Half Causal EstimatorOverview
The Half Causal Estimator is a specialized filtering method that provides responsive averages of market variables (volume, true range, or price change) with significantly reduced time delay compared to traditional moving averages. It employs a hybrid approach that leverages both historical data and time-of-day patterns to create a timely representation of market activity while maintaining smooth output.
Core Concept
Traditional moving averages suffer from time lag, which can delay signals and reduce their effectiveness for real-time decision making. The Half Causal Estimator addresses this limitation by using a non-causal filtering method that incorporates recent historical data (the causal component) alongside expected future behavior based on time-of-day patterns (the non-causal component).
This dual approach allows the filter to respond more quickly to changing market conditions while maintaining smoothness. The name "Half Causal" refers to this hybrid methodology—half of the data window comes from actual historical observations, while the other half is derived from time-of-day patterns observed over multiple days. By incorporating these "future" values from past patterns, the estimator can reduce the inherent lag present in traditional moving averages.
How It Works
The indicator operates through several coordinated steps. First, it stores and organizes market data by specific times of day (minutes/hours). Then it builds a profile of typical behavior for each time period. For calculations, it creates a filtering window where half consists of recent actual data and half consists of expected future values based on historical time-of-day patterns. Finally, it applies a kernel-based smoothing function to weight the values in this composite window.
This approach is particularly effective because market variables like volume, true range, and price changes tend to follow recognizable intraday patterns (they are positive values without DC components). By leveraging these patterns, the indicator doesn't try to predict future values in the traditional sense, but rather incorporates the average historical behavior at those future times into the current estimate.
The benefit of using this "average future data" approach is that it counteracts the lag inherent in traditional moving averages. In a standard moving average, recent price action is underweighted because older data points hold equal influence. By incorporating time-of-day averages for future periods, the Half Causal Estimator essentially shifts the center of the filter window closer to the current bar, resulting in more timely outputs while maintaining smoothing benefits.
Understanding Kernel Smoothing
At the heart of the Half Causal Estimator is kernel smoothing, a statistical technique that creates weighted averages where points closer to the center receive higher weights. This approach offers several advantages over simple moving averages. Unlike simple moving averages that weight all points equally, kernel smoothing applies a mathematically defined weight distribution. The weighting function helps minimize the impact of outliers and random fluctuations. Additionally, by adjusting the kernel width parameter, users can fine-tune the balance between responsiveness and smoothness.
The indicator supports three kernel types. The Gaussian kernel uses a bell-shaped distribution that weights central points heavily while still considering distant points. The Epanechnikov kernel employs a parabolic function that provides efficient noise reduction with a finite support range. The Triangular kernel applies a linear weighting that decreases uniformly from center to edges. These kernel functions provide the mathematical foundation for how the filter processes the combined window of past and "future" data points.
Applicable Data Sources
The indicator can be applied to three different data sources: volume (the trading volume of the security), true range (expressed as a percentage, measuring volatility), and change (the absolute percentage change from one closing price to the next).
Each of these variables shares the characteristic of being consistently positive and exhibiting cyclical intraday patterns, making them ideal candidates for this filtering approach.
Practical Applications
The Half Causal Estimator excels in scenarios where timely information is crucial. It helps in identifying volume climaxes or diminishing volume trends earlier than conventional indicators. It can detect changes in volatility patterns with reduced lag. The indicator is also useful for recognizing shifts in price momentum before they become obvious in price action, and providing smoother data for algorithmic trading systems that require reduced noise without sacrificing timeliness.
When volatility or volume spikes occur, conventional moving averages typically lag behind, potentially causing missed opportunities or delayed responses. The Half Causal Estimator produces signals that align more closely with actual market turns.
Technical Implementation
The implementation of the Half Causal Estimator involves several technical components working together. Data collection and organization is the first step—the indicator maintains a data structure that organizes market data by specific times of day. This creates a historical record of how volume, true range, or price change typically behaves at each minute/hour of the trading day.
For each calculation, the indicator constructs a composite window consisting of recent actual data points from the current session (the causal half) and historical averages for upcoming time periods from previous sessions (the non-causal half). The selected kernel function is then applied to this composite window, creating a weighted average where points closer to the center receive higher weights according to the mathematical properties of the chosen kernel. Finally, the kernel weights are normalized to ensure the output maintains proper scaling regardless of the kernel type or width parameter.
This framework enables the indicator to leverage the predictable time-of-day components in market data without trying to predict specific future values. Instead, it uses average historical patterns to reduce lag while maintaining the statistical benefits of smoothing techniques.
