EMA Oscillator [Alpha Extract]A precision mean reversion analysis tool that combines advanced Z-score methodology with dual threshold systems to identify extreme price deviations from trend equilibrium. Utilizing sophisticated statistical normalization and adaptive percentage-based thresholds, this indicator provides high-probability reversal signals based on standard deviation analysis and dynamic range calculations with institutional-grade accuracy for systematic counter-trend trading opportunities.
🔶 Advanced Statistical Normalization
Calculates normalized distance between price and exponential moving average using rolling standard deviation methodology for consistent interpretation across timeframes. The system applies Z-score transformation to quantify price displacement significance, ensuring statistical validity regardless of market volatility conditions.
// Core EMA and Oscillator Calculation
ema_values = ta.ema(close, ema_period)
oscillator_values = close - ema_values
rolling_std = ta.stdev(oscillator_values, ema_period)
z_score = oscillator_values / rolling_std
🔶 Dual Threshold System
Implements both statistical significance thresholds (±1σ, ±2σ, ±3σ) and percentage-based dynamic thresholds calculated from recent oscillator range extremes. This hybrid approach ensures consistent probability-based signals while adapting to varying market volatility regimes and maintaining signal relevance during structural market changes.
// Statistical Thresholds
mild_threshold = 1.0 // ±1σ (68% confidence)
moderate_threshold = 2.0 // ±2σ (95% confidence)
extreme_threshold = 3.0 // ±3σ (99.7% confidence)
// Percentage-Based Dynamic Thresholds
osc_high = ta.highest(math.abs(z_score), lookback_period)
mild_pct_thresh = osc_high * (mild_pct / 100.0)
moderate_pct_thresh = osc_high * (moderate_pct / 100.0)
extreme_pct_thresh = osc_high * (extreme_pct / 100.0)
🔶 Signal Generation Framework
Triggers buy/sell alerts when Z-score crosses extreme threshold boundaries, indicating statistically significant price deviations with high mean reversion probability. The system generates continuation signals at moderate levels and reversal signals at extreme boundaries with comprehensive alert integration.
// Extreme Signal Detection
sell_signal = ta.crossover(z_score, selected_extreme)
buy_signal = ta.crossunder(z_score, -selected_extreme)
// Dynamic Color Coding
signal_color = z_score >= selected_extreme ? #ff0303 : // Extremely Overbought
z_score >= selected_moderate ? #ff6a6a : // Overbought
z_score >= selected_mild ? #b86456 : // Mildly Overbought
z_score > -selected_mild ? #a1a1a1 : // Neutral
z_score > -selected_moderate ? #01b844 : // Mildly Oversold
z_score > -selected_extreme ? #00ff66 : // Oversold
#00ff66 // Extremely Oversold
🔶 Visual Structure Analysis
Provides a six-tier color gradient system with dynamic background zones indicating mild, moderate, and extreme conditions. The histogram visualization displays Z-score intensity with threshold reference lines and zero-line equilibrium context for precise mean reversion timing.
snapshot
4H
1D
🔶 Adaptive Threshold Selection
Features intelligent threshold switching between statistical significance levels and percentage-based dynamic ranges. The percentage system automatically adjusts to current volatility conditions using configurable lookback periods, while statistical thresholds maintain consistent probability-based signal generation across market cycles.
🔶 Performance Optimization
Utilizes efficient rolling calculations with configurable EMA periods and threshold parameters for optimal performance across all timeframes. The system includes comprehensive alert functionality with customizable notification preferences and visual signal overlay options.
🔶 Market Oscillator Interpretation
Z-score > +3σ indicates statistically significant overbought conditions with high reversal probability, while Z-score < -3σ signals extreme oversold levels suitable for counter-trend entries. Moderate thresholds (±2σ) capture 95% of normal price distributions, making breaches statistically significant for systematic trading approaches.
snapshot
🔶 Intelligent Signal Management
Automatic signal filtering prevents false alerts through extreme threshold crossover requirements, while maintaining sensitivity to genuine statistical deviations. The dual threshold system provides both conservative statistical approaches and adaptive market condition responses for varying trading styles.
Why Choose EMA Oscillator ?
This indicator provides traders with statistically-grounded mean reversion analysis through sophisticated Z-score normalization methodology. By combining traditional statistical significance thresholds with adaptive percentage-based extremes, it maintains effectiveness across varying market conditions while delivering high-probability reversal signals based on quantifiable price displacement from trend equilibrium, enabling systematic counter-trend trading approaches with defined statistical confidence levels and comprehensive risk management parameters.
Btc!
BTC NY Session Envelopes: Dynamic Levels & Settle AlertsCore Concept and Genesis
Born from forex institutional timing principles, this tool has been precision-engineered for the relentless pace of Bitcoin and cryptocurrency markets. It visualizes adaptive session-derived boundaries—spanning weekly, daily, and Asia-specific envelopes—capped with a Friday US settlement "sentinel" zone. Enhanced with targeted alerts for crossings of Asia highs/lows, daily highs/lows, weekly highs/lows, and the settle midpoint, it empowers traders to capture momentum shifts in real-time, transforming raw price data into actionable intelligence for volatile, non-stop assets.
The Fusion Edge: What Sets This Apart
This isn't a generic level plotter; it's a synergistic ecosystem where NY-timed envelopes intersect to reveal hidden confluences, like Asia's quiet buildup funneling into daily volatility spikes or the US settle acting as a "gap magnet" for weekend resolutions. Tailored for BTC's unique liquidity flows, it employs a low-timeframe data pull for noise-free accuracy, sidestepping common pitfalls in 24/7 charts. The built-in alerts—firing on precise crossovers—add a proactive layer, alerting to potential "liquidity hunts" or reversals (e.g., a breakout above weekly high amid high volume). In personal simulations across 500+ BTC sessions, this setup flagged ~65% of high-conviction moves with fewer false positives than isolated tools—always backtest to confirm your edge.
Inner Mechanics: A Transparent Peek
Weekly/Daily Envelopes: Anchored to 5pm NY resets for institutional alignment; computes highs/lows/mids through ongoing max/min accumulation, sourced from a user-defined sub-timeframe for cross-chart reliability.
Asia Envelope: A dynamic 8pm-3am NY capture window that evolves bar-by-bar, spotlighting pre-London setups often overlooked in crypto.
US Settle Sentinel: Zeroes in on Friday's 4:45pm NY 15-minute finale, rendering a containment box and midpoint to forecast post-weekend reactions. Overlaps are intelligently clustered in labels for at-a-glance clarity, with extension options for forward projection.
Timeframe-Adaptive Visibility: To declutter higher timeframes and focus on relevant horizons, the Asia envelope auto-hides on charts above 1hr, while daily envelopes vanish above 4hr—ensuring a streamlined view for swing or position traders without sacrificing intraday detail.
Alert System: Leverages crossover/crossunder detection on closing prices against levels, with granular triggers (e.g., "Surge Beyond Asia Low") for customized notifications—perfect for webhook integrations or mobile pings.
Strategic Deployment and Scenarios
BTC Day-Trading Playbook: Initiate longs when price rebounds from Asia low near a daily mid, amplified by an alert on "Dip Below Daily Low" for entry confirmation—pair with external volume spikes for confluence.
Trend Harmony: Overlay with a 200-period EMA; use "Breach Under Weekly High" alerts to exit longs in downtrends, safeguarding against fakeouts.
Caveats and Optimization: Thrives in momentum-driven phases but tune out in ultra-low volatility; alerts activate post-bar, so layer with candlestick patterns. Ideal for 15m-4H frames on perpetual futures like BTCUSDT.P.
Exclusive Access Rationale (If Restricted) The bespoke crypto recalibrations, seamless multi-envelope fusion, and alert-driven foresight deliver a tactical advantage absent in off-the-shelf alternatives—reach out via TradingView message for tailored access and optimization insights.
Advanced Trend Momentum [Alpha Extract]The Advanced Trend Momentum indicator provides traders with deep insights into market dynamics by combining exponential moving average analysis with RSI momentum assessment and dynamic support/resistance detection. This sophisticated multi-dimensional tool helps identify trend changes, momentum divergences, and key structural levels, offering actionable buy and sell signals based on trend strength and momentum convergence.
🔶 CALCULATION
The indicator processes market data through multiple analytical methods:
Dual EMA Analysis: Calculates fast and slow exponential moving averages with dynamic trend direction assessment and ATR-normalized strength measurement.
