200SMA Distance OscillatorThe oscillator measures the percentage deviation of closing price x from SMA200.
The idea behind the oscillator was preceded by an analysis of how often MAs in the index hold/bounce or are broken through.
Basically, the idea was about index analysis, i.e., the macro picture of a market.
Who wants to buy individual stocks when the overall market is plummeting ;-)
Or in other words: How long are you long in a market? When is it time to take profits?
After the analysis of the stability of SMAs in the index was rather modest (ratio of just under 6:4 for bounce to breakout – overall in 20, 50, 100, and 200 frames from 2020 to 2025), it was noticeable that the percentage over- or underperformance was scalable, especially in indices.
And since indices generally move upwards, there were fixed limits for over- and underestimations – especially in the longer term (SMA200) – unlike with individual stocks.
It is therefore more a question of macro trends and less of short-term movements, e.g., in day trading.
It was now interesting to see at what percentage range counter-movements were likely – particularly in the positive range for profit-taking, but of course also in the negative range for entry into sold-off markets.
If, for example, closing prices around +25% above SMA200 were reached in the NDX, the probability is very high that the market has overreacted and an interim correction will follow – so the theory goes.
On the other hand, continuous levels of +5 to +10% are a product of healthy positive development in a bull market and do not necessarily require action.
The oscillator was specifically designed for the NDX, but can also be used for the SPX and others.
The style was based on the RSI, so that the color level rises from 10% to 20% (overbought/oversold principle).
Based on manually examined movements, the criteria were set as follows:
+/-10% = flow / no color background
> +/-10% = border areas / color background
The center line represents the 252 average of the percentage deviations and could also be used as a trigger, provided it has been historically examined and is valid.
The oscillator is very interesting because it behaves completely differently from one financial instrument to another and, as a result, also in the timeframes (4h, D, W).
It would probably make sense to change the flow and border levels in the code when using it outside of indices.
The fact is that the oscillator must be “adjusted” to each instrument in order to achieve its goal of providing the best possible prediction. “Adjusting” refers to the analysis of the levels at which an instrument/asset usually reacts.
As with all indicators and oscillators, it is advisable to take other indicators and, in particular, macro news into account when analyzing this development.
If I find any substantial correlations with other indicators, I will be happy to provide an update.
The idea came from me, the code from Grok.
The code is not 100% perfect, but the data (percentage deviation, color background) is correct according to initial analysis.
In the settings, you can make the lines of the plots invisible. This makes the oscillator clearer. You can also adjust the settings for the average line.
In den Scripts nach "spx" suchen
Flux-Tensor Singularity [FTS]Flux-Tensor Singularity - Multi-Factor Market Pressure Indicator
The Flux-Tensor Singularity (FTS) is an advanced multi-factor oscillator that combines volume analysis, momentum tracking, and volatility-weighted normalization to identify critical market inflection points. Unlike traditional single-factor indicators, FTS synthesizes price velocity, volume mass, and volatility context into a unified framework that adapts to changing market regimes.
This indicator identifies extreme market conditions (termed "singularities") where multiple confirming factors converge, then uses a sophisticated scoring system to determine directional bias. It is designed for traders seeking high-probability setups with built-in confluence requirements.
THEORETICAL FOUNDATION
The indicator is built on the premise that market time is not constant - different market conditions contain varying levels of information density. A 1-minute bar during a major news event contains far more actionable information than a 1-minute bar during overnight low-volume trading. Traditional indicators treat all bars equally; FTS does not.
The theoretical framework draws conceptual parallels to physics (purely as a mental model, not literal physics):
Volume as Mass: Large volume represents significant market participation and "weight" behind price moves. Just as massive objects have stronger gravitational effects, high-volume moves carry more significance.
Price Change as Velocity: The rate of price movement through price space represents momentum and directional force.
Volatility as Time Dilation: When volatility is high relative to its historical norm, the "information density" of each bar increases. The indicator weights these periods more heavily, similar to how time dilates near massive objects in physics.
This is a pedagogical metaphor to create a coherent mental model - the underlying mathematics are standard financial calculations combined in a novel way.
MATHEMATICAL FRAMEWORK
The indicator calculates a composite singularity value through four distinct steps:
Step 1: Raw Singularity Calculation
S_raw = (ΔP × V) × γ²
Where:
ΔP = Price Velocity = close - close
V = Volume Mass = log(volume + 1)
γ² = Time Dilation Factor = (ATR_local / ATR_global)²
Volume Transformation: Volume is log-transformed because raw volume can have extreme outliers (10x-100x normal). The logarithm compresses these spikes while preserving their significance. This is standard practice in volume analysis.
Volatility Weighting: The ratio of short-term ATR (5 periods) to long-term ATR (user-defined lookback) is squared to create a volatility amplification factor. When local volatility exceeds global volatility, this ratio increases, amplifying the raw singularity value. This makes the indicator regime-aware.
Step 2: Normalization
The raw singularity values are normalized to a 0-100 scale using a stochastic-style calculation:
S_normalized = ((S_raw - S_min) / (S_max - S_min)) × 100
Where S_min and S_max are the lowest and highest raw singularity values over the lookback period.
Step 3: Epsilon Compression
S_compressed = 50 + ((S_normalized - 50) / ε)
This is the critical innovation that makes the sensitivity control functional. By applying compression AFTER normalization, the epsilon parameter actually affects the final output:
ε < 1.0: Expands range (more signals)
ε = 1.0: No change (default)
ε > 1.0: Compresses toward 50 (fewer, higher-quality signals)
For example, with ε = 2.0, a normalized value of 90 becomes 70, making threshold breaches rarer and more significant.
Step 4: Smoothing
S_final = EMA(S_compressed, smoothing_period)
An exponential moving average removes high-frequency noise while preserving trend.
SIGNAL GENERATION LOGIC
When the tensor crosses above the upper threshold (default 90) or below the lower threshold (default 10), an extreme event is detected. However, the indicator does NOT immediately generate a buy or sell signal. Instead, it analyzes market context through a multi-factor scoring system:
Scoring Components:
Price Structure (+1 point): Current bar bullish/bearish
Momentum (+1 point): Price higher/lower than N bars ago
Trend Context (+2 points): Fast EMA above/below slow EMA (weighted heavier)
Acceleration (+1 point): Rate of change increasing/decreasing
Volume Multiplier (×1.5): If volume > average, multiply score
The highest score (bullish vs bearish) determines signal direction. This prevents the common indicator failure mode of "overbought can stay overbought" by requiring directional confirmation.
Signal Conditions:
A BUY signal requires:
Extreme event detection (tensor crosses threshold)
Bullish score > Bearish score
Price confirmation: Bullish candle (optional, user-controlled)
Volume confirmation: Volume > average (optional, user-controlled)
Momentum confirmation: Positive momentum (optional, user-controlled)
A SELL signal requires the inverse conditions.
INPUTS EXPLAINED - Core Parameters:
Global Horizon (Context): Default 20. Lookback period for normalization and volatility comparison. Higher values = smoother but less responsive. Lower values = more signals but potentially more noise.
Tensor Smoothing: Default 3. EMA period applied to final output. Removes "quantum foam" (high-frequency noise). Range 1-20.
Singularity Threshold: Default 90. Values above this (or below 100-threshold) trigger extreme event detection. Higher = rarer, stronger signals.
Signal Sensitivity (Epsilon): Default 1.0. Post-normalization compression factor. This is the key innovation - it actually works because it's applied AFTER normalization. Range 0.1-5.0.
Signal Interpreter Toggles:
Require Price Confirmation: Default ON. Only generates buy signals on bullish candles, sell signals on bearish candles. Reduces false signals but may delay entry.
Require Volume Confirmation: Default ON. Only signals when volume > average. Critical for stocks/crypto, less important for forex (unreliable volume data).
Use Momentum Filter: Default ON. Requires momentum agreement with signal direction. Prevents counter-trend signals.
Momentum Lookback: Default 5. Number of bars for momentum calculation. Shorter = more responsive, longer = trend-following bias.
Visual Controls:
Colors: Customizable colors for bullish flux, bearish flux, background, and event horizon.
Visual Transparency: Default 85. Master control for all visual elements (accretion disk, field lines, particles, etc.). Range 50-99. Signals and dashboard have separate controls.
Visibility Toggles: Individual on/off switches for:
Gravitational field lines (trend EMAs)
Field reversals (trend crossovers)
Accretion disk (background gradient)
Singularity diamonds (neutral extreme events)
Energy particles (volume bursts)
Event horizon flash (extreme event background)
Signal background flash
Signal Size: Tiny/Small/Normal triangle size
Signal Offsets: Separate controls for buy and sell signal vertical positioning (percentage of price)
Dashboard Settings:
Show Dashboard: Toggle on/off
Position: 9 placement options (all corners, centers, middles)
Text Size: Tiny/Small/Normal/Large
Background Transparency: 0-50, separate from visual transparency
VISUAL ELEMENTS EXPLAINED
1. Accretion Disk (Background Gradient):
A three-layer gradient background that intensifies as the tensor approaches extremes. The outer disk appears at any non-neutral reading, the inner disk activates above 70 or below 30, and the core layer appears above 85 or below 15. Color indicates direction (cyan = bullish, red = bearish). This provides instant visual feedback on market pressure intensity.
2. Gravitational Field Lines (EMAs):
Two trend-following EMAs (10 and 30 period) visualized as colored lines. These represent the "curvature" of market trend - when they diverge, trend is strong; when they converge, trend is weakening. Crossovers mark potential trend reversals.
3. Field Reversals (Circles):
Small circles appear when the fast EMA crosses the slow EMA, indicating a potential trend change. These are distinct from extreme events and appear at normal market structure shifts.
4. Singularity Diamonds:
Small diamond shapes appear when the tensor reaches extreme levels (>90 or <10) but doesn't meet the full signal criteria. These are "watch" events - extreme pressure exists but directional confirmation is lacking.
5. Energy Particles (Dots):
Tiny dots appear when volume exceeds 2× average, indicating significant participation. Color matches bar direction. These highlight genuine high-conviction moves versus low-volume drifts.
6. Event Horizon Flash:
A golden background flash appears the instant any extreme threshold is breached, before directional analysis. This alerts you to pay attention.