Configuration Options
The indicator provides several customization options. The data period setting determines the number of days of observations to store (0 uses all available data). Filter length controls the number of historical data points for the filter (total window size is length × 2 - 1). Filter width adjusts the width of the kernel function. Users can also select between Gaussian, Epanechnikov, and Triangular kernel functions, and customize visual settings such as colors and line width.
These parameters allow for fine-tuning the balance between responsiveness and smoothness based on individual trading preferences and the specific characteristics of the traded instrument.
Limitations
The indicator requires minute-based intraday timeframes, securities with volume data (when using volume as the source), and sufficient historical data to establish time-of-day patterns.
Conclusion
The Half Causal Estimator represents an innovative approach to technical analysis that addresses one of the fundamental limitations of traditional indicators: time lag. By incorporating time-of-day patterns into its calculations, it provides a more timely representation of market variables while maintaining the noise-reduction benefits of smoothing. This makes it a valuable tool for traders who need to make decisions based on real-time information about volume, volatility, or price changes.
Forecasting
Multi-Factor Reversal AnalyzerMulti-Factor Reversal Analyzer – Quantitative Reversal Signal System
OVERVIEW
Multi-Factor Reversal Analyzer is a comprehensive technical analysis toolkit designed to detect market tops and bottoms with high precision. It combines trend momentum analysis, price action behavior, wave oscillation structure, and volatility breakout potential into one unified indicator.
This tool is ideal for traders seeking to catch reversals, filter false breakouts, and enhance entry/exit timing through a blend of leading and lagging signals. Whether you’re a discretionary trader or building a systematic strategy, this multi-dimensional model provides clarity across market regimes.
IMPLEMENTATION PRINCIPLES
1. Trend Strength Detector
Analyzes price and volume momentum using directional bias and volume-weighted trend scoring to quantify bullish or bearish strength.
2. Price Action Index
Measures trend stability and directional momentum through a composite score based on price volatility, stochastic behavior, and signal-to-noise dispersion metrics.
3. Wave Trend Oscillator
Identifies turning points and potential divergences using normalized smoothed lines and histogram differentials.
4. Volatility Gold Zone
Detects moments of extremely compressed volatility, signaling potential large-move breakout conditions.
5. Multi-Divergence Detection
Tracks regular and hidden bullish/bearish divergences across multiple oscillators for reversal confirmation.
KEY FEATURES
1. Multi-Layer Reversal Logic
• Combines trend scoring, oscillator divergence, and volatility squeezes for triangulated reversal detection.
• Helps traders distinguish between trend pullbacks and true reversals.
2. Advanced Divergence Detection
• Detects both regular and hidden divergences using pivot-based confirmation logic.
• Customizable lookback ranges and pivot sensitivity provide flexible tuning for different market styles.
3. Gold Zone Volatility Compression
• Highlights pre-breakout zones using custom oscillation models (RSI, harmonic, Karobein, etc.).
• Improves anticipation of breakout opportunities following low-volatility compressions.
4. Trend Direction Context
• PAI and Trend Score components provide top-down insight into prevailing bias.
• Built-in “Straddle Area” highlights consolidation zones; breakouts from this area often signal new trend phases.
5. Flexible Visualization
• Color-coded trend bars, reversal markers, normalized oscillator plots, and trend strength labels.
• Designed for both visual discretionary traders and data-driven system developers.
USAGE GUIDELINES
1. Applicable Markets
• Suitable for stocks, crypto, futures, and forex
• Supports reversal, mean-reversion, and breakout trading styles
2. Recommended Timeframes
• Short-term traders: 5m / 15m / 1H — use Wave Trend divergence + Gold Zone
• Swing traders: 4H / Daily — rely on Price Action Index and Trend Detector
• Macro trend context: use PAI HTF mode for higher timeframe overlays
3. Reversal Strategy Flow
• Watch for divergence (WT/PAI) + Gold Zone compression
• Confirm with Trend Score weakening or flipping
• Use Straddle Area breakout for final trigger
• Optional: enable bar coloring or labels for visual reinforcement
• The indicator performs optimally when used in conjunction with a harmonic pattern recognition tool
4. Additional Note on the Gold Zone
The “Gold Zone” does not directly indicate a market bottom. Since it is displayed at the bottom of the chart, it may be misunderstood as a bullish signal. In reality, the Gold Zone represents a compression of price momentum and volatility, suggesting that a significant directional move is about to occur. The direction of that move—upward or downward—should be determined by analyzing the histogram:
• If histogram momentum is weakening, the Gold Zone may precede a downward move.
