and HTF alignment.
- **Short Entry**: Mirror for bearish dominance in downtrends near resistance.
- **Exits**: Bearish/neutral shift, or fixed TP (5%) / SL (2%)—pyramiding disabled, 10% equity sizing.
- Backtest range: Jan 1, 2020 – Dec 31, 2025 (editable). Initial capital: $10,000.
- **Interactive Dashboard** (Top-Right Panel):
Real-time insights including:
- Market phase (e.g., "Bullish Phase (Avg Str: 8.2)"), active pattern (e.g., "BULLISH: Bullish Engulfing (Str: 10.0, Bars: 2)"), and trend status.
- Strength breakdowns (Bull/Bear/Neutral counts & averages).
- Filter status (e.g., "Volume: ✔ Spike", "ATR: Enabled (L:0.8, S:0.3)").
- Backtest stats: Total trades, win rate, streak, and last entry/exit details (price & timestamp).
Toggle mode: Strategy (live trades) or Indicator (signals only).
- **Advanced Alerts** (15+ Toggleable Types):
Set up via TradingView's "Any alert() function call" for bar-close triggers:
- Entry/Exit signals with strength & pattern details.
- Strong patterns (≥2 bullish/bearish), neutral indecision, volume spikes.
- S/R breakouts, HTF reversals, high-confidence singles (≥8.0 strength).
- Conflicting signals, MA crossovers, ATR volatility bursts, multi-bar completions.
Example: "STRONG BULLISH PATTERN detected! Strength: 9.5 | Top Pattern: Three White Soldiers | Trend: Up".
**Customization & Usage Tips**
- **Inputs Groups**: Strategy toggles, confirmations, exits, backtest dates, and 15+ alert switches—all intuitively grouped.
- **Optimization**: Tune min strengths for aggressive (lower) or conservative (higher) trading; enable/disable filters to suit your style (e.g., disable S/R for scalping).
- **Best For**: Forex, stocks, crypto on 1H–Daily charts. Test on historical data to refine TP/SL.
- **Limitations**: No external data installs; relies on built-in TA functions. Patterns are probabilistic—combine with your risk management.
Master the candles like a grandmaster. Deploy on TradingView, backtest relentlessly, and let dominance begin! Questions? Drop a comment.
*Version: 1.0 | Updated: September 2025 | Credits: Built on Pine Script v5 with nods to Nison's timeless techniques.*
Tape Speed Pulse (Pace + Direction) [v6 + Climax]Tape Speed Pulse (Pace + Direction)
One-liner:
A lightweight “tape pulse” that turns intraday bursts of buying/selling into an easy-to-read histogram, with surge, slowdown, and climax (exhaustion) markers for fast decision-making. Use on sec and min charts.
What it measures
Pace (RVOL): current bar volume vs the recent average (smoothed).
Direction proxy: uptick/downtick by comparing close to close .
Pulse (histogram): direction × pace, so you see who’s pushing and how fast.
Colors
- Lime = Buy surge (pace ≥ threshold & upticking)
- Red = Sell surge (pace ≥ threshold & downticking)
- Teal = Buy pressure, sub-threshold
- Orange = Sell pressure, sub-threshold
- Faded/gray = Near-neutral pace (below the Neutral Band)
Lines (toggleable)
-White = Pace (RVOL)
- Yellow = Slowdown line = a drop of X% from the last 30-bar peak pace
Background tint mirrors the current state so you can glance risk: greenish for buy pressure, reddish for sell pressure.
Signals & alerts
- BUY surge – fires when pace crosses above the surge threshold with uptick direction (optional acceleration & uptick streak filters; cooldown prevents spam).
- SELL surge – mirror logic to downside.
- Slowdown – fires when pace crosses below the yellow slowdown line while direction ≤ 0 (early fade warning).
Climax (exhaustion)
- Buy Climax: previous bar was a buy surge with a large upper wick; current bar slows (below slowdown line) and direction ≤ 0.
- Sell Climax: mirror (large lower wick → slowdown → direction ≥ 0).
- Great for trimming/tight stops or fade setups at obvious spikes.
- Create alerts via Add alert → Condition: this indicator → choose the specific alert (BUY surge, SELL surge, Slowdown, Buy Climax, Sell Climax).
How to use it (playbook)
- Longs (e.g., VWAP reclaim / micro pullback)
- Only take entries when the pulse is teal→lime (buy pressure to buy surge).
- Into prior highs/VWAP bands, take partials on lime spikes.
- If you get a Slowdown dot and bars turn orange/red, tighten or exit.
Shorts (failed reclaim / lower-high)
- Look for teal→orange→red with rising pace at a level.
- Add confidence if a Buy Climax printed right before (exhaustion).
- Risk above the spike; don’t fight true ignitions out of bases.
Simple guardrails
- Avoid new longs when the histogram is orange/red; avoid new shorts when teal/lime.
- Use with VWAP + 9/20 EMA or your levels. The pulse is confirmation, not the whole thesis.
Inputs (what they do & when to tweak)
- Pace lookback (bars) – window for average volume. Lower = faster; higher = steadier.
Too jumpy? raise it. Missing quick bursts? lower it.
- Smoothing EMA (bars) – smooths pace. Higher = calmer.
Use 4–6 during the open; 3–4 midday.
- Surge threshold (× RVOL) – how fast counts as a surge.
Too many surges? raise it. Too late? lower it slightly.
- Slowdown drop from 30-bar max (%) – how far below the recent peak pace to call a slowdown.
Higher % = later slowdown; lower % = earlier warning.
- Neutral band (× RVOL) – paces below this fade to gray.
Raise to clean up noise; lower to see subtle pressure.
- Min seconds between signals – cooldown to prevent spam.
Increase in chop; reduce if you want more pings.
- BUY/SELL: min consecutive upticks/downticks – tiny streak filter.
Raise to avoid wiggles; lower for earlier signals.
Require pace accelerating into signal – ON = avoid stall breakouts; OFF = earlier pings.
Climax options: wick % threshold & “require slowdown cross”.
Raise wick% / require cross to be stricter; lower to catch more fades.
Quick presets
- Low-float runner, 5–10s chart
- Lookback 20, Smoothing 3–4, Surge 2.2–2.8, Slowdown 35–45, Neutral 1.0–1.2, Cooldown 15–25s, Streaks 2–3, Accel ON.
- Thick large-cap, 1-min
- Lookback 20–30, Smoothing 5–7, Surge 1.5–1.9, Slowdown 25–35, Neutral 0.8–1.0, Cooldown 30–60s, Streaks 2, Accel ON.
- Open vs Midday vs Power Hour
- Open: higher Surge, more Smoothing, longer Cooldown.