RSI Momentum Engine: Implements RSI-based momentum analysis with enhanced overbought/oversold detection and momentum velocity calculations.
Pivot-Based Structure: Identifies and tracks dynamic support and resistance levels using pivot point analysis with configurable level management.
Signal Integration: Combines trend direction, momentum characteristics, and structural proximity to generate high-probability trading signals.
Formula:
Fast EMA = EMA(Close, Fast Length)
Slow EMA = EMA(Close, Slow Length)
Trend Direction = Fast EMA > Slow EMA ? 1 : -1
Trend Strength = |Fast EMA - Slow EMA| / ATR(Period) × 100
RSI Momentum = RSI(Close, RSI Length)
Momentum Value = Change(Close, 5) / ATR(10) × 100
Pivot Support/Resistance = Dynamic pivot arrays with configurable lookback periods
Bullish Signal = Trend Change + Momentum Confirmation + Strength > 1%
Bearish Signal = Trend Change + Momentum Confirmation + Strength > 1%
🔶 DETAILS
Visual Features:
Trend EMAs: Fast and slow exponential moving averages with dynamic color coding (bullish/bearish)
Enhanced RSI: RSI oscillator with color-coded zones, gradient fills, and reference bands at overbought/oversold levels
Trend Fill: Dynamic gradient between EMAs indicating trend strength and direction
Support/Resistance Lines: Horizontal levels extending from pivot-based calculations with configurable maximum levels
Momentum Candles: Color-coded candlestick overlay reflecting combined trend and momentum conditions
Divergence Markers: Diamond-shaped signals highlighting bullish and bearish momentum divergences
Analysis Table: Real-time summary of trend direction, strength percentage, RSI value, and momentum reading
Interpretation:
Trend Direction: Bullish when Fast EMA crosses above Slow EMA with strength confirmation
Trend Strength > 1%: Strong trending conditions with institutional participation
RSI > 70: Overbought conditions, potential selling opportunity
RSI < 30: Oversold conditions, potential buying opportunity
Momentum Divergence: Price and momentum moving opposite directions signal potential reversals
Support/Resistance Proximity: Dynamic levels provide optimal entry/exit zones
Combined Signals: Trend changes with momentum confirmation generate high-probability opportunities
🔶 EXAMPLES
Trend Confirmation: Fast EMA crossing above Slow EMA with trend strength exceeding 1% and positive momentum confirms strong bullish conditions.
Example: During institutional accumulation phases, EMA crossovers with momentum confirmation have historically preceded significant upward moves, providing optimal long entry points.
15min
4H
Momentum Divergence Detection: RSI reaching overbought levels while momentum decreases despite rising prices signals potential trend exhaustion.
Example: Bearish divergence signals appearing at resistance levels have marked major market tops, allowing traders to secure profits before corrections.
Support/Resistance Integration: Dynamic pivot-based levels combined with trend and momentum signals create high-probability trading zones.
Example: Bullish trend changes occurring near established support levels offer optimal risk-reward entries with clearly defined stop-loss levels.
Multi-Dimensional Confirmation: The indicator's combination of trend, momentum, and structural analysis provides comprehensive market validation.
Example: When trend direction aligns with momentum characteristics near key structural levels, the confluence creates institutional-grade trading opportunities with enhanced probability of success.
🔶 SETTINGS
Customization Options:
Trend Analysis: Fast EMA Length (default: 12), Slow EMA Length (default: 26), Trend Strength Period (default: 14)
Support & Resistance: Pivot Length for level detection (default: 10), Maximum S/R Levels displayed (default: 3), Toggle S/R visibility
Momentum Settings: RSI Length (default: 14), Oversold Level (default: 30), Overbought Level (default: 70)
Visual Configuration: Color schemes for bullish/bearish/neutral conditions, transparency settings for fills, momentum candle overlay toggle
Display Options: Analysis table visibility, divergence marker size, alert system configuration
The Advanced Trend Momentum indicator provides traders with comprehensive insights into market dynamics through its sophisticated integration of trend analysis, momentum assessment, and structural level detection. By combining multiple analytical dimensions into a unified framework, this tool helps identify high-probability opportunities while filtering out market noise through its multi-confirmation approach, enabling traders to make informed decisions across various market cycles and timeframes.
BTC Power Law Valuation BandsBTC Power Law Rainbow
A long-term valuation framework for Bitcoin based on Power Law growth — designed to help identify macro accumulation and distribution zones, aligned with long-term investor behavior.
🔍 What Is a Power Law?
A Power Law is a mathematical relationship where one quantity varies as a power of another. In this model:
Price ≈ a × (Time)^b
It captures the non-linear, exponentially slowing growth of Bitcoin over time. Rather than using linear or cyclical models, this approach aligns with how complex systems, such as networks or monetary adoption curves, often grow — rapidly at first, and then more slowly, but persistently.
🧠 Why Power Law for BTC?
Bitcoin:
Has finite supply and increasing adoption.
Operates as a monetary network , where Metcalfe’s Law and power laws naturally emerge.
Exhibits exponential growth over logarithmic time when viewed on a log-log chart .
This makes it uniquely well-suited for power law modeling.
🌈 How to Use the Valuation Bands
The central white line represents the modeled fair value according to the power law.
Colored bands represent deviations from the model in logarithmic space, acting as macro zones:
🔵 Lower Bands: Deep value / Accumulation zones.
🟡 Mid Bands: Fair value.
🔴 Upper Bands: Euphoria / Risk of macro tops.
📐 Smart Money Concepts (SMC) Alignment
Accumulation: Occurs when price consolidates near lower bands — often aligning with institutional positioning.
Markup: As price re-enters or ascends the bands, we often see breakout behavior and trend expansion.
Distribution: When price extends above upper bands, potential for exit liquidity creation and distribution events.
Reversion: Historically, price mean-reverts toward the model — rarely staying outside the bands for long.
This makes the model useful for:
Cycle timing
Long-term DCA strategy zones
Identifying value dislocations
Filtering short-term noise
⚠️ Disclaimer
This tool is for educational and informational purposes only . It is not financial advice. The power law model is a non-predictive, mathematical framework and does not guarantee future price movements .
Always use additional tools, risk management, and your own judgment before making trading or investment decisions.
Volume Profile Grid [Alpha Extract]A sophisticated volume distribution analysis system that transforms market activity into institutional-grade visual profiles, revealing hidden support/resistance zones and market participant behavior. Utilizing advanced price level segmentation, bullish/bearish volume separation, and dynamic range analysis, the Volume Profile Grid delivers comprehensive market structure insights with Point of Control (POC) identification, Value Area boundaries, and volume delta analysis. The system features intelligent visualization modes, real-time sentiment analysis, and flexible range selection to provide traders with clear, actionable volume-based market context.
🔶 Dynamic Range Analysis Engine
Implements dual-mode range selection with visible chart analysis and fixed period lookback, automatically adjusting to current market view or analyzing specified historical periods. The system intelligently calculates optimal bar counts while maintaining performance through configurable maximum limits, ensuring responsive profile generation across all timeframes with institutional-grade precision.
// Dynamic period calculation with intelligent caching
get_analysis_period() =>
if i_use_visible_range
chart_start_time = chart.left_visible_bar_time
current_time = last_bar_time
time_span = current_time - chart_start_time
tf_seconds = timeframe.in_seconds()
estimated_bars = time_span / (tf_seconds * 1000)
range_bars = math.floor(estimated_bars)
final_bars = math.min(range_bars, i_max_visible_bars)
math.max(final_bars, 50) // Minimum threshold
else
math.max(i_periods, 50)
🔶 Advanced Bull/Bear Volume Separation
Employs sophisticated candle classification algorithms to separate bullish and bearish volume at each price level, with weighted distribution based on bar intersection ratios. The system analyzes open/close relationships to determine volume direction, applying proportional allocation for doji patterns and ensuring accurate representation of buying versus selling pressure across the entire price spectrum.
🔶 Multi-Mode Volume Visualization
Features three distinct display modes for bull/bear volume representation: Split mode creates mirrored profiles from a central axis, Side by Side mode displays sequential bull/bear segments, and Stacked mode separates volumes vertically. Each mode offers unique insights into market participant behavior with customizable width, thickness, and color parameters for optimal visual clarity.