7. Signal Background Flash:
When a full buy/sell signal is confirmed, the background flashes cyan (buy) or red (sell). This is your primary alert that all conditions are met.
8. Signal Triangles:
The actual buy (▲) and sell (▼) markers. These only appear when ALL selected confirmation criteria are satisfied. Position is offset from bars to avoid overlap with other indicators.
DASHBOARD METRICS EXPLAINED
The dashboard displays real-time calculated values:
Event Density: Current tensor value (0-100). Above 90 or below 10 = critical. Icon changes: 🔥 (extreme high), ❄️ (extreme low), ○ (neutral).
Time Dilation (γ): Current volatility ratio squared. Values >2.0 indicate extreme volatility environments. >1.5 = elevated, >1.0 = above average. Icon: ⚡ (extreme), ⚠ (elevated), ○ (normal).
Mass (Vol): Log-transformed volume value. Compared to volume ratio (current/average). Icon: ● (>2× avg), ◐ (>1× avg), ○ (below avg).
Velocity (ΔP): Raw price change. Direction arrow indicates momentum direction. Shows the actual price delta value.
Bullish Flux: Current bullish context score. Displayed as both a bar chart (visual) and numeric value. Brighter when bullish score dominates.
Bearish Flux: Current bearish context score. Same visualization as bullish flux. These scores compete - the winner determines signal direction.
Field: Trend direction based on EMA relationship. "Repulsive" (uptrend), "Attractive" (downtrend), "Neutral" (ranging). Icon: ⬆⬇↔
State: Current market condition:
🚀 EJECTION: Buy signal active
💥 COLLAPSE: Sell signal active
⚠ CRITICAL: Extreme event, no directional confirmation
● STABLE: Normal market conditions
HOW TO USE THE INDICATOR
1. Wait for Extreme Events:
The indicator is designed to be selective. Don't trade every fluctuation - wait for tensor to reach >90 or <10. This alone is not a signal.
2. Check Context Scores:
Look at the Bullish Flux vs Bearish Flux in the dashboard. If scores are close (within 1-2 points), the market is indecisive - skip the trade.
3. Confirm with Signals:
Only act when a full triangle signal appears (▲ or ▼). This means ALL your selected confirmation criteria have been met.
4. Use with Price Structure:
Combine with support/resistance levels. A buy signal AT support is higher probability than a buy signal in the middle of nowhere.
5. Respect the Dashboard State:
When State shows "CRITICAL" (⚠), it means extreme pressure exists but direction is unclear. These are the most dangerous moments - wait for resolution.
6. Volume Matters:
Energy particles (dots) and the Mass metric tell you if institutions are participating. Signals without volume confirmation are lower probability.
MARKET AND TIMEFRAME RECOMMENDATIONS
Scalping (1m-5m):
Lookback: 10-14
Smoothing: 5-7
Threshold: 85
Epsilon: 0.5-0.7
Note: Expect more noise. Confirm with Level 2 data. Best on highly liquid instruments.
Intraday (15m-1h):
Lookback: 20-30 (default settings work well)
Smoothing: 3-5
Threshold: 90
Epsilon: 1.0
Note: Sweet spot for the indicator. High win rate on liquid stocks, forex majors, and crypto.
Swing Trading (4h-1D):
Lookback: 30-50
Smoothing: 3
Threshold: 90-95
Epsilon: 1.5-2.0
Note: Signals are rare but high conviction. Combine with higher timeframe trend analysis.
Position Trading (1D-1W):
Lookback: 50-100
Smoothing: 5-7
Threshold: 95
Epsilon: 2.0-3.0
Note: Extremely rare signals. Only trade the most extreme events. Expect massive moves.
Market-Specific Settings:
Forex (EUR/USD, GBP/USD, etc.):
Volume data is unreliable (spot forex has no centralized volume)
Disable "Require Volume Confirmation"
Focus on momentum and trend filters
News events create extreme singularities
Best on 15m-1h timeframes
Stocks (High-Volume Equities):
Volume confirmation is CRITICAL - keep it ON
Works excellently on AAPL, TSLA, SPY, etc.
Morning session (9:30-11:00 ET) shows highest event density
Earnings announcements create guaranteed extreme events
Best on 5m-1h for day trading, 1D for swing trading
Crypto (BTC, ETH, major alts):
Reduce threshold to 85 (crypto has constant high volatility)
Volume spikes are THE primary signal - keep volume confirmation ON
Works exceptionally well due to 24/7 trading and high volatility
Epsilon can be reduced to 0.7-0.8 for more signals
Best on 15m-4h timeframes
Commodities (Gold, Oil, etc.):
Gold responds to macro events (Fed announcements, geopolitical events)
Oil responds to supply shocks
Use daily timeframe minimum
Increase lookback to 50+
These are slow-moving markets - be patient
Indices (SPX, NDX, etc.):
Institutional volume matters - keep volume confirmation ON
Opening hour (9:30-10:30 ET) = highest singularity probability
Strong correlation with VIX - high VIX = more extreme events
Best on 15m-1h for day trading
WHAT MAKES THIS INDICATOR UNIQUE
1. Post-Normalization Sensitivity Control:
Unlike most oscillators where sensitivity controls don't actually work (they're applied before normalization, which then rescales everything), FTS applies epsilon compression AFTER normalization. This means the sensitivity parameter genuinely affects signal frequency. This is a novel implementation not found in standard oscillators.
2. Multi-Factor Confluence Requirement:
The indicator doesn't just detect "overbought" or "oversold" - it detects extreme conditions AND THEN analyzes context through five separate factors (price structure, momentum, trend, acceleration, volume). Most indicators are single-factor; FTS requires confluence.
3. Volatility-Weighted Normalization:
By squaring the ATR ratio (local/global), the indicator adapts to changing market regimes. A 1% move in a low-volatility environment is treated differently than a 1% move in a high-volatility environment. Traditional indicators treat all moves equally regardless of context.
4. Volume Integration at the Core:
Volume isn't an afterthought or optional filter - it's baked into the fundamental equation as "mass." The log transformation handles outliers elegantly while preserving significance. Most price-based indicators completely ignore volume.
5. Adaptive Scoring System:
Rather than fixed buy/sell rules ("RSI >70 = sell"), FTS uses competitive scoring where bullish and bearish evidence compete. The winner determines direction. This solves the classic problem of "overbought markets can stay overbought during strong uptrends."
6. Comprehensive Visual Feedback:
The multi-layer visualization system (accretion disk, field lines, particles, flashes) provides instant intuitive feedback on market state without requiring dashboard reading. You can see pressure building before extreme thresholds are hit.
7. Separate Extreme Detection and Signal Generation:
"Singularity diamonds" show extreme events that don't meet full criteria, while "signal triangles" only appear when ALL conditions are met. This distinction helps traders understand when pressure exists versus when it's actionable.
COMPARISON TO EXISTING INDICATORS
vs. RSI/Stochastic:
These normalize price relative to recent range. FTS normalizes (price change × log volume × volatility ratio) - a composite metric, not just price position.
vs. Chaikin Money Flow:
CMF combines price and volume but lacks volatility context and doesn't use adaptive normalization or post-normalization compression.
vs. Bollinger Bands + Volume:
Bollinger Bands show volatility but don't integrate volume or create a unified oscillator. They're separate components, not synthesized.
vs. MACD:
MACD is pure momentum. FTS combines momentum with volume weighting and volatility context, plus provides a normalized 0-100 scale.
The specific combination of log-volume weighting, squared volatility amplification, post-normalization epsilon compression, and multi-factor directional scoring is unique to this indicator.
LIMITATIONS AND PROPER DISCLOSURE
Not a Holy Grail:
No indicator is perfect. This tool identifies high-probability setups but cannot predict the future. Losses will occur. Use proper risk management.
Requires Confirmation:
Best used in conjunction with price action analysis, support/resistance levels, and higher timeframe trend. Don't trade signals blindly.
Volume Data Dependency:
On forex (spot) and some low-volume instruments, volume data is unreliable or tick-volume only. Disable volume confirmation in these cases.
Lagging Components:
The EMA smoothing and trend filters are inherently lagging. In extremely fast moves, signals may appear after the initial thrust.
Extreme Event Rarity:
With conservative settings (high threshold, high epsilon), signals can be rare. This is by design - quality over quantity. If you need more frequent signals, reduce threshold to 85 and epsilon to 0.7.
Not Financial Advice:
This indicator is an analytical tool. All trading decisions and their consequences are solely your responsibility. Past performance does not guarantee future results.
BEST PRACTICES
Don't trade every singularity - wait for context confirmation
Higher timeframes = higher reliability
Combine with support/resistance for entry refinement
Volume confirmation is CRITICAL for stocks/crypto (toggle off only for forex)
During major news events, singularities are inevitable but direction may be uncertain - use wider stops
When bullish and bearish flux scores are close, skip the trade
Test settings on your specific instrument/timeframe before live trading
Use the dashboard actively - it contains critical diagnostic information
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
TICK & ADD Market Internals SuiteOverview: This is the ultimate Market Internals tool designed for professional SPX/ES and NQ intraday traders.
Traders often monitor both TICK (for short-term timing) and ADD (for daily trend context). However, displaying them on the same chart is usually problematic due to their different scales (TICK ±1000 vs. ADD ±2000), causing chart compression.
Market Internals Suite solves this with a smart "Visual Scaling" algorithm, perfectly fusing TICK Candles and the ADD Line into a single, coherent pane.
Key Features
1.Hybrid Visualization:
· TICK (Foreground): Displayed as OHLC Candles to capture instant liquidity sweeps and wicks.
· ADD (Background): Displayed as a clean Line to show the underlying market breadth trend without clutter.
2.Smart Visual Scaling:
· To prevent chart distortion, the ADD line is visually scaled down (Default Ratio: 1.5).
· This aligns the ADD trend volatility with the TICK range, allowing you to instantly spot divergences or resonance between sentiment and trend.
3.Real-Time Data Dashboard:
· Never lose track of the actual numbers. A dashboard in the top-right corner displays the TRUE values for both TICK and ADD (unscaled).
· Customizable Text Size: You can adjust the dashboard font size (Small/Normal/Large/Huge) in the settings to fit your screen.
4.TICK Extreme Alerts:
· Visual Highlight: The chart background highlights (Green/Red) only when TICK hits the extreme ±1000 levels.