• If histogram momentum is strengthening, it may signal an upcoming rebound or rally.
Treat the Gold Zone as a warning of impending volatility, and always combine it with trend indicators for accurate directional judgment.
RISK DISCLAIMER
• This indicator calculates trend direction based on historical data and cannot guarantee future market performance. When using this indicator for trading, always combine it with other technical analysis tools, fundamental analysis, and personal trading experience for comprehensive decision-making.
• Market conditions are uncertain, and trend signals may result in false positives or lag. Traders should avoid over-reliance on indicator signals and implement stop-loss strategies and risk management techniques to reduce potential losses.
• Leverage trading carries high risks and may result in rapid capital loss. If using this indicator in leveraged markets (such as futures, forex, or cryptocurrency derivatives), exercise caution, manage risks properly, and set reasonable stop-loss/take-profit levels to protect funds.
• All trading decisions are the sole responsibility of the trader. The developer is not liable for any trading losses. This indicator is for technical analysis reference only and does not constitute investment advice.
• Before live trading, it is recommended to use a demo account for testing to fully understand how to use the indicator and apply proper risk management strategies.
CHANGELOG
v1.0: Initial release featuring integrated Price Action Index, Trend Strength Scoring, Wave Trend Oscillator, Gold Zone Compression Detection, and dual-type divergence recognition. Supports higher timeframe (HTF) synchronization, visual signal markers, and diversified parameter configurations.
Daily Time Range HighlightThis Pine Script code creates a TradingView indicator that allows users to highlight a specific time range on a chosen day of the week. It draws a customizable colored box on the price chart, spanning from the session's start to end and covering the highest high and lowest low within that period. Users can enable or disable the highlighting, select the day of the week and time range, and customize the appearance of the highlight box through the indicator's settings.
M2 Global Liquidity Index (108-day delay)This indicator tracks global liquidity by summing the M2 money supply of the largest economies (China, USA, Europe, Japan, and the UK), adjusted to USD via exchange rates. By delaying the indicator by 108 days, it reveals how global monetary expansion or contraction leads Bitcoin’s price action.
Recently, during the last cycle, Bitcoin has been closely mirroring the movements of global liquidity, rising as liquidity increases and pulling back during contractions. This tool offers powerful macroeconomic insights for those trading or accumulating BTC.
BEAST Empathy Meter - English VersionBEAST Empathy Meter – AI-powered Market Sentiment & Entry Clarity
The BEAST Empathy Meter is an advanced AI-powered trading companion that helps traders identify market sentiment, emotional extremes, and precise entry conditions for both Long and Short trades. Designed as a fusion of emotional analytics and technical clarity, it decodes market dynamics using logic-based metrics rather than traditional noise.
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## 📌 What does the BEAST Empathy Meter do?
It analyzes the psychological state of the market using 4 key modules:
1. **EmpathyScore System** – Calculates emotional momentum based on candle structure, volatility, ROC, MACD, RSI, volume and trend behavior.
2. **Fear & Greed Indicator** – Combines volatility, momentum, volume spikes and cluster sentiment (SPX, BTC, VIX) into a single intuitive score.
3. **Entry Confidence Matrix** – Dynamically scores trade setups from 0%–100% based on logic, clarity, trend alignment, and confirmation.
4. **Forecast Probability** – Assesses the strength of agreement between trend, momentum, GCN, cluster alignment, and WaveTrend dynamics.
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## ⚙️ How it works
- The **EmpathyScore** ranges from –100 (Fear) to +100 (Greed), showing the emotional intensity of the market.
- A **dynamic entryScore** calculates the confidence of current setups and highlights when a Long or Short trade is potentially favorable.
- The **MetaScore** label combines risk, entryScore and forecast alignment to guide clear decisions:
- ✅ "🔥 Trade Recommended"
- ⚠️ "Mixed Signal"
- 🚫 "No Trade"
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## 🧠 How to trade with it
- **Only trade when the MetaScore says "🔥 Trade Recommended"**.
- Use the **Entry Confidence table** to evaluate risk, confidence, forecast probability and WaveTrend validation.
- Confirm alignment with the **Fear & Greed bar**, sentiment tunnel, and cluster overview (SPX / BTC / VIX).
- Avoid trades during neutral or uncertain phases, especially when emotions and momentum disagree.
