TradeVision Pro - Multi-Factor Analysis System═══════════════════════════════════════════════════════════════════
TRADEVISION PRO - MULTI-FACTOR ANALYSIS SYSTEM
Created by Zakaria Safri
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A comprehensive technical analysis tool combining multiple factors for
signal generation, trend analysis, and dynamic risk management visualization.
Designed for educational purposes to study multi-factor convergence trading
strategies across all markets and timeframes.
⚠️ IMPORTANT DISCLAIMER:
This indicator is provided for EDUCATIONAL and INFORMATIONAL purposes only.
It does NOT constitute financial advice, investment advice, or trading advice.
Past performance does not guarantee future results. Trading involves
substantial risk of loss. Always do your own research and consult a
financial advisor before making trading decisions.
🎯 KEY FEATURES
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✅ MULTI-FACTOR SIGNAL GENERATION
• Price Volume Trend (PVT) analysis
• Rate of Change (ROC) momentum confirmation
• Volume-Weighted Moving Average (VWMA) trend filter
• Simple Moving Average (SMA) price smoothing
• Signals only when all factors align
✅ DYNAMIC RISK VISUALIZATION (Educational Only)
• ATR-based stop loss calculation
• Risk-reward based take profit levels (1-5 targets)
• Visual lines and labels showing entry, SL, and TPs
• Automatically adapts to market volatility
• ⚠️ VISUAL REFERENCE ONLY - Does not execute trades
✅ SUPPORT & RESISTANCE DETECTION
• Automatic pivot-based level identification
• Red dashed lines for resistance zones
• Green dashed lines for support areas
• Helps identify key price levels
✅ VWMA TREND BANDS
• Volume-weighted moving average with standard deviation
• Color-changing bands (Green = Uptrend, Red = Downtrend)
• Filled band area for easy visualization
• Volume-confirmed trend strength
✅ TREND DETECTION SYSTEM
• Counting-based trend confirmation
• Three states: Up Trend, Down Trend, Ranging
• Requires threshold of consecutive bars
• Independent trend validation
✅ PRICE RANGE VISUALIZATION
• High/Low range lines showing market structure
• Filled area highlighting price volatility
• Helps identify breakout zones
✅ COMPREHENSIVE INFO TABLE
• Real-time trend status
• Last signal type (BUY/SELL)
• Entry price display
• Stop loss level
• All active take profit levels
• Clean, professional layout
✅ OPTIONAL FEATURES
• Bar coloring by trend direction
• Customizable alert notifications
• Toggle visibility for all components
• Fully configurable parameters
📊 HOW IT WORKS
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SIGNAL METHODOLOGY:
BUY SIGNAL generates when ALL conditions are met:
• Smoothed price > Moving Average (upward price trend)
• PVT > PVT Average (volume supporting uptrend)
• ROC > 0 (positive momentum)
• Close > VWMA (above volume-weighted average)
SELL SIGNAL generates when ALL conditions are met:
• Smoothed price < Moving Average (downward price trend)
• PVT < PVT Average (volume supporting downtrend)
• ROC < 0 (negative momentum)
• Close < VWMA (below volume-weighted average)
This multi-factor approach filters out weak signals and waits for
strong convergence before generating alerts.
RISK CALCULATION:
Stop Loss = Entry ± (ATR × SL Multiplier)
• Uses Average True Range for volatility measurement
• Automatically adjusts to market conditions
Take Profit Levels = Entry ± (Risk Distance × TP Multiplier × Level)
• Risk Distance = |Entry - Stop Loss|
• Creates risk-reward based targets
• Example: TP Multiplier 1.0 = 1:1, 2:2, 3:3 risk-reward
⚠️ NOTE: All risk levels are VISUAL REFERENCES for educational study.
They do not execute trades automatically.
⚙️ SETTINGS GUIDE
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SIGNAL SETTINGS:
• Signal Length (14): Main calculation period for averages
• Smooth Length (8): Price data smoothing period
• PVT Length (14): Price Volume Trend calculation period
• ROC Length (9): Rate of Change momentum period
RISK MANAGEMENT (Visual Only):
• ATR Length (14): Volatility measurement lookback
• SL Multiplier (2.2): Stop loss distance (× ATR)
• TP Multiplier (1.0): Risk-reward ratio per TP level
• TP Levels (1-5): Number of take profit targets to display
• Show TP/SL Lines: Toggle visual reference lines
SUPPORT & RESISTANCE:
• Pivot Lookback (10): Sensitivity for S/R detection
• Show SR: Toggle support/resistance lines
VWMA BANDS:
• VWMA Length (20): Volume-weighted average period
• Show Bands: Toggle band visibility
TREND DETECTION:
• Trend Threshold (5): Consecutive bars required for trend
PRICE LINES:
• Period (20): High/low calculation lookback
• Show: Toggle price range visualization
DISPLAY OPTIONS:
• Signals: Show/hide BUY/SELL labels
• Table: Show/hide information panel
• Color Bars: Enable trend-based bar coloring
ALERTS:
• Enable: Activate alert notifications for signals
💡 USAGE INSTRUCTIONS
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RECOMMENDED APPROACH:
• Works on all timeframes (1m to Monthly)
• Suitable for all markets (Stocks, Forex, Crypto, etc.)
• Best used with additional analysis and confirmation
• Always practice proper risk management
ENTRY STRATEGY:
1. Wait for BUY or SELL signal to appear
2. Check trend table for trend confirmation
3. Verify VWMA band color matches signal direction
4. Look for nearby support/resistance confluence
5. Consider entering on next candle open
6. Use visual SL level for risk management
EXIT STRATEGY:
1. Use TP levels as potential exit zones
2. Consider scaling out at multiple TP levels
3. Exit on opposite signal
4. Adjust stops as trade progresses
5. Account for spread and slippage
TREND TRADING:
• "Up Trend" → Focus on BUY signals
• "Down Trend" → Focus on SELL signals
• "Ranging" → Wait for clear trend or use range strategies
🎨 VISUAL ELEMENTS
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• GREEN VWMA BANDS → Bullish trend indication
• RED VWMA BANDS → Bearish trend indication
• ORANGE DASHED LINE → Entry price reference
• RED SOLID LINE → Stop loss level
• GREEN DOTTED LINES → Take profit targets
• RED DASHED LINES → Resistance levels
• GREEN DASHED LINES → Support levels
• GREY FILLED AREA → Price high/low range
• GREEN BUY LABEL → Long signal
• RED SELL LABEL → Short signal
• BLUE INFO TABLE → Current trade details
• GREEN/RED BARS → Trend direction (optional)
⚠️ IMPORTANT NOTES
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RISK WARNING:
• Trading involves substantial risk of loss
• You can lose more than your initial investment
• Past performance does not guarantee future results
• No indicator is 100% accurate
• Always use proper position sizing
• Never risk more than you can afford to lose
EDUCATIONAL PURPOSE:
• This tool is for learning and research
• Not a complete trading system
• Should be combined with other analysis
• Requires interpretation and context
• Test thoroughly before live use
• Consider consulting a financial advisor
TECHNICAL LIMITATIONS:
• Signals lag price action (all indicators lag)
• False signals occur in choppy markets
• Works better in trending conditions
• Support/resistance levels are approximate
• TP/SL levels are suggestions, not guarantees
📚 METHODOLOGY
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This indicator combines established technical analysis concepts:
• Price Volume Trend (PVT): Volume-weighted price momentum
• Rate of Change (ROC): Momentum measurement
• Volume-Weighted Moving Average (VWMA): Trend identification
• Average True Range (ATR): Volatility measurement (J. Welles Wilder)
• Pivot Points: Support/resistance detection
All methods are based on publicly available technical analysis
principles. No proprietary or "secret" algorithms are used.
⚖️ FULL DISCLAIMER
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LIABILITY:
The creator (Zakaria Safri) assumes NO liability for:
• Trading losses or damages of any kind
• Loss of capital or profits
• Incorrect signal interpretation
• Technical issues, bugs, or errors
• Any consequences of using this tool
USER RESPONSIBILITY:
By using this indicator, you acknowledge that:
• You are solely responsible for your trading decisions
• You understand the substantial risks involved
• You will not hold the creator liable for losses
• You will conduct your own research and analysis
• You may consult a licensed financial professional
• You are using this tool entirely at your own risk
AS-IS PROVISION:
This indicator is provided "AS IS" without warranty of any kind,
express or implied, including but not limited to warranties of
merchantability, fitness for a particular purpose, or non-infringement.
The creator is not a registered investment advisor, financial planner,
or broker-dealer. This tool is not approved or endorsed by any
financial authority.
📞 ABOUT THE CREATOR
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Created by: Zakaria Safri
Specialization: Technical analysis indicator development
Focus: Multi-factor analysis, risk visualization, trend detection
This is an educational tool designed to demonstrate technical
analysis concepts and multi-factor signal generation methods.
📋 VERSION INFO
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Version: 1.0
Platform: TradingView Pine Script v5
License: Mozilla Public License 2.0
Creator: Zakaria Safri
Year: 2024
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Study Carefully, Trade Wisely, Manage Risk Properly
TradeVision Pro - Educational Trading Tool
Created by Zakaria Safri
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Search in scripts for "algo"
Cross3x v2Cross3x – Smart Trend & Rejection Detection System
Cross3x is a precision trading indicator designed for traders who combine trend-following with early reversal detection. Built on a triple moving average core, it delivers high-quality signals with minimal noise and maximum clarity.
Core Features:
Trend Filtered Crossover: Uses a fast EMA (18), slow EMA (33), and long-term SMA (99) to generate reliable entry signals only in the direction of the dominant trend.
Dynamic SL/TP/BE Management:
Stop Loss placed at the lowest/highest extreme over a user-defined lookback.
Take Profit calculated using a customizable Risk/Reward ratio.
Break-Even level set as a percentage between entry and TP (e.g., 10% = BE just above entry).
Early Rejection Signals: Flags potential reversals when price tests a moving average with a long wick during a countertrend candle — ideal for spotting pullbacks before the next leg.
Green flag: "Potential Long Setup" after a bullish rejection.
Red flag: "Potential Short Setup" after a bearish rejection.
Confirmation Points: Circles appear when price retraces cleanly after a crossover, signaling optimal entry zones.