· The ADD line remains clean and alert-free to serve as a stable reference.
Strategy: Context + Timing:
1.Trend Resonance
When the ADD line trends upward and TICK candles consistently maintain levels above zero, it indicates a healthy, strong trend. This is a signal to look for trend-following long setups.
2.Divergence Analysis (The "Holy Grail" Signal)
This combination view makes spotting internal divergences incredibly easy:
· Bearish Divergence: When Price makes a New High, but the ADD line or TICK peaks make a Lower High. This suggests buying exhaustion beneath the surface and often precedes a reversal down.
· Bullish Divergence: When Price makes a New Low, but the ADD line or TICK lows make a Higher Low. This suggests that selling pressure is being absorbed, signaling a potential bounce or reversal up.
TICK Indicator with Extreme AlertsOverview:
This indicator is designed to provide intraday traders (especially those trading SPX, ES, and NQ) with a clearer NYSE TICK analysis tool featuring visual alerts. Unlike traditional TICK line charts, this indicator utilizes OHLC Candlesticks to display data, allowing you to fully view the Open, High, Low, and Close within a specific timeframe, thereby capturing instantaneous liquidity sweeps.
Core Features & Logic:
Candlestick Visualization (OHLC Candles): Uses the USI:TICK.US data source by default. The candlestick patterns allow you to clearly see if the TICK pierced key levels intraday but retraced by the close—vital information that standard line charts often miss.
Dual Key Level System: The indicator is designed with two independent reference tiers for trend observation and reversal detection:
Reference Lines (+/- 800): Marked by gray dashed lines. These represent the standard bull/bear dividing zones. When TICK sustains above +800 or below -800, it typically indicates a strong trending market.
Extreme Alerts (+/- 1000): These thresholds are used to identify extreme market sentiment (overbought/oversold conditions).
Background Highlight Alerts (Visual Alerts): To reduce screen-watching fatigue, the indicator automatically highlights the candlestick background when extreme market sentiment occurs:
Green Background: Triggered when TICK High breaks above +1000. Represents extreme buying sentiment, potentially indicating exhaustion or a short squeeze.
Red Background: Triggered when TICK Low drops below -1000. Represents extreme panic selling (Washout), often serving as a potential signal for an intraday reversal or a short-term bottom.
Custom Settings:
All thresholds (800 reference lines, 1000 alert lines) are fully adjustable in the settings.
All colors (Candles, Reference Lines, Background Alert Colors) can be customized.
Use Cases: This tool is ideal for intraday counter-trend or trend-following trading when combined with Price Action analysis and key Support & Resistance levels.
Percentage Distance from 200-Week SMA200-Week SMA % Distance Oscillator (Clean & Simple)
This lightweight, no-nonsense indicator shows how far the current price is from the classic 200-week Simple Moving Average, expressed as a percentage.
Key features:
• True percentage distance: (Price − 200w SMA) / 200w SMA × 100
• Auto-scaling oscillator (no forced ±100% range → the line actually moves and looks alive)
• Clean zero line
• +10% overbought and −10% oversold levels with subtle background shading
• Real-time table showing the exact current percentage
• Small label on the last bar for instant reading
• Alert conditions when price moves >10% above or below the 200-week SMA
Why 200-week SMA?
Many legendary investors and hedge funds (Stan Druckenmiller, Paul Tudor Jones, etc.) use the 200-week SMA as their ultimate long-term trend anchor. Being +10% or more above it has historically signaled extreme optimism, while −10% or lower has marked deep pessimism and generational buying opportunities.
Perfect for Bitcoin, SPX, gold, individual stocks – works on any timeframe (looks especially good on daily and weekly charts).
Open-source • No repainting • Minimalist & fast
Enjoy and trade well!
Trend-S&R-WiP11-15-2025: This new indicator is my 5/15-Min-ORB-Trend-Finder-WiP indicator simplified to only have:
> Market Open
> 5-Min & 15-Min High/Low
> Support/Resistance lines
> Fair Value Gaps (FVGs)
> a Trend Line
> a Trend table
Recommended to be used with my other indicator: Buy-or-Sell-WiP
Strategy:
> I only trade one ticker, SPX, with ODTE CALL/PUT Credit Spreads
> use Break & Retest with 5-Min High/Low or 15-Min High/Low or FVGs
> 📈 Bullish Trend
Trade: PUT Credit Spread
Trend Confirmations:
Trend Line is green
MACD Histogram is green
Price Condition: Nearest resistance 8-10 points above market price
> 📉 Bearish Trend
Trade: CALL Credit Spread
Trend Confirmations:
Trend Line is purple
MACD Histogram is red
Price Condition: Nearest support 8-10 points below market price
> Fair Value Gaps (FVGs)
- Trade anytime during the day using Break & Retest and all indicator confirmations shown above
🎯 Wyckoff Order Block Entry System🎯 Wyckoff Order Block Entry System
📝 INDICATOR DESCRIPTION
🎯 Wyckoff Order Block Entry System Short Description:
Professional institutional zone trading combined with Wyckoff methodology. Identifies high-probability entries where smart money meets classic price action patterns.
Full Description:
Wyckoff Order Block Entry System is a precision trading tool that combines two powerful concepts:
Order Blocks - Institutional zones where large players place their orders
Wyckoff Method - Classic price action patterns revealing smart money behavior
🎯 What Makes This Different?
Unlike traditional indicators that flood your chart with signals, this system only triggers entries when BOTH conditions are met:
Price enters an institutional Order Block zone (current timeframe OR higher timeframe)
A Wyckoff pattern occurs (Spring, SOS, Upthrust, or SOW)
This dual-confirmation approach ensures you're trading with institutional flow at optimal entry points.
📊 Key Features:
✅ Order Block Detection
Automatically identifies institutional buying/selling zones
Current timeframe order blocks (solid lines)
Higher timeframe order blocks (dashed lines) for stronger zones
Customizable strength and extension settings
✅ 4 Wyckoff Entry Patterns
SPRING (Bullish Reversal): Fake breakdown below support → Quick recovery
SOS (Sign of Strength): Strong bullish candle after accumulation
UPTHRUST (Bearish Reversal): Fake breakout above resistance → Quick rejection
SOW (Sign of Weakness): Strong bearish candle after distribution
✅ Clean Visual Design
Minimalist approach - only essential information
Color-coded zones (Green = Bullish, Red = Bearish, Cyan/Magenta = HTF)
Clear entry signals with pattern type labels
No chart clutter - focus on what matters
✅ Multi-Timeframe Analysis
Integrates higher timeframe order blocks
HTF signals marked with "+HTF" tag for extra confidence
Fully customizable HTF selection (H1, H4, Daily, etc.)
✅ Smart Alerts
Entry signal alerts (Long/Short)
Order block formation alerts
HTF order block alerts
Customizable alert messages
💡 How To Use:
Setup: Add indicator to your chart, configure HTF timeframe (default H1)
Wait: Let order blocks form (green/red boxes appear)
Watch: Price returns to order block zone
Entry: Signal appears when Wyckoff pattern confirms
Trade: Enter with the signal, stop below/above order block
📈 Best For:
Forex pairs (all majors and crosses)
Gold (XAUUSD)
Crypto (BTC, ETH, etc.)
Indices (SPX, NAS100, etc.)
Stocks
Commodities
⏱️ Recommended Timeframes:
M15 for scalping
M30 for day trading
H1 for swing trading
H4 for position trading
🎯 Win Rate Expectations:
Current TF signals: 60-70%
HTF signals (+HTF tag): 70-80%
Spring/Upthrust patterns: Highest probability
Works on ALL liquid markets
⚙️ Customizable Settings:
Order block detection parameters
HTF timeframe selection
Wyckoff sensitivity (swing length, volume threshold)
Zone extension duration
Color schemes
📚 Trading Strategy:
This indicator works best when:
Trading in the direction of higher timeframe trend
Using proper risk management (1-2% per trade)
Placing stops just outside order block zones
Taking profits at opposite order blocks
Focusing on HTF signals for higher quality
🔒 Risk Management:
Always use stop losses! Recommended placement:
LONG: 10-20 pips below order block
SHORT: 10-20 pips above order block
Target: Minimum 1:2 risk/reward ratio
💎 Why Traders Love This System:
"Finally, an indicator that doesn't spam my chart with useless signals!" - The quality-over-quantity approach means you only get high-probability setups.
"The HTF order blocks changed my trading!" - Multi-timeframe analysis built-in removes the need for manual higher timeframe checks.
"Wyckoff + Order Blocks = Perfect combination!" - Two proven concepts working together create powerful confluence.
📊 Universal Application:
This system works on ANY liquid market with sufficient volume:
✅ Forex (EUR/USD, GBP/USD, USD/JPY, etc.)
✅ Commodities (Gold, Silver, Oil, etc.)
✅ Indices (S&P 500, NASDAQ, DAX, etc.)
✅ Cryptocurrencies (Bitcoin, Ethereum, etc.)
✅ Stocks (Large cap with good liquidity)
🎓 Educational Value:
Beyond just signals, this indicator teaches you:
How institutional traders think
Where smart money places orders
Classic Wyckoff accumulation/distribution patterns
Multi-timeframe analysis techniques
⚡ Performance:
Lightning-fast calculations
No repainting
Real-time signal generation
Clean code, optimized for speed
🚀 Get Started:
Add to your favorite chart
Adjust HTF timeframe to match your trading style
Wait for high-quality signals
Trade with confidence
Remember: Quality beats quantity. This system prioritizes precision over frequency. You might see 2-5 signals per day on M30 - and that's exactly the point. Each signal is carefully filtered for maximum probability.
Ready to trade like institutions?
👉 Add this indicator to your chart now
👉 Configure your preferred HTF timeframe
👉 Start catching high-probability setups
👉 Trade smarter, not harder
Questions or feedback? Drop a comment below!
Found this useful? Hit that ⭐ button and share with fellow traders!
Happy Trading! 🚀📈
Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
Slick Strategy Weekly PCS TesterInspired by the book “The Slick Strategy: A Unique Profitable Options Trading Method.” This indicator tests weekly SPX put-credit spreads set below Monday’s open and judged at Friday’s close.
WHAT IT DOES
• Sets weekly PCS level = Monday (or first trading day) OPEN − your offset; win/loss checked at Friday close.