---
## 🔍 Originality
This indicator is 100% custom-built from the ground up and merges emotional sentiment, trend validation and machine-learning-inspired logic for a unique, forward-thinking approach to market timing. It is not a mashup of existing open-source indicators.
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## 📷 Recommended chart setup
Use a clean chart with the BEAST Empathy Meter as your main overlay. The indicator works best on 30-minute to 1-hour charts, but is flexible enough to adapt to multiple timeframes.
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Jos Way - Federal Reserve Total Assets // Days Offset =Indicators are lagging on the market and visa-versa. With this indicator you can offset the time so reading and analysing is now more intuitive...
50/200 EMA Scalping StratejisiThis Pine Script is the Trading View version of the strategy you saw on the webpage. The core components of the strategy are:
1. **50 EMA and 200 EMA Tracking**: The moving averages that form the foundation of the strategy.
2. **Crossover Detection**: The 50 EMA crossing above the 200 EMA (long position) or crossing below the 200 EMA (short position).
3. **Price Retest**: After the crossover, the price touches the 200 EMA and reacts.
4. **Confirmation Candle**: A confirmatory candle formation after the price test (green candle with close above 200 EMA for long positions, red candle with close below 200 EMA for short positions).
5. **Stop Loss**: Automatic stop loss levels at 0.10% below/above the entry price.
6. **ATR and ADX Indicators**: Technical indicators that measure volatility and trend strength.
7. **Visual Markers**: Clear visual signals for crossovers, retest points, and confirmed entry signals.
8. **Dynamic Table**: An information table displaying current status, price, and indicator values.
The script also automatically shows the recommended leverage level based on the cryptocurrency (8x for BTC/ETH, 5x for others).
Sun Moon Conjunctions Trine Oppositions 2025this script is an astrological tool designed to overlay significant Sun-Moon aspect events for 2025 on a Bitcoin chart. It highlights key lunar phases and aspects—Conjunctions (New Moon) in blue, Squares in red, Oppositions (Full Moon) in purple, and Trines in green—using background colors and labeled markers. Users can toggle visibility for each aspect type and adjust label sizes via customizable inputs. The script accurately marks events from January through December 2025, with labels appearing once per event, making it a valuable resource for exploring potential correlations between lunar cycles and Bitcoin price movements.
Wyckoff S-bar and RS-bar DetectorThis script is used for detecting Significant candle/bar according to Wyckoff definition.
Highly appriciate your feedback if any issue during your usage.
Sessions with Mausa session high/low tracker that draws flat, horizontal lines for Asia, London, and New York trading sessions. It updates those levels in real time during each session, locks them in once the session ends, and keeps them on the chart for context.
At a glance, you always know:
Where each session’s highs and lows were set
Which session produced them (ASIA, LDN, NY labels float cleanly above the highs)
When price is approaching or reacting to prior session levels
🔹 Use Cases:
• Key Levels – See where Asia, London, or NY set boundaries, and watch how price respects or rejects them
• Breakout Zones – Monitor when price breaks above/below session highs/lows
• Session Structure – Know instantly if a move happened during London or NY without squinting at the clock
• Backtesting – Keep historic session levels on the chart for reference — nothing gets deleted
• Confluence – Align these levels with support/resistance, fibs, or liquidity zones
Simple, visual, no distractions — just session structure at a glance.
RVOL Effort Matrix💪🏻 RVOL Effort Matrix is a tiered volume framework that translates crowd participation into structure-aware visual zones. Rather than simply flagging spikes, it measures each bar’s volume as a ratio of its historical average and assigns to that effort dynamic tiers, creating a real-time map of conviction , exhaustion , and imbalance —before price even confirms.
⚖️ At its core, the tool builds a histogram of relative volume (RVOL). When enabled, a second layer overlays directional effort by estimating buy vs sell volume using candle body logic. If the candle closes higher, green (buy) volume dominates. If it closes lower, red (sell) volume leads. These components are stacked proportionally and inset beneath a colored cap line—a small but powerful layer that maintains visibility of the true effort tier even when split bars are active. The cap matches the original zone color, preserving context at all times.
Coloration communicates rhythm, tempo, and potential turning points:
• 🔴 = structurally weak effort, i.e. failed moves, fake-outs or trend exhaustion
• 🟡 = neutral volume, as seen in consolidations or pullbacks
• 🟢 = genuine commitment, good for continuation, breakout filters, or early rotation signals
• 🟣 = explosive volume signaling either climax or institutional entry—beware!