Interactive Dashboard: Real-time table showing current signal, SL, and TP levels.
Customizable Alerts: Fully configurable alerts for entries, confirmation points, and rejection setups.
Why Use Cross3x?
It doesn’t just follow trends — it anticipates them. By combining classical crossovers with smart rejection logic and structured risk management, Cross3x helps you enter earlier, manage risk better, and stay aligned with market momentum.
Perfect for swing traders, intraday scalpers, and algorithmic strategies seeking a clean, robust foundation.
Usage Tips:
Combine "Potential" flags with order blocks or key levels for higher accuracy.
Use confirmation circles as entry triggers after early setups.
Adjust RR and BE% based on volatility and trading style.
Deploy Cross3x to turn simple crossovers into a complete trading methodology.
Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
• Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
• Timeframes. One minute to daily
• Default demo used in the publication. QQQ on one hour
• Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
• What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
• Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
• Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
• Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
• Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
• Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
• Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
• Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
• Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
• Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
• Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
• Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
• The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
• Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
• Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
• Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
• When polarity flips from plus to minus, the strategy closes any long and enters a short.
• When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
• White polarity plot around the zero line
• A dotted reference line at zero named Zen
• Green background tint for positive polarity and red background tint for negative polarity
• Strategy long and short markers placed by the TradingView engine at entry and at close conditions
• No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
• Price source. Default ohlc4. Stable for noisy symbols.
• Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
• Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
• Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
• Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
• Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
• Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
• Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
• Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
• Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
• Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
• Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
• Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
• Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
• Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
• Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
• This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
• Initial capital 25000
• Base currency Default
• Default order size method percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Honest limitations and failure modes
• Past results do not guarantee future outcomes
• Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
• Gap heavy symbols may benefit from the MAD Z normalization
• Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
• Session time is the exchange time of the chart
• If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
• None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
• Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
• Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
• Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
• Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
• Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
• Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
• Initial capital 25000
• Base currency Default
• Default order size percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Dataset and sample size
• Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
• Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
• Add alertcondition lines for long, short, and exit short
• Add optional table with component readouts
• Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
Metallic Retracement LevelsThere's something that's always bothered me about how traders use Fibonacci retracements. Everyone treats the golden ratio like it's the only game in town, but mathematically speaking, it's completely arbitrary. The golden ratio is just the first member of an infinite family of metallic means, and there's no particular reason why 1.618 should be special for markets when we have the silver ratio at 2.414, the bronze ratio at 3.303, and literally every other metallic mean extending to infinity. We just picked one and decided it was magical.
The metallic means are a sequence of mathematical constants that generalize the golden ratio. They're defined by the equation x² = kx + 1, where k is any positive integer. When k equals 1, you get the golden ratio. When k equals 2, you get the silver ratio. When k equals 3, you get bronze, and so on forever. Each metallic mean generates its own set of ratios through successive powers, just like how the golden ratio gives you 0.618, 0.382, 0.236 and so forth. The silver ratio produces a completely different set of retracement levels, as does bronze, as does any arbitrary metallic number you want to choose.
This indicator calculates these metallic means using the standard alpha and beta formulas. For any metallic number k, alpha equals (k + sqrt(k² + 4)) / 2, and we generate retracement ratios by raising alpha to various negative powers. The script algorithmically generates these levels instead of hardcoding them, which is how it should have been done from the start. It's genuinely silly that most fib tools just hardcode the ratios when the math to generate them is straightforward. Even worse, traditional fib retracements use 0.5 as a level, which isn't even a fibonacci ratio. It's just thrown in there because it seems like it should be important.
The indicator works by first detecting swing points using the Sylvain Zig-Zag . The zig-zag identifies significant price swings by combining percentage change with ATR adjustments, filtering out noise and connecting major pivot points. This is what drives the retracement levels. Once a new swing is confirmed, the script calculates the range between the last two pivot points and generates metallic retracement levels from the most recent swing low or high.
You can adjust which metallic number to use (golden, silver, bronze, or any positive integer), control how many power ratios to display above and below the 1.0 level, and set how many complete retracement cycles you want drawn. The levels extend from the swing point and show you where price might react based on whichever metallic mean you've selected. The zig-zag settings let you tune the sensitivity of swing detection through ATR period, ATR multiplier, percentage reversal, and additional absolute or tick-based reversal values.
What this really demonstrates is that retracement analysis is more flexible than most traders realize. There's no mathematical law that says markets must respect the golden ratio over any other metallic mean. They're all valid mathematical constructs with the same kind of recursive properties. By making this tool, I wanted to highlight that using fibonacci retracements involves an arbitrary choice, and maybe that choice should be more deliberate or at least tested against alternatives. You can experiment with different metallic numbers and see which ones seem to work better for your particular market or timeframe, or just use this to understand that the standard fib levels everyone uses aren't as fundamental as they appear.
Herd Flow Oscillator — Volume Distribution Herd Flow Oscillator — Scientific Volume Distribution (herd-accurate rev)
A composite order-flow oscillator designed to surface true herding behavior — not just random bursts of buying or selling.
It’s built to detect when market participants start acting together, showing persistent, one-sided activity that statistically breaks away from normal market randomness.
Unlike traditional volume or momentum indicators, this tool doesn’t just look for “who’s buying” or “who’s selling.”
It tries to quantify crowd behavior by blending multiple statistical tests that describe how collective sentiment and coordination unfold in price and volume dynamics.
What it shows
The Herd Flow Oscillator works as a multi-layer detector of crowd-driven flow in the market. It examines how signed volume (buy vs. sell pressure) evolves, how persistent it is, and whether those actions are unusually coordinated compared to random expectations.
HerdFlow Composite (z) — the main signal line, showing how statistically extreme the current herding pressure is.
When this crosses above or below your set thresholds, it suggests a high probability of collective buying or selling.
You can optionally reveal component panels for deeper insight into why herding is detected:
DVI (Directional Volume Imbalance): Measures the ratio of bullish vs. bearish volume.
If it’s strongly positive, more volume is hitting the ask (buying); if negative, more is hitting the bid (selling).
LSV-style Herd Index : Inspired by academic finance measures of “herding.”
It compares how often volume is buying vs. selling versus what would happen by random chance.
If the result is significantly above chance, it means traders are collectively biased in one direction.
O rder-Flow Persistence (ρ 1..K): Averages autocorrelation of signed volume over several lags.
In simpler terms: checks if buying/selling pressure tends to continue in the same direction across bars.
Positive persistence = ongoing coordination, not just isolated trades.
Runs-Test Herding (−Z) : Statistical test that checks how often trade direction flips.
When there are fewer direction changes than expected, it means trades are clustering — a hallmark of herd behavior.
Skew (signed volume): Measures whether signed volume is heavily tilted to one side.
A positive skew means more aggressive buying bursts; a negative skew means more intense selling bursts.
CVD Slope (z): Looks at the slope of the Cumulative Volume Delta — essentially how quickly buy/sell pressure is accelerating.
It’s a short-term flow acceleration measure.
Shapes & background
▲ “BH” at the bottom = Bull Herding; ▼ “BH-” at the top = Bear Herding.
These markers appear when all conditions align to confirm a herding regime.
Persistence and clustering both confirm coordinated downside flow.
Core Windows
Primary Window (N) — the main sample length for herding calculations.
It’s like the "memory span" for detecting coordinated behavior. A longer N means smoother, more reliable signals.
Short Window (Nshort) — used for short-term measurements like imbalance and slope.
Smaller values react faster but can be noisy; larger values are steadier but slower.
Long Window (Nlong) — used for z-score normalization (statistical scaling).
This helps the indicator understand what’s “normal” behavior over a longer horizon, so it can spot when things deviate too far.
Autocorr lags (acLags) — how many steps to check when measuring persistence.
Higher values (e.g., 3–5) look further back to see if trends are truly continuing.
Calculation Options
Price Proxy for Tick Rule — defines how to decide if a trade is “buy” or “sell.”
hlc3 (average of high, low, and close) works as a neutral, smooth price proxy.
Use ATR for scaling — keeps signals comparable across assets and timeframes by dividing by volatility (ATR).
Prevents high-volatility periods from dominating the signal.
Median Filter (bars) — smooths out erratic data spikes without heavily lagging the response.
Odd values like 3 or 5 work best.
Signal Thresholds
Composite z-threshold — determines how extreme behavior must be before it counts as “herding.”
Higher values = fewer, more confident signals.
Imbalance threshold — the minimum directional volume imbalance to trigger interest.
Plotting
Show component panels — useful for analysts and developers who want to inspect the math behind signals.
Fill strong herding zones — purely visual aid to highlight key periods of coordinated trading.
How to use it (practical tips)
Understand the purpose: This is not just a “buy/sell” tool.
It’s a behavioral detector that identifies when traders or algorithms start acting in the same direction.
Timeframe flexibility:
15m–1h: reveals short-term crowd shifts.
4h–1D: better for swing-trade context and institutional positioning.
Combine with structure or trend:
When HerdFlow confirms a bullish regime during a breakout or retest, it adds confidence.
Conversely, a bearish cluster at resistance may hint at a crowd-driven rejection.
Threshold tuning:
To make it more selective, increase zThr and imbThr.
To make it more sensitive, lower those thresholds but expand your primary window N for smoother results.
Cross-market consistency:
Keep “Use ATR for scaling” enabled to maintain consistency across different instruments or timeframes.
Denoising:
A small median filter (3–5 bars) removes flicker from volume spikes but still preserves the essential crowd patterns.
Reading the components (why signals fire)
Each sub-metric describes a unique “dimension” of crowd behavior:
DVI: how imbalanced buying vs selling is.
Herd Index: how biased that imbalance is compared to random expectation.
Persistence (ρ): how continuous those flows are.
Runs-Test: how clumped together trades are — clustering means the crowd’s acting in sync.
Skew: how lopsided the volume distribution is — sudden surges of one-sided aggression.
CVD Slope: how strongly accelerating the current directional flow is.
When all of these line up, you’re seeing evidence that market participants are collectively moving in the same direction — i.e., true herding.
Friday & Monday HighlighterFriday & Monday Institutional Range Marker — Know Where Big Firms Set the Trap!
🧠 Description
This indicator automatically highlights Friday and Monday sessions on your chart — days when institutional players and algorithmic firms (like Citadel, Jane Street, or Tower Research) quietly shape the upcoming week’s price structure.