• Optional core filter at entry: Price ≥ 200-SMA AND 10-SMA ≥ 20-SMA; pause if Price < both 10 & 20 while > 200.
• Reference modes: Strict = Mon OPEN vs Fri SMAs (no repaint); Mid = Mon OPEN vs Mon SMAs
KEY INPUTS
• Date range (Start/End) to limit backtest window.
• Offset mode/value (Points or Percent).
• Entry day (Monday only or first trading day).
• Core filters (On/Off) and Strict/Mid reference.
• SMA settings (source; 10/20/200 lengths).
• Table settings (position, size, padding, border).
VISUALS
• Active week line: Orange = trade taken; Gray = skipped.
• History: Green = win; Red = loss; Purple = skipped.
• Optional week bands highlight active/win/loss/skipped weeks (adjustable opacity).
TABLE
• Shows Date range, Trades, Wins, Losses, Win rate, and Active level (this week’s PCS price).
NOTES
• PCS level freezes at week open and persists through the week.
Smart VWAP FVG SystemSmart VWAP FVG System - Professional Multi-Filter Trading Indicator
📊 OVERVIEW
The Smart VWAP FVG System is an advanced multi-layered trading indicator that combines institutional volume analysis, multi-timeframe VWAP trend confirmation, and Fair Value Gap detection to identify high-probability trade entries. This indicator uses a sophisticated filtering mechanism where signals appear only when multiple independent confirmation criteria align simultaneously.
Recommended Timeframe: 5-minute (M5) or higher. The indicator works best on M5, M15, and M30 charts for intraday trading.
🎯 ORIGINALITY & PURPOSE
This indicator is original because it combines three distinct analytical methods into a unified decision-making system:
Market Profile Volume Analysis - Identifies institutional accumulation/distribution zones
Dual VWAP Filtering - Confirms trend direction using two independent VWAP calculations
Fair Value Gap Detection - Validates institutional interest through price inefficiency zones
The key innovation is the directional filter system: the primary Market Profile generates BUY-ONLY or SELL-ONLY states based on higher timeframe value area reversals, which then controls which signals from the main system are displayed. This creates a multi-timeframe confluence that significantly reduces false signals.
Unlike simple indicator mashups, each component serves a specific purpose:
Market Profile → Direction bias (trend filter)
Primary VWAP (Session) → Short-term trend confirmation
Secondary VWAP (Week) → Medium-term trend confirmation
FVG Detection → Institutional activity validation
🔧 HOW IT WORKS
1. Primary Market Profile Filter (Higher Timeframe)
The indicator calculates Market Profile on a higher timeframe (default: 1 hour) to determine the overall market structure:
Value Area High (VAH): Top 70% of volume distribution
Value Area Low (VAL): Bottom 70% of volume distribution
Point of Control (POC): Price level with highest volume
When price reaches VAH and reverses down → SELL-ONLY mode activated
When price reaches VAL and reverses up → BUY-ONLY mode activated
This higher timeframe filter ensures you're trading in the direction of institutional flow.
2. Dual VWAP System
Two independent VWAP calculations provide multi-timeframe trend confirmation:
Primary VWAP (Session-based): Resets daily, tracks intraday momentum
Secondary VWAP (Week-based): Resets weekly, confirms longer-term trend
Filter Logic:
BUY signals require: Price > Primary VWAP AND Price > Secondary VWAP
SELL signals require: Price < Primary VWAP AND Price < Secondary VWAP
This dual confirmation prevents counter-trend trades during ranging conditions.
3. Fair Value Gap (FVG) Detection
FVG zones identify price inefficiencies where institutional orders were executed rapidly:
Bullish FVG: Gap between candle .high and candle .low (upward imbalance)
Bearish FVG: Gap between candle .high and candle .low (downward imbalance)
The indicator monitors recent FVG formation (lookback: 50 bars) and requires:
Bullish FVG present for BUY signals
Bearish FVG present for SELL signals
FVG zones are displayed as colored boxes and automatically marked as "mitigated" when price fills the gap.
4. Main Trading Signal Logic
The secondary Market Profile (default: 1 hour) generates the actual trading signals:
BUY Signal Conditions:
Price reaches Value Area Low
Reversal pattern confirmed (minimum 1 bar)
Price > Primary VWAP
Price > Secondary VWAP (if filter enabled)
Recent Bullish FVG detected (if filter enabled)
Primary MP Filter = BUY-ONLY or NEUTRAL
SELL Signal Conditions:
Price reaches Value Area High
Reversal pattern confirmed (minimum 1 bar)
Price < Primary VWAP
Price < Secondary VWAP (if filter enabled)
Recent Bearish FVG detected (if filter enabled)
Primary MP Filter = SELL-ONLY or NEUTRAL
All conditions must be TRUE simultaneously for a signal to appear.
📈 VISUAL ELEMENTS
On Chart:
🟢 Green Triangle (▲) = BUY Signal
🔴 Red Triangle (▼) = SELL Signal
🟦 Blue horizontal lines = Value Area zones
🟡 Yellow line = Point of Control (POC)
🟩 Green boxes = Bullish FVG zones
🟥 Red boxes = Bearish FVG zones
🔵 Blue line = Primary VWAP (Session)
⚪ White line = Secondary VWAP (Week)
Info Panel (Top Right):
Real-time status display showing:
Filter Direction (BUY ONLY / SELL ONLY / NEUTRAL)
Active timeframes for both MP filters
FVG filter status and count
VWAP positions (ABOVE/BELOW)
Signal enablement status
Alert status
⚙️ KEY SETTINGS
MP/TPO Filter Settings (Primary Indicator)
MP Filter Time Frame: 60 minutes (controls directional bias)
Filter Value Area %: 70% (standard Market Profile calculation)
Filter Alert Distance: 1 bar
Filter Min Bars for Reversal: 1 bar
Filter Alert Zone Margin: 0.01 (1%)
FVG Filter Settings
Use FVG Filter: Enabled (toggle on/off)
FVG Timeframe: 60 minutes (1 hour)
FVG Filter Mode: Both (require bullish FVG for BUY, bearish for SELL)
FVG Lookback Period: 50 bars (how far back to search)
Show FVG Formation Signals: Optional visual markers
Max FVG on Chart: 50 zones
Show Mitigated FVG: Display filled gaps
Market Profile Settings
Higher Time Frame: 60 minutes (for main signals)
Percent for Value Area: 70%
Show POC Line: Enabled
Keep Old MPs: Enabled (maintain historical profiles)
Primary VWAP Filter
Use Primary VWAP Filter: Enabled
Primary VWAP Anchor Period: Session (resets daily)
Primary VWAP Source: HLC3 (typical price)
Secondary VWAP Filter
Use Secondary VWAP Filter: Enabled
Secondary VWAP Anchor Period: Week (resets weekly)
Secondary VWAP Filter Mode: Both
Secondary VWAP Line Color: White
Trading Signals
Show Trading Signals on Chart: Enabled
Show SELL Signals: Enabled
Show BUY Signals: Enabled
Alert Distance: 1 bar
Min Bars for Reversal: 1 bar
Alert Zone Margin: 0.01 (1%)
Retest Search Period: 20 bars
Min Bars Between Retests: 5 bars
Show Only Retests: Disabled
Alert Settings
Enable Trading Notifications: Enabled
VAH Reversal Alert: Enabled (SELL signals)
VAL Reversal Alert: Enabled (BUY signals)
Time Filter Settings
Filter Alerts By Time: Optional (exclude specific hours)
⚠️ IMPORTANT WARNINGS & LIMITATIONS
1. Repainting Behavior
CRITICAL: This indicator uses lookahead=barmerge.lookahead_on to access higher timeframe data immediately for FVG detection. This is necessary to provide real-time FVG zone visualization but has the following implications:
FVG zones may shift slightly until the higher timeframe candle closes
FVG detection signals are preliminary until HTF bar confirmation
The main trading signals (triangles) appear on confirmed bars and do not repaint
Best Practice: Always wait for the current timeframe bar to close before acting on signals. The filter status and FVG zones are informational but may adjust as new data arrives.
2. Minimum Timeframe
Do NOT use on timeframes below 5 minutes (M5)
Recommended: M5, M15, M30 for intraday trading
Higher timeframes (H1, H4) can also be used but will generate fewer signals
3. Multiple Filters Can Block Signals
By design, this indicator is conservative. When all filters are enabled:
Signals appear ONLY when all conditions align
You may see extended periods with no signals
This is intentional to reduce false positives
If you see no signals:
Check the Info Panel to see which filters are failing
Consider adjusting FVG lookback period
Temporarily disable FVG filter to test
Verify VWAP filters match current market trend
4. Market Profile Limitations
Market Profile requires sufficient volume data
Low-volume instruments may produce unreliable profiles
Value Areas update only on higher timeframe bar close
Works best on liquid markets (major forex pairs, indices, crypto)
📖 HOW TO USE
Step 1: Add to Chart
Apply indicator to M5 or higher timeframe chart
Ensure chart shows volume data
Use standard candles (NOT Heikin Ashi, Renko, etc.)
Step 2: Configure Settings
Primary MP Filter TF: Set to 60 (1 hour) minimum, or 240 (4 hour) for swing trading
Main MP TF: Set to 60 (1 hour) for intraday signals
FVG Timeframe: Match or exceed main MP timeframe
Leave other settings at default initially
Step 3: Understand the Info Panel
Monitor the top-right panel:
FILTER STATUS: Shows current directional bias
NEUTRAL = Both signals allowed
BUY ONLY = Only green triangles will appear
SELL ONLY = Only red triangles will appear
FVG Filter: Shows if bullish/bearish gaps detected recently
VWAP positions: Confirms trend alignment
Step 4: Take Signals
For BUY Signal (Green Triangle ▲):
Wait for green triangle to appear
Check Info Panel shows ✓ for BUY signals
Confirm current bar has closed
Enter long position
Stop loss: Below recent VAL or swing low
Target: Previous Value Area High or 1.5-2× risk
For SELL Signal (Red Triangle ▼):
Wait for red triangle to appear
Check Info Panel shows ✓ for SELL signals
Confirm current bar has closed
Enter short position
Stop loss: Above recent VAH or swing high
Target: Previous Value Area Low or 1.5-2× risk
Step 5: Risk Management
Risk per trade: Maximum 1-2% of account equity
Position sizing: Adjust based on stop loss distance
Avoid trading: During major news events or time filter periods
Multiple confirmations: Look for confluence with price action (support/resistance, trendlines)
🎓 UNDERLYING CONCEPTS
Market Profile Theory
Developed by J. Peter Steidlmayer in the 1980s, Market Profile organizes price and volume data to identify:
Value Areas: Where 70% of trading activity occurred
POC: Price level with highest acceptance (most volume)
Imbalances: When price moves away from value quickly
This indicator uses TPO (Time Price Opportunity) calculation method to build the volume profile distribution.