- Midday: lower Surge, less Smoothing to catch subtler pushes.
- Power hour: moderate Surge; keep Slowdown on for exits.
Reading common patterns
- Ignition (likely continuation): lime spike out of a base that holds above a level while pace stays above yellow.
- Exhaustion (likely fade): lime spike late in a run with upper wick → Slowdown → orange/red. The Buy Climax diamond is your tell.
Limits / notes
This is an OHLCV-based proxy (TradingView Pine can’t read raw tape/DOM). It won’t match Bookmap/Jigsaw tick-for-tick, but it’s fast and objective.
Use with levels and a risk plan. Past performance ≠ future results. Educational only.
HIFI Altcoin Season Index (Total3 vs BTC)This indicator helps you determine whether the crypto market is in an "altcoin season" or a "bitcoin season." It doesn't compare every single altcoin to Bitcoin individually; instead, it uses a more efficient approach.
Methodology
The index calculates the difference in price performance over a selected period (default 90 days) between the total market capitalization of altcoins without Ethereum (TOTAL3) and Bitcoin (BTC).
Interpretation
Value above 75: TOTAL3 is showing significantly stronger growth than BTC, indicating an ALTCOIN SEASON. 🚀
Value below 25: BTC is outperforming TOTAL3, indicating a BITCOIN SEASON. 👑
Value between 25 and 75: The market is in a mixed or neutral phase. 🤷
Benefits
This method avoids the technical limitations of Pine Script when requesting data for a large number of symbols, making the indicator stable and reliable.
Disclaimer: This indicator is a tool for market analysis and should not be considered financial advice.
ATR Future Movement Range Projection
The "ATR Future Movement Range Projection" is a custom TradingView Pine Script indicator designed to forecast potential price ranges for a stock (or any asset) over short-term (1-month) and medium-term (3-month) horizons. It leverages the Average True Range (ATR) as a measure of volatility to estimate how far the price might move, while incorporating recent momentum bias based on the proportion of bullish (green) vs. bearish (red) candles. This creates asymmetric projections: in bullish periods, the upside range is larger than the downside, and vice versa.
The indicator is overlaid on the chart, plotting horizontal lines for the projected high and low prices for both timeframes. Additionally, it displays a small table in the top-right corner summarizing the projected prices and the percentage change required from the current close to reach them. This makes it useful for traders assessing potential targets, risk-reward ratios, or option strategies, as it combines volatility forecasting with directional sentiment.
Key features:
- **Volatility Basis**: Uses weekly ATR to derive a stable daily volatility estimate, avoiding noise from shorter timeframes.
- **Momentum Adjustment**: Analyzes recent candle colors to tilt projections toward the prevailing trend (e.g., more upside if more green candles).
- **Time Horizons**: Fixed at 1 month (21 trading days) and 3 months (63 trading days), assuming ~21 trading days per month (excluding weekends/holidays).
- **User Adjustable**: The ATR length/lookback (default 50) can be tweaked via inputs.
- **Visuals**: Green/lime lines for highs, red/orange for lows; a semi-transparent table for quick reference.
- **Limitations**: This is a probabilistic projection based on historical volatility and momentum—it doesn't predict direction with certainty and assumes volatility persists. It ignores external factors like news, earnings, or market regimes. Best used on daily charts for stocks/ETFs.
The indicator doesn't generate buy/sell signals but helps visualize "expected" ranges, similar to how implied volatility informs option pricing.
### How It Works Step-by-Step
The script executes on each bar update (typically daily timeframe) and follows this logic:
1. **Input Configuration**:
- ATR Length (Lookback): Default 50 bars. This controls both the ATR calculation period and the candle count window. You can adjust it in the indicator settings.
2. **Calculate Weekly ATR**:
- Fetches the ATR from the weekly timeframe using `request.security` with a length of 50 weeks.
- ATR measures average price range (high-low, adjusted for gaps), representing volatility.
3. **Derive Daily ATR**:
- Divides the weekly ATR by 5 (approximating 5 trading days per week) to get an equivalent daily volatility estimate.
- Example: If weekly ATR is $5, daily ATR ≈ $1.
4. **Define Projection Periods**:
- 1 Month: 21 trading days.
- 3 Months: 63 trading days (21 × 3).
- These are hardcoded but based on standard trading calendar assumptions.
5. **Compute Base Projections**:
- Base projection = Daily ATR × Days in period.
- This gives the total expected movement (range) without direction: e.g., for 3 months, $1 daily ATR × 63 = $63 total range.
6. **Analyze Candle Momentum (Win Rate)**:
- Counts green candles (close > open) and red candles (close < open) over the last 50 bars (ignores dojis where close == open).
- Total colored candles = green + red.
- Win rate = green / total colored (as a fraction, e.g., 0.7 for 70%). Defaults to 0.5 if no colored candles.
- This acts as a simple momentum proxy: higher win rate implies bullish bias.
7. **Adjust Projections Asymmetrically**:
- Upside projection = Base projection × Win rate.
- Downside projection = Base projection × (1 - Win rate).
- This skews the range: e.g., 70% win rate means 70% of the total range allocated to upside, 30% to downside.
8. **Calculate Projected Prices**:
- High = Current close + Upside projection.
- Low = Current close - Downside projection.
- Done separately for 1M and 3M.
9. **Plot Lines**:
- 3M High: Solid green line.
- 3M Low: Solid red line.
- 1M High: Dashed lime line.
- 1M Low: Dashed orange line.
- Lines extend horizontally from the current bar onward.
10. **Display Table**:
- A 3-column table (Projection, Price, % Change) in the top-right.
- Rows for 1M High/Low and 3M High/Low, color-coded.
- % Change = ((Projected price - Close) / Close) × 100.
- Updates dynamically with new data.
The entire process repeats on each new bar, so projections evolve as volatility and momentum change.
### Examples
Here are two hypothetical examples using the indicator on a daily chart. Assume it's applied to a stock like AAPL, but with made-up data for illustration. (In TradingView, you'd add the script to see real outputs.)
#### Example 1: Bullish Scenario (High Win Rate)
- Current Close: $150.
- Weekly ATR (50 periods): $10 → Daily ATR: $10 / 5 = $2.
- Last 50 Candles: 35 green, 15 red → Total colored: 50 → Win Rate: 35/50 = 0.7 (70%).
- Base Projections:
- 1M: $2 × 21 = $42.
- 3M: $2 × 63 = $126.
- Adjusted Projections:
- 1M Upside: $42 × 0.7 = $29.4 → High: $150 + $29.4 = $179.4 (+19.6%).
- 1M Downside: $42 × 0.3 = $12.6 → Low: $150 - $12.6 = $137.4 (-8.4%).