// Bull/Bear volume calculation with weighted distribution
for bar_offset = 0 to actual_periods - 1
bar_high = high
bar_low = low
bar_volume = volume
// Calculate intersection weight
weight = math.min(bar_high, next_level) - math.max(bar_low, current_level)
weight := weight / (bar_high - bar_low)
weighted_volume = bar_volume * weight
// Classify volume direction
if bar_close > bar_open
level_bull_volume += weighted_volume
else if bar_close < bar_open
level_bear_volume += weighted_volume
else // Doji handling
level_bull_volume += weighted_volume * 0.5
level_bear_volume += weighted_volume * 0.5
🔶 Point of Control & Value Area Detection
Implements institutional-standard POC identification by locating the price level with maximum volume accumulation, providing critical support/resistance zones. The Value Area calculation uses sophisticated sorting algorithms to identify the price range containing 70% of trading volume, revealing the market's accepted value zone where institutional participants concentrate their activity.
🔶 Volume Delta Analysis System
Incorporates real-time volume delta calculation with configurable dominance thresholds to identify significant bull/bear imbalances. The system visually highlights price levels where buying or selling pressure exceeds threshold percentages, providing immediate insight into directional volume flow and potential reversal zones through color-coded delta indicators.
// Value Area calculation using 70% volume accumulation
total_volume_sum = array.sum(total_volumes)
target_volume = total_volume_sum * 0.70
// Sort volumes to find highest activity zones
for i = 0 to array.size(sorted_volumes) - 2
for j = i + 1 to array.size(sorted_volumes) - 1
if array.get(sorted_volumes, j) > array.get(sorted_volumes, i)
// Swap and track indices for value area boundaries
// Accumulate until 70% threshold reached
for i = 0 to array.size(sorted_indices) - 1
accumulated_volume += vol
array.push(va_levels, array.get(volume_levels, idx))
if accumulated_volume >= target_volume
break
❓How It Works
🔶 Weighted Volume Distribution
Implements proportional volume allocation based on the percentage of each bar that intersects with price levels. When a bar spans multiple levels, volume is distributed proportionally based on the intersection ratio, ensuring precise representation of trading activity across the entire price spectrum without double-counting or volume loss.
🔶 Real-Time Profile Generation
Profiles regenerate on each bar close when in visible range mode, automatically adapting to chart zoom and scroll actions. The system maintains optimal performance through intelligent caching mechanisms and selective line updates, ensuring smooth operation even with maximum resolution settings and extended analysis periods.
🔶 Market Sentiment Analysis
Features comprehensive volume analysis table displaying total volume metrics, bullish/bearish percentages, and overall market sentiment classification. The system calculates volume dominance ratios in real-time, providing immediate insight into whether buyers or sellers control the current price structure with percentage-based sentiment thresholds.
🔶 Visual Profile Mapping
Provides multi-layered visual feedback through colored volume bars, POC line highlighting, Value Area boundaries, and optional delta indicators. The system supports profile mirroring for alternative perspectives, line extension for future reference, and customizable label positioning with detailed price information at critical levels.
Why Choose Volume Profile Grid
The Volume Profile Grid represents the evolution of volume analysis tools, combining traditional volume profile concepts with modern visualization techniques and intelligent analysis algorithms. By integrating dynamic range selection, sophisticated bull/bear separation, and multi-mode visualization with POC/Value Area detection, it provides traders with institutional-quality market structure analysis that adapts to any trading style. The comprehensive delta analysis and sentiment monitoring system eliminates guesswork while the flexible visualization options ensure optimal clarity across all market conditions, making it an essential tool for traders seeking to understand true market dynamics through volume-based price discovery.
Ultron Indicator BTCUSDT Ultron BTCUSDT Indicator (invite-only).
• Clear trend & reversion signals
• Next-bar execution parity and frozen TSL visuals
• Run on 4hr Binance BTCUSDT chart
• Risk sizing that uses your equity input
Usage: Add to chart → Settings → Inputs → set “Your Current Trading Equity (USD)”.
⚠️ Software tool for educational/informational use only. Not financial advice.
Past performance is not indicative of future results. You are responsible for your trades.
[c3s] CWS - M2 Global Liquidity Index & BTC Correlation CWS - M2 Global Liquidity Index with Offset BTC Correlation
This custom indicator visualizes and analyzes the relationship between the global M2 money supply and Bitcoin (BTC) price movements. It calculates the correlation between these two variables to provide insights into how changes in global liquidity may impact Bitcoin’s price over time.
Key Features:
Global M2 Liquidity Index Calculation:
Fetches M2 money supply data from multiple economies (China, US, EU, Japan, UK) and normalizes using currency exchange rates (e.g., CNY/USD, EUR/USD).
Combines all M2 data points and normalizes by dividing by 1 trillion (1e12) for easier visualization.
Offset for M2 Data:
The offset parameter allows users to shift the M2 data by a specified number of days, helping track the influence of past global liquidity on Bitcoin.
BTC Price Correlation:
Computes the correlation between shifted global M2 liquidity and Bitcoin (BTC) price, using a 52-day lookback period by default.
Correlation Quality Display:
Categorizes correlation quality as:
Excellent : Correlation >= 0.8
Good : Correlation >= 0.6 and < 0.8
Weak : Correlation >= 0.4 and < 0.6
Very Weak : Correlation < 0.4
Displays correlation quality as a label on the chart for easy assessment.
Visual Enhancements:
Labels : Displays dynamic labels on the chart with metrics like M2 value and correlation.
Plot Shapes : Uses shapes to indicate data availability for global M2 and correlation.
Data Table : Optionally shows a data table in the top-right corner summarizing:
Global M2 value (in trillions)
The correlation between global M2 and BTC
The correlation quality
Optional Debugging:
Debug plots help identify when data is missing for M2 or correlation, ensuring transparency and accurate functionality.
Inputs:
Offset: Shift the M2 data (in days) to see past liquidity effects on Bitcoin.
Lookback Period: Number of periods (default 52) used to calculate the correlation.
Show Labels: Toggle to show or hide labels for M2 and correlation values.
Show Table: Toggle to show or hide the data table in the top-right corner.
Usage:
Ideal for traders and analysts seeking to understand the relationship between global liquidity and Bitcoin price. The offset and lookback period can be adjusted to explore different timeframes and correlation strengths, aiding more informed trading decisions.
Mutanabby_AI | Algo Pro Strategy# Mutanabby_AI | Algo Pro Strategy: Advanced Candlestick Pattern Trading System
## Strategy Overview
The Mutanabby_AI Algo Pro Strategy represents a systematic approach to automated trading based on advanced candlestick pattern recognition and multi-layered technical filtering. This strategy transforms traditional engulfing pattern analysis into a comprehensive trading system with sophisticated risk management and flexible position sizing capabilities.
The strategy operates on a long-only basis, entering positions when bullish engulfing patterns meet specific technical criteria and exiting when bearish engulfing patterns indicate potential trend reversals. The system incorporates multiple confirmation layers to enhance signal reliability while providing comprehensive customization options for different trading approaches and risk management preferences.
## Core Algorithm Architecture
The strategy foundation relies on bullish and bearish engulfing candlestick pattern recognition enhanced through technical analysis filtering mechanisms. Entry signals require simultaneous satisfaction of four distinct criteria: confirmed bullish engulfing pattern formation, candle stability analysis indicating decisive price action, RSI momentum confirmation below specified thresholds, and price decline verification over adjustable lookback periods.
The candle stability index measures the ratio between candlestick body size and total range including wicks, ensuring only well-formed patterns with clear directional conviction generate trading signals. This filtering mechanism eliminates indecisive market conditions where pattern reliability diminishes significantly.
RSI integration provides momentum confirmation by requiring oversold conditions before entry signal generation, ensuring alignment between pattern formation and underlying momentum characteristics. The RSI threshold remains fully adjustable to accommodate different market conditions and volatility environments.
Price decline verification examines whether current prices have decreased over a specified period, confirming that bullish engulfing patterns occur after meaningful downward movement rather than during sideways consolidation phases. This requirement enhances the probability of successful reversal pattern completion.
## Advanced Position Management System
The strategy incorporates dual position sizing methodologies to accommodate different account sizes and risk management approaches. Percentage-based position sizing calculates trade quantities as equity percentages, enabling consistent risk exposure across varying account balances and market conditions. This approach proves particularly valuable for systematic trading approaches and portfolio management applications.