VWAP (Volume Weighted Average Price)
VWAP represents the average price weighted by volume, showing where institutional traders are positioned:
Price above VWAP = Bullish (institutions accumulated lower)
Price below VWAP = Bearish (institutions distributed higher)
Using dual VWAP (Session + Week) creates multi-timeframe trend alignment.
Fair Value Gaps (FVG)
Also known as "imbalance" or "inefficiency," FVG occurs when:
Price moves so rapidly that a gap forms in the candlestick structure
Indicates institutional order flow (large market orders)
Price often returns to "fill" these gaps (rebalance)
The 3-candle FVG pattern (gap between candle and candle ) is widely used in ICT (Inner Circle Trader) methodology and Smart Money Concepts.
🔍 CREDITS & CODE ATTRIBUTION
This indicator builds upon established technical analysis concepts and combines multiple methodologies:
1. Market Profile / TPO Calculation
Concept Origin: J. Peter Steidlmayer (Chicago Board of Trade, 1980s)
Code Inspiration: TradingView's public domain Market Profile examples
Modifications: Custom filtering logic for directional bias, dual timeframe implementation
2. VWAP Calculation
Concept Origin: Standard financial instrument (widely used since 1980s)
Code Base: TradingView built-in ta.vwap() function (public domain)
Modifications: Dual VWAP system with independent anchor periods, custom filtering modes
3. Fair Value Gap Detection
Concept Origin: Inner Circle Trader (ICT) / Smart Money Concepts methodology
Code Implementation: Original implementation based on 3-candle gap pattern
Features: Multi-timeframe detection, automatic mitigation tracking, visual zone display
4. Pine Script Framework
Language: Pine Script v6 (TradingView)
Built-in Functions Used:
ta.vwap() - Volume weighted average price
request.security() - Higher timeframe data access
ta.change() - Period detection
ta.cum() - Cumulative volume
time() - Timestamp functions
Note: All code is original implementation. While concepts are based on established trading methodologies, the combination, filtering logic, and execution are unique to this indicator.
📊 RECOMMENDED INSTRUMENTS
Best Performance:
Major Forex Pairs (EURUSD, GBPUSD, USDJPY)
Stock Indices (ES, NQ, SPX, DAX)
Major Cryptocurrencies (BTCUSD, ETHUSD)
Liquid Stocks (high daily volume)
Avoid:
Low-volume altcoins
Illiquid stocks
Exotic forex pairs with wide spreads
⚡ PERFORMANCE TIPS
Start Conservative: Enable all filters initially
Reduce Filters Gradually: If too few signals, disable Secondary VWAP filter first
Match Timeframes: Keep MP Filter TF and FVG TF at same value
Backtest First: Review historical performance on your preferred instrument/timeframe
Combine with Price Action: Look for support/resistance confluence
Use Time Filter: Avoid low-liquidity hours (optional setting)
🚫 WHAT THIS INDICATOR DOES NOT DO
Does not guarantee profits - No trading system is 100% accurate
Does not predict the future - Based on historical patterns
Does not replace risk management - Always use stop losses
Does not work on all instruments - Requires volume data and liquidity
Does not provide exact entry/exit prices - Signals are zones, not precise levels
Does not account for fundamentals - Purely technical analysis
📜 DISCLAIMER
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results.
Trading Risk Warning:
All trading involves risk of loss
You can lose more than your initial investment (leverage products)
Only trade with capital you can afford to lose
Always use appropriate position sizing and risk management
Consider seeking advice from a licensed financial advisor
Technical Limitations:
Indicator may repaint FVG zones until HTF bar closes
Signals are based on historical patterns that may not repeat
Market conditions change and no system works in all environments
Volume data quality varies by exchange/broker
By using this indicator, you acknowledge these risks and agree that the author bears no responsibility for trading losses.
📞 SUPPORT & UPDATES
Questions? Comment on this publication
Issues? Describe the problem with chart screenshot
Feature Requests? Suggest improvements in comments
Updates: Will be published as new versions using TradingView's update feature
📝 VERSION HISTORY
Version 1.0 (Current)
Initial public release
Multi-filter system: MP + Dual VWAP + FVG
Directional bias filter
Real-time info panel
Comprehensive alert system
Time-based filtering
Thank you for using Smart VWAP FVG System!
Happy Trading! 📈
Ben's BTC Macro Fair Value OscillatorBen's BTC Macro Fair Value Oscillator
Overview
The **BTC Macro Fair Value Oscillator** is a non-crypto fair value framework that uses macro asset relationships (equities, dollar, gold) to estimate Bitcoin's "macro-driven fair value" and identify mean-reversion opportunities.
"Is BTC cheap or expensive right now?" on the 4 Hour Timeframe ONLY
### Key Features
✅ **Macro-driven**: Uses QQQ, DXY, XAUUSD instead of on-chain or crypto metrics
✅ **Dynamic weighting**: Assets weighted by rolling correlation strength
✅ **Mean-reversion signals**: Identifies when BTC is cheap/expensive vs macro
✅ **Validated parameters**: Optimized through 5-year backtest (Sharpe 6.7-9.9)
✅ **Visual transparency**: Live correlation panel, fair value bands, statistics
✅ **Non-repainting**: All calculations use confirmed historical data only
### What This Indicator Does
- Builds a **synthetic macro composite** from traditional assets
- Runs a **rolling regression** to predict BTC price from macro
- Calculates **deviation z-score** (how far BTC is from macro fair value)
- Generates **entry signals** when BTC is extremely cheap vs macro (dev < -2)
- Generates **exit signals** when BTC returns to fair value (dev > 0)
### What This Indicator Is NOT
❌ Not a high-frequency trading system (sparse signals by design)
❌ Not optimized for absolute returns (optimized for Sharpe ratio)
❌ Not suitable as standalone trading system (best as overlay/confirmation)
❌ Not predictive of short-term price movements (mean-reversion timeframe: days to weeks)
---
## Core Concept
### The Premise
Bitcoin doesn't trade in a vacuum. It's influenced by:
- **Risk appetite** (equities: QQQ, SPX)
- **Dollar strength** (DXY - inverse to risk assets)
- **Safe haven flows** (Gold: XAUUSD)
When macro conditions are "good for BTC" (risk-on, weak dollar, strong equities), BTC should trade higher. When macro conditions turn against it, BTC should trade lower.
### The Innovation
Instead of looking at BTC in isolation, this indicator:
1. **Measures how strongly** BTC currently correlates with each macro asset
2. **Builds a weighted composite** of those macro returns (the "D" driver)
3. **Regresses BTC price on D** to estimate "macro fair value"
4. **Tracks the deviation** between actual price and fair value
5. **Signals mean reversion** when deviation becomes extreme
### The Edge
The validated edge comes from:
- **Extreme deviations predict future returns** (dev < -2 → +1.67% over 12 bars)
- **Monotonic relationship** (more negative dev → higher forward returns)
- **Works out-of-sample** (test Sharpe +83-87% better than training)
- **Low correlation with buy & hold** (provides diversification value)
---
## Methodology
### Step 1: Macro Composite Driver D(t)
The indicator builds a weighted composite of macro asset returns:
**Process:**
1. Calculate **log returns** for BTC and each macro reference (QQQ, DXY, XAUUSD)
2. Compute **rolling correlation** between BTC and each reference over `corrLen` bars
3. **Weight each asset** by `|correlation|` if above `minCorrAbs` threshold, else 0
4. **Sign-adjust** weights (+1 for positive corr, -1 for negative) to handle inverse relationships
5. **Z-score normalize** each reference's returns over `fvWindow`
6. **Composite D(t)** = weighted sum of sign-adjusted z-scores
**Formula:**
```
For each reference i:
corr_i = correlation(BTC_returns, ref_i_returns, corrLen)
weight_i = |corr_i| if |corr_i| >= minCorrAbs else 0
sign_i = +1 if corr_i >= 0 else -1
z_i = (ref_i_returns - mean) / std
contrib_i = sign_i * z_i * weight_i
D(t) = sum(contrib_i) / sum(weight_i)
```
**Key Insight:** D(t) represents "how good macro conditions are for BTC right now" in a normalized, correlation-weighted way.
---
### Step 2: Fair Value Regression
Uses rolling linear regression to predict BTC price from D(t):
**Model:**
```
BTC_price(t) = α + β * D(t)
```
**Calculation (Pine Script approach):**
```
corr_CD = correlation(BTC_price, D, fvWindow)
sd_price = stdev(BTC_price, fvWindow)
sd_D = stdev(D, fvWindow)
cov = corr_CD * sd_price * sd_D
var_D = variance(D, fvWindow)
β = cov / var_D
α = mean(BTC_price) - β * mean(D)
fair_value(t) = α + β * D(t)