- 3M Upside: $126 × 0.7 = $88.2 → High: $150 + $88.2 = $238.2 (+58.8%).
- 3M Downside: $126 × 0.3 = $37.8 → Low: $150 - $37.8 = $112.2 (-25.2%).
- On the Chart: Green/lime lines skewed higher; table shows bullish % changes (e.g., +58.8% for 3M high).
- Interpretation: Suggests stronger potential upside due to recent bullish momentum; useful for call options or long positions.
#### Example 2: Bearish Scenario (Low Win Rate)
- Current Close: $50.
- Weekly ATR (50 periods): $3 → Daily ATR: $3 / 5 = $0.6.
- Last 50 Candles: 20 green, 30 red → Total colored: 50 → Win Rate: 20/50 = 0.4 (40%).
- Base Projections:
- 1M: $0.6 × 21 = $12.6.
- 3M: $0.6 × 63 = $37.8.
- Adjusted Projections:
- 1M Upside: $12.6 × 0.4 = $5.04 → High: $50 + $5.04 = $55.04 (+10.1%).
- 1M Downside: $12.6 × 0.6 = $7.56 → Low: $50 - $7.56 = $42.44 (-15.1%).
- 3M Upside: $37.8 × 0.4 = $15.12 → High: $50 + $15.12 = $65.12 (+30.2%).
- 3M Downside: $37.8 × 0.6 = $22.68 → Low: $50 - $22.68 = $27.32 (-45.4%).
- On the Chart: Red/orange lines skewed lower; table highlights larger downside % (e.g., -45.4% for 3M low).
- Interpretation: Indicates bearish risk; might prompt protective puts or short strategies.
#### Example 3: Neutral Scenario (Balanced Win Rate)
- Current Close: $100.
- Weekly ATR: $5 → Daily ATR: $1.
- Last 50 Candles: 25 green, 25 red → Win Rate: 0.5 (50%).
- Projections become symmetric:
- 1M: Base $21 → Upside/Downside $10.5 each → High $110.5 (+10.5%), Low $89.5 (-10.5%).
- 3M: Base $63 → Upside/Downside $31.5 each → High $131.5 (+31.5%), Low $68.5 (-31.5%).
- Interpretation: Pure volatility-based range, no directional bias—ideal for straddle options or range trading.
In real use, test on historical data: e.g., if past projections captured actual moves ~68% of the time (1 standard deviation for ATR), it validates the volatility assumption. Adjust the lookback for different assets (shorter for volatile cryptos, longer for stable blue-chips).
BTC/USD 3-Min Binary Prediction [v7.2 EN]BTC/USD 3-Minute Binary Prediction Indicator v7.2 - Complete Guide
Overview
This is an advanced technical analysis indicator designed for Bitcoin/USD binary options trading with 3-minute expiration times. The system aims for an 83% win rate by combining multiple analysis layers and pattern recognition.
How It Works
Core Prediction Logic
- Timeframe: Predicts whether BTC price will be ±$25 higher (HIGH) or lower (LOW) after 3 minutes
- Entry Signals: Generates HIGH/LOW signals when confidence exceeds threshold (default 75%)
- Verification: Automatically tracks and displays win/loss statistics in real-time
5-Layer Filter System
The indicator uses a sophisticated scoring system (0-100 points):
1. Trend Filter (25 points) - Analyzes EMA alignments and price momentum
2. Leading Indicators (25 points) - RSI and MACD divergence analysis
3. Volume Confirmation (20 points) - Detects unusual volume patterns
4. Support/Resistance (15 points) - Identifies key price levels
5. Momentum Alignment (15 points) - Measures acceleration and deceleration
Pattern Recognition
Automatically detects and visualizes:
- Double Tops/Bottoms - Reversal patterns
- Triangles - Ascending, descending, symmetrical
- Channels - Trending price channels
- Candlestick Patterns - Engulfing, hammer, hanging man
Multi-Timeframe Analysis
- Uses 1-minute and 5-minute data for confirmation
- Aligns multiple timeframes for higher probability trades
- Monitors trend consistency across timeframes
Key Features
Display Panels
1. Statistics Panel (Top Right)
- Overall win rate percentage
- Hourly performance (wins/losses)
- Daily performance
- Current system status
2. Analysis Panel (Left Side)
- Market trend analysis
- RSI status (overbought/oversold)
- Volume conditions
- Filter scores for each component
- Final HIGH/LOW/WAIT decision
Visual Signals
- Green Triangle (↑) = HIGH prediction
- Red Triangle (↓) = LOW prediction
- Yellow Background = Entry opportunity
- Blue Background = Waiting for result
Configuration Options
Basic Settings
- Range Width: Target price movement (default $50 = ±$25)
- Min Confidence: Minimum confidence to enter (default 75%)
- Max Daily Trades: Risk management limit (default 5)
Filters (Can be toggled on/off)
- Trend Filter
- Volume Confirmation
- Support/Resistance Filter
- Momentum Alignment
Display Options
- Show/hide signals, statistics, analysis
- Minimal Mode for cleaner charts
- EMA line visibility
Important Risk Warnings
Binary Options Trading Risks:
1. High Risk Product - Binary options are extremely risky and banned in many countries
2. Not Investment Advice - This tool is for educational/analytical purposes only
3. No Guaranteed Returns - Past performance doesn't predict future results
4. Capital at Risk - You can lose your entire investment in seconds
Technical Limitations:
- Requires stable internet connection
- Performance varies with market conditions
- High volatility can reduce accuracy
- Not suitable for news events or low liquidity periods
Best Practices
1. Paper Trade First - Test thoroughly on demo accounts
2. Risk Management - Never risk more than 1-2% per trade
3. Market Conditions - Works best in normal volatility conditions
4. Avoid Major Events - Don't trade during major news releases
5. Monitor Performance - Track your actual results vs displayed statistics
Setup Instructions
1. Add to TradingView chart (BTC/USD preferred)
2. Use 30-second or 1-minute chart timeframe
3. Adjust settings based on your risk tolerance
4. Monitor F-Score (should be >65 for entries)
5. Wait for clear HIGH/LOW signals with high confidence
Alert Configuration
The indicator provides three alert types:
- HIGH Signal alerts
- LOW Signal alerts
- General entry opportunity alerts
Legal Disclaimer
Binary options trading may not be legal in your jurisdiction. Many countries including the USA, Canada, and EU nations have restrictions or outright bans on binary options. Always check local regulations and consult with financial advisors before trading.
Remember: This is a technical analysis tool, not a money-printing machine. Successful trading requires discipline, risk management, and continuous learning. The displayed statistics are historical and don't guarantee future performance.