🔍 Why Friday & Monday matter
Friday : Large institutions often book profits or hedge into the weekend. Their final-hour moves reveal the next week’s bias.
Monday : Big players rebuild positions, absorbing liquidity left behind by retail traders.
Together, these two days define the range traps and breakout zones that often control price action until midweek.
> In short, the Friday–Monday high and low often act as invisible walls — guiding scalpers, option sellers, and swing traders alike.
🧩 What this tool does
✅ Highlights Friday (red) and Monday (green) sessions
✅ Adds optional day labels above bars
✅ Works across all timeframes (best on 15min to 1hr charts)
✅ Helps you visually identify where institutions likely built their positions
Use it to quickly spot:
* Range boundaries that trap traders
* Gap zones likely to get filled
* High–low sweeps before reversals
⚙️ Recommended Use
1. Mark Friday’s high–low → Watch for liquidity sweeps on Monday.
2. When Monday holds above Friday’s high , breakout continuation is likely.
3. When Monday fails below Friday’s low , expect a reversal or trap.
4. Combine this with OI shifts, IV crush, and FII–DII flow data for confirmation.
⚠️ Disclaimer
This indicator is for **educational and analytical purposes only**.
It does **not constitute financial advice** or a trading signal.
Markets are dynamic — always perform your own research before trading or investing.
3D Candles (Zeiierman)█ Overview
3D Candles (Zeiierman) is a unique 3D take on classic candlesticks, offering a fresh, high-clarity way to visualize price action directly on your chart. Visualizing price in alternative ways can help traders interpret the same data differently and potentially gain a new perspective.
█ How It Works
⚪ 3D Body Construction
For each bar, the script computes the candle body (open/close bounds), then projects a top face offset by a depth amount. The depth is proportional to that candle’s high–low range, so it looks consistent across symbols with different prices/precisions.
rng = math.max(1e-10, high - low ) // candle range
depthMag = rng * depthPct * factorMag // % of range, shaped by tilt amount
depth = depthMag * factorSign // direction from dev (up/down)
depthPct → how “thick” the 3D effect is, as a % of each candle’s own range.
factorMag → scales the effect based on your tilt input (dev), with a smooth curve so small tilts still show.
factorSign → applies the direction of the tilt (up or down).
⚪ Tilt & Perspective
Tilt is controlled by dev and translated into a gentle perspective factor:
slope = (4.0 * math.abs(dev)) / width
factorMag = math.pow(math.min(1.0, slope), 0.5) // sqrt softens response
factorSign = dev == 0 ? 0.0 : math.sign(dev) // direction (up/down)
Larger dev → stronger 3D presence (up to a cap).
The square-root curve makes small dev values noticeable without overdoing it.
█ How to Use
Traders can use 3D Candles just like regular candlesticks. The difference is the 3D visualization, which can broaden your view and help you notice price behavior from a fresh perspective.
⚪ Quick setup (dual-view):
Split your TradingView layout into two synchronized charts.
Right pane: keep your standard candlestick or bar chart for live execution.
Left pane: add 3D Candles (Zeiierman) to compare the same symbol/timeframe.
Observe differences: the 3D rendering can make expansion/contraction and body emphasis easier to spot at a glance.
█ Go Full 3D
Take the experience further by pairing 3D Candles (Zeiierman) with Volume Profile 3D (Zeiierman) , a perfect complement that shows where activity is concentrated, while your 3D candles show how the price unfolded.
█ Settings
Candles — How many 3D candles to draw. Higher values draw more shapes and may impact performance on slower machines.
Block Width (bars) — Visual thickness of each 3D candle along the x-axis. Larger values look chunkier but can overlap more.
Up/Down — Controls the tilt and strength of the 3D top face.
3D depth (% of range) — Thickness of the 3D effect as a percentage of each candle’s own high–low range. Larger values exaggerate the depth.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
Machine Learning Price Predictor: Ridge AR [Bitwardex]🔹Machine Learning Price Predictor: Ridge AR is a research-oriented indicator demonstrating the use of Regularized AutoRegression (Ridge AR) for short-term price forecasting.
The model combines autoregressive structure with Ridge regularization , providing stability under noisy or volatile market conditions.
The latest version introduces Bull and Bear signals , visually representing the current momentum phase and model direction directly on the chart.
Unlike traditional linear regression, Ridge AR minimizes overfitting, stabilizes coefficient dynamics, and enhances predictive consistency in correlated datasets.
The script plots:
Fit Line — in-sample fitted data;
Forecast Line — out-of-sample projection;
Trend Segments — color-coded bullish/bearish sections;
Bull/Bear Labels 🐂🐻 — dynamic visual signals showing directional bias.
Designed for researchers, students, and developers, this tool helps explore regularized time-series forecasting in Pine Script™.
🧩 Ridge AR Settings
Training Window — number of bars used for model training;
Forecast Horizon — forecast length (bars ahead);
AR Order — number of lags used as features;
Ridge Strength (λ) — regularization coefficient;
Damping Factor — exponential trend decay rate;
Trend Length — period for trend/volatility estimation;
Momentum Weight — strength of the recent move;
Mean Reversion — pullback intensity toward the mean.
🧮 Data Processing
Prefilter:
None — raw close price;
EMA — exponential smoothing;
SuperSmoother — Ehlers filter for noise reduction.
EMA Length, SuperSmoother Length — smoothing parameters.
🖥️ Display Settings
Update Mode:
Lock — static model;
Update Once Reached — rebuild after forecast horizon;
Continuous — update every bar.
Forecast Color — projection line color;
Bullish/Bearish Colors — colors for trend segments.
🐂🐻 Bull/Bear Signal System
The Bull/Bear Signal System adds directional visual cues to highlight local momentum shifts and model-based trend confirmation.
Bull (🐂) — appears when upward momentum is confirmed (momentum > 0) .
Displayed below the bar, colored with Bullish Color.
Bear (🐻) — appears when downward momentum is dominant (momentum < 0) .
Displayed above the bar, colored with Bearish Color.
Signals are generated during model recalculations or when the directional bias changes in Continuous mode.
These visual markers are analytical aids , not trading triggers.
🧠 Core Algorithmic Components
Regularized AutoRegression (Ridge AR):
Solves: (X′X+λI)−1X′y
to derive stable regression coefficients.
Matrix and Pseudoinverse Operations — implemented natively in Pine Script™.
Prefiltering (EMA / Ehlers SuperSmoother) — stabilizes noisy data.
Forecast Dynamics — integrates damping, momentum, and mean reversion.
Trend Visualization — color-coded bullish/bearish line segments.
Bull/Bear Signal Engine — visualizes real-time impulse direction.
📊 Applications
Academic and educational purposes;
Demonstration of Ridge Regression and AR models;
Analysis of bull/bear market phase transitions;
Visualization of time-series dependencies.
⚠️ Disclaimer
This script is provided for educational and research purposes only.
It does not provide trading or investment advice.
The author assumes no liability for financial losses resulting from its use.
Use responsibly and at your own risk.
ADX - Globx Options & Futures 2.0The ADX Globx Options & Futures is a custom-built trend strength indicator designed to replicate and enhance the classic Average Directional Index (ADX) model, commonly used in professional trading platforms such as IQ Option.
This version is optimized for options and futures trading, providing precise directional strength readings through adaptive smoothing and configurable parameters.
Concept and Logic
This indicator measures the strength of the current trend, regardless of its direction (bullish or bearish), by comparing directional movement between price highs and lows over a defined period.
It uses three main components:
+DI (Positive Directional Indicator): represents bullish strength.
–DI (Negative Directional Indicator): represents bearish strength.
ADX (Average Directional Index): measures the intensity of the prevailing trend, independent of direction.
The script follows the original logic proposed by J. Welles Wilder Jr., but introduces enhanced smoothing flexibility.
Users can choose between EMA (Exponential Moving Average) and Wilder’s RMA (Running Moving Average) for both DI and ADX calculations, allowing closer alignment with various platform implementations (IQ Option, MetaTrader, etc.).
How It Works
Directional Movement Calculation
The script computes upward and downward movements (+DM and –DM) by comparing the differences in highs and lows between consecutive candles.
Only positive directional changes that exceed the opposite side are considered.
This ensures each bar contributes only one valid directional movement.
True Range and Smoothing
The True Range (TR) is calculated using ta.tr(true) to include price gaps—replicating how professional derivatives platforms account for volatility jumps.
Both TR and DM values are smoothed using the selected averaging method (EMA or Wilder).
Directional Index and ADX
The smoothed +DI and –DI values are normalized over the True Range to form the Directional Index (DX), which measures the percentage difference between the two.
The ADX is then derived by smoothing the DX values, providing a stable reading of overall market strength.
Visual Representation
The ADX (white line) indicates the overall trend strength.
The +DI (dark blue) and –DI (dark red) lines show which side (bullish or bearish) is currently dominant.
Reference levels at 20 and 25 serve as strength thresholds:
Below 20 → Weak or sideways market.
Above 25 → Strong and directional trend.
Usage and Interpretation
When ADX rises above 25, the market shows a strong trend — use +DI > –DI for bullish confirmation, or the opposite for bearish momentum.
A falling ADX suggests decreasing trend strength and potential consolidation.
The default parameters (ADX Length = 34, DI Length = 34, both smoothed by EMA) match IQ Option’s internal ADX configuration, ensuring consistency between platforms.
Works on any timeframe or asset class, but is especially tuned for futures and options volatility dynamics.
Originality and Improvements
Unlike many open-source ADX indicators, this version:
Recreates IQ Option’s 34-length EMA-based ADX calculation with exact parameter alignment.
Provides selectable smoothing algorithms (EMA or Wilder) to switch between modern and classic formulations.
Uses dark-theme-optimized visuals with fine line weight and subtle contrast for clean visibility.
Maintains constant guide levels (20/25) rendered globally for precision and style compliance in Pine Script v6.
Is fully rewritten for Pine Script v6, ensuring compatibility and optimized execution.
Recommended Use
Combine with trend-following systems or breakout strategies.
Ideal for identifying market strength before engaging in options directionals or futures entries.
Use the ADX to confirm breakout momentum or filter sideways markets.