```
**Result:** A time-varying "macro fair value" line that adapts as correlations change.
---
### Step 3: Deviation Oscillator
Measures how far BTC price has deviated from fair value:
**Calculation:**
```
residual(t) = BTC_price(t) - fair_value(t)
residual_std = stdev(residual, normWindow)
deviation(t) = residual(t) / residual_std
```
**Interpretation:**
- `dev = 0` → BTC at fair value
- `dev = -2` → BTC is 2 standard deviations **cheap** vs macro
- `dev = +2` → BTC is 2 standard deviations **rich** vs macro
---
### Step 4: Signal Generation
**Long Entry:** `dev` crosses below `-2.0` (BTC extremely cheap vs macro)
**Long Exit:** `dev` crosses above `0.0` (BTC returns to fair value)
**No shorting** in default config (risk management choice - crypto volatility)
---
## How It Works
### Visual Components
#### 1. Price Chart (Main Panel)
**Fair Value Line (Orange):**
- The estimated "macro-driven fair value" for BTC
- Calculated from rolling regression on macro composite
**Fair Value Bands:**
- **±1σ** (light): 68% confidence zone
- **±2σ** (medium): 95% confidence zone
- **±3σ** (dark, dots): 99.7% confidence zone
**Entry/Exit Markers:**
- **Green "LONG" label** below bar: Entry signal (dev < -2)
- **Red "EXIT" label** above bar: Exit signal (dev > 0)
#### 2. Deviation Oscillator (Separate Pane)
**Line plot:**
- Shows current deviation z-score
- **Green** when dev < -2 (cheap)
- **Red** when dev > +2 (rich)
- **Gray** when neutral
**Histogram:**
- Visual representation of deviation magnitude
- Green bars = negative deviation (cheap)
- Red bars = positive deviation (rich)
**Threshold lines:**
- **Green dashed at -2.0**: Entry threshold
- **Red dashed at 0.0**: Exit threshold
- **Gray solid at 0**: Fair value line
#### 3. Correlation Panel (Top-Right)
Shows live correlation and weighting for each macro asset:
| Asset | Corr | Weight |
|-------|------|--------|
| QQQ | +0.45 | 0.45 |
| DXY | -0.32 | 0.32 |
| XAUUSD | +0.15 | 0.00 |
| Avg \|Corr\| | 0.31 | 0.77 |
**Reading:**
- **Corr**: Current rolling correlation with BTC (-1 to +1)
- **Weight**: How much this asset contributes to fair value (0 = excluded)
- **Avg |Corr|**: Average correlation strength (should be > 0.2 for reliable signals)
**Colors:**
- Green/Red corr = positive/negative correlation
- White weight = asset included, Gray = excluded (below minCorrAbs)
#### 4. Statistics Label (Bottom-Right)
```
━━━ BTC Macro FV ━━━
Dev: -2.34
Price: $103,192
FV: $110,500
Status: CHEAP ⬇
β: 103.52
```
**Fields:**
- **Dev**: Current deviation z-score
- **Price**: Current BTC close price
- **FV**: Current macro fair value estimate
- **Status**: CHEAP (< -2), RICH (> +2), or FAIR
- **β**: Current regression beta (sensitivity to macro)
---
## Installation & Setup
### TradingView Setup
1. Open TradingView and navigate to any **BTC chart** (BTCUSD, BTCUSDT, etc.)
2. Open **Pine Editor** (bottom panel)
3. Click **"+ New"** → **"Blank indicator"**
4. **Delete** all default code
5. **Copy** the entire Pine Script from `GHPT_optimized.pine`
6. **Paste** into the editor
7. Click **"Save"** and name it "BTC Macro Fair Value Oscillator"
8. Click **"Add to Chart"**
### Recommended Chart Settings
**Timeframe:** 4h (validated timeframe)
**Chart Type:** Candlestick or Heikin Ashi
**Overlay:** Yes (indicator plots on price chart + separate pane)
**Alternative Timeframes:**
- Daily: Works but slower signals
- 1h-2h: May work but not validated
- < 1h: Not recommended (too noisy)
### Symbol Requirements
**Primary:** BTC/USD or BTC/USDT on any exchange
**Macro References:** Automatically fetched
- QQQ (Nasdaq 100 ETF)
- DXY (US Dollar Index)
- XAUUSD (Gold spot)
**Data Requirements:**
- At least **90 bars** of history (warmup period)
- Premium TradingView recommended for full historical data
---
## Reading the Indicator
### Identifying Signals
#### Strong Long Signal (High Conviction)
- ✅ Deviation < -2.0 (extreme undervaluation)
- ✅ Avg |Corr| > 0.3 (strong macro relationships)
- ✅ Price touching or below -2σ band
- ✅ "LONG" label appears below bar
**Interpretation:** BTC is extremely cheap relative to macro conditions. Historical data shows +1.67% average return over next 12 bars (48 hours at 4h timeframe).
#### Moderate Long Signal (Lower Conviction)
- ⚠️ Deviation between -1.5 and -2.0
- ⚠️ Avg |Corr| between 0.2-0.3
- ⚠️ Price approaching -2σ band
**Interpretation:** BTC is cheap but not extreme. Consider as confirmation for other signals.
#### Exit Signal
- 🔴 Deviation crosses above 0 (returns to fair value)
- 🔴 "EXIT" label appears above bar
**Interpretation:** Mean reversion complete. Close long positions.
#### Strong Short/Avoid Signal
- 🔴 Deviation > +2.0 (extreme overvaluation)
- 🔴 Avg |Corr| > 0.3
- 🔴 Price touching or above +2σ band
**Interpretation:** BTC is expensive vs macro. Historical data shows -1.79% average return over next 12 bars. Consider exiting longs or reducing exposure.
### Regime Detection
**Strong Regime (Reliable Signals):**
- Avg |Corr| > 0.3
- Multiple assets weighted > 0
- Fair value line tracking price reasonably well
**Weak Regime (Unreliable Signals):**
- Avg |Corr| < 0.2
- Most weights = 0 (grayed out)
- Fair value line diverging wildly from price
- **Action:** Ignore signals until correlations strengthen
BB SPY Mean Reversion Investment StrategySummary
Mean reversion first, continuation second. This strategy targets equities and ETFs on daily timeframes. It waits for price to revert from a Bollinger location with candle and EMA agreement, then manages risk with ATR based exits. Uniqueness comes from two elements working together. One, an adaptive band multiplier driven by volatility of volatility that expands or contracts the envelope as conditions change. Two, a bias memory that re arms the same direction after any stop, target, or time exit until a true opposite signal appears. Add it to a clean chart, use the markers and levels, and select on bar close for conservative alerts. Shapes can move while the bar is open and settle on close.
Scope and intent
• Markets. Currently adapted for SPY, needs to be optimized for other assets
• Timeframes. Daily primary. Other frames are possible but not the default
• Default demo. SPY on daily
• Purpose. Trade mean reversion entries that can chain into a longer swing by splitting holds into ATR or time segments
Originality and usefulness
• Novelty. Adaptive band width from volatility of volatility plus a persistent bias array that keeps the original direction alive across sequential entries until an opposite setup is confirmed
• Failure modes mitigated. False starts in chop are reduced by candle color and EMA location. Missed continuation after a take profit or stop is addressed by the re arm engine. Oversized envelopes during quiet regimes are avoided by the adaptive multiplier
• Testability. Every module has Inputs and visible levels so users can see why a suggestion appears
• Portable yardstick. All risk and targets are expressed in ATR units
Method overview in plain language
The engine measures where price sits relative to Bollinger bands, confirms with candle color and EMA location, requires ADX for shorts(in our case long close since we use it currently as long only), and optionally requires a trend or mean reversion regime using band width percent rank and basis slope. Risk uses ATR for stop, target, and optional breakeven. A small array stores the last confirmed direction. While flat, the engine keeps a pending order in that direction. The array flips only when a true opposite setup appears.
Base measures
• Range basis. True Range smoothed over a user defined ATR Length
• Return basis. Not required
Components
• Bollinger envelope. SMA length and standard deviation multiplier. Entry is based on cross of close through the band with location bias
• Candle and EMA filter. Close relative to open and close relative to EMA align direction
• ADX gate for shorts. Requires minimum trend strength for short trades
• Adaptive multiplier. Band width scales using volatility of volatility so envelopes breathe with conditions
• Regime gate optional. Band width percent rank and basis slope identify trend or mean reversion regimes
• Risk manager. ATR stop, ATR target, optional breakeven, optional time exit
• Bias memory. Array stores last confirmed direction and re arms entries while flat
Fusion rule
Minimum satisfied gates count style. All required gates must be true. Optional gates are controlled in Inputs. Bias memory never overrides an opposite confirmed setup.
Signal rule
• Long setup when close crosses up through the lower band, the bar closes green, and close is above the long EMA
• Short setup when close crosses down through the upper band, the bar closes red, close is below the short EMA, and ADX is above the minimum
• While flat the model keeps a pending order in the stored direction until a true opposite setup appears
• IN LONG or IN SHORT describes states between entry and exit
What you will see on the chart
• Markers for Long and Short setups
• Exit markers from ATR or time rules
• Reference levels for entry, stop, and target
• Bollinger bands and optional adaptive bands
Inputs with guidance
Setup
• Signal timeframe. Uses the chart timeframe
• Invert direction optional. Flips long and short
Logic
• BB Length. Typical 10 to 50. Higher smooths more
• BB Mult. Typical 1.0 to 2.5. Higher widens entries
• EMA Length long. Typical 10 to 50
• EMA Length short. Typical 5 to 30
• ADX Minimum for short. Typical 15 to 35
Filters
• Regime Type. none or trend or mean reversion
• Rank Lookback. Typical 100 to 300
• Basis Slope Length and Threshold. Larger values reduce false trends
Risk
• ATR Length. Typical 10 to 21
• ATR Stop Mult. Typical 1.0 to 3.0
• ATR Take Profit Mult. Typical 2.0 to 5.0
• Breakeven Trigger R. Move stop to entry after the chosen multiple
• Time Exit. Minimum bars and extension when profit exceeds a fraction of ATR
Bias and rearm
• Bias flips kept. Array depth
• Keep rearm when flat. Maintain a pending order while flat
UI
• Show markers and levels. Clean defaults
Usage recipes
Alerts update in real time and can change while the bar forms. Select on bar close for conservative workflows.
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• If any higher timeframe calls are enabled, request.security uses lookahead off
• Commission 0.03 percent
• Slippage 3 ticks
• Default order size method Percent of equity with value 5
• Pyramiding 0
• Process orders on close On
• Bar magnifier Off
• Recalculate after order is filled Off
• Calc on every tick Off
Realism and responsible publication
No performance claims. Costs and fills vary by venue. Shapes can move intrabar and settle on close. Strategies use standard candles only.
Honest limitations and failure modes
High impact releases and thin liquidity can break assumptions. Gap heavy symbols may require larger ATR. Very quiet regimes can reduce contrast in the mean reversion signal. If stop and target can both be touched inside one bar, outcome follows the TradingView order model for that bar path.
Regimes with extreme one sided trend and very low volatility can reduce mean reversion edges. Results vary by symbol and venue. Past results never guarantee future outcomes.
Open source reuse and credits
None.