Weekly pecentage tracker by PRIVATE
Settings Picture below this link: 👇
i.ibb.co
What it is
A lightweight “Weekly % Tracker” overlay that lets you manually enter weekly performance (in percent) for XAUUSD + up to 10 FX pairs, then shows:
a small table panel with each enabled symbol and its % result
one TOTAL row (Sum / Average / Compounded across all enabled symbols)
an optional mini badge showing the % for a single selected symbol
Nothing is auto-calculated from price—you type the % yourself.
Key settings
Panel: show/hide, position, number of decimals, colors (background, text, green/red).
Total mode:
Sum – adds percentages
Average – mean of enabled rows
Compounded –
(
∏
(
1
+
𝑝
/
100
)
−
1
)
×
100
(∏(1+p/100)−1)×100
Symbols:
XAUUSD (toggle + label + % input)
10 FX pairs (each has On/Off, label text, % input). You can rename labels to any symbol text you want.
Mini badge: show/hide, position, and symbol to display.
How it works
Overlay indicator: overlay=true; just draws UI on the chart (no plots).
Arrays (syms, vals, ons) collect the row data in order: XAU first, then FX1…FX10.
Helpers:
posFrom() converts a position string (e.g., “Top Right”) into a position.* constant.
wp_col() picks green/red/neutral based on the sign of the %.
wp_round() rounds values to the selected decimals.
calc_total() computes the TOTAL with the chosen mode over enabled rows only.
Table creation logic:
Counts how many rows are enabled.
If none enabled or panel is off: the panel table is deleted, so no box/background is visible.
If enabled and on: the panel is (re)created at the chosen position.
On each last bar (barstate.islast), it clears the table to transparent (bgcolor=na) and then fills one row per enabled symbol, followed by a single TOTAL row.
Mini badge:
Always (re)created on position change.
Shows selected symbol’s % (or “-” if that symbol isn’t enabled or has no value).
Colors text green/red by sign.
Notes & limits
It’s manual input—the script doesn’t read trades or P/L from price.
You can rename each row’s label to match any symbol name you want.
When no rows are enabled, the panel disappears entirely (no empty background).
Designed to be light: only draws tables; no heavy plotting.
If you want the TOTAL row to be optional, or different color thresholds, or CSV-style export/import of the values, say the word and I’ll add it.
Inside Candle DivergenceStudy Material: Inside Candle Divergence Indicator (aiTrendview)
1. Introduction
The Inside Candle Divergence Indicator is a custom tool built on TradingView using Pine Script. It is designed to help traders identify potential reversal points or trend continuations using a mix of candlestick analysis, RSI (Relative Strength Index), VWAP (Volume Weighted Average Price), Pivot Points, and Volume analytics. The tool also provides a dashboard table on the chart, summarizing all key values in a single glance for traders and analysts.
This indicator is not just a signal generator but also an educational framework—explaining how different concepts in technical analysis combine to build a systematic approach for market entries and exits.
________________________________________
2. Core Concepts Behind the Tool
A. Inside Candle Pattern
An Inside Candle forms when the current candle’s high is lower than or equal to the previous candle’s high, and the low is higher than or equal to the previous candle’s low.
• This means the entire price action of the current candle is "inside" the range of the previous candle.
• A bullish inside candle occurs when the close is higher than the open.
• A bearish inside candle occurs when the close is lower than the open.
This pattern shows market indecision but also sets up potential breakouts or trend reversals.
________________________________________
B. RSI (Relative Strength Index)
The indicator calculates RSI using the formula from the ta.rsi() function in TradingView. RSI helps measure momentum in the market.
• A low RSI (below 25) signals an oversold zone → possible buy.
• A high RSI (above 75) signals an overbought zone → possible sell.
By combining RSI with the Inside Candle, the indicator ensures that signals are triggered only when momentum and price patterns confirm each other.
________________________________________
C. Buy & Sell Signals
• Buy Signal: Triggered when RSI < Buy Level (default 25) and a bullish inside candle forms.
• Sell Signal: Triggered when RSI > Sell Level (default 75) and a bearish inside candle forms.
When triggered, the chart displays a BUY (green label below candle) or SELL (red label above candle) marker. The indicator also saves the entry price and signal bar for future reference inside the dashboard.
________________________________________
D. VWAP (Volume Weighted Average Price)
VWAP is calculated using the typical price (H+L+C)/3 and weighting it by volume.
• VWAP shows the average trading price weighted by volume, widely used by institutions.
• The tool calculates the distance of price from VWAP in % terms.
• If price is far above VWAP, the market may be overheated (overbought). If far below, it may be undervalued (oversold).
________________________________________
E. Volume Analysis
The tool splits volume into Buy Volume and Sell Volume:
• Buy Volume: If close > open.
• Sell Volume: If close ≤ open.
• Cumulative totals are maintained, and percentages are calculated to show what proportion of total market volume is bullish vs bearish.
• A progress bar style visual (using blocks █) shows the dominance of buyers or sellers.
This allows traders to quickly measure whether buyers or sellers are controlling the market trend.
________________________________________
F. Daily Pivot Points
Pivot Points are calculated using the previous day’s high, low, and close:
• Pivot = (High + Low + Close) / 3
• R1, S1, R2, S2, R3, S3 levels are derived from this pivot.
• These levels act as support and resistance zones.
The script plots Pivot, R1, and S1 lines on the chart for easy reference.
________________________________________
G. Trend Direction
The indicator checks where the price is compared to R1 and S1:
• If price > R1 → Bullish Trend
• If price < S1 → Bearish Trend
• Otherwise → Neutral Trend
The trend direction is displayed in the dashboard with arrows (↑, ↓, →).
________________________________________
H. Price Change Calculation
The tool calculates:
• Price Change = Current Close – Previous Close
• Percentage Change = (Change / Previous Close) × 100
• Displays ▲ (green upward) or ▼ (red downward) with the exact percentage.
This gives traders a quick snapshot of intraday price movement.
________________________________________
I. Dashboard Table
One of the most powerful features is the real-time dashboard table shown on the chart. It contains:
1. Symbol & Price Info (Current ticker, price, change %)
2. RSI Reading (with color coding: green for oversold, red for overbought)
3. VWAP and Distance from VWAP
4. Volume Analysis with Progress Bar (Buy vs Sell %)
5. Pivot Levels (Pivot, R1, S1)
6. Trend Direction (Bullish, Bearish, Neutral)
7. Signal Status (Last Buy/Sell signal with entry price)
This reduces the need for multiple indicators and gives traders a command-center view directly on the chart.