Disclaimer
This script is for educational and analytical purposes. It does not constitute financial advice or a trading signal. Users are encouraged to validate the indicator within their own trading strategies and risk frameworks.
Market Structure Report Library [TradingFinder]🔵 Introduction
Market Structure is one of the most fundamental concepts in Price Action and Smart Money theory. In simple terms, it represents how price moves between highs and lows and reveals which phase of the market cycle we are currently in uptrend, downtrend, or transition.
Each structure in the market is formed by a combination of Breaks of Structure (BoS) and Changes of Character (CHoCH) :
BoS occurs when the market breaks a previous high or low, confirming the continuation of the current trend.
CHoCH occurs when price breaks in the opposite direction for the first time, signaling a potential trend reversal.
Since price movement is inherently fractal, market structure can be analyzed on two distinct levels :
Major / External Structure: represents the dominant macro trend.
Minor / Internal Structure: represents corrective or smaller-scale movements within the larger trend.
🔵 Library Purpose
The “Market Structure Report Library” is designed to automatically detect the current market structure type in real time.
Without drawing or displaying any visuals, it analyzes raw price data and returns a series of logical and textual outputs (Return Values) that describe the current structural state of the market.
It provides the following information :
Trend Type :
External Trend (Major): Up Trend, Down Trend, No Trend
Internal Trend (Minor): Up Trend, Down Trend, No Trend
Structure Type :
BoS : Confirms trend continuation
CHoCH : Indicates a potential trend reversal
Consecutive BoS Counter : Measures trend strength on both Major and Minor levels.
Candle Type : Returns the current candle’s condition(Bullish, Bearish, Doji)
This library is specifically designed for use in Smart Money–based screeners, indicators, and algorithmic strategies.
It can analyze multiple symbols and timeframes simultaneously and return the exact structure type (BoS or CHoCH) and trend direction for each.
🔵 Function Outputs
The function MS() processes the price data and returns seven key outputs,
each representing a distinct structural state of the market. These values can be used in indicators, strategies, or multi-symbol screeners.
🟣 ExternalTrend
Type : string
Description : Represents the direction of the Major (External) market structure.
Possible values :
Up Trend
Down Trend
No Trend
This is determined based on the behavior of Major Pivots (swing highs/lows).
🟣 InternalTrend
Type : string
Description : Represents the direction of the Minor (Internal) market structure.
Possible values :
Up Trend
Down Trend
No Trend
🟣 M_State
Type : string
Description : Specifies the type of the latest Major Structure event.
Possible values :
BoS
CHoCH
🟣 m_State
Type : string
Description : Specifies the type of the latest Minor Structure event.
Possible values :
BoS
CHoCH
🟣 MBoS_Counter
Type : integer
Description : Counts the number of consecutive structural breaks (BoS) in the Major structure.
Useful for evaluating trend strength :
Increasing count: indicates trend continuation.
Reset to zero: typically occurs after a CHoCH.
🟣 mBoS_Counter
Type : integer
Description : Counts the number of consecutive structural breaks in the Minor structure.
Helps analyze the micro structure of the market on lower timeframes.
Higher value : strong internal trend.
Reset : indicates a minor pullback or reversal.
🟣 Candle_Type
Type : string
Description : Represents the type of the current candle.
Possible values :
Bullish
Bearish
Doji
import TFlab/Market_Structure_Report_Library_TradingFinder/1 as MSS
PP = input.int (5 , 'Market Structure Pivot Period' , group = 'Symbol 1' )
= MSS.MS(PP)
Session Volume Spike Detector (MTF Arrows)Overview
The Session Volume Spike Detector is a precision multi-timeframe (MTF) tool that identifies sudden surges in buy or sell volume during key market windows. It highlights high-impact institutional participation by comparing current volume against its historical baseline and short-term highs, then plots directional markers on your chart.
This version adds MTF awareness, showing spikes from 1-minute, 5-minute, and 10-minute frames on a single chart. It’s ideal for traders monitoring microstructure shifts across multiple time compressions while staying on a fast chart (like 1-second or 1-minute).
Key Features
Dual Session Windows (DST-aware)
Automatically tracks Morning (05:30–08:30 MT) and Midday (11:00–13:30 MT) activity, adjusted for daylight savings.
Directional Spike Detection
Flags Buy spikes (green triangles) and Sell spikes (magenta triangles) using dynamic volume gates, Z-Score normalization, and recent-bar jump filters.
Multi-Timeframe Projection
Displays higher-timeframe (1m / 5m / 10m) spikes directly on your active chart for continuous visual context — even on sub-minute intervals.
Adaptive Volume Logic
Each spike is validated against:
Volume ≥ SMA × multiplier
Volume ≥ recent-high × jump factor
Optional Z-Score threshold for statistical significance
Session-Only Filtering
Ensures spikes are only plotted within specified trading sessions — ideal for futures or intraday equity traders.
Configurable Alerts
Built-in alert conditions for:
Any timeframe (MTF aggregate)
Individual 1m, 5m, or 10m windows
Alerts trigger only when a new qualifying spike appears at the close of its bar.
Use Cases
Detect algorithmic or institutional activity bursts inside your trading window.
Track confluence of volume surges across multiple timeframes.
Combine with FVGs, bank levels, or range breakouts to identify probable continuation or reversal zones.
Build custom automation or alert workflows around statistically unusual participation spikes.
Recommended Settings
Use on 1-minute chart for full MTF display.
Adjust the SMA length (default 20) and Z-Score threshold (default 3.0) to suit market volatility.
For scalping or high-frequency environments, disable the 10m layer to reduce visual clutter.
Credits
Developed by Jason Hyde
© 2025 — All rights reserved.
Designed for clarity, precision, and MTF-synchronized institutional volume detection.
Bitcoin Cycle History Visualization [SwissAlgo]BTC 4-Year Cycle Tops & Bottoms
Historical visualization of Bitcoin's market cycles from 2010 to present, with projections based on weighted averages of past performance.
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CALCULATION METHODOLOGY
Why Bottom-to-Bottom Cycle Measurement?
This indicator defines cycles as bottom-to-bottom periods. This is one of several valid approaches to Bitcoin cycle analysis:
- Focuses on market behavior (price bottoms) rather than supply schedule events (halving-to-halving)
- Bottoms may offer good reference points for some analytical purposes
- Tops tend to be extended periods that are harder to define precisely
- Aligns with how some traditional asset cycles are measured and the timing observed in the broader "risk-on" assets category
- Halving events are shown separately (yellow backgrounds) for reference
- Neither halving-based nor bottom-based measurement is inherently superior
Different analysts prefer different cycle definitions based on their analytical goals. This approach prioritizes observable market turning points.
Cycle Date Definitions
- Approximate monthly ranges used for each event (e.g., Nov 2022 bottom = Nov 1-30, 2022)
- Cycle 1: Jul 2010 bottom → Jun 2011 top → Nov 2011 bottom
- Cycle 2: Nov 2011 bottom → Dec 2013 top → Jan 2015 bottom
- Cycle 3: Jan 2015 bottom → Dec 2017 top → Dec 2018 bottom
- Cycle 4: Dec 2018 bottom → Nov 2021 top → Nov 2022 bottom
- Future cycles will be added as new top/bottom dates become firm
Duration Calculations
- Days = timestamp difference converted to days (milliseconds ÷ 86,400,000)
- Bottom → Top: days from cycle bottom to peak
- Top → Bottom: days from peak to next cycle bottom
- Bottom → Bottom: full cycle duration (sum of above)
Price Change Calculations
- % Change = ((New Price - Old Price) / Old Price) × 100
- Example: $200 → $19,700 = ((19,700 - 200) / 200) × 100 = 9,750% gain
- Approximate historical prices used (rounded to significant figures)
Weighted Average Formula
Recent cycles weighted more heavily to reflect the evolved market structure:
- Cycle 1 (2010-2011): EXCLUDED (too early-stage, tiny market cap)
- Cycle 2 (2011-2015): Weight = 1x
- Cycle 3 (2015-2018): Weight = 3x
- Cycle 4 (2018-2022): Weight = 5x
Formula: Weighted Avg = (C2×1 + C3×3 + C4×5) / (1+3+5)
Example for Bottom→Top days: (761×1 + 1065×3 + 1066×5) / 9 = 1,032 days
Projection Method
- Projected Top Date = Nov 2022 bottom + weighted avg Bottom→Top days
- Projected Bottom Date = Nov 2022 bottom + weighted avg Bottom→Bottom days
- Current days elapsed compared to weighted averages
- Warning symbol (⚠) shown when the current cycle exceeds the historical average
Technical Implementation
- Historical cycle dates are hardcoded (not algorithmically detected)
- Dates represent approximate monthly ranges for each event
- The indicator will be updated as the Cycle 5 top and bottom dates become confirmed
- Updates require manual code maintenance - not automatic
- Users should verify they're using the latest version for current cycle data
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FEATURES
- Background highlights for historical tops (red), bottoms (green), and halving events (yellow)
- Data table showing cycle durations and price changes
- Visual cycle boundary boxes with subtle coloring
- Projected timeframes displayed as dashed vertical lines
- Toggle on/off for each visual element
- Customizable background colors
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DISPLAY SETTINGS
- Show/hide cycle tops, bottoms, halvings, data table, and cycle boxes
- Customizable background colors for each event type
- Clean, institutional-grade visual design suitable for analysis
UPDATES & MAINTENANCE
This indicator is maintained as new cycle events occur. When Cycle 5's top and bottom are confirmed with sufficient time elapsed, the code and projections will be updated accordingly. Check for the latest version periodically.
OPEN SOURCE
Code available for review, modification, and improvement. Educational transparency is prioritized.
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IMPORTANT LIMITATIONS
⚠ EXTREMELY SMALL SAMPLE SIZE
Based on only 4 complete cycles (2011-2022). In statistical analysis, this is insufficient for reliable predictions.
⚠ CHANGED MARKET STRUCTURE
Bitcoin's market has fundamentally evolved since early cycles:
- 2010-2015: Tiny market cap, retail-only, unregulated
- 2024-2025: Institutional adoption, spot ETFs, regulatory frameworks, macro correlation
The environment that created past patterns no longer exists in the same form.
⚠ NO PREDICTIVE GUARANTEE
Historical patterns can and do break. Market cycles are not laws of physics. Past performance does not guarantee future results. The next cycle may not follow historical averages.