Backtest realism
Costs are realistic for liquid equities. Sizing does not exceed five percent per trade by default. Any departure should be justified by the user.
If you got any questions please le me know
Index Weighted Returns [SS]This is the index weighted return indicator.
It supports a few ETFs, including:
SPY/SPX
QQQ/NDX
ARKK
SMH
UFO
XBI
QTUM
What it does is it takes the top, approximately 40, of the most heavily weighted tickers on the ETF, monitors their returns using the request security function, and then uses their weight to calculate the synthetic returns of the ETF of interest.
For example, in the chart we have SMH.
The indicator is looking at the top weighted tickers of SMH, calculating their returns, adjusting it for their individual weight on SMH and then predicting the expected return of SMH based on the weighing and holding's returns themselves.
How to Use it
The indicator is pretty straight forward, you select which ever index you are on and your desired timeframe (you can do as low as 30-Minutes or as high as monthly or quarterly).
The indicator will then retrieve the top holdings for that ticker, their corresponding weights and calculate the expected daily return based on the weight and return of these tickers.
It will plot this return for you on the chart.
Other Options
There is an optional table for you to view the actual weight, ticker composition and period returns for each of the top x tickers for an index. You can simply toggle "Show Table" in the settings menu, and it will show you the list of all tickers included, their period returns and their weight on the ETF.
Tips for Use
Works well to see when an index may be over the actual top weighted tickers, implying a pullback/sell, or under. For example:
SPY today fell well below its top tickers and is currently rallying back up to the expected close range.
You can see in the primary chart, SMH fell below and returned to its balance, being at the expected close range based on its component tickers.
That is the indicator!
Its simple but powerful!
Hope you enjoy and as always, safe trades!
VIX OscillatorVIX Oscillator for catching vol signals on the same chart as your index of choice.
- Configurable levels that alert you when certain thresholds are broken
- Shaded background that make it simple to tell when you are in low vol/high vol regimes
- Moving line tracking price so that you can easily see bull/bear divergences against SPX building
NY VIX Channel Trend US Futures Day Trade StrategyNY VIX Channel Trend Strategy
Summary in one paragraph
Session anchored intraday strategy for index futures such as ES and NQ on one to fifteen minute charts. It acts only after the first configurable window of New York Regular Trading Hours and uses a VIX derived daily implied move to form a realistic channel from the session open. Originality comes from using a pure implied volatility yardstick as portable support and resistance, then committing in the direction of the first window close relative to the open. Add it to a clean chart and trade the simple visuals. For conservative alerts use on bar close.
Scope and intent
• Markets. Index futures ES and NQ
• Timeframes. One to thirty minutes
• Default demo. ES1 on five minutes
• Purpose. Provide a portable intraday yardstick for entries and exits without curve fitting
• Limits. This is a strategy. Orders are simulated on standard candles
Originality and usefulness
• Unique concept. A VIX only channel anchored at 09:30 New York plus a single window trend test
• Addresses. False urgency at session open and unrealistic bands from arbitrary multipliers
• Testability. Every input is visible and the channel is plotted so users can audit behavior
• Portable yardstick. Daily implied move equals VIX percent divided by square root of two hundred fifty two
• Protected status. None. Method and use are fully disclosed
Method overview in plain language
Take the daily VIX or VIX9D value, convert it to a daily fraction by dividing by square root of two hundred fifty two, then anchor a symmetric channel at the New York session open. Observe the first N minutes. If that window closes above the open the bias is long. If it closes below the open the bias is short. One trade per session. Exits occur at the channel boundary or at a bracket based on a user selected VIX factor. Positions are closed a set number of minutes before the session ends.
Base measures
Return basis. The daily implied move unit equals VIX percent divided by square root of two hundred fifty two and serves as the distance unit for targets and stops.
Components
• VIX Channel. Top, mid, bottom lines anchored at 09:30 New York. No extra multipliers
• Window Trend. Close of the first N minutes relative to the session open sets direction
• Risk Bracket. Take profit and stop loss equal to VIX unit times user factor
• Session Window. Uses the exchange time of the chart
Fusion rule
Minimum gates count equals one. The trade only arms after the window has elapsed and a direction exists. One entry per session.
Signal rule
• Long when the window close is above the session open and the window has completed
• Short when the window close is below the session open and the window has completed
• Exit on channel touch. Long exits at the top. Short exits at the bottom
• Flat thirty minutes before the session close or at the user setting
Inputs with guidance
Setup
• Use VIX9D. Width source. Typical true for fast tone or false for baseline
• Use daily OPEN. Toggle for sensitivity to overnight changes
Logic
• Window minutes. Five to one hundred twenty. Larger values delay entries and reduce whipsaw
• VIX factor for TP. Zero point five to two. Raising it widens the profit target
• VIX factor for SL. Zero point five to two. Raising it widens the stop
• Exit minutes before close. Fifteen to ninety. Raising it exits earlier
Properties visible in this publication
• Initial capital one hundred thousand USD
• Base currency USD
• request.security uses lookahead off
• Commission cash per contract two point five $ per each contract. Slippage one tick
• Default order size method FIXED with value one contract. Pyramiding zero. Process orders on close ON. Bar magnifier OFF. Recalculate after order is filled OFF. Calc on every tick ON
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Fills and slippage vary by venue. Shapes can move while a bar forms and settle on close. Strategy uses standard candles.
Honest limitations and failure modes
Economic releases and thin liquidity can break the channel. Very quiet regimes can reduce signal contrast. Session windows follow the exchange time of the chart. If both stop and target can be hit within one bar, assume stop first for conservative reading without bar magnifier.
Works best in liquid hours of New York RTH. Very large gaps and surprise news may exceed the implied channel. Always validate on the symbols you trade.
Entries and exits
• Entry logic. After the first window, go long if the window close is above the session open, go short if below
• Exit logic. Long exits at the channel top or at the take profit or stop. Short exits at the channel bottom or at the take profit or stop. Flat before session close by the configured minutes
• Risk model. Initial stop and target based on the VIX unit times user factors. No trail and no break even. No cooldown
• Tie handling. Treat as stop first for conservative interpretation
Position sizing
Fixed size one contract per trade. Target risk per trade should generally remain near one percent of account equity. Risk is based on the daily volatility value, the max loss from the tests for one year duration with 5min chart was 4%, while the avg loss was below <1% of the total capital.
If you have any questions please let me know. Thank you for coming by !
Pullback Levels from ATH# ATH Pullback Levels
**Assess correction depth with precision – 5%, 10%, 15%, 20% below All-Time High**
---
### Overview
This indicator draws **horizontal support lines** at **5%, 10%, 15%, and 20%** below the **All-Time High (ATH)** of any asset. Perfect for **swing traders**, **long-term investors**, and **bull market participants** who want to:
- Measure **pullback depth** in real-time
- Identify **potential support zones**
- Set **alerts** when price enters key retracement levels
---
### Features
| Feature | Description |
|--------|-------------|
| **Dynamic ATH Tracking** | Automatically updates with every new high |
| **4 Pullback Levels** | 5%, 10%, 15%, 20% below ATH |
| **Live Pullback % Label** | Shows current % drop from ATH (top-right) |
| **Customizable Lines** | Toggle visibility, change colors & styles |
| **Built-in Alerts** | Trigger on entry into each zone |
| **No Errors** | Works on 50k+ bar charts (BTC, SPX, etc.) |
| **Time-Based Lines** | Uses `xloc.bar_time` – no 500-bar future limit |
---
### How to Use
1. Apply to any chart (stocks, crypto, forex, indices)
2. Watch the **info box** for current pullback %
3. Use lines as **potential buy zones** during corrections
4. Set **alerts** to be notified when price enters a level
> Example: If ATH = $100 →
> - 5% = $95
> - 10% = $90
> - 15% = $85
> - 20% = $80
---
### Inputs
- **Show 5% / 10% / 15% / 20% Level** → Toggle on/off
- **Line Colors** → Fully customizable
- **Line Style** → Solid, Dashed, or Dotted
---
### Alerts
Create alerts directly from the indicator:
- `"Entered 5% Pullback"`
- `"Entered 10% Pullback"`
- etc.
---
### Best For
- Bull market corrections
- Long-term position sizing
- Risk management in uptrends
- Swing entries on dips
---
### Notes
- Works on **all timeframes**
- **Log scale compatible** (lines adjust correctly)
- No repainting – ATH only updates on confirmed highs
---
**Built with Pine Script v6 – Clean, fast, reliable.**
*Happy trading!*
5-Year Returns Chart BTCvsSPXvsGOLDvsNVDACompare between thes 4 assets:
BTC
NVDA
SPX
GOLD
With an initial 1000$ investment in the last 5 years each return
S&P Trading System with PivotsThe S&P Trading System with Pivots is a TradingView indicator designed for the 30-minute SPX chart to guide SPY options trading. It uses a trend-following strategy with:
10 SMA and 50 SMA: Plots a 10-period (blue) and 50-period (red) Simple Moving Average. A bullish crossover (10 SMA > 50 SMA) signals a potential buy (green triangle below bar), while a bearish crossunder (10 SMA < 50 SMA) signals a sell or exit (red triangle above bar).
Trend Bias: Colors the background green (bullish) or red (bearish) based on SMA positions.
Pivot Points: Marks recent highs (orange circles) and lows (purple circles) as potential resistance and support levels, using a 5-bar lookback period.
Trading Toolkit - Comprehensive AnalysisTrading Toolkit – Comprehensive Analysis
A unified trading analysis toolkit with four sections:
📊 Company Info
Fundamentals, market cap, sector, and earnings countdown.
📅 Performance
Date‑range analysis with key metrics.
🎯 Market Sentiment
CNN‑style Fear & Greed Index (7 components) + 150‑SMA positioning.
🛡️ Risk Levels
ATR/MAD‑based stop‑loss and take‑profit calculations.
Key Features
CNN‑style Fear & Greed approximation using:
Momentum: S&P 500 vs 125‑DMA
Price Strength: NYSE 52‑week highs vs lows
Market Breadth: McClellan Volume Summation (Up/Down volume)
Put/Call Ratio: 5‑day average (inverted)
Volatility: VIX vs 50‑DMA (inverted)
Safe‑Haven Demand: 20‑day SPY–IEF return spread
Junk‑Bond Demand: HY vs IG credit spread (inverted)
Normalization: z‑score → percentile (0–100) with ±3 clipping.