________________________________________
J. Alerts
The tool generates alerts whenever a Buy or Sell condition is met. Traders can set up TradingView alerts to be notified instantly when:
• Buy Signal Alert → RSI oversold + Bullish inside candle
• Sell Signal Alert → RSI overbought + Bearish inside candle
This ensures no opportunity is missed even if you’re not actively monitoring the chart.
________________________________________
K. Background Highlights
The chart background also changes faintly (light green or light red) when a Buy or Sell condition is triggered. This gives traders visual confirmation along with signals and alerts.
________________________________________
3. Practical Use of This Tool
• Scalpers & Intraday Traders can use it for quick momentum-based entries.
• Swing Traders can use the RSI + Inside Candle + Pivot Points to find medium-term reversals.
• Analysts can use the dashboard for real-time summaries in reports.
• Volume Analysis helps understand institutional activity.
Remember: This is not a standalone holy grail. It must be used with proper risk management and confirmation from higher timeframes.
________________________________________
4. Strict Disclaimer (aiTrendview)
⚠️ Disclaimer from aiTrendview:
This indicator is designed for educational and analytical purposes only. It is not financial advice or a guaranteed trading strategy. Markets are inherently risky and unpredictable; past performance of indicators does not ensure future results. Trading involves risk of financial loss, and traders must use proper risk management, stop-loss, and independent judgment.
aiTrendview strictly follows TradingView.com rules and compliance guidelines.
Any misuse of this tool, its code, or analytical features for unauthorized commercial purposes, false promises, or misleading activities is strictly discouraged. The creators of this script and aiTrendview will not be responsible for any losses, damages, or misuse arising from its application. Always trade responsibly and only with money you can afford to lose.
________________________________________
ST-Stochastic DashboardST-Stochastic Dashboard: User Manual & Functionality
1. Introduction
The ST-Stochastic Dashboard is a comprehensive tool designed for traders who utilize the Stochastic Oscillator. It combines two key features into a single indicator:
A standard, fully customizable Stochastic Oscillator plotted directly on your chart.
A powerful Multi-Timeframe (MTF) Dashboard that shows the status of the Stochastic %K value across three different timeframes of your choice.
This allows you to analyze momentum on your current timeframe while simultaneously monitoring for confluence or divergence on higher or lower timeframes, all without leaving your chart.
Disclaimer: In accordance with TradingView's House Rules, this document describes the technical functionality of the indicator. It is not financial advice. The indicator provides data based on user-defined parameters; all trading decisions are the sole responsibility of the user. Past performance is not indicative of future results.
2. How It Works (Functionality)
The indicator is divided into two main components:
A. The Main Stochastic Indicator (Chart Pane)
This is the visual representation of the Stochastic Oscillator for the chart's current timeframe.
%K Line (Blue): This is the main line of the oscillator. It shows the current closing price in relation to the high-low range over a user-defined period. A high value means the price is closing near the top of its recent range; a low value means it's closing near the bottom.
%D Line (Black): This is the signal line, which is a moving average of the %K line. It is used to smooth out the %K line and generate trading signals.
Overbought Zone (Red Area): By default, this zone is above the 75 level. When the Stochastic lines are in this area, it indicates that the asset may be "overbought," meaning the price is trading near the peak of its recent price range.
Oversold Zone (Blue Area): By default, this zone is below the 25 level. When the Stochastic lines are in this area, it indicates that the asset may be "oversold," meaning the price is trading near the bottom of its recent price range.
Crossover Signals:
Buy Signal (Blue Up Triangle): A blue triangle appears below the candles when the %K line crosses above the Oversold line (e.g., from 24 to 26). This suggests a potential shift from bearish to bullish momentum.
Sell Signal (Red Down Triangle): A red triangle appears above the candles when the %K line crosses below the Overbought line (e.g., from 76 to 74). This suggests a potential shift from bullish to bearish momentum.
B. The Multi-Timeframe Dashboard (Table on Chart)
This is the informational table that appears on your chart. Its purpose is to give you a quick, at-a-glance summary of the Stochastic's condition on other timeframes.
Function: The script uses TradingView's request.security() function to pull the %K value from three other timeframes that you specify in the settings.
Efficiency: The table is designed to update only on the last (most recent) bar (barstate.islast) to ensure the script runs efficiently and does not slow down your chart.
Columns:
Timeframe: Displays the timeframe you have selected (e.g., '5', '15', '60').
Stoch %K: Shows the current numerical value of the %K line for that specific timeframe, rounded to two decimal places.
Status: Interprets the %K value and displays a clear status:
OVERBOUGHT (Red Background): The %K value is above the "Upper Line" setting.
OVERSOLD (Blue Background): The %K value is below the "Lower Line" setting.
NEUTRAL (Black/Dark Background): The %K value is between the Overbought and Oversold levels.
3. Settings / Parameters in Detail
You can access these settings by clicking the "Settings" (cogwheel) icon on the indicator name.
Stochastic Settings
This group controls the behavior and appearance of the main Stochastic indicator plotted in the pane.
Stochastic Period (length)
Description: This is the lookback period used to calculate the Stochastic Oscillator. It defines the number of past bars to consider for the high-low range.
Default: 9
%K Smoothing (smoothK)
Description: This is the moving average period used to smooth the raw Stochastic value, creating the %K line. A higher value results in a smoother, less sensitive line.
Default: 3
%D Smoothing (smoothD)
Description: This is the moving average period applied to the %K line to create the %D (signal) line. A higher value creates a smoother signal line that lags further behind the %K line.
Default: 6
Lower Line (Oversold) (ul)
Description: This sets the threshold for the oversold condition. When the %K line is below this value, the dashboard will show "OVERSOLD". It is also the level the %K line must cross above to trigger a Buy Signal triangle.
Default: 25
Upper Line (Overbought) (ll)
Description: This sets the threshold for the overbought condition. When the %K line is above this value, the dashboard will show "OVERBOUGHT". It is also the level the %K line must cross below to trigger a Sell Signal triangle.
Default: 75
Dashboard Settings
This group controls the data and appearance of the multi-timeframe table.
Timeframe 1 (tf1)
Description: The first timeframe to be displayed in the dashboard.
Default: 5 (5 minutes)
Timeframe 2 (tf2)
Description: The second timeframe to be displayed in the dashboard.
Default: 15 (15 minutes)
Timeframe 3 (tf3)
Description: The third timeframe to be displayed in the dashboard.
Default: 60 (1 hour)
Dashboard Position (table_pos)
Description: Allows you to select where the dashboard table will appear on your chart.