Fixed quantity sizing provides precise control over trade sizes independent of account equity fluctuations, offering predictable position management for specific trading strategies or when implementing precise risk allocation models. The system enables seamless switching between sizing methods through simple configuration adjustments.
Position quantity calculations integrate seamlessly with TradingView's strategy testing framework, ensuring accurate backtesting results and realistic performance evaluation across different market conditions and time periods. The implementation maintains consistency between historical testing and live trading applications.
## Comprehensive Risk Management Framework
The strategy features dual stop loss methodologies addressing different risk management philosophies and market analysis approaches. Entry price-based stop losses calculate stop levels as fixed percentages below entry prices, providing predictable risk exposure and consistent risk-reward ratio maintenance across all trades.
The percentage-based stop loss system enables precise risk control by limiting maximum loss per trade to predetermined levels regardless of market volatility or entry timing. This approach proves essential for systematic trading strategies requiring consistent risk parameters and capital preservation during adverse market conditions.
Lowest low-based stop losses identify recent price support levels by analyzing minimum prices over adjustable lookback periods, placing stops below these technical levels with additional buffer percentages. This methodology aligns stop placement with market structure rather than arbitrary percentage calculations, potentially improving stop loss effectiveness during normal market fluctuations.
The lookback period adjustment enables optimization for different timeframes and market characteristics, with shorter periods providing tighter stops for active trading and longer periods offering broader stops suitable for position trading approaches. Buffer percentage additions ensure stops remain below obvious support levels where other market participants might place similar orders.
## Visual Customization and Interface Design
The strategy provides comprehensive visual customization through eight predefined color schemes designed for different chart backgrounds and personal preferences. Color scheme options include Classic bright green and red combinations, Ocean themes featuring blue and orange contrasts, Sunset combinations using gold and crimson, and Neon schemes providing high visibility through bright color selections.
Professional color schemes such as Forest, Royal, and Fire themes offer sophisticated alternatives suitable for business presentations and professional trading environments. The Custom color scheme enables precise color selection through individual color picker controls, maintaining maximum flexibility for specific visual requirements.
Label styling options accommodate different chart analysis preferences through text bubble, triangle, and arrow display formats. Size adjustments range from tiny through huge settings, ensuring appropriate visual scaling across different screen resolutions and chart configurations. Text color customization maintains readability across various chart themes and background selections.
## Signal Quality Enhancement Features
The strategy incorporates signal filtering mechanisms designed to eliminate repetitive signal generation during choppy market conditions. The disable repeating signals option prevents consecutive identical signals until opposing conditions occur, reducing overtrading during consolidation phases and improving overall signal quality.
Signal confirmation requirements ensure all technical criteria align before trade execution, reducing false signal occurrence while maintaining reasonable trading frequency for active strategies. The multi-layered approach balances signal quality against opportunity frequency through adjustable parameter optimization.
Entry and exit visualization provides clear trade identification through customizable labels positioned at relevant price levels. Stop loss visualization displays active risk levels through colored line plots, ensuring complete transparency regarding current risk management parameters during live trading operations.
## Implementation Guidelines and Optimization
The strategy performs effectively across multiple timeframes with optimal results typically occurring on intermediate timeframes ranging from fifteen minutes through four hours. Higher timeframes provide more reliable pattern formation and reduced false signal occurrence, while lower timeframes increase trading frequency at the expense of some signal reliability.
Parameter optimization should focus on RSI threshold adjustments based on market volatility characteristics and candlestick pattern timeframe analysis. Higher RSI thresholds generate fewer but potentially higher quality signals, while lower thresholds increase signal frequency with corresponding reliability considerations.
Stop loss method selection depends on trading style preferences and market analysis philosophy. Entry price-based stops suit systematic approaches requiring consistent risk parameters, while lowest low-based stops align with technical analysis methodologies emphasizing market structure recognition.
## Performance Considerations and Risk Disclosure
The strategy operates exclusively on long positions, making it unsuitable for bear market conditions or extended downtrend periods. Users should consider market environment analysis and broader trend assessment before implementing the strategy during adverse market conditions.
Candlestick pattern reliability varies significantly across different market conditions, with higher reliability typically occurring during trending markets compared to ranging or volatile conditions. Strategy performance may deteriorate during periods of reduced pattern effectiveness or increased market noise.
Risk management through stop loss implementation remains essential for capital preservation during adverse market movements. The strategy does not guarantee profitable outcomes and requires proper position sizing and risk management to prevent significant capital loss during unfavorable trading periods.
## Technical Specifications
The strategy utilizes standard TradingView Pine Script functions ensuring compatibility across all supported instruments and timeframes. Default configuration employs 14-period RSI calculations, adjustable candle stability thresholds, and customizable price decline verification periods optimized for general market conditions.
Initial capital settings default to $10,000 with percentage-based equity allocation, though users can adjust these parameters based on account size and risk tolerance requirements. The strategy maintains detailed trade logs and performance metrics through TradingView's integrated backtesting framework.
Alert integration enables real-time notification of entry and exit signals, stop loss executions, and other significant trading events. The comprehensive alert system supports automated trading applications and manual trade management approaches through detailed signal information provision.
## Conclusion
The Mutanabby_AI Algo Pro Strategy provides a systematic framework for candlestick pattern trading with comprehensive risk management and position sizing flexibility. The strategy's strength lies in its multi-layered confirmation approach and sophisticated customization options, enabling adaptation to various trading styles and market conditions.
Successful implementation requires understanding of candlestick pattern analysis principles and appropriate parameter optimization for specific market characteristics. The strategy serves traders seeking automated execution of proven technical analysis techniques while maintaining comprehensive control over risk management and position sizing methodologies.
BTC CME Futures Gaps (BTCGapHunt_CME)BTC CME Futures Gaps Indicator
Overview
This indicator visualises price gaps between the daily close and open of Bitcoin CME futures (CME:BTC1!). These gaps are often revisited ("filled") by market price action and may serve as technical targets.
Thanks
... to Maven and the Blockchain Masons (x.com/Masons_DAO) to push me on this topic.
What Is a CME Gap?
CME Bitcoin Futures do not trade 24/7. Gaps form when the market reopens at a different price than where it last closed.
Gaps are often used as support/resistance or liquidity targets.
This indicator tracks, visualises, and alerts on these gaps.
Key Features
Automatic gap detection using daily open/close on CME:BTC1!
Dynamic gap size threshold based on ATR (Average True Range)
Highlight unfilled gaps and track partial fills visually
Alerts for gap formation and fill events
Parameter overlay showing real-time settings
Supported and Overrideable Parameters
ATR Length: Defines the lookback period for ATR calculation (default: 14)
Gap Size Multiplier: Multiplies the ATR to set the dynamic gap threshold (default: 1.0)
Proximity Threshold: Price distance from gap edge to consider it filled (default: 100 USD)
Max Gaps Tracked: Maximum number of concurrent gaps shown (default: 50)
Alerts Enabled: Toggle alerts for gap formation and gap fill events
How the Gap Size Is Calculated
Minimum Gap Size = ATR(14) * Gap Size Multiplier
ATR Length and Gap Size Multiplier are configurable.
Gap threshold adjusts dynamically with market volatility.
Visual Guide
Red Box: Fully unfilled gap
Lemon Yellow Box: Partially filled gap
Right Margin Boxes: Snapshot of unfilled gaps for quick access
Top-Right Panel: Current ATR, Gap Size, Thresholds, etc.
Alerts
Gap Formed: A new gap is detected.
Gap Filled: The gap is either partially or fully filled.
Recommended Timeframes
1H, 4H, 1D (best resolution)
Designed for BTC spot/perpetual charts (e.g., BTCUSD, BTCUSDT)
How To Use
Add the script to your BTC chart.
Monitor red/yellow boxes for unfilled gaps.
Check config panel for current threshold and settings.
Enable alerts via TradingView for real-time updates.
Notes
Up to 50 gaps are tracked (adjustable).
Data source: CME futures via request.security.
All visuals and alerts are time-synced with your chart.
Disclaimer
This script is for educational purposes only. Trade at your own risk.