CNN‑aligned thresholds:
Extreme Fear: 0–24 | Fear: 25–44 | Neutral: 45–54 | Greed: 55–74 | Extreme Greed: 75+.
Risk tools: ATR & MAD volatility measures with configurable multipliers.
Flexible layout: vertical or side‑by‑side columns.
Data Sources
S&P 500: CBOE:SPX or AMEX:SPY
NYSE: INDEX:HIGN, INDEX:LOWN, USI:UVOL, USI:DVOL
Options: USI:PCC (Total PCR), fallback INDEX:CPCS (Equity PCR)
Volatility: CBOE:VIX
Treasuries: NASDAQ:IEF
Credit Spreads: FRED:BAMLH0A0HYM2, FRED:BAMLC0A0CM
Risk Management
ATR risk bands: 🟢 ≤3%, 🟡 3–6%, ⚪ 6–10%, 🟠 10–15%, 🔴 >15%
MAD‑based stop‑loss and take‑profit calculations.
Author: Daniel Dahan
(AI Generated, Merged & enhanced version with CNN‑style Fear & Greed)
Distance % from sma/ema + Percentile BandsThis script is breadth indicator for long term bull and bear markets.
Default settings:
AU:
- 200m SMA
- Percentile Lookback: 99%
- Lookback Period: 240 M
AG: TBD
SPX: TBD
TriAnchor Elastic Reversion US Market SPY and QQQ adaptedSummary in one paragraph
Mean-reversion strategy for liquid ETFs, index futures, large-cap equities, and major crypto on intraday to daily timeframes. It waits for three anchored VWAP stretches to become statistically extreme, aligns with bar-shape and breadth, and fades the move. Originality comes from fusing daily, weekly, and monthly AVWAP distances into a single ATR-normalized energy percentile, then gating with a robust Z-score and a session-safe gap filter.
Scope and intent
• Markets: SPY QQQ IWM NDX large caps liquid futures liquid crypto
• Timeframes: 5 min to 1 day
• Default demo: SPY on 60 min
• Purpose: fade stretched moves only when multi-anchor context and breadth agree
• Limits: strategy uses standard candles for signals and orders only
Originality and usefulness
• Unique fusion: tri-anchor AVWAP energy percentile plus robust Z of close plus shape-in-range gate plus breadth Z of SPY QQQ IWM
• Failure mode addressed: chasing extended moves and fading during index-wide thrusts
• Testability: each component is an input and visible in orders list via L and S tags
• Portable yardstick: distances are ATR-normalized so thresholds transfer across symbols
• Open source: method and implementation are disclosed for community review
Method overview in plain language
Base measures
• Range basis: ATR(length = atr_len) as the normalization unit
• Return basis: not used directly; we use rank statistics for stability
Components
• Tri-Anchor Energy: squared distances of price from daily, weekly, monthly AVWAPs, each divided by ATR, then summed and ranked to a percentile over base_len
• Robust Z of Close: median and MAD based Z to avoid outliers
• Shape Gate: position of close inside bar range to require capitulation for longs and exhaustion for shorts
• Breadth Gate: average robust Z of SPY QQQ IWM to avoid fading when the tape is one-sided
• Gap Shock: skip signals after large session gaps
Fusion rule
• All required gates must be true: Energy ≥ energy_trig_prc, |Robust Z| ≥ z_trig, Shape satisfied, Breadth confirmed, Gap filter clear
Signal rule
• Long: energy extreme, Z negative beyond threshold, close near bar low, breadth Z ≤ −breadth_z_ok
• Short: energy extreme, Z positive beyond threshold, close near bar high, breadth Z ≥ +breadth_z_ok
What you will see on the chart
• Standard strategy arrows for entries and exits
• Optional short-side brackets: ATR stop and ATR take profit if enabled
Inputs with guidance
Setup
• Base length: window for percentile ranks and medians. Typical 40 to 80. Longer smooths, shorter reacts.
• ATR length: normalization unit. Typical 10 to 20. Higher reduces noise.
• VWAP band stdev: volatility bands for anchors. Typical 2.0 to 4.0.
• Robust Z window: 40 to 100. Larger for stability.
• Robust Z entry magnitude: 1.2 to 2.2. Higher means stronger extremes only.
• Energy percentile trigger: 90 to 99.5. Higher limits signals to rare stretches.
• Bar close in range gate long: 0.05 to 0.25. Larger requires deeper capitulation for longs.
Regime and Breadth
• Use breadth gate: on when trading indices or broad ETFs.
• Breadth Z confirm magnitude: 0.8 to 1.8. Higher avoids fighting thrusts.
• Gap shock percent: 1.0 to 5.0. Larger allows more gaps to trade.
Risk — Short only
• Enable short SL TP: on to bracket shorts.
• Short ATR stop mult: 1.0 to 3.0.
• Short ATR take profit mult: 1.0 to 6.0.
Properties visible in this publication
• Initial capital: 25000USD
• Default order size: Percent of total equity 3%
• Pyramiding: 0
• Commission: 0.03 percent
• Slippage: 5 ticks
• Process orders on close: OFF
• Bar magnifier: OFF
• Recalculate after order is filled: OFF
• Calc on every tick: OFF
• request.security lookahead off where used
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Fills and slippage vary by venue
• Shapes can move during bar formation and settle on close
• Standard candles only for strategies
Honest limitations and failure modes
• Economic releases or very thin liquidity can overwhelm mean-reversion logic
• Heavy gap regimes may require larger gap filter or TR-based tuning
• Very quiet regimes reduce signal contrast; extend windows or raise thresholds
Open source reuse and credits
• None
Strategy notice
Orders are simulated by TradingView on standard candles. request.security uses lookahead off where applicable. Non-standard charts are not supported for execution.
Entries and exits
• Entry logic: as in Signal rule above
• Exit logic: short side optional ATR stop and ATR take profit via brackets; long side closes on opposite setup
• Risk model: ATR-based brackets on shorts when enabled
• Tie handling: stop first when both could be touched inside one bar
Dataset and sample size
• Test across your visible history. For robust inference prefer 100 plus trades.
FluxGate Daily Swing StrategySummary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
• Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
• Timeframes. From one minute to daily
• Default demo in this publication. SPY on one day timeframe
• Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
• Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
• Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
• Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
• Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
• Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
• Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
• Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
• Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
• Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
• Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
• Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
• Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
• Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
• Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
• Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
• Normalize the three drivers after removing overlap
• Blend with weights that adapt to your aggression input
• Multiply by the gates to respect path quality
• Smooth just enough to avoid jitter while keeping timing responsive
• Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
• The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
• A long suggestion appears when the long score crosses above its long threshold while all gates are active
• A short suggestion appears when the short score crosses below its short threshold while all gates are active
• If any required gate is missing the state is wait
• When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
• Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
• Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
• Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
• Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
• Entry mode. Both or Long only or Short only
Complementary risk engine
• Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
• ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
• ATR length. Default fourteen
• Stop multiple. Default one point five times the anchor ATR
• Use take profit. On by default
• Take profit in R. Default two R
• Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
• Entry mode Both
• ATR anchor Week
• Aggression Long zero point five Aggression Short zero point three
• Stop multiple one point five Take profit two R
• Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
• Session windows optional if you add them in your copy
• ATR anchor Day
• Lower aggression both sides
• Breakeven later and trailing later so the first bounce has room
• This favors fade entries that still convert into trends when the path stays clean
Swing continuation
• Signal timeframe four hours or one day
• Confirm timeframe one day if you choose to include bias
• ATR anchor Week or Month
• Larger base windows and a steady two R target
• This accepts fewer entries and aims for larger holds
Properties visible in this publication
• Initial capital 25.000
• Base currency USD
• Default order size percent of equity value three - 3% of the total capital
• Pyramiding zero
• Commission zero point zero three percent - 0.03% of total capital
• Slippage five ticks
• Process orders on close off
• Recalculate after order is filled off
• Calc on every tick off
• Bar magnifier off
• Any request security calls use lookahead off everywhere
Realism and responsible publication
• No performance promises. Past results never guarantee future outcomes
• Fills and slippage vary by venue and feed
• Strategies run on standard candles only
• Shapes can update while a bar is forming and settle on close
• Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
• Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
• Gap heavy symbols often behave better with a True Range basis for risk than a simple range
• Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
• Session windows follow the exchange time of the chart if you add them
• If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
• No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
Position Size ToolPosition Size Tool
What it does:
Shows a small on-chart table that converts per-ticker dollar amounts into share counts (shares = amount ÷ current price) for up to 4 configurable tickers.
Inputs (indicator settings)
Ticker 1–4 — select the symbol (TradingView will show the exchange-qualified form like BATS:TQQQ in the settings).
Ticker N $ Amount — dollar amount to convert into shares for that ticker.
Show Ticker N — toggle each row on/off.
Table Text Color — color of the table text.
Table Position — screen location (Top/ Middle/ Bottom × Left/Center/Right).
Font Size — Small / Medium / Large.
Show Empty Top Row — optional spacer row.
What the table displays
Left column: the ticker symbol only (the script strips the exchange prefix for display, so BATS:TQQQ appears as TQQQ in the table).
Right column: the calculated share count, formatted to two decimal places (or "—" if price is not available or zero).
Table updates on the chart’s timeframe using live/last bar prices.
How to use
Add the indicator to a chart.
Open the indicator’s settings panel.
In Ticker 1–4, type/select the symbols you want (you may see the exchange prefix there; that’s TradingView’s UI).
Enter the dollar amounts for each ticker.
Use Show Ticker N to hide/show rows.
Adjust text color, font size, and table position as desired.
Notes
The settings field will always show the exchange-qualified symbol (TradingView behavior); the script strips the exchange only for the on-chart display.
If the selected symbol has no price data on the chart/timeframe, the table shows "—".
Shares are computed as amt ÷ current close from the requested symbol and timeframe.
Example of how to use this tool:
Monitor an index and execute trades on leveraged derivative products. This tool will determine the quantity of shares that can be purchased with a pre-determined dollar amount. Ex: Monitor SPX for entry/exit signals and execute trades on UPRO/SPXU/SPXL/SPXS.
Input a ticker and a dollar amount for position size, shares that can be purchased will be calculated based on the current asset price.
This tool can be helpful for those that use multiple platforms simultaneously to monitor and execute trades.