Options: top_right, top_left, bottom_right, bottom_left
Default: bottom_right
4. How to Use & Interpret
Configuration: Adjust the Stochastic Settings to match your trading strategy. The default values (9, 3, 6) are common, but feel free to experiment. Set the Dashboard Settings to the timeframes that are most relevant to your analysis (e.g., your entry timeframe, a medium-term timeframe, and a long-term trend timeframe).
Analysis with the Dashboard: The primary strength of this tool is confluence. Look for situations where multiple timeframes align. For example:
If the dashboard shows OVERSOLD on the 15-minute, 60-minute, and your current 5-minute chart, a subsequent Buy Signal on your 5-minute chart may carry more weight.
Conversely, if your 5-minute chart shows OVERSOLD but the 60-minute chart is strongly OVERBOUGHT, it could indicate that you are looking at a minor pullback in a larger downtrend.
Interpreting States:
Overbought is not an automatic "sell" signal. It simply means momentum has been strong to the upside, and the price is near its recent peak. It could signal a potential reversal, but the price can also remain overbought for extended periods in a strong uptrend.
Oversold is not an automatic "buy" signal. It means momentum has been strong to the downside. While it can signal a potential bounce, prices can remain oversold for a long time in a strong downtrend.
Use the signals and dashboard states as a source of information to complement your overall trading strategy, which should include other forms of analysis such as price action, support/resistance levels, or other indicators.
[blackcat] L1 Value Trend IndicatorOVERVIEW
The L1 Value Trend Indicator is a sophisticated technical analysis tool designed for TradingView users seeking advanced market trend identification and trading signals. This comprehensive indicator combines multiple analytical techniques to provide traders with a holistic view of market dynamics, helping identify potential entry and exit points through various signal mechanisms. 📈 It features a main Value Trend line along with a lagged version, golden cross and dead cross signals, and multiple technical indicators including RSI, Williams %R, Stochastic %K/D, and Relative Strength calculations. The indicator also includes reference levels for support and resistance analysis, making it a versatile tool for both short-term and long-term trading strategies. ✅
FEATURES
📈 Primary Value Trend Line: Calculates a smoothed value trend using a combination of SMA and custom smoothing techniques
🔍 Value Trend Lag: Implements a lagged version of the main trend line for cross-over analysis
🚀 Golden Cross & Dead Cross Signals: Identifies buy/sell opportunities when the main trend line crosses its lagged version
💸 Multi-Indicator Integration: Combines multiple technical analysis tools for comprehensive market view
📊 RSI Calculations: Includes 6-period, 7-period, and 13-period RSI calculations for momentum analysis
📈 Williams %R: Provides overbought/oversold conditions using the Williams %R formula
📉 Stochastic Oscillator: Implements both Stochastic %K and %D calculations for momentum confirmation
📋 Relative Strength: Calculates relative strength based on highest highs and current price
✅ Visual Labels: Displays BUY and SELL labels on chart when crossover conditions are met
📣 Alert Conditions: Provides automated alert conditions for golden cross and dead cross events
📌 Reference Levels: Plots entry (25) and exit (75) reference lines for support/resistance analysis
HOW TO USE
Copy the Script: Copy the complete Pine Script code from the original file
Open TradingView: Navigate to TradingView website or application
Access Pine Editor: Go to the Pine Script editor (usually found in the chart toolbar)
Paste Code: Paste the copied script into the editor
Save Script: Save the script with a descriptive name like " L1 Value Trend Indicator"
Select Chart: Choose the chart where you want to apply the indicator
Add Indicator: Apply the indicator to your chart
Configure Parameters: Adjust input parameters to customize behavior
Monitor Signals: Watch for golden cross (BUY) and dead cross (SELL) signals
Use Reference Levels: Monitor entry (25) and exit (75) lines for support/resistance levels
LIMITATIONS
⚠️ Potential Repainting: The script may repaint due to lookahead bias in some calculations
📉 Lookahead Bias: Some calculations may reference future values, potentially causing repainting issues
🔄 Parameter Sensitivity: Results may vary significantly with different parameter settings
📉 Computational Complexity: May impact chart performance with heavy calculations on large datasets
📊 Resource Usage: Requires significant processing power for multiple indicator calculations
🔄 Data Sensitivity: Results may be affected by data quality and market conditions
NOTES
📈 Signal Timing: Cross-over signals may lag behind actual price movements
📉 Parameter Optimization: Optimal parameters may vary by market conditions and asset type
📋 Market Conditions: Performance may vary significantly across different market environments
📈 Multi-Indicator: Combine signals with other technical indicators for confirmation
📉 Timeframe Analysis: Use multiple timeframes for enhanced signal accuracy
📋 Volume Analysis: Incorporate volume data for additional confirmation
📈 Strategy Integration: Consider using this indicator as part of a broader trading strategy
📉 Risk Management: Use signals as part of a comprehensive risk management approach
📋 Backtesting: Test parameter combinations with historical data before live trading
THANKS
🙏 Original Creator: blackcat1402 creates the L1 Value Trend Indicator
📚 Community Contributions: Recognition to TradingView community for continuous improvements and contributions
📈 Collaborative Development: Appreciation for collaborative efforts in enhancing technical analysis tools
📉 TradingView Community: Special thanks to TradingView community members for their ongoing support and feedback
📋 Educational Resources: Recognition of educational resources that helped in understanding technical analysis principles
Advanced Price Ranges ICTThis indicator automatically divides price into fixed ranges (configurable in points or pips) and plots important reference levels such as the high, low, 50% midpoint, and 25%/75% quarters. It is designed to help traders visualize structured price movement, spot confluence zones, and frame their trading bias around clean range-based levels.
🔹 Key Features
Custom Range Size: Define ranges in points (e.g., 100, 50, 25, 10) or in Forex pips.
Forex Mode: Automatically adapts pip size (0.0001 or 0.01 for JPY pairs).
Dynamic Anchoring: Price ranges automatically align to the current price, snapping into blocks.
Multiple Ranges: Option to extend visualization above and below the current active block for a complete grid.
Level Types:
High / Low of the range
50% midpoint
25% and 75% quarters
Custom Styling: Adjustable line colors and widths for each level type.
Labels: Optional right-edge labels showing level type and exact price.
Alerts: Built-in alerts for when price crosses the range high, low, or 50% midpoint.
🔹 Use Cases
Quickly map out 100/50/25/10 point structures like Zeussy’s advanced price range method.
Identify key reaction levels where liquidity is often built or swept.
Support ICT-style concepts like range-based bias, fair value gaps, and liquidity pools.
Works for indices, futures, crypto, and forex.
🔹 Customization
Range increments can be set to any size (default 100).
Toggle which levels are shown (High/Low, Midpoint, Quarters).
Adjustable line widths, colors, and label visibility.
Extend ranges above and below for broader market context.