M2 Global Liquidity Index [Extended + Empirical BTC Offset]M2 Global Liquidity Index
This script visualizes global M2 liquidity based on major economic zones (USA, China, Eurozone, Japan, UK), with the option to include extended countries such as Switzerland, Canada, India, Russia, Brazil, South Korea, Mexico, and South Africa.
The indicator includes an empirically derived offset to reflect how Bitcoin historically reacts with a time lag—typically around 12 weeks—after shifts in global liquidity.
Features:
Predefined empirical offset options ranging from 12 to 120 days
Automatic offset adjustment when applied to the weekly chart
Optional inclusion of extended global M2 sources
Important:
This indicator is intended only for use on the weekly chart. It provides meaningful and accurate results exclusively in this time frame, due to the nature of the offset-based correlation logic.
Use cases:
Macro-level analysis of Bitcoin’s price movements
Identifying early signs of potential market tops or bottoms in relation to liquidity flows
LTPI BTC | JeffreyTimmermansLong-Term Trend Probability Indicator
The "Long-Term Trend Probability Indicator" on BTC is a custom-built tool designed to analyze BTC from a long-term perspective. Unlike short-term indicators that react to price volatility, LTPI focuses on major trend shifts on BTC, and therefore across the entire crypto market, helping to identify major trend shifts early.
This version of the LTPI is applied to BTC, making it a BTC specific trend following tool, but very broad (crypto wise), because BTC is the biggest asset.
Key Features
Long-Term Focus:
Designed for macro market analysis with less sensitivity to short-term noise.
8 Input Signals:
Combines 8 carefully selected inputs (trend following indicators) into a single score that reflects the overall market condition.
Market Regimes:
Classifies the BTC trend into:
Bullish: Strong uptrend, expansion phase
Bearish: Strong downtrend, contraction phase
Neutral: Transitional or uncertain
Visual Background:
Background colors clearly display which regime is active.
Comprehensive Dashboard:
The panel at the bottom shows each input’s state, the composite LTPI score, and the resulting market trend.
How It Works
Inputs Analysis:
Each of the 8 inputs outputs one of three states:
+1 (Bullish)
-1 (Bearish)
0 (Neutral)
Score Calculation:
The total score is the sum of all 8 input signals divided by 8.
Score > 0.1 = Bullish
Score < -0.1 = Bearish
Between -0.1 and 0.1 = Neutral
Background Coloring:
Background colors dynamically adjust to reflect the long-term market regime.
Use Cases
Long-Term Positioning:
Identify periods of global expansion or contraction to position yourself accordingly.
Macro Confirmation:
Use LTPI in combination with medium-term (MTPI) and short-term tools for multi-timeframe confirmation.
Market Timing:
Alerts when LTPI crosses key thresholds help highlight the start of major bullish or bearish phases.
Dynamic Alerts:
Bullish Entry: LTPI score crosses above 0.1
Bearish Entry: LTPI score crosses below -0.1
Neutral Zone: Score moves back between -0.1 and 0.1
Conclusion
The Long-Term Trend Probability Indicator (LTPI – BTC) is a powerful tool for identifying long-term market phases across the entire crypto ecosystem. By focusing on long term trends and combining 8 inputs into a single probability score, it provides a clear macro trend perspective for strategic decision-making.
TFPS - TradFi-Pressure-Score (Adaptive)The data-driven answer to an irreversible market reality.
This indicator quantifies the combined pressure from the S&P 500, VIX, DXY, and US10Y, whose correlation to crypto has reached peak values of 0.87. Your decisive macro edge, in real-time.
This indicator is built on a fundamental analysis of market data from the last five years. The analysis proves an irreversible transformation: The crypto market has evolved into a high-beta risk asset, its fate inextricably linked to Traditional Finance (TradFi).
The empirical data is clear:
Bitcoin increasingly behaves like a leveraged version of the S&P 500.
The correlation to stock indices, with peak values of up to 0.87, is statistically highly significant.
The "digital gold" safe-haven narrative is refuted by the data; the correlation to gold (0.04) is virtually non-existent and statistically insignificant.
This means: Standard indicators like RSI or MACD are insufficient for today's market conditions. They only see price, ignoring the powerful external context that now dominates price action.
The TradFi Pressure Score (TFPS) is the answer to this data-driven reality. It's your institutional-grade macro dashboard, aggregating the four most dominant external forces into a single, actionable score:
S&P 500 (SPY): The pulse of global risk appetite. A rising S&P signals a "risk-on" environment, fueling capital flows into crypto.
VIX: The market's "Fear Gauge". A rising VIX signals a "risk-off" flight to safety, draining liquidity from crypto.
DXY (US-Dollar Index): The counter-pole to risk assets. A strong Dollar (rising DXY) tightens global liquidity, creating significant headwinds for Bitcoin.
US 10Y Yield: The opportunity cost of capital. Rising yields make risk-free assets more attractive, pulling capital away from non-yielding assets like crypto.
What makes TFPS truly unique?
Dynamic Weighting (its secret weapon): Which factor matters most today? The DXY or the VIX? TFPS continuously analyzes the correlation of all four factors to your chosen asset (e.g., Bitcoin) and automatically adjusts their weight in real-time. This ensures you're always focused on what's currently driving the market.
Adaptive Engine : What drives a 15-minute chart is different from a daily chart. The TFPS engine automatically adapts its lookback periods and calculations to your chosen timeframe for optimal relevance.
Clear, Actionable Signals Designed for Traders:
Pressure Line (>0 or <0): Instantly see if the world's largest financial forces are providing a tailwind or a headwind for your trade.
Z-Score (Extreme Readings) : Get early warnings of extreme macro "Greed" or "Fear". Readings above +2 or below -2 have historically pinpointed moments of market exhaustion that often precede major trend reversals.
Regime Change : A fundamental shift in the nature of TradFi pressure is visualized with a clear signal, providing unambiguous macro insights.
Lead/Lag Status : Gain a critical edge by knowing who's in the driver's seat. The dashboard tells you if TradFi is LEADING the price action or if crypto is moving independently, allowing you to focus on the right information source.
This is a private beta. I am granting exclusive access to a limited number of traders who understand this new market reality. In exchange for your valuable feedback, you will be among the first to leverage what I believe is the new standard for macro analysis in crypto trading.
Request access to trade with the full context.
BTC PL Trend + Floor - Log PilotBTC Power Law Trend + Floor with forward projection.
Sky blue for the trend. Neon orange for the floor. Both project forward in dotted green.
Tracks Bitcoin’s long-term arc and structural support through time since Genesis.
Test protectedPrepare to challenge conventional analysis with Testing Bang, a bold script tailored for AAPL’s battlefield. This strategy doesn’t play defense—it takes decisive action. Triggered at a pivotal moment in Apple’s historical price path, it demonstrates how surgical precision and daring risk management converge to test reversal points with confidence. Built using Pine Script v6, the code aligns stop-loss logic with targeted entry behavior on bar index 10381.
Whether you’re exploring script mechanics or sharpening your backtest instincts, Testing Bang shows how even a single trade can reveal the psychological layers behind price movement. With the bar magnifier disabled, traders witness raw market behavior—a powerful lens for those who dare to refine strategy in the wild. Step in, test your edge, and see if your timing can match Apple’s thunder.
PRO Trading Averaging Beta(v1)Adaptive Position Scaling
Automatically increases position size during pullbacks using exponential volume scaling (1x, 2x, 4x, etc.). This reduces average entry cost and accelerates breakeven when price reverses.
Multi-Timeframe Confirmation
All indicators operate on a higher timeframe (120 minutes), providing:
Noise-filtered signals
Stronger trend alignment
Reduced false entries
Triple-Layer Entry Logic
Requires simultaneous confluence of:
Custom Bollinger Band penetration
RSI oversold filter (above critical threshold)
Golden cross confirmation (fast MA > slow MA)
Volatility assessment via ATR
Intelligent Exit System
Position closure triggers when either:
Fixed profit target (% of account) is reached
Technical boundary (upper Bollinger Band) is touched
⚙️ Core Mechanics:
graph LR
A --> B
B --> C{Initial Entry: 1% capital}
C --> D
D -->|Yes| E
D -->|No| F
E --> G{Max Averaging Levels?}
G -->|No| D
G -->|Yes| H
F --> I
📊 Implementation Guide:
Capital Configuration
Set initial_capital to your actual account size
Calculate base contract size:
(Account Size × 0.01) / (Instrument Price × Point Value)
Example: $10,000 account → 0.01 BTC futures contracts
Pyramiding Structure
Volume progression per averaging level:
Level 1: 1× (Base volume)
Level 2: 2×
Level 3: 4×
Level 4: 8×
Level 5: 16×
Level 6: 32×
(Max 6 levels configurable in strategy settings)
Custom Entry Variations
Alternative approach for swing captures:
// Enter only at 3rd averaging with 5% capital
if averaging_condition and strategy.opentrades == 2
strategy.entry("SwingEntry", strategy.long, qty=base_order_size*5)
Risk Management Protocol
No traditional stop-loss (replaced by averaging)
Break-even trigger: Manually move to breakeven at +0.5% profit
Max exposure: Capped at 6 averaging levels
Commissions: Pre-configured at 0.1% per trade
⚠️ Critical Risk Disclosures:
"Past Performance ≠ Future Results"
Historical optimization requires continuous forward testing ("Walk Forward" in TV).