⚠ LENGTHENING CYCLE THEORY
Some analysts believe cycles are extending over time (diminishing returns, maturing market). If true, simple averaging underestimates future cycle lengths.
⚠ SELF-FULFILLING PROPHECY RISK
The halving narrative may be partially circular - it works because people believe it works. Sufficient changes in market structure or participant behavior can invalidate the pattern.
⚠ APPROXIMATE DATA
Historical prices rounded to significant figures. Exact bottom/top dates vary by exchange. Month-long ranges are used for simplicity.
EDUCATIONAL USE ONLY
This indicator is designed for historical analysis and understanding Bitcoin's past behavior. It is NOT:
- Trading advice or financial recommendations
- A guarantee or prediction of future price movements
- Suitable as a sole basis for investment decisions
- A replacement for fundamental or technical analysis
The projections show "what if the pattern continues exactly" - not "what will happen."
Always conduct independent research, understand the risks, and consult qualified financial advisors before making investment decisions. Only invest what you can afford to lose.
Triple Gaussian Smoothed Ribbon [BOSWaves]Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework
Overview
The Triple Gaussian Smoothed Ribbon is a next-generation market visualization framework built on the principles of Gaussian filtering - a mathematical model from digital signal processing designed to remove noise while preserving the integrity of the underlying trend.
Unlike conventional moving averages that suffer from phase lag and overreaction to volatility spikes, Gaussian smoothing produces a symmetrical, low-lag curve that isolates meaningful directional shifts with exceptional clarity.
Developed under the Adaptive Gaussian Framework, this indicator extends the classical Gaussian model into a multi-stage smoothing and visualization system. By layering three progressive Gaussian filters and rendering their interactions as a gradient-based ribbon field, it translates market energy into a coherent, visually structured trend environment. Each ribbon layer represents a progressively smoothed component of price motion, producing a high-fidelity gradient field that evolves in sync with real-time trend strength and momentum.
The result is a uniquely fluid trend and reversal detection system - one that feels organic, adapts seamlessly across timeframes, and reveals hidden transitions in market structure long before traditional indicators confirm them.
Theoretical Foundation
The Gaussian filter, derived from the Gaussian function developed by Carl Friedrich Gauss in 1809, operates on the principle of weighted symmetry, assigning higher importance to central price data while tapering influence toward historical extremes following a bell-curve distribution. This symmetrical design minimizes phase distortion and smooths without introducing lag spikes — a stark contrast to exponential or linear filters that sacrifice temporal accuracy for responsiveness.
By cascading three Gaussian stages in sequence, the indicator creates a multi-frequency decomposition of price action:
The first stage captures immediate trend transitions.
The second absorbs mid-term volatility ripples.
The third stabilizes structural directionality.
The final composite ribbon reflects the market’s dominant frequency - a smoothed yet reactive trend spine - while an independent, heavier Gaussian smoothing serves as a reference layer to gauge whether the primary motion leads or lags relative to broader market structure.
This multi-layered Gaussian framework effectively replicates the behavior of a signal-processing filter bank: isolating meaningful cyclical movements, suppressing random noise, and revealing phase shifts with minimal delay.
How It Works
Triple Gaussian Core
Price data is passed through three successive Gaussian smoothing stages, each refining the trend further and removing higher-frequency distortions.
The result is a fluid, continuously adaptive baseline that responds naturally to directional changes without overshooting or flattening key inflection points.
Adaptive Ribbon Architecture
The indicator visualizes its internal dynamics through a five-layer gradient ribbon. Each layer represents a progressively delayed Gaussian curve, creating a color field that dynamically shifts between bullish and bearish tones.
Expanding ribbons indicate accelerating momentum and trend conviction.
Compressing ribbons reflect consolidation and volatility contraction.
The smooth color gradient provides a real-time depiction of energy buildup or dissipation within the trend, making it visually clear when the market is entering a state of expansion, transition, or exhaustion.
Momentum-Weighted Opacity
Ribbon transparency adjusts according to normalized momentum strength.
As trend force builds, colors intensify and layers become more opaque, signifying conviction.
When momentum wanes, ribbons fade - an early visual cue for potential reversals or pauses in trend continuation.
Candle Gradient Integration
Optional candle coloring ties the chart’s candles to the prevailing Gaussian gradient, allowing traders to view raw price action and smoothed wave dynamics as a unified system.
This integration produces a visually coherent chart environment that communicates directional intent instantly.
Signal Detection Logic
Directional cues emerge when the smoother, broader Gaussian curve crosses the faster-reacting Gaussian line, marking structural inflection points in the filtered trend.
Bullish shifts : short-term momentum transitions upward through the long-term baseline after a localized trough.
Bearish shifts : momentum declines through the baseline following a local peak.
To maintain integrity in choppy markets, the framework applies a trend-strength and separation filter, which blocks weak or overlapping conditions where movement lacks conviction.
Interpretation
The Triple Gaussian Smoothed Ribbon provides a layered, intuitive read on market structure:
Trend Continuation : Expanding ribbons with deep color intensity confirm directional strength.
Reversal Phases : Color gradients flip direction, indicating a phase shift or exhaustion point.
Compression Zones : Tight, pale ribbons reveal equilibrium phases often preceding breakouts.
Momentum Divergence : Fading color intensity despite continued price movement signals weakening conviction.
These transitions mirror the natural ebb and flow of market energy - captured through the Gaussian filter’s ability to represent smooth curvature without distortion.
Strategy Integration
Trend Following
Engage during strong directional expansions. When ribbons widen and color gradients intensify, the trend is accelerating with high confidence.
Reversal Identification
Monitor for full gradient inversion and fading momentum opacity. These conditions often precede transitional phases and early reversals.
Breakout Anticipation
Flat, compressed ribbons signal low volatility and energy buildup. A sudden gradient expansion with renewed opacity confirms breakout initiation.
Multi-Timeframe Alignment
Use higher timeframes to establish directional bias and lower timeframes for entry during compression-to-expansion transitions.
Technical Implementation Details
Triple Gaussian Stack : Sequential smoothing stages produce low-lag, high-purity signals.
Adaptive Ribbon Rendering : Five-layer Gaussian visualization for gradient-based trend depth.
Momentum Normalization : Opacity dynamically tied to trend strength and volatility context.
Consolidation Filter : Suppresses false signals in low-energy or range-bound conditions.
Integrated Candle Mode : Optional color synchronization with underlying gradient flow.
Alert System : Built-in notifications for bullish and bearish transitions.
This structure blends the precision of digital signal processing with the readability of visual market analysis, creating a clean but information-rich framework.
Optimal Application Parameters
Asset Recommendations
Cryptocurrency : Higher smoothing and sigma for stability under volatility.
Forex : Balanced parameters for cycle identification and reduced noise.
Equities : Moderate Gaussian length for responsive yet stable trend reads.
Indices & Futures : Longer smoothing periods for structural confirmation.
Timeframe Recommendations
Scalping (1 - 5m) : Use shorter smoothing for fast reactivity.
Intraday (15m - 1h) : Mid-length Gaussian chain for balance.
Swing (4h - 1D) : Prioritize clarity and opacity-driven trend phases.
Position (Daily - Weekly) : Longer smoothing to capture macro rhythm.
Performance Characteristics
Most Effective In :
Trending markets with recurring volatility cycles.
Transitional phases where early directional confirmation is crucial.
Less Effective In:
Ultra-low volume markets with erratic tick data.
Random, micro-chop conditions with no structural flow.
Integration Guidelines
Pair with volatility or volume expansion tools for enhanced breakout confirmation.
Use ribbon compression to anticipate volatility shifts.
Align entries with gradient expansion in the dominant color direction.
Scale position size relative to opacity strength and ribbon width.
Disclaimer
The Triple Gaussian Smoothed Ribbon – Adaptive Gaussian Framework is designed as a signal visualization and trend interpretation tool, not a standalone trading system. Its accuracy depends on appropriate parameter tuning, contextual confirmation, and disciplined risk management. It should be applied as part of a comprehensive technical or algorithmic trading strategy.
Katana_Fox RSI Pro - Advanced Momentum Indicator with Clear BUOverview:
Connors RSI Pro is a sophisticated enhancement of the classic Connors RSI indicator, designed for traders who demand professional-grade tools. This premium version combines multiple momentum components with intelligent signaling and beautiful visualization to give you an edge in the markets.
Key Features:
🎯 Clear BUY/SELL Signal System
BUY signals in green when CRSI crosses above oversold level
SELL signals in red when CRSI crosses below overbought level
Clean, professional labels that are easy to read
Customizable overbought/oversold levels (70/30 default)
🎨 Professional Visualization
Modern color scheme that adapts to market conditions
Customizable background fills for better readability
Smooth, easy-to-read line plotting
⚡ Enhanced Calculations
Triple-component momentum analysis (RSI, UpDown RSI, Percent Rank)
EMA smoothing for reduced noise and false signals
Configurable lengths for each component
🔔 Advanced Alert System
4 distinct alert conditions for various market scenarios
Compatible with TradingView's native alert system
Perfect for automated trading strategies
Input Parameters:
RSI Length (3): Period for standard RSI calculation
UpDown Length (2): Period for UpDown RSI component
ROC Length (100): Period for Rate of Change percentile ranking
Signal Alerts: Toggle BUY/SELL signals on/off
Custom Colors: Choose between classic and modern color schemes
Trading Signals:
BUY (Green Label): Bullish signal when CRSI crosses above oversold level
SELL (Red Label): Bearish signal when CRSI crosses below overbought level
Background Colors: Visual zones indicating momentum strength
Ideal For:
Swing traders seeking momentum reversals
Day traders looking for overbought/oversold conditions
Algorithmic traders needing reliable signals
Technical analysts wanting multi-timeframe confirmation
How to Use:
Oversold Bounce: Enter long when CRSI shows BUY signal above 30
Overbought Rejection: Enter short when CRSI shows SELL signal below 70
Trend Confirmation: Use the 50-level crossover for trend direction
Divergence Trading: Look for price/indicator divergences at extremes
Upgrade your trading arsenal with Connors RSI Pro - where professional analytics meet clear trading signals!