Background shading (optional) mirrors these zones across the pane for structural scanning at a glance. Volume bars can be toggled between full-stack mode or clean column view. Every layer is modular—built for composability with tools like ZVOL or OBVX Conviction Bias.
🧐 Ideal Use-Cases:
• 🕰 HTF bias anchoring → LTF execution
• 🧭 Identifying when structure is being driven by real crowd pressure
• 🚫 Fading green/fuchsia bars that fail to break structure
• ✅ Riding green/fuchsia follow-through in directional moves
🍷 Recommended Pairings:
• ZVOL for statistically significant volume anomaly detection
• OBVX Conviction Bias ↔️ for directional confirmation of effort zones
• SUPeR TReND 2.718 for structure-congruent entry filtering
• ATR Turbulence Ribbon to distinguish expansion pressure from churn
🥁 RVOL Effort Matrix is all about seeing—how much pressure is behind a move, whether that pressure is sustainable, and whether the crowd is aligned with price. It's volume, but readable. It’s structure, but dynamic. It’s the difference between obeying noise and trading to the beat of the market.
4 Fast Stochastic Indicators with %K Smoothingsimilar 4 fast stochastic indicator with different type of indicators it showing bullish bearish ness in different time intervasl u can analyze easily
OBVX Conviction Bias🧮 The OBVX Conviction Bias overlay tracks the flow of directional volume using the classic On-Balance Volume calculation, then filters it through a layered moving average system to expose crowd commitment , pressure transitions , and momentum fatigue . The tool applies two smoothed averages to the OBV line—a fast curve and a longer-term baseline scaled using Euler’s constant (2.718)—and visualizes their relationship using a color-coded crossover ribbon and pressure fills. When used correctly, it reveals whether a move is being supported by meaningful volume, or whether the crowd is starting to disengage.
🚦 The core signal compares OBV to its fast moving average. When OBV climbs above the short average, it fills green—suggesting real directional effort. When OBV sinks below, the fill turns maroon—flagging fading conviction or pullback potential. A second fill between the short and long OBV moving averages captures the broader trend of volume intention. If the short is above the long, this space fills greenish, showing constructive pressure. If it flips, the fill fades red, signaling crowd hesitation, rotation, or early exhaustion.
⚖️ All smoothing is user-selectable, defaulting to VWMA for effort-sensitive structure. The long-term average is auto-scaled using the natural exponential multiplier (2.718), offering rhythm that reflects the curve of participation. OBVX Conviction Bias isn’t trying to predict—it’s trying to show you where the crowd is leaning , and whether that lean is gaining traction or losing strength.
🧐 Ideal Use-Cases:
• Detect divergence between volume flow and price action
• Confirm breakout validity with volume alignment
• Fade breakouts where OBV fails to follow through
• Time pullback entries when OBV pressure resumes in trend direction
🍷 Recommended Pairings:
• ZVOL to measure whether volume is statistically significant or just noise (as shown)
• RVOL Effort Matrix to validate crowd effort by tier and structure zone
• SUPeR TReND 2.718 and/or MA Ribbons for directional confluence
• ATR Turbulence to track volatility-phase alignment with volume intention
RVOL Effort Matrix⚖️ RVOL Effort Matrix is a tiered volume framework that translates crowd participation into structure-aware visual zones. Rather than simply flagging spikes, it measures each bar’s volume as a ratio of its historical average and classifies that effort dynamic tiers to create a real-time map of conviction, exhaustion, and imbalance—before price even confirms.
💪🏻 At its core, the tool builds a histogram of relative volume (RVOL) When enabled, a second layer overlays directional effort by estimating buy vs sell volume using candle body logic. If the candle closes higher, green (buy) volume dominates. If it closes lower, red (sell) volume leads. These components are stacked proportionally and inset beneath a colored cap line—a small but powerful layer that maintains visibility of the true effort tier even when split bars are active. The cap matches the original zone color, preserving context at all times.
Coloration communicates rhythm, tempo, and potential turning points:
• 🔴 = structurally weak effort, i.e. failed moves, fake-outs or trend exhaustion
• 🟡 = neutral volume, as seen in consolidations or pullbacks
• 🟢 = genuine commitment, good for continuation, breakout filters, or early rotation signals
• 🟣 = explosive volume signaling either climax or institutional entry—beware!
Background shading (optional) mirrors these zones across the pane for structural scanning at a glance. Volume bars can be toggled between full-stack mode or clean column view. Every layer is modular—built for composability with tools like ΣVOL or OBV Intention Bias.