Pyramiding Hazards
Exponential volume growth demands:
Minimum 20% free margin buffer
High liquidity instruments (spread < 0.5% of ATR)
Strict per-level risk calculation
Market Regime Dependence
Peak efficiency during:
Strong trends with 2-4% retracements
Assets with ATR > 1.5% of daily range
Avoid ranging/low-volatility conditions
💡 Pro Usage Recommendations:
Position Sizing Formula
For futures: Contracts = (Capital × Risk %) / (Entry Price × Point Value × Stop Distance)
Profit Protection
Close 50% position at 50% profit target, trail remainder
Event Safety
Disable averaging during:
High-impact news events
Exchange outages
Abnormal volume spikes
pie
title Risk Allocation per Level
“First Entry” : 12
“Level 2” : 18
“Level 3” : 25
“Level 4” : 45
ESSENTIAL: This strategy demands strict discipline. Terminate averaging when price action deviates from expected patterns. Always maintain reserve capital exceeding maximum drawdown requirements. Regularly validate strategy performance against current market dynamics.
🔥 Уникальные особенности и ценность:
Адаптивное усреднение
Стратегия автоматически увеличивает позицию при движении против вас, используя экспоненциальное наращивание объема (1x, 2x, 4x и т.д.). Это снижает среднюю цену входа и ускоряет выход в прибыль при развороте.
Мультитаймфреймная фильтрация
Все индикаторы работают на старшем таймфрейме (120 минут), что:
Фильтрует рыночный шум
Обеспечивает более надежные сигналы
Синхронизируется с глобальным трендом
Комбинированный триггер входа
Для активации требуется одновременное выполнение 4 условий:
Пробитие кастомной полосы Боллинджера
Подтверждение тренда (быстрая MA > медленной MA)
Контроль перепроданности (RSI выше критического уровня)
Фильтр волатильности (ATR)
Двойной механизм выхода
Закрытие позиций происходит при:
Достижении целевого уровня прибыли (% от депозита)
Техническом сигнале (касание верхней полосы Боллинджера)
⚙️ Как работает стратегия:
graph TD
A --> B
B --> C{Первый вход: 1% депозита}
C --> D
D -->|Да| E
D -->|Нет| F
E --> G{Достигнут лимит усреднений?}
G -->|Нет| D
G -->|Да| H
F --> I
📊 Как пользоваться:
Стартовые настройки
Base Order Size: Стартовый объем = 1% депозита
(Пример: при $10 000 депозита = 0.01 контракта)
initial_capital: Укажите ваш реальный депозит
Правила пирамидинга
Объем наращивается по схеме:
Уровень 1: 1x (базовый объем)
Уровень 2: 2x
Уровень 3: 4x
Уровень 4: 8x
Уровень 5: 16x
Уровень 6: 32x
РЕКОМЕНДУЕТСЯ Максимум 6 уровней усреднения (настраивается в pyramiding)
Кастомизация входов
Пример модификации для агрессивной тактики:
// Вход только на 3-м усреднении с 5% депозита
if averaging_condition and strategy.opentrades == 2
strategy.entry("BuyAggressive", strategy.long, qty=base_order_size*5)
Можно поставить параметр пираммидинг 1 и получать больше сигналов на младших тайм фреймах
Управление рисками
Стоп-лосс: Не используется (заменен усреднением)
Перевод в безубыток: Активируйте вручную при +0.5%
Максимальная просадка: Рекомендуется Ограничивать 6 уровнями усреднения
Комиссии: Учтены (0.1% от объема сделки)
Критические предупреждения:
"Вчера ≠ Сегодня"
Стратегия оптимизирована под историческую волатильность. Регулярно тестируйте на новых данных (режим "Перед тест" в TV).
Опасность усреднения
Экспоненциальный рост объема требует:
Глубокого расчета риска на уровень
Минимум 20% свободного маржи
Ликвидный инструмент (спред < 0.5% от ATR)
Рыночные условия
Максимальная эффективность в:
Трендовых рынках с коррекциями 2-4%
Инструментах с ATR > дневного диапазона 1.5%
💡 Рекомендации по использованию:
Для фьючерсов: Рассчитайте контракты через (капитал * 0.01) / (цена * пункт_стоимости)
При 50% достижении цели прибыли - закройте 50% позиции
Отключайте усреднение при выходе макро-новостей
pie
title Распределение риска
"Первый вход" : 10
"Уровень 2" : 20
"Уровень 3" : 30
"Уровень 4" : 40
ВАЖНО: Эта стратегия требует дисциплины! Прекращайте усреднение при отклонении рынка от исторических паттернов. Всегда имейте резервный капитал для экстренных случаев.
BTC_News_2025Library "BTC_News_2025"
This library contains the tooltips used in the script "Bitcoin History Events (BTC Story)"
V1 News from January to May
tt_020125()
tt_070125()
tt_200125()
tt_270125()
tt_300125()
tt_030225()
tt_260225()
tt_240225()
tt_020325()
tt_030325()
tt_090325()
tt_110325()
tt_190325()
tt_280325()
tt_310325()
tt_020425()
tt_060425()
tt_090425()
tt_150425()
tt_190425()
tt_220425()
tt_050525()
tt_080525()
tt_130525()
tt_200525()
tt_220525()
Engineer_Invest Support BTCDescription of the "Engineer_Invest Support BTC" indicator
The indicator is designed to highlight a dynamic support level using a combination of a smoothed trend and an assessment of market volatility. Its key features are:
1. Calculating the baseline using the EMA:
The script calculates an exponential moving average (EMA) of the opening price with a configurable period (200 by default). This allows you to create a reliable basis for interpreting price movements, minimizing the impact of short-term fluctuations.
2. Volatility assessment via ATR:
To analyze market variability, the method of calculating the average true range (ATR) multiplied by a given coefficient (default is 5) is used. This approach helps accurately reflect the current market volatility by adjusting the support level depending on the intensity of price fluctuations.
3. Fixed estimated timeframe:
The main calculation is performed on a fixed 3-day interval, which guarantees the stability of the plotted lines regardless of the selected base time interval of the graph. This avoids the undesirable effects of short-term "noise" and ensures the consistency of analytics, especially in highly volatile markets such as cryptocurrencies.
4. Dynamic line formation:
Based on the calculated values of EMA and ATR, the lower boundary of the channel is determined, which is drawn with a bold green line – it serves as a dynamic support zone. At the same time, the ATR value from the previous bar is used to increase the stability of the calculation, which helps smooth out extreme market surges.
5. Flexibility and customization:
Indicator parameters such as the ATR period, the ATR Multiplier coefficient, and a fixed estimated timeframe are available for change. This allows traders to adapt the script to individual strategies and features of the analyzed asset.
Practical application:
- Determining support levels: The indicator helps to identify potential areas where the asset price may find support in a decline.
- Adaptability to market conditions: Using ATR makes it possible to take into account volatility, which is especially important for active markets, for example, for BTC.
- Stability of signals on any timeframe: Due to the fixed 3-day calculation interval, the support line remains unchanged even when the base graphical interval is changed.
The "Engineer_Invest Support BTC" indicator is a well-thought-out analytical solution for technical analysis, combining elements of trend smoothing and a volatility filter. It can be used as an independent tool to find key support levels, or combined with other analysis methods to form a more complete picture of market dynamics.
Important!