Multi-TF FVG Kerze Break AlertHere's a breakdown of the key files:
App.tsx: This is the main component that orchestrates the entire user interface. It manages the application's state, including the input Pine Script, the selected target language, the resulting converted code, and the loading/error states.
services/geminiService.ts: This file handles all communication with the Google Gemini API. It takes the Pine Script and the target language, constructs a detailed prompt instructing the AI on how to perform the conversion, sends the request, and processes the response.
components/CodeEditor.tsx: A reusable UI component that provides a styled for both displaying the input Pine Script and the read-only output.
constants.ts: This file centralizes static data. It contains the list of target languages for the dropdown menu and the default Pine Script code that loads when the application first starts.
index.html & index.tsx: These are the standard entry points for the React application, responsible for setting up the web page and mounting the main App component.
In essence, the application provides a user-friendly interface for developers to convert financial trading algorithms written in TradingView's Pine Script into other popular programming languages, leveraging the power of the Gemini AI model to perform the translation.
Synthetic Implied APROverview
The Synthetic Implied APR is an artificial implied APR, designed to imitate the implied APR seen when trading cryptocurrency funding rates. It combines real-time funding rates with premium data to calculate an artificial market expectation of the annualized funding rate.
The (actual) implied APR is the market's expectation of the annualized funding rate. This is dependent on bid/ask impacts of the implied APR, something which is currently unavailable to fetch with TradingView. In essence, an implied APR of X% means traders believe that asset's funding fees to average X% when annualized.
What's important to understand, is that the actual value of the synthetic implied APR is not relevant. We only simply use its relative changes when we trade (i.e if it crosses above/below its MA for a given weight). Even for the same asset, the implied APRs will change depending on days to maturity.
How it calculates
The synthetic implied APR is calculated with these steps:
Collects premium data from perpetual futures markets using optimized lower timeframe requests (check my 'Predicted Funding Rates' indicator)
Calculates the funding rate by adding the premium to an interest rate component (clamped within exchange limits)
Derives the underlying APR from the 8-hour funding rate (funding rate × 3 × 365)
Apply a weighed formula that imitates both the direction (underlying APR) with the volatility of prices (from the premium index and funding)
premium_component = (prem_avg / 50 ) * 365
weighedprem = (weight * fr) + ((1 - weight) * apr) + (premium_component * 0.3)
impliedAPR = math.avg(weighedprem, ta.sma(apr, maLength))
How to use it: Generally
Preface: Funding rates are an indication of market sentiment
If funding is positive, generally the market is bullish as longs are willing to pay shorts funding
If funding is negative, generally the market is bearish as shorts are willing to pay longs funding
So, this script can be used like a typical oscillator:
Bullish: If implied APR > MA OR if implied APR MA is green
Bearish: If implied APR < MA OR if implied APR MA is red
The components:
Synthetic Implied APR: The main metric. At current setting of 0.7, it imitates volatility
Weight: The higher the value, the smoother the synthetic implied APR is (and MA too). This value is very important to the imitation. At 0.7, it imitates the actual volatility of the implied APR. At weight = 1, it becomes very smooth. Perfect for trading
Synthetic Implied APR Moving Average: A moving average of the Synthetic implied APR. Can choose from multiple selections, (SMA, EMA, WMA, HMA, VWMA, RMA)
How to use it: Trading Funding
When trading funding there're multiple ways to use it with different settings
Trade funding rates with trend changes
Settings: Weight = 1
Method 1: When the implied APR MA turns green, long funding rates (or short if red)
Method 2: When the implied APR crosses above the MA, long funding rates (or short when crosses below)
Trade funding rates with MA pullbacks
Settings: Weight = 0.7, timeframe 15m
In an uptrend: When implied APR crosses below then above the script, long funding opportunity
In an downtrend: When implied APR crosses above then below the script, shortfunding opportunity
You can determine the trend with the method before, using a weight of 1
To trade funding rates, it's best to have these 3 scripts at these settings:
Predicted Funding Rates: This allows you to see the predicted funding rates and see if they've maxxed out for added confluence too (+/-0.01% usually for Binance BTC futures)
Synthetic implied APR: At weight 1, the MA provides a good trend (whether close above/below or colour change)
Synthetic implied APR: At weight 0.7, it provides a good imitation of volatility
How to use it: Trading Futures
When trading futures:
You can determine roughly what the trend is, if the assumption is made that funding rates can help identify trends if used as a sentiment indicator. It should be supplemented with traditional trend trading methods
To prevent whipsaws, weight should remain high
Long trend: When the implied APR MA turns green OR when it crosses above its MA
Short trend: When the implied APR MA turns red OR when it below above its MA
Why it's original
This indicator introduces a unique synthetic weighting system that combines funding rates, underlying APR, and premium components in a way not found in existing TradingView scripts. Trading funding rates is a niche area, there aren't that many scripts currently available. And to my knowledge, there's no synthetic implied APR scripts available on TradingView either. So I believe this script to be original in that sense.
Notes
Because it depends on my triangular weighting algos, optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off. Best timeframes for intraday trading using this are 15m or 1 hour
The higher the timeframe, the lower the MA one should use. At 1 hour, 200 or higher is best. At say, 4h, length of 50 is best
Only works for coins that have a Binance premium index
Inputs
Funding Period - Select between "1 Hour" or "8 Hour" funding cycles. 8 hours is standard for Binance
Table - Toggle the information dashboard on/off to show or hide real-time metrics including funding rate, premium, and APR value
Weight - Controls the balance between funding rate (higher values = smoother) and APR (lower values = more responsive) in the calculation, ranging from 0.0 to 1.0. Default is 0.7, this imitates the volatility
Auto Timeframe Implied Length - Automatically calculates optimal smoothing length based on your chart timeframe for consistent behavior across different time periods
Manual Implied Length - Sets a fixed smoothing length (in bars) when auto mode is disabled, with lower values being more responsive and higher values being smoother
Show Implied APR MA - Displays an additional moving average line of the Synthetic Implied APR to help identify trend direction and crossover signals
MA Type for Implied APR - Selects the calculation method (SMA, EMA, WMA, HMA, VWMA, or RMA) for the moving average, each offering different responsiveness and lag characteristics
MA Length for Implied APR - Sets the lookback period (1-500 bars) for the moving average, with shorter lengths providing more signals and longer lengths filtering noise
Show Underlying APR - Displays the raw APR calculation (without synthetic weighting) as a reference line to compare against the main indicator
Bullish Color - Sets the color for positive values in the table and rising MA line
Bearish Color - Sets the color for negative values in the table and falling MA line
Table Background - Customizes the background color and transparency of the information dashboard
Table Text Color - Sets the color for label text in the left column of the information table
Table Text Size - Controls the font size of table text with options from Tiny to Huge
Adaptive Machine Learning Trading System [PhenLabs]📊Adaptive ML Trading System
Version: PineScript™v6
📌Description
The Adaptive ML Trading System is a sophisticated machine learning indicator that combines ensemble modeling with advanced technical analysis. This system uses XGBoost, Random Forest, and Neural Network algorithms to generate high-confidence trading signals while incorporating robust risk management features. Traders benefit from objective, data-driven decision-making that adapts to changing market conditions.
🚀Points of Innovation
• Machine Learning Ensemble - Three integrated models (XGBoost, Random Forest, Neural Network)
• Confidence-Based Trading - Only executes trades when ML confidence exceeds threshold
• Dynamic Risk Management - ATR-based stop loss and max drawdown protection
• Adaptive Position Sizing - Volatility-adjusted position sizing with confidence weighting
• Real-Time Performance Metrics - Live tracking of win rate, Sharpe ratio, and performance
• Multi-Timeframe Feature Analysis - Adaptive lookback periods for different market regimes
🔧Core Components
• ML Ensemble Engine - Weighted combination of XGBoost, Random Forest, and Neural Network outputs
• Feature Normalization System - Advanced preprocessing with custom tanh/sigmoid activation
• Risk Management Module - Dynamic position sizing and drawdown protection
• Performance Dashboard - Real-time metrics and risk status monitoring
• Alert System - Comprehensive alert conditions for entries, exits, and risk events
🔥Key Features
• High-confidence ML signals with customizable confidence thresholds
• Multiple trading modes (Conservative, Balanced, Aggressive) for different risk profiles
• Integrated stop loss and risk management with ATR-based calculations
• Real-time performance metrics including win rate and Sharpe ratio
• Comprehensive alert system with entry, exit, and risk management notifications
• Visual confidence bands and threshold indicators for easy signal interpretation
🎨Visualization
• ML Signal Line - Primary signal output ranging from -1 to +1
• Confidence Bands - Visual representation of model confidence levels
• Threshold Lines - Customizable buy/sell threshold levels
• Position Histogram - Current market position visualization
• Performance Tables - Real-time metrics display in customizable positions
📖Usage Guidelines
Model Configuration
• Confidence Threshold: Default 0.55, Range 0.5-0.95 - Minimum confidence for signals
• Model Sensitivity: Default 0.9, Range 0.1-2.0 - Adjusts signal sensitivity
• Ensemble Mode: Conservative/Balanced/Aggressive - Trading style preference
• Signal Threshold: Default 0.55, Range 0.3-0.9 - ML signal threshold for entries
Risk Management
• Position Size %: Default 10%, Range 1-50% - Portfolio percentage per trade
• Max Drawdown %: Default 15%, Range 5-30% - Maximum allowed drawdown
• Stop Loss ATR: Default 2.0, Range 0.5-5.0 - Stop loss in ATR multiples
• Dynamic Sizing: Default true - Volatility-based position adjustment
Display Settings
• Show Signals: Default true - Display entry/exit signals
• Show Threshold Signals: Default true - Display ±0.6 threshold crosses
• Show Confidence Bands: Default true - Display ML confidence levels
• Performance Dashboard: Default true - Show metrics table
✅Best Use Cases
• Swing trading with 1-5 day holding periods
• Trend-following strategies in established trends
• Volatility breakout trading during high-confidence periods
• Risk-adjusted position sizing for portfolio management
• Multi-timeframe confirmation for existing strategies
⚠️Limitations
• Requires sufficient historical data for accurate ML predictions
• May experience low confidence periods in choppy markets
• Performance varies across different asset classes and timeframes
• Not suitable for very short-term scalping strategies
• Requires understanding of basic risk management principles
💡What Makes This Unique
• True machine learning ensemble with multiple model types
• Confidence-based trading rather than simple signal generation
• Integrated risk management with dynamic position sizing
• Real-time performance tracking and metrics
• Adaptive parameters that adjust to market conditions
🔬How It Works
Feature Calculation: Computes 20+ technical features from price/volume data
Feature Normalization: Applies custom normalization for ML compatibility
Ensemble Prediction: Combines XGBoost, Random Forest, and Neural Network outputs
Signal Generation: Produces confidence-weighted trading signals
Risk Management: Applies position sizing and stop loss rules
Execution: Generates alerts and visual signals based on thresholds
💡Note:
This indicator works best on daily and 4-hour timeframes for most assets. Ensure you understand the risk management settings before live trading. The system includes automatic risk-off modes that halt trading during excessive drawdown periods.