SHHHHHHH“Round Numbers — 100/50/25”
lines… endless lines… they whisper in 25s, scream in 50s, collapse in 100s.
price dances on the grid, you don’t trade it, it trades you.
blue for the void. orange for the in-between. green for the fracture.
extend both. never stop. above and below. above and below.
do not ask why 25. do not ask why 50. the 100s already know.
quarter. half. whole. repeat until delirium.
add it to chart → stare too long → numbers start staring back.
T-Virus Sentiment [hapharmonic]🧬 T-Virus Sentiment: Visualize the Market's DNA
Remember the iconic T-Virus vial from the first Resident Evil? That powerful, swirling helix of potential has always fascinated me. It sparked an idea: what if we could visualize the market's underlying health in a similar way? What if we could capture the "genetic code" of market sentiment and contain it within a dynamic, 3D indicator? This project is the result of that idea, brought to life with Pine Script.
The indicator's main goal is to measure the strength and direction of market sentiment by analyzing the "genetic code" of price action through a variety of trusted indicators. The result is displayed as a liquid level within a DNA helix, a bubble density representing buying pressure, and a T-Virus mascot that reflects the overall mood.
🧐 Core Concept: How It Works
The primary output of the indicator is the "Active %" gauge you see on the right side of the vial. This percentage represents the overall sentiment score, calculated as an average from 7 different technical analysis tools. Each tool is analyzed on every bar and assigned a score from 1 (strong bearish pressure) to 5 (strong bullish potential).
In this indicator, we re-imagine market dynamics through the lens of a viral outbreak. A strong bear market is like a virus taking hold, pulling all technical signals down into a state of weakness. Conversely, a powerful bull market is like an antiviral serum ; positive signals rise and spread toward the top of the vial, indicating that the system is being injected with strength.
This is not just another line on a chart. It's a comprehensive sentiment dashboard designed to give an immediate, at-a-glance understanding of the confluence between 7 classic technical indicators. The incredible 3D model of the vial itself was inspired by a design concept found here .
⚛️ The 4 Core Elements of T-Virus Sentiment
These four elements work in harmony to give a complete, multi-faceted picture of market sentiment. Each component tells a different part of the story.
The Virus Mascot: An instant emotional cue. This character provides the quickest possible read on the overall market mood, combining sentiment with volume pressure.
The Antiviral Serum Level: The main quantitative output. This is the liquid level in the DNA helix and the percentage gauge on the right, representing the average sentiment score from all 7 indicators.
Buy Pressure & Bubble Density: This visualizes volume flow. The density of bubbles represents the intensity of accumulation (buying) versus distribution (selling). It's the "power" behind the move.
The Signal Distribution: This shows the confluence (or dispersion) of sentiment. Are all signals bullish and clustered at the top, or are they scattered, indicating a conflicted market? The position of the indicator labels is crucial, as each is assigned to one of five distinct zones:
Base Bottom: The market is at its weakest. Signals here suggest strong bearish control and distribution.
Lower Zone: The market is still bearish, but signals may be showing early signs of accumulation or bottoming.
Neutral Core (Center): A state of balance or sideways consolidation. The market is waiting for a new direction.
Upper Zone: Bullish momentum is becoming clear. Signals are strengthening and showing bullish control.
Top Cap: The market is "heating up" with strong bullish sentiment, potentially nearing overbought conditions.
🐂🐻 The Virus Mascot: The At-a-Glance Indicator
This character acts as a shortcut to confirm market health. It combines the sentiment score with volume, preventing false confidence in a low-volume rally.
Its state is determined by a dual-check: the overall "Antiviral Serum Level" and the "Buy Pressure" must both be above 50%.
Green & Smiling: The 'all clear' signal. This means that not only is the overall technical sentiment bullish, but it's also being supported by real buying pressure. This is a sign of a healthy bull market.
Red & Angry: A warning sign. This appears if either the sentiment is weak, or a bullish sentiment is not being confirmed by buying volume. The latter could indicate a potential "bull trap" or an exhaustive move.
This mascot can be disabled from the settings page under "Virus Mascot Styling" if a cleaner look is preferred.
🫧 Bubble Density: Gauging Buy vs. Sell Pressure
The bubbles visualize the battle between buyers and sellers. There are two modes to control how this is calculated:
Mode 1: Visible Range (The 'Big Picture' View)
This default mode is best for getting a broad, contextual understanding of the current session. It dynamically analyzes the volume of every single candlestick currently visible on the screen to calculate the buy/sell pressure ratio. It answers the question: "Over the entire period I'm looking at, who is in control?" As you zoom in or out, the calculation adapts.
Mode 2: Custom Lookback (The 'Precision' View)
This mode is for traders who need to analyze short-term pressure. You can define a fixed number of recent bars to analyze, which is perfect for scalping or understanding the volume dynamics leading into a key level. It answers the question: "What is happening right now ?" In the example above, a lookback of 2 focuses only on the most recent action, clearly showing intense, immediate selling pressure (few bubbles) and a corresponding drop in the sentiment score to 29%.
ℹ️ Interactive Tooltips: Dive Deeper
We believe in transparency, not 'black box' indicators. This feature transforms the indicator from a visual aid into an active learning tool.
Simply hover the mouse over any indicator label (like EMA, OBV, etc.) to get a detailed tooltip. It will explain the specific data points and thresholds that signal met to be placed in its current zone. This helps build trust in the signals and allows users to fine-tune the indicator settings to better match their own trading style.
🎯 The Scoring Logic Breakdown
The "Antiviral Serum Level" gauge is the average score from 7 technical analysis tools. Each is graded on a 5-point scale (1=Strong Bearish to 5=Strong Bullish). Here’s a detailed, transparent look at how each "gene" is evaluated:
Relative Strength Index (RSI)
Measures momentum and overbought/oversold conditions.
Group 1 (Strong Bearish): RSI > 80 (Extreme Overbought)
Group 2 (Bearish): 70 < RSI ≤ 80 (Overbought)
Group 3 (Neutral): 30 ≤ RSI ≤ 70
Group 4 (Bullish): 20 ≤ RSI < 30 (Oversold)
Group 5 (Strong Bullish): RSI < 20 (Extreme Oversold)
Exponential Moving Averages (EMA)
Evaluates the trend's strength and structure based on the alignment of multiple EMAs (9, 21, 50, 100, 200, 250).
Group 1 (Strong Bearish): A perfect bearish sequence (9 < 21 < 50 < ...)
Group 2 (Bearish Transition): Early signs of a potential reversal (e.g., 9 > 21 but still below 50)
Group 3 (Neutral / Mixed): MAs are intertwined or showing a partial bullish sequence.