This indicator is designed and optimized exclusively for working with BTC. His calculations take into account the unique features of bitcoin's market dynamics and volatility, which provides the most reliable determination of support levels for this particular asset. The use of this instrument in other markets may not provide the expected signal accuracy.
BTC Spot/Perp Price DeltaThe indicator gathers price from 3 btc spot pairs (largest by volume) and 3 btc perp pairs (also largest by volume).
The average Spot and Perp prices are then derived.
The indicator plots the price difference between the Spot average and the Perps average (Spot minus Perps).
Green plot above the zero line means Spot price is higher than the Perp price at a candle close - Contango.
Red plot below the zero line means Spot Price is lower than the Perp price at a candle close - Backwardation.
The orange line is the EMA. Default value is 100 periods. Changeable by User.
Use cases:
1. Perp market is way larger than the Spot market, measured by traded Volume. We may say that the Perps market is more "stable", because it is more liquid. When Spot price deviates a lot from the Perps price, in both positive and negative directions, we may expect a mean reversion.
High Green or Red indicator values = expect price reversion.
2. Helps to observe absorption. If the indicator values are high (in both directions), but the price is barely moving, we can come to a conclusion that the opposite side Limit orders are being deployed to absorb Spot market orders.
Typically, this also indicates mean reversion.
3. You are welcome to use the indicator and perhaps find your own use cases.
Any suggestions on how to improve this indicator are welcome.
Spent Output Profit Ratio Z-Score | Vistula LabsOverview
The Spent Output Profit Ratio (SOPR) Z-Score indicator is a sophisticated tool designed by Vistula Labs to help cryptocurrency traders analyze market sentiment and identify potential trend reversals. It leverages on-chain data from Glassnode to calculate the Spent Output Profit Ratio (SOPR) for Bitcoin and Ethereum, transforming this metric into a Z-Score for easy interpretation.
What is SOPR?
Spent Output Profit Ratio (SOPR) measures the profit ratio of spent outputs (transactions) on the blockchain:
SOPR > 1: Indicates that, on average, coins are being sold at a profit.
SOPR < 1: Suggests that coins are being sold at a loss.
SOPR = 1: Break-even point, often seen as a key psychological level.
SOPR provides insights into holder behavior—whether they are locking in profits or cutting losses—making it a valuable gauge of market sentiment.
How It Works
The indicator applies a Z-Score to the SOPR data to normalize it relative to its historical behavior:
Z-Score = (Smoothed SOPR - Moving Average of Smoothed SOPR) / Standard Deviation of Smoothed SOPR
Smoothed SOPR: A moving average (e.g., WMA) of SOPR over a short period (default: 30 bars) to reduce noise.
Moving Average of Smoothed SOPR: A longer moving average (default: 180 bars) of the smoothed SOPR.
Standard Deviation: Calculated over a lookback period (default: 200 bars).
This Z-Score highlights how extreme the current SOPR is compared to its historical norm, helping traders spot significant deviations.
Key Features
Data Source:
Selectable between BTC and ETH, using daily SOPR data from Glassnode.
Customization:
Moving Average Types: Choose from SMA, EMA, DEMA, RMA, WMA, or VWMA for both smoothing and main averages.
Lengths: Adjust the smoothing period (default: 30) and main moving average length (default: 180).
Z-Score Lookback: Default is 200 bars.
Thresholds: Set levels for long/short signals and overbought/oversold conditions.
Signals:
Long Signal: Triggered when Z-Score crosses above 1.02, suggesting potential upward momentum.
Short Signal: Triggered when Z-Score crosses below -0.66, indicating potential downward momentum.
Overbought/Oversold Conditions:
Overbought: Z-Score > 2.5, signaling potential overvaluation.
Oversold: Z-Score < -2.0, indicating potential undervaluation.
Visualizations:
Z-Score Plot: Teal for long signals, magenta for short signals.
Threshold Lines: Dashed for long/short, solid for overbought/oversold.
Candlestick Coloring: Matches signal colors.
Arrows: Green up-triangles for long entries, red down-triangles for short entries.
Background Colors: Magenta for overbought, teal for oversold.
Alerts:
Conditions for Long Opportunity, Short Opportunity, Overbought, and Oversold.
Usage Guide
Select Cryptocurrency: Choose BTC or ETH.
Adjust Moving Averages: Customize types and lengths for smoothing and main averages.
Set Thresholds: Define Z-Score levels for signals and extreme conditions.
Monitor Signals: Use color changes, arrows, and background highlights to identify opportunities.
Enable Alerts: Stay informed without constant chart watching.
Interpretation
High Z-Score (>1.02): SOPR is significantly above its historical mean, potentially indicating overvaluation or strong bullish momentum.
Low Z-Score (<-0.66): SOPR is below its mean, suggesting undervaluation or bearish momentum.
Extreme Conditions: Z-Scores above 2.5 or below -2.0 highlight overbought or oversold markets, often preceding reversals.
Conclusion
The SOPR Z-Score indicator combines on-chain data with statistical analysis to provide traders with a clear, actionable view of market sentiment. Its customizable settings, visual clarity, and alert system make it an essential tool for both novice and experienced traders seeking an edge in the cryptocurrency markets.
Supply In Profit Z-Score | Vistula LabsOverview
The Supply In Profit Z-Score indicator is a Pine Script™ tool developed by Vistula Labs for technical analysis of cryptocurrencies, specifically Bitcoin (BTC) and Ethereum (ETH). It utilizes on-chain data from IntoTheBlock to calculate the difference between the percentage of addresses in profit and those in loss, transforming this metric into a Z-Score. This indicator helps traders identify market sentiment, trend-following opportunities, and overbought or oversold conditions.
What is Supply In Profit?
Supply In Profit is defined as the net difference between the percentage of addresses in profit and those in loss:
Profit Percentage: The proportion of addresses where the current value of holdings exceeds the acquisition price.
Loss Percentage: The proportion of addresses where the current value is below the acquisition price.
A positive value indicates more addresses are in profit, suggesting bullish sentiment, while a negative value indicates widespread losses, hinting at bearish sentiment.
How It Works
The indicator computes a Z-Score to normalize the Supply In Profit data relative to its historical behavior:
Z-Score = (Current Supply In Profit - Moving Average of Supply In Profit) / Standard Deviation of Supply In Profit
Current Supply In Profit: The latest profit-minus-loss percentage.
Moving Average: A customizable average (e.g., EMA, SMA) over a default 180-bar period.
Standard Deviation: Calculated over a default 200-bar lookback period.
Key Features
Data Source:
Selectable between BTC and ETH, pulling daily profit/loss percentage data from IntoTheBlock.
Customization:
Moving Average Type: Options include SMA, EMA, DEMA, RMA, WMA, or VWMA (default: EMA).
Moving Average Length: Default is 180 bars.
Z-Score Lookback: Default is 200 bars.
Thresholds: Adjustable for long/short signals and overbought/oversold levels.
Signals:
Long Signal: Z-Score crosses above the Long Threshold (default: 1.0).
Short Signal: Z-Score crosses below the Short Threshold (default: -0.64).
Overbought/Oversold Conditions:
Overbought: Z-Score > 3.0.
Oversold: Z-Score < -2.0.
Visualizations:
Z-Score Plot: Teal for long signals, magenta for short signals.
Threshold Lines: Dashed lines for long/short, solid lines for overbought/oversold.
Candlestick Coloring: Matches signal colors (teal/magenta).
Arrows: Green up-triangles for long entries, red down-triangles for short entries.
Background Colors: Magenta for overbought, teal for oversold.
Alerts:
Conditions for Long Opportunity, Short Opportunity, Overbought, and Oversold.
Usage Guide
Trend Following
Long Entry: When Z-Score crosses above 1.0, indicating potential upward momentum.
Short Entry: When Z-Score crosses below -0.64, suggesting potential downward momentum.
Overbought/Oversold Analysis
Overbought (Z-Score > 3.0): Consider profit-taking or preparing for a reversal.
Oversold (Z-Score < -2.0): Look for buying opportunities or exiting shorts.
Timeframe
Uses daily IntoTheBlock data, ideal for medium to long-term analysis.
Interpretation
High Z-Score: Indicates Supply In Profit is significantly above its historical mean, potentially signaling overvaluation.
Low Z-Score: Suggests Supply In Profit is below its mean, indicating possible undervaluation.
Signals and thresholds help traders act on shifts in market sentiment or extreme conditions.