Predicted Funding RatesOverview
The Predicted Funding Rates indicator calculates real-time funding rate estimates for perpetual futures contracts on Binance. It uses triangular weighting algorithms on multiple different timeframes to ensure an accurate prediction.
Funding rates are periodic payments between long and short position holders in perpetual futures markets
If positive, longs pay shorts (usually bullish)
If negative, shorts pay longs (usually bearish)
This is a prediction. Actual funding rates depend on the instantaneous premium index, derived from bid/ask impacts of futures. So whilst it may imitate it similarly, it won't be completely accurate.
This only applies currently to Binance funding rates, as HyperLiquid premium data isn't available. Other Exchanges may be added if their premium data is uploaded.
Methods
Method 1: Collects premium 1-minunute data using triangular weighing over 8 hours. This granular method fills in predicted funding for 4h and less recent data
Method 2: Multi-time frame approach. Daily uses 1 hour data in the calculation, 4h + timeframes use 15M data. This dynamic method fills in higher timeframes and parts where there's unavailable premium data on the 1min.
How it works
1) Premium data is collected across multiple timeframes (depending on the timeframe)
2) Triangular weighing is applied to emphasize recent data points linearly
Tri_Weighing = (data *1 + data *2 + data *3 + data *4) / (1+2+3+4)
3) Finally, the funding rate is calculated
FundingRate = Premium + clamp(interest rate - Premium, -0.05, 0.05)
where the interest rate is 0.01% as per Binance
Triangular weighting is calculated on collected premium data, where recent data receives progressively higher weight (1, 2, 3, 4...). This linear weighting scheme provides responsiveness to recent market conditions while maintaining stability, similar to an exponential moving average but with predictable, linear characteristics
A visual representation:
Data points: ──────────────>
Weights: 1 2 3 4 5
Importance: ▂ ▃ ▅ ▆ █
How to use it
For futures traders:
If funding is trending up, the market can be interpreted as being in a bull market
If trending down, the market can be interpreted as being in a bear market
Even used simply, it allows you to gauge roughly how well the market is performing per funding. It can basically be gauged as a sentiment indicator too
For funding rate traders:
If funding is up, it can indicate a long on implied APR values
If funding is down, it can indicate a short on implied APR values
It also includes an underlying APR, which is the annualized funding rate. For Binance, it is current funding * (24/8) * 365
For Position Traders: Monitor predicted funding rates before entering large positions. Extremely high positive rates (>0.05% for 8-hour periods) suggest overleveraged longs and potential reversal risk. Conversely, extreme negative rates indicate shorts dominance
Table:
Funding rate: Gives the predicted funding rate as a percentage
Current premium: Displays the current premium (difference between perpetual futures price and the underlying spot) as a percentage
Funding period: You can choose between 1 hour funding (HyperLiquid usually) and 8 hour funding (Binance)
APR: Underlying annualized funding rate
What makes it original
Whilst some predicted funding scripts exist, some aren't as accurate or have gaps in data. And seeing as funding values are generally missing from TV tickers, this gives traders accessibility to the script when they would have to use other platforms
Notes
Currently only compatible with symbols that have Binance USDT premium indices
Optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off
Actual funding rates may differ
Inputs
Funding Period: Choose between "8 Hour" (standard Binance cycle) or "1 Hour" (divides the 8-hour rate by 8 for granular comparison)
Plot Type: Display as "Funding Rate" (percentage per interval) or "APR" (annualized rate calculated as 8-hour rate × 3 × 365)
Table: Toggle the information table showing current funding rate, premium, funding period, and APR in the top-right corner
Positive Colour: Sets the colour for positive funding rates where longs pay shorts (default: #00ffbb turquoise)
Negative Colour: Sets the colour for negative funding rates where shorts pay longs (default: red)
Table Background: Controls the background colour and transparency of the information table (default: transparent dark blue)
Table Text Colour: Sets the colour for all text labels in the information table (default: white)
Table Text Size: Controls font size with options from Tiny to Huge, with Small as the default balance of readability and space
MACD Forecast [Titans_Invest]MACD Forecast — The Future of MACD in Trading
The MACD has always been one of the most powerful tools in technical analysis.
But what if you could see where it’s going, instead of just reacting to what has already happened?
Introducing MACD Forecast — the natural evolution of the MACD Full , now taken to the next level. It’s the world’s first MACD designed not only to analyze the present but also to predict the future behavior of momentum.
By combining the classic MACD structure with projections powered by Linear Regression, this indicator gives traders an anticipatory, predictive view, redefining what’s possible in technical analysis.
Forget lagging indicators.
This is the smartest, most advanced, and most accurate MACD ever created.
🍟 WHY MACD FORECAST IS REVOLUTIONARY
Unlike the traditional MACD, which only reflects current and past price dynamics, the MACD Forecast uses regression-based projection models to anticipate where the MACD line, signal line, and histogram are heading.
This means traders can:
• See MACD crossovers before they happen.
• Spot trend reversals earlier than most.
• Gain an unprecedented timing advantage in both discretionary and automated trading.
In other words: this indicator lets you trade ahead of time.
🔮 FORECAST ENGINE — POWERED BY LINEAR REGRESSION
At its core, the MACD Forecast integrates Linear Regression (ta.linreg) to project the MACD’s future behavior with exceptional accuracy.
Projection Modes:
• Flat Projection: Assumes trend continuity at the current level.
• LinReg Projection: Applies linear regression across N periods to mathematically forecast momentum shifts.
This dual system offers both a conservative and adaptive view of market direction.
📐 ACCURACY WITH FULL CUSTOMIZATION
Just like the MACD Full, this new version comes with 20 customizable buy-entry conditions and 20 sell-entry conditions — now enhanced with forecast-based rules that anticipate crossovers and trend reversals.
You’re not just reacting — you’re strategizing ahead of time.
⯁ HOW TO USE MACD FORECAST❓
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
🤖 BUILT FOR AUTOMATION AND BOTS 🤖
Whether for manual trading, quantitative strategies, or advanced algorithms, the MACD Forecast was designed to integrate seamlessly with automated systems.
With predictive logic at its core, your strategies can finally react to what’s coming, not just what already happened.
🥇 WHY THIS INDICATOR IS UNIQUE 🥇
• World’s first MACD with Linear Regression Forecasting
• Predictive Crossovers (before they appear on the chart)
• Maximum flexibility with Long & Short combinations — 20+ fully configurable conditions for tailor-made strategies
• Fully automatable for quantitative systems and advanced bots
This isn’t just an update.
It’s the final evolution of the MACD.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔮 Linear Regression Function 🔮
______________________________________________________
• Our indicator includes MACD forecasts powered by linear regression.
Forecast Types:
• Flat: Assumes prices will stay the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset : Offset.
• return: Linear regression curve.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : MACD Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
🎗️ In memory of João Guilherme — your light will live on forever.
Volume Profile 3D (Zeiierman)█ Overview
Volume Profile 3D (Zeiierman) is a next-generation volume profile that renders market participation as a 3D-style profile directly on your chart. Instead of flat histograms, you get a depth-aware profile with parallax, gradient transparency, and bull/bear separation, so you can see where liquidity stacked up and how it shifted during the move.
Highlights:
3D visual effect with perspective and depth shading for clarity.
Bull/Bear separation to see whether up bars or down bars created the volume.
Flexible colors and gradients that highlight where the most significant trading activity took place.
This is a state-of-the-art volume profile — visually powerful, highly flexible, and unlike anything else available.
█ How It Works
⚪ Profile Construction
The price range (from highest to lowest) is divided into a number of levels (buckets). Each bar’s volume is added to the correct level, based on its average price. This builds a map of where trading volume was concentrated.
You can choose to:
Aggregate all volume at each level, or
Split bullish vs. bearish volume , slightly offset for clarity.
This creates a clear view of which price zones matter most to the market.
⚪ 3D Effect Creation
The unique part of this indicator is how the 3D projection is built. Each volume block’s width is scaled to its relative size, then tilted with a slope factor to create a depth effect.
maxVol = bins.bu.max() + bins.be.max()
width = math.max(1, math.floor(bucketVol / maxVol * ((bar_index - start) * mult)))
slope = -(step * dev) / ((bar_index - start) * (mult/2))
factor = math.pow(math.min(1.0, math.abs(slope) / step), .5)
width → determines how far the volume extends, based on relative strength.
slope → creates the angled projection for the 3D look.
factor → adjusts perspective to make deeper areas shrink naturally.
The result is a 3D-style volume profile where large areas pop forward and smaller areas fade back, giving you immediate visual context.
█ How to Use
⚪ Support & Resistance Zones (HVNs and Value Area)
Regions where a lot of volume traded tend to act like walls:
If price approaches a high-volume area from above, it may act as support.
From below, it may act as resistance.
Traders often enter or exit near these zones because they represent strong agreement among market participants.
⚪ POC Rejections & Mean Reversions
The Point of Control (POC) is the single price level with the highest volume in the profile.
When price returns to the POC and rejects it, that’s often a signal for reversal trades.
In ranging markets, price may bounce between edges of the Value Area and revert to POC.
⚪ Breakouts via Low-Volume Zones (LVNs)
Low volume areas (gaps in the profile) offer path of least resistance:
Price often moves quickly through these thin zones when momentum builds.
Use them to spot breakouts or continuation trades.
⚪ Directional Insight
Use the bull/bear separation to see whether buyers or sellers dominated at key levels.
█ Settings
Use Active Chart – Profile updates with visible candles.