Group 4 (Bullish): A strong bullish sequence is forming (e.g., 9 > 21 > 50 > 100)
Group 5 (Strong Bullish): A perfect bullish sequence (9 > 21 > 50 > 100 > 200 > 250)
Moving Average Convergence Divergence (MACD)
Analyzes the relationship between two moving averages to gauge momentum.
Group 1 (Strong Bearish): MACD & Histogram are negative and momentum is falling.
Group 2 (Weakening Bearish): MACD is negative but the histogram is rising or positive.
Group 3 (Neutral / Crossover): A crossover event is occurring near the zero line.
Group 4 (Bullish): MACD & Histogram are positive.
Group 5 (Strong Bullish): MACD & Histogram are positive, rising strongly, and accelerating.
Average Directional Index (ADX)
Measures trend strength, not direction. The score is based on both ADX value and the dominance of DI+ vs DI-.
Group 1 (Bearish / No Trend): ADX < 20 and DI- is dominant.
Group 2 (Developing Bearish Trend): 20 ≤ ADX < 25 and DI- is dominant.
Group 3 (Neutral / Indecision): Trend is weak or DI+ and DI- are nearly equal.
Group 4 (Developing Bullish Trend): 25 ≤ ADX ≤ 40 and DI+ is dominant.
Group 5 (Strong Bullish Trend): ADX > 40 and DI+ is dominant.
Ichimoku Cloud (IKH)
A comprehensive indicator that defines support/resistance, momentum, and trend direction.
Group 1 (Strong Bearish): Price is below the Kumo, Tenkan < Kijun, and Chikou is below price.
Group 2 (Bearish): Price is inside or below the Kumo, with mixed secondary signals.
Group 3 (Neutral / Ranging): Price is inside the Kumo, often with a Tenkan/Kijun cross.
Group 4 (Bullish): Price is above the Kumo with strong primary signals.
Group 5 (Strong Bullish): All signals are aligned bullishly: price above Kumo, bullish Tenkan/Kijun cross, bullish future Kumo, and Chikou above price.
Bollinger Bands (BB)
Measures volatility and relative price levels.
Group 1 (Strong Bearish): Price is below the lower band.
Group 2 (Bearish Territory): Price is between the lower band and the basis line.
Group 3 (Neutral): Price is hovering around the basis line.
Group 4 (Bullish Territory): Price is between the basis line and the upper band.
Group 5 (Strong Bullish): Price is above the upper band.
On-Balance Volume (OBV)
Uses volume flow to predict price changes. The score is based on OBV's trend and its position relative to its moving average.
Group 1 (Strong Bearish): OBV is below its MA and falling.
Group 2 (Weakening Bearish): OBV is below its MA but showing signs of rising.
Group 3 (Neutral): OBV is very close to its MA.
Group 4 (Bullish): OBV is above its MA and rising.
Group 5 (Strong Bullish): OBV is above its MA, rising strongly, and showing signs of a volume spike.
🧭 How to Use the T-Virus Sentiment Indicator
IMPORTANT: This indicator is a sentiment dashboard , not a direct buy/sell signal generator. Its strength lies in showing confluence and providing a quick, holistic view of the market's technical health.
Confirmation Tool: Use the "Active %" gauge to confirm a trade setup from your primary strategy. For example, if you see a bullish chart pattern, a high and rising sentiment score can add confidence to your trade.
Momentum & Trend Gauge: A consistently high score (e.g., > 75%) suggests strong, established bullish momentum. A consistently low score (< 25%) suggests strong bearish control. A score hovering around 50% often indicates a ranging or indecisive market.
Divergence & Warning System: Pay attention to divergences. If the price is making new highs but the sentiment score is failing to follow or is actively decreasing, it could be an early warning sign that the underlying momentum is weakening.
⚙️ Settings & Customization
The indicator is highly customizable to fit any trading style.
Position & Anchor: Control where the vial appears on the chart.
Styling (Vial, Helix, etc.): Nearly every visual element can be color-customized.
Signals: This is where the real power is. All underlying indicator parameters (RSI length, MACD settings, etc.) can be fine-tuned to match a personal strategy. The text labels can also be disabled if the chart feels cluttered.
Enjoy visualizing the market's DNA with the T-Virus Sentiment indicator
VWAP For Loop [BackQuant]VWAP For Loop
What this tool does—in one sentence
A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts.
Plain-English overview
Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context.
Under the hood
• Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls:
Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year.
• For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP .
– If VWAP > VWAP , add +1.
– Else, add −1.
The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45.
• Signal logic (stateful)
– Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags).
– Short on crossunder of lower (e.g., dropping below −10).
– A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence.
Why VWAP + a breadth score?
• VWAP aggregates both price and volume—where participants actually traded.
• The breadth-style count rewards consistency of the anchored trend, not one-off spikes.
• Thresholds give you binary structure when you need it (alerts, automation), without complex math.
What you’ll see on the chart
• Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral).
• Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors).
• Threshold guides — Horizontal lines for the long/short bands (toggle).
• Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors.
Input map (quick reference)
• VWAP Anchor Period — Day, Week, Month, Quarter, Year.
• Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons.
• Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below).
• UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors.
Interpreting the score
• Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength.
• Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness.
• Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise.
Why the asymmetric default thresholds?
• Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.”
• Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to:
– Capture sustained uptrends only when they’re very strong.
– Flag downside turns as they occur, rather than waiting for an extreme negative breadth.
Tuning guide
Choose an anchor that matches your horizon
– Intraday scalps : Day anchor on intraday charts.
– Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles.
Pick the for-loop window
– Larger N (bigger end) = stronger evidence requirement, smoother oscillator.
– Smaller N = faster, more reactive score.
Set achievable thresholds
– Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger.
– Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior.
Match visuals to intent
– Enabling VWAP coloring lets you see regime directly on price.
– Background shading is useful for discretionary reading; turn it off for cleaner automation displays.
Playbook examples
• Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing.
• Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off.
• Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder.
Behavior around resets (important)
Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes.
Alerts included
• VWAP FL Long — Fires when the long condition is true (score > upper and not in short).
• VWAP FL Short — Fires on crossunder of the lower threshold (event-driven).
Messages include {{ticker}} and {{interval}} placeholders for routing.
Strengths
• Simple, transparent math — Easy to reason about and validate.
• Volume-aware by construction — Decisions reference VWAP, not just price.
• Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output).
Limitations & cautions
• Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N.
• Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N.
• Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature.
• VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic.
Suggested starting profiles
• Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON.
• Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF.
• Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired.
Implementation notes
• The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss).
• HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range.
• For-loop cap is kept modest (≤50) for performance and clarity.
How to use this responsibly
Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns.
Summary
VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.