🧐 Best used in:
• 🕰 HTF bias anchoring → LTF execution
• 🧭 Identifying when structure is being driven by real crowd pressure
• 🚫 Fading green/fuchsia bars that fail to break structure
• ✅ Riding green/fuchsia follow-through in directional moves
🍷 Recommended pairings:
• ZVOL for statistically significant volume anomaly detection
• OBV Intention Bias ↔️ for directional confirmation of effort zones
• SUPeR TReND 2.718 for structure-congruent entry filtering
• ATR Turbulence Ribbon to distinguish expansion pressure from churn
🥁 RVOL Effort Matrix is all about seeing—how much pressure is behind a move, whether that pressure is sustainable, and whether the crowd is aligned with price. It's volume, but readable. It’s structure, but dynamic. It’s the difference between chasing noise and trading with rhythm.
4 Fast Stochastic Indicatorsthis contain four type of stochastic in different time frames it explain hte bullish bearish ness in different time frames
Multi TF Fibonacci Divergence StrategyTake 2
The 1 hour and 4 hour time frame must be above the 200 Exponential Moving average for buy trades, and below the 200 Exponential Moving Average for sell trades.
Price on the previous day's daily candle must have closed above the candle before its body and wick for buys and below it for sells. (Example: Today is Monday and price has not yet closed, fridays daily candle closed above the thursday candles body and wick for buys and below it for sells)
Price on The 15 minute time frame must retrace past the 50% level on the fibonacci indicator. Price must not close beyond the 78.6% level on the fibonacci indicator. (on the 5 minute time frame, 15 minute time frame, 1 hour time frame, 4 hour time frame.)
Price on the 15 minute time frame must have retraced to the -27% or -61.8 levels on the fibonacci indicator. (Price must not close beyond the 78.6% fibonacci level on the hourly time frame)
Price on the 15 minute time frame or the 5 minute time frame must show bullish divergence once price has touched the -27% or -61.8% fibonacci level for buys and bearish divergence for sells. (This only applies to the 1 hour time frame retraced market structure on the 15 minute and 5 minute time frame only)
EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)
🚨 Main Utility: Early Squeeze Warning
The primary function of this indicator is to warn traders early when the market is approaching a "squeeze"—a tightening condition that often precedes significant moves or regime shifts. By visually highlighting areas of increasing tension, it helps traders anticipate potential volatility and prepare accordingly. This is intended to be a statistically and psychologically grounded replacement of so-called "fib-time-zones," which are overly-deterministic and subjective.
📌 Overview
The EMA-Based Squeeze Dynamics indicator projects future regime shifts (such as golden and death crosses) using exponential moving averages (EMAs). It employs historical interval data and current market conditions to dynamically forecast when the critical EMAs (50-period and 200-period) will reconverge, marking likely trend-change points.
This indicator leverages two core ideas:
Behavioral finance theory: Traders often collectively anticipate popular EMA crossovers, creating a self-fulfilling prophecy (normative social influence), similar to findings from Solomon Asch’s conformity experiments.
Bayesian-like updates: It utilizes historical crossover intervals as a prior, dynamically updating expectations based on evolving market data, ensuring its signals remain objectively grounded in actual market behavior.
⚙️ Technical & Mathematical Explanation
1. EMA Calculations and Regime Definitions
The indicator uses three EMAs:
Fast (9-period): Represents short-term price movement.
Medial (50-period): Indicates medium-term trend direction.
Slow (200-period): Defines long-term market sentiment.
Regime States:
Bullish: 50 EMA is above the 200 EMA.
Bearish: 50 EMA is below the 200 EMA.
A shift between these states triggers visual markers (arrows and labels) directly on the chart.
2. Gap Dynamics and Historical Intervals
At each crossover:
The indicator records the gap (distance) between the 50 and 200 EMAs.
It tracks the historical intervals between past crossovers.
An Exponentially Weighted Moving Average (EWMA) of these intervals is calculated, weighting recent intervals more heavily, dynamically updating expectations.
Important note:
After every regime shift, the projected crossover line resets its calculation. This reset is visually evident as the projection line appears to move further away after each regime change, temporarily "repelled" until the EMAs begin converging again. This ensures projections remain realistic, grounded in actual EMA convergence, and prevents overly optimistic forecasts immediately after a regime shift.
3. Gap Momentum & Adaptive Scaling
The indicator measures how quickly or slowly the gap between EMAs is changing ("gap momentum") and adjusts its forecast accordingly:
If the gap narrows rapidly, a crossover becomes more imminent.
If the gap widens, the next crossover is pushed further into the future.
The "gap factor" dynamically scales the projection based on recent gap momentum, bounded between reasonable limits (0.7–1.3).
4. Squeeze Ratio & Background Color (Visual Cues)
A "squeeze ratio" is computed when market conditions indicate tightening:
In a bullish regime, if the fast EMA is below the medial EMA (price pulling back towards long-term support), the squeeze ratio increases.
In a bearish regime, if the fast EMA rises above the medial EMA (price rallying into long-term resistance), the squeeze ratio increases.
What the Background Colors Mean:
Red Background: Indicates a bullish squeeze—price is compressing downward, hinting a bullish reversal or continuation breakout may occur soon.
Green Background: Indicates a bearish squeeze—price is compressing upward, suggesting a bearish reversal or continuation breakout could soon follow.
Opacity Explanation:
The transparency (opacity) of the background indicates the intensity of the squeeze:
High Opacity (solid color): Strong squeeze, high likelihood of imminent volatility or regime shift.
Low Opacity (faint color): Mild squeeze, signaling early stages of tightening.
Thus, more vivid colors serve as urgent visual warnings that a squeeze is rapidly intensifying.
5. Projected Next Crossover and Pseudo Crossover Mechanism
The indicator calculates an estimated future bar when a crossover (and thus, regime shift) is expected to occur. This calculation incorporates:
Historical EWMA interval.
Current squeeze intensity.
Gap momentum.
A dynamic penalty based on divergence from baseline conditions.
The "Pseudo Crossover" Explained:
A key adaptive feature is the pseudo crossover mechanism. If price action significantly deviates from the projected crossover (for example, if price stays beyond the projected line longer than expected), the indicator acknowledges the projection was incorrect and triggers a "pseudo crossover" event. Essentially, this acts as a reset, updating historical intervals with a weighted adjustment to recalibrate future predictions. In other words, if the indicator’s initial forecast proves inaccurate, it recognizes this quickly, resets itself, and tries again—ensuring it remains responsive and adaptive to actual market conditions.
🧠 Behavioral Theory: Normative Social Influence
This indicator is rooted in behavioral finance theory, specifically leveraging normative social influence (conformity). Traders commonly watch EMA signals (especially the 50 and 200 EMA crossovers). When traders collectively anticipate these signals, they begin trading ahead of actual crossovers, effectively creating self-fulfilling prophecies—similar to Solomon Asch’s famous conformity experiments, where individuals adopted group behaviors even against direct evidence.
This behavior means genuine regime shifts (actual EMA crossovers) rarely occur until EMAs visibly reconverge due to widespread anticipatory trading activity. The indicator quantifies these dynamics by objectively measuring EMA convergence and updating projections accordingly.
📊 How to Use This Indicator
Monitor the background color and opacity as primary visual cues.
A strongly colored background (solid red/green) is an early alert that a squeeze is intensifying—prepare for potential volatility or a regime shift.
Projected crossover lines give a dynamic target bar to watch for trend reversals or confirmations.
After each regime shift, expect a reset of the projection line. The line may seem initially repelled from price action, but it will recalibrate as EMAs converge again.
Trust the pseudo crossover mechanism to automatically recalibrate the indicator if its original projection misses.
🎯 Why Choose This Indicator?
Early Warning: Visual squeeze intensity helps anticipate market breakouts.
Behaviorally Grounded: Leverages real trader psychology (conformity and anticipation).
Objective & Adaptive: Uses real-time, data-driven updates rather than static levels or subjective analysis.
Easy to Interpret: Clear visual signals (arrows, labels, colors) simplify trading decisions.
Self-correcting (Pseudo Crossovers): Quickly adjusts when initial predictions miss, maintaining accuracy over time.
Summary:
The EMA-Based Squeeze Dynamics Indicator combines behavioral insights, dynamic Bayesian-like updates, intuitive visual cues, and a self-correcting pseudo crossover feature to offer traders a reliable early warning system for market squeezes and impending regime shifts. It transparently recalibrates after each regime shift and automatically resets whenever projections prove inaccurate—ensuring you always have an adaptive, realistic forecast.
Whether you're a discretionary trader or algorithmic strategist, this indicator provides a powerful tool to navigate market volatility effectively.
Happy Trading! 📈✨
Multi TF Fibonacci Divergence Strategy✅ Buy Trade Conditions
Trend Confirmation:
The 1-hour and 4-hour charts must be above the 200 EMA.
Daily Candle Confirmation:
The previous daily candle must have closed above the body and wick of the candle before it (e.g., Friday's candle must close above Thursday’s for a buy).
Fibonacci Retracement:
On the 15-minute chart, price must:
Retrace past the 50% level of a Fibonacci drawn from recent swing high/low.
Not close beyond the 78.6% level.
Fibonacci Extension Target:
Price must touch either the -27% or -61.8% extension level (based on the same swing).
It must not close beyond the 78.6% retracement level on higher timeframes.
Bullish Divergence:
Bullish RSI divergence on the 15-minute chart, confirmed by structure on the 1-hour chart.
Session Filter:
Trade signals only trigger during the asset's active trading session (user-defined).
❌ Sell Trade Conditions
All the above are mirrored in the opposite direction:
Below 200 EMA on 1H & 4H
Daily candle closes below prior candle’s body and wick
Fibonacci retrace above 50%, no close beyond 78.6%
Target hit at -27% or -61.8%
Bearish RSI divergence
In-session signal
ATR Normalized⸻
🧠 First, What is ATR?
ATR (Average True Range) is a volatility indicator — it shows how much an asset moves (up or down) on average over a specific number of periods.
• Higher ATR = more volatility
• Lower ATR = less volatility
The classic ATR doesn’t care about direction — just how much the price moves.
⸻
📈 What is ATR Normalized?
Normalized ATR takes the ATR value and scales it to make it easier to compare across different stocks or timeframes.
It gives you a percentage-type value to understand volatility relative to historical average volatility.
⸻
🧮 The Formula (Simplified):
ATR_Normalized = (ATR(13) / SMA(ATR(13), 52)) * 100
⸻
📌 So, What Does (13, 52, 80) Mean?
These are user-defined input parameters for the custom ATR_Normalized indicator:
Parameter Meaning
13 Period for calculating ATR (short-term volatility)
52 Period for calculating the SMA (average ATR over a longer period)
80 Threshold level line (usually used as an alert zone for high volatility)
⸻
🧠 How to Interpret It on the Chart:
• If ATR_Normalized is above 80 (the red line):
• Volatility is unusually high
• Could be a sign of a breakout, news event, or reversal risk
• If ATR_Normalized is below 80:
• Volatility is within a normal range
• Calm markets or consolidation
⸻
💡 Example Use Cases:
1. Identify breakouts or trend starts
• Spikes in normalized ATR often come before large moves.
2. Filter trades based on volatility
• Avoid entering positions when volatility is too high or too low.
⸻
SECTORSSP500 Sector indicator relative to each other. Sectors above 50 buy and less than 50 is sell signal.
SignalX Market Snapshot Exporter
✅ SignalX Daily Bias + Timing Engine (Reusable Routine)
Inputs:
1-day CSV (5min or 1min timeframe)
Columns: open, high, low, close, volume, HMA10, HMA30, SMA10–200, Up/Down Trend, Engulfing, Doji, Pin Bar
Outputs:
1. 🎯 Directional Bias (Long / Short / Neutral)
Based on:
Price relative to 10/20/50 SMAs
HMA10 > HMA30 (bullish slope), or reverse
Up/Down Trend Flags (majority)
Volume confirmation (trending day vs low-vol chop)
2. 🕒 High-Probability Trade Times
Spots times with:
Volume Spike + Trend alignment
Shape pattern confirmation (engulfing, pin bar)
SMA breakout zones
3. 📊 Trade Setup Template
Direction
Entry time (window)
Suggested SL = recent swing ± buffer
TP = SL × 2 (adjustable)
✅ Why This File Works for Bias + Time Planning
You’ve included:
Price action: OHLC (Open/High/Low/Close)
Trend indicators: Up Trend, Down Trend, HMA10/30, SMA10/20/50/100/200
Volume & spikes
Candlestick patterns: Engulfings, Doji, Pin Bar
Trend flags: Up Trend Flag, Down Trend Flag
This gives me everything needed to:
Determine directional bias for the day (Long / Short / Neutral)
Identify high-probability time zones (based on volume spikes + trend alignment)
Suggest SL/TP-friendly zones based on structure
XLEVEL RISK ON/OFFThis is a risk on/off indicator .
SHOWS all macro indicators like
VIX,SP500,DXY, US10Y, OIL, GOLD .
If the background color is red its risk off.
If the background color is blue its risk on.
If gray and its mixed.
It helps me a lot with trade decisions.
Horizontal Line at LevelsThis line drawing based on value to predict the market is moving on specific area marked and can alter according to level planned as per the market