Custom Period – Fixed number of bars.
Up/Down – Adjust tilt for the 3D angle.
Left/Right – Scale width of the profile.
Aggregated – Merge bull/bear volume.
Bull/Bear Shift – Separate bullish and bearish volume.
Buckets – Number of price levels.
Choose from templates or set custom colors.
POC Gradient option makes high volume bolder, low volume lighter.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Advanced Market Structure [OmegaTools]📌 Market Structure
Advanced Market Structure is a next–generation indicator designed to decode price structure in real time by combining classical swing–based analysis with modern quantitative confirmation techniques. Built for traders who demand both precision and adaptability, it provides a robust multi–layered framework to identify structural shifts, trend continuations, and potential reversals across any asset class or timeframe.
Unlike traditional structure indicators that rely solely on visual swing identification, Market Structure introduces an integrated methodology: pivot detection, Donchian trend modeling, statistical confirmation via Z–Score, and volume–based validation. Each element contributes to a comprehensive, systematic representation of the underlying market dynamics.
🔑 Core Features
1. Five Distinct Market Structure Modes
Standard Mode:
Captures structural breaks through classical swing high/low pivots. Ideal for discretionary traders looking for clarity in directional bias.
Confirmed Breakout Mode:
Requires validation beyond the initial pivot break, filtering out noise and reducing false positives.
Donchian Trend HL (High/Low):
Establishes structure based on absolute highs and lows over rolling lookback windows. This approach highlights broader momentum shifts and trend–defining extremes.
Donchian Trend CC (Close/Close):
Similar to HL mode, but calculated using closing prices, enabling more precise bias identification where close–to–close structure carries stronger statistical weight.
Average Mode:
A composite methodology that synthesizes the four models into a weighted signal, producing a balanced structural bias designed to minimize model–specific weaknesses.
2. Dynamic Pivot Recognition with Auto–Updating Levels
Swing highs and lows are automatically detected and plotted with adaptive horizontal levels. These dynamic support/resistance markers continuously extend into the future, ensuring that historically significant levels remain visible and actionable.
3. Color–Adaptive Candlesticks
Price bars are dynamically recolored to reflect the prevailing structural regime: bullish (default blue), bearish (default red), or neutral (gray). This enables instant visual recognition of regime changes without requiring external confirmation.
4. Statistical Reversal Triggers
The script integrates a 21–period Z–Score calculation applied to closing prices, combined with multi–layered volume confirmation (SMA and EMA convergence).
Bullish trigger: Z–Score < –2 with structural confirmation and volume support.
Bearish trigger: Z–Score > +2 with structural confirmation and volume support.
Signals are plotted as diamond markers above or below the bars, identifying potential high–probability reversal setups in real time.
5. Integrated Alpha Backtesting Engine
Each market structure mode is evaluated through a built–in backtesting routine, tracking hit ratios and consistency across the most recent ~2000 structural events.
Performance metrics (“Alpha”) are displayed directly on–chart via a dedicated Performance Dashboard Table, allowing side–by–side comparison of Standard, Confirmed Breakout, Donchian HL, Donchian CC, and Average models.
Traders can instantly evaluate which structural methodology best adapts to the current market conditions.
🎯 Practical Advantages
Systematic Clarity: Eliminates subjectivity in defining structural bias, offering a rules–based framework.
Statistical Transparency: Built–in performance metrics validate each mode in real time, allowing informed decision–making.
Noise Reduction: Confirmed Breakouts and Donchian modes filter out common traps in structural trading.
Multi–Asset Adaptability: Optimized for scalping, intraday, swing, and multi–day strategies across FX, equities, futures, commodities, and crypto.
Complementary Usage: Works as a stand–alone structure identifier or as a quantitative filter in larger algorithmic/trading frameworks.
⚙️ Ideal Users
Discretionary traders seeking an objective reference for structural bias.
Quantitative/systematic traders requiring on–chart statistical validation of structural regimes.
Technical analysts leveraging pivots, Donchian channels, and price action as part of broader frameworks.
Portfolio traders integrating structure into multi–factor models.
💡 Why This Tool?
Market Structure is not a static indicator — it is an adaptive framework. By merging classical pivot theory with Donchian–style momentum analysis, and reinforcing both with statistical backtesting and volume confirmation, it provides traders with a unique ability:
To see the structure,
To measure its reliability,
And to act with confidence on quantifiably validated signals.
SCTI - D14SCTI - D14 Comprehensive Technical Analysis Suite
English Description
SCTI D14 is an advanced multi-component technical analysis indicator designed for professional traders and analysts. This comprehensive suite combines multiple analytical tools into a single, powerful indicator that provides deep market insights across various timeframes and methodologies.
Core Components:
1. EMA System (Exponential Moving Averages)
13 customizable EMA lines with periods ranging from 8 to 2584
Fibonacci-based periods (8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584)
Color-coded visualization for easy trend identification
Individual toggle controls for each EMA line
2. TFMA (Multi-Timeframe Moving Averages)
Cross-timeframe analysis with 3 independent EMA calculations
Real-time labels showing trend direction and price relationships
Customizable timeframes for each moving average
Percentage deviation display from current price
3. PMA (Precision Moving Average Cloud)
7-layer moving average system with customizable periods
Fill areas between moving averages for trend visualization
Support and resistance zone identification
Dynamic color-coded trend clouds
4. VWAP (Volume Weighted Average Price)
Multiple anchor points (Session, Week, Month, Quarter, Year, Earnings, Dividends, Splits)
Standard deviation bands for volatility analysis
Automatic session detection and anchoring
Statistical price level identification
5. Advanced Divergence Detector
12 technical indicators for divergence analysis (MACD, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, VW-MACD, CMF, MFI, External)
Regular and hidden divergences detection
Bullish and bearish signals with visual confirmation
Customizable sensitivity and filtering options
Real-time alerts for divergence formations
6. Volume Profile & Node Analysis
Comprehensive volume distribution analysis
Point of Control (POC) identification
Value Area High/Low (VAH/VAL) calculations
Volume peaks and troughs detection
Support and resistance levels based on volume
7. Smart Money Concepts
Market structure analysis with Break of Structure (BOS) and Change of Character (CHoCH)
Internal and swing structure detection
Equal highs and lows identification
Fair Value Gaps (FVG) detection and visualization
Liquidity zones and institutional flow analysis
8. Trading Sessions
9 major trading sessions (Asia, Sydney, Tokyo, Shanghai, Hong Kong, Europe, London, New York, NYSE)
Real-time session status and countdown timers
Session volume and performance tracking
Customizable session boxes and labels
Statistical session analysis table
Key Features:
Modular Design: Enable/disable any component independently
Real-time Analysis: Live updates with market data
Multi-timeframe Support: Works across all chart timeframes
Customizable Alerts: Set alerts for any detected pattern or signal
Professional Visualization: Clean, organized display with customizable colors
Performance Optimized: Efficient code for smooth chart performance
Use Cases:
Trend Analysis: Identify market direction using multiple EMA systems
Entry/Exit Points: Use divergences and structure breaks for timing
Risk Management: Utilize volume profiles and session analysis for better positioning
Multi-timeframe Analysis: Confirm signals across different timeframes
Institutional Analysis: Track smart money flows and market structure
Perfect For:
Day traders seeking comprehensive market analysis
Swing traders needing multi-timeframe confirmation
Professional analysts requiring detailed market structure insights
Algorithmic traders looking for systematic signal generation
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中文描述
SCTI - D14是一个先进的多组件技术分析指标，专为专业交易者和分析师设计。这个综合套件将多种分析工具整合到一个强大的指标中，在各种时间框架和方法论中提供深度市场洞察。
核心组件：
1. EMA系统（指数移动平均线）
13条可定制EMA线，周期从8到2584
基于斐波那契的周期（8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584）
颜色编码可视化，便于趋势识别
每条EMA线的独立切换控制
2. TFMA（多时间框架移动平均线）
跨时间框架分析，包含3个独立的EMA计算
实时标签显示趋势方向和价格关系
每个移动平均线的可定制时间框架
显示与当前价格的百分比偏差
3. PMA（精密移动平均云）
7层移动平均系统，周期可定制
移动平均线间填充区域用于趋势可视化
支撑阻力区域识别
动态颜色编码趋势云
4. VWAP（成交量加权平均价格）
多个锚点（交易时段、周、月、季、年、财报、分红、拆股）
标准差带用于波动性分析
自动时段检测和锚定
统计价格水平识别
5. 高级背离检测器
12个技术指标用于背离分析（MACD、RSI、随机指标、CCI、威廉姆斯%R、Bias、动量、OBV、VW-MACD、CMF、MFI、外部指标）
常规和隐藏背离检测
看涨看跌信号配视觉确认
可定制敏感度和过滤选项
背离形成的实时警报
6. 成交量分布与节点分析
全面的成交量分布分析
控制点（POC）识别
价值区域高/低点（VAH/VAL）计算
成交量峰值和低谷检测
基于成交量的支撑阻力水平
7. 聪明钱概念
市场结构分析，包括结构突破（BOS）和结构转变（CHoCH）
内部和摆动结构检测
等高等低识别
公允价值缺口（FVG）检测和可视化
流动性区域和机构资金流分析
8. 交易时区
9个主要交易时段（亚洲、悉尼、东京、上海、香港、欧洲、伦敦、纽约、纽交所）
实时时段状态和倒计时器
时段成交量和表现跟踪
可定制时段框和标签
统计时段分析表格
主要特性：
模块化设计：可独立启用/禁用任何组件
实时分析：随市场数据实时更新
多时间框架支持：适用于所有图表时间框架
可定制警报：为任何检测到的模式或信号设置警报
专业可视化：清洁、有序的显示界面，颜色可定制
性能优化：高效代码确保图表流畅运行
使用场景：
趋势分析：使用多重EMA系统识别市场方向
入场/出场点：利用背离和结构突破进行时机选择
风险管理：利用成交量分布和时段分析进行更好定位
多时间框架分析：在不同时间框架间确认信号
机构分析：跟踪聪明钱流向和市场结构
适用于：
寻求全面市场分析的日内交易者
需要多时间框架确认的摆动交易者
需要详细市场结构洞察的专业分析师
寻求系统化信号生成的算法交易者