Conclusion
The Supply In Profit Z-Score indicator provides a robust, data-driven approach to analyzing cryptocurrency market trends and sentiment. By combining on-chain metrics with statistical normalization, it empowers traders to make informed decisions based on historical context and current market dynamics.
BTC Dominance Excluding StablecoinsBTC Dominance Excluding Stablecoins
Description:
The "BTC Dominance Excluding Stablecoins" indicator calculates Bitcoin's dominance as a percentage of the total cryptocurrency market capitalization, excluding the market caps of major stablecoins (USDT and USDC). Unlike the standard BTC.D ticker, which includes stablecoins in the total market cap, this indicator provides a clearer view of Bitcoin’s dominance relative to the "non-stable" crypto market. This can be useful for traders and analysts who want to assess Bitcoin’s strength without the influence of stablecoin market caps, which often skew dominance metrics during periods of high stablecoin usage.
How It Works:
Bitcoin Market Cap: Fetches Bitcoin’s market capitalization using CRYPTOCAP:BTC.
Total Market Cap: Retrieves the total cryptocurrency market cap via CRYPTOCAP:TOTAL.
Stablecoin Adjustment: Subtracts the market caps of USDT (CRYPTOCAP:USDT) and USDC (CRYPTOCAP:USDC) from the total market cap.
Dominance Calculation: Computes Bitcoin’s dominance as (BTC Market Cap / Adjusted Total Market Cap) * 100, where the adjusted total excludes stablecoins.
Output: Plots the resulting dominance percentage as a line chart.
Features:
Displays Bitcoin dominance excluding stablecoins on any timeframe.
Customizable line color and thickness for better visualization.
Provides a more accurate representation of Bitcoin’s market share in the volatile, non-stablecoin crypto ecosystem.
Usage:
Add this indicator to your TradingView chart to compare Bitcoin’s dominance against the broader altcoin market, free from stablecoin distortions. Use it alongside other indicators like BTC.D or price charts to analyze market trends, especially during periods of high stablecoin inflows or outflows.
Notes:
The indicator currently excludes USDT and USDC, the two largest stablecoins by market cap. Additional stablecoins (e.g., DAI, BUSD) can be added by modifying the script if desired.
Data is sourced from TradingView’s CRYPTOCAP symbols, which may have slight delays or variations depending on exchange data feeds.
Best used on daily or higher timeframes for smoother, more reliable results.
Author:
Created by K Du₿
Version:
Pine Script v5
Breaking Structures (javieresfeliz)This TradingView script is designed to identify market structure changes, using a break of highs and lows approach, as well as technical indicators such as ATR, RSI, and EMAs (Exponential Moving Averages). It is aimed at detecting bullish and bearish trends, signaling possible entry and exit points based on various factors. It also offers additional confirmations to avoid false signals and provides a clear visualization of buy and sell signals.
Main Features:
Indicators Used:
ATR (Average True Range): Used to calculate a volatility range, which helps set stop-loss levels and price targets based on the current market volatility.
EMAs (50 and 200): Exponential Moving Averages (EMAs) are used to determine the short-term and long-term trends. The 50-period EMA is used to identify the short-term trend, while the 200-period EMA is used to identify the long-term trend.
RSI (Relative Strength Index): Used to identify overbought or oversold conditions in the market, providing additional buy or sell signals.
Volume: Used to confirm the validity of a signal. An increase in volume can confirm a structure break and provide more reliability to the signal.
Break of Structure Detection (BOS):
Bullish Break: Generated when the price surpasses previous highs.
Bearish Break: Generated when the price falls below previous lows.
Change of Character (CHOCH):
Bullish Trend: Defined by a close above the open and above the 50 EMA.
Bearish Trend: Defined by a close below the open and below the 50 EMA.
Buy and Sell Conditions:
Buy (Long): Activated when several conditions are met, including a bullish change of character, a bullish structure break, the price closing above the previous value plus a multiple of the ATR, and additional confirmations from RSI and volume.
Sell (Short): Activated when several conditions are met, including a bearish change of character, a bearish structure break, the price closing below the previous value minus a multiple of the ATR, with additional confirmations from RSI and volume.
Entry and Exit Signals:
Long Entry (Buy): Executed when the buy conditions are met.
Short Entry (Sell): Executed when the sell conditions are met.
Position Close: Positions are closed when the price crosses below (for long positions) or above (for short positions) the 50 EMA.
Historical Highs and Lows Lines:
The script draws lines of historical highs and lows from the last 288 and 60 periods to show key support and resistance levels on the chart.
Signal Table Across Multiple Timeframes:
The script displays a table in the top-right corner of the chart with indicators like the EMA trend, RSI value, and MACD histogram for timeframes of 1 minute, 5 minutes, 30 minutes, 1 hour, 4 hours, daily, and weekly.
Precautions:
Does not guarantee profits: Although the script is designed to detect structure breaks and possible trend changes, it does not guarantee 100% profitable signals. The market is always subject to risk and unpredictable volatility.
Requires adjustments for each asset: Parameters such as ATR length and EMA lengths should be adjusted according to the asset being analyzed and market conditions.
Use of additional confirmations: To reduce false signals, the script uses additional confirmations like RSI and volume, but it is always recommended to perform additional analysis before making trading decisions.
Changing trends: The change of character (CHOCH) can be a useful indicator, but it can give false signals in highly volatile markets or during prolonged consolidations.
Relies on historical data: This script relies on historical data to identify highs and lows. It does not consider fundamental events that may significantly impact the market.
Requires constant monitoring: Although the signals are automated, it is important to monitor open positions and make adjustments if market conditions change.
Risk of false signals: In low liquidity markets or consolidations, structure breaks can be false, so it’s recommended to pay attention to any additional confirmation signals or use a proper risk management strategy.
Volumen trend indicator 5MVOLUMEN TREND INDICATOR
Introduction
This indicator on TradingView provides a combination of technical analysis through a data table and visual elements on the chart. Its purpose is to provide a comprehensive view of the analyzed asset, facilitating decision-making.
How It Works
The indicator operates on two levels:
Data Table:
Displays key information about the asset's trend.
Includes metrics such as the current price, percentage change, volatility, and other relevant variables.
Can be customized to include additional indicators as needed.
Provides a quick analysis without the need to interpret complex charts.
Technical Elements on the Chart:
Incorporates dynamic support and resistance lines.
Can include moving averages, Bollinger Bands, RSI, or other custom indicators.
Offers visual alerts for significant changes in the asset's trend.
Facilitates detailed technical analysis through direct observation of patterns and signals.
Default Technical Indicators
The indicator comes with the following default pre-configured technical indicators:
Exponential Moving Average (EMA) 9:
This EMA responds more quickly to price movements, making it ideal for identifying short-term trends. It is generally used to detect crossovers with other EMAs or prices and is considered an entry or exit signal.
Exponential Moving Average (EMA) 21:
The 21-period EMA is used to identify medium-term trends. Its interaction with the 9 EMA is key to confirming buy or sell signals when both cross.
RSI (Relative Strength Index):
It is used to measure the magnitude of recent gains and losses of an asset, helping to identify overbought or oversold conditions.
Bollinger Bands:
These bands help identify volatility levels and potential reversal points. Price touching the upper or lower bands can be an important signal of trend change or continuation.
Customization
The user can modify several aspects of the indicator, such as:
Colors and styles of visual elements on the chart.
Types of indicators to include in the table.
Configuration of alerts and notifications.
Time interval for calculations and data updates.
EMA values (the periods can be changed if other configurations are desired).
Recommended Usage
To make the most of the indicator:
Use the data table to get an overview of the asset.
Analyze the technical elements on the chart to confirm trends.
Set alerts to avoid missing key opportunities.
Compare the information with other indicators and data sources before making decisions.
Precautions and Best Practices
Avoid relying solely on the indicator: Complement it with other technical and fundamental analysis.
Adjust the settings according to the asset's volatility: Not all strategies work the same across different markets.
Don’t overload the chart with too many elements: This can create visual noise and confusion in interpretation.
Test it on a demo account before trading live: To familiarize yourself with the indicator's functionality and adjustments.
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Remember that no system is perfect, keep these considerations in mind for this indicator:
Do not trade when a signal appears during an opposite trend:
Do not trade when the market is uncertain in its direction or within a parallel channel: