Profit Hunter @DaviddTechProfit Hunter @DaviddTech is an advanced multi-strategy indicator designed to give traders a significant edge in identifying high-probability trading opportunities across all market conditions. By combining the power of T3 adaptive moving averages, ADX-based trend strength analysis, SuperTrend trailing stops, and dynamic support/resistance detection, this indicator delivers a complete trading system in one powerful package.
## 📊 Recommended Usage
Timeframes: Most effective on 1H, 4H, and Daily charts for swing trading; 5M and 15M for day trading
Markets: Works across all markets including Forex, Crypto, Indices, and Stocks
Setup Guidelines: Look for T3 crossovers with strong ADX readings (>25) coinciding with breakout signals (yellow dots/red crosses) near key support/resistance levels for highest probability entries
## 🔥 Key Features:
### T3 Adaptive Trend Detection:
Utilizes premium T3 adaptive indicators instead of standard EMAs for superior smoothing and accuracy
Dynamic color-shifting cloud formation between fast and slow T3 lines reveals immediate trend direction
Proprietary transparency algorithm intensifies cloud colors during strong trends based on real-time ADX readings
### Advanced Support & Resistance Mapping:
Automatically identifies and marks key market structure levels during T3 crossovers
Dynamic horizontal level plotting with optional extension for monitoring future price interactions
Intelligent level validation - converts to dotted lines when price breaks through, maintaining visual clarity
### SuperTrend Trailing Stoploss System:
Professional-grade white trailing stop indicator adapts to market volatility using ATR calculations
Generates precise entry and exit signals with optional buy/sell labels at critical reversal points
Visual trend state highlighting for immediate assessment of current market position
### Breakout Detection & Confirmation:
Sophisticated dual-algorithm breakout system combining Bollinger Bands and Keltner Channels
Visual breakout alerts with yellow dots (bullish) and red crosses (bearish) for instant pattern recognition
Validates breakouts against T3 trend direction to minimize false signals
### Alpha Edge Color System:
Utilizes DaviddTech's signature color scheme with bullish green and bearish pink
Revolutionary transparency algorithm translates ADX readings into precise visual intensity
Higher ADX values produce more vivid colors, instantly communicating trend strength without additional indicators
## 💰 Trading Applications:
Alpha Discovery: Identify emerging trends before the majority of market participants
Precision Entry/Exit: Use SuperTrend signals combined with support/resistance levels for optimal trade execution
Risk Management: Set stops based on the white trailing stoploss line for mathematically-optimized protection
Trend Confirmation: Validate setups using the T3 cloud direction and ADX-based intensity
Breakout Trading: Capture explosive moves with confirmed Bollinger/Keltner breakout signals
Swing Position Management: Monitor extended support/resistance levels for multi-day positioning
## ✨ Strategy Example
As shown in the chart image, ideal entries occur when:
The T3 cloud turns bullish (green) or bearish (pink) with strong color intensity
A yellow dot (bullish) or red cross (bearish) breakout signal appears
Price respects the white SuperTrend line as support/resistance
The trade aligns with key horizontal support/resistance levels identified by the indicator
## 📝 Attribution
This indicator builds upon and enhances concepts from:
Market Trend Levels Detector by BigBeluga (support/resistance detection framework)
T3 indicator implementation by DaviddTech (adaptive moving average system)
Average Directional Index (ADX) methodology for trend strength measurement
Profit Hunter @DaviddTech represents the culmination of advanced technical analysis methodologies in one seamless system.
Wyszukaj w skryptach "market structure"
Supertrend and Fast and Slow EMA StrategyThis strategy combines Exponential Moving Averages (EMAs) and Average True Range (ATR) to create a simple, yet effective, trend-following approach. The strategy filters out fake or sideways signals by incorporating the ATR as a volatility filter, ensuring that trades are only taken during trending conditions. The key idea is to buy when the short-term trend (Fast EMA) aligns with the long-term trend (Slow EMA), and to avoid trades during low volatility periods.
How It Works:
EMA Crossover:
1). Buy Signal: When the Fast EMA (shorter-term, e.g., 20-period) crosses above the Slow EMA (longer-term, e.g., 50-period), this indicates a potential uptrend.
2). Sell Signal: When the Fast EMA crosses below the Slow EMA, this indicates a potential downtrend.
ATR Filter:
1). The ATR (Average True Range) is used to measure market volatility.
2). Trending Market: If the ATR is above a certain threshold, it indicates high volatility and a trending market. Only when ATR is above the threshold will the strategy generate buy/sell signals.
3). Sideways Market: If ATR is low (sideways or choppy market), the strategy will suppress signals to avoid entering during non-trending conditions.
When to Buy:
1). Condition 1: The Fast EMA crosses above the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, indicating that the market is trending (not sideways or choppy).
When to Sell:
1). Condition 1: The Fast EMA crosses below the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, confirming that the market is in a downtrend.
When Not to Enter the Trade:
1). Sideways Market: If the ATR is below the threshold, signaling low volatility and sideways or choppy market conditions, the strategy will not trigger any buy or sell signals.
2). False Crossovers: In low volatility conditions, price action tends to be noisy, which could lead to false signals. Therefore, avoiding trades during these periods reduces the risk of false breakouts.
Additional Factors to Consider Adding:
=> RSI (Relative Strength Index): Adding an RSI filter can help confirm overbought or oversold conditions to avoid buying into overextended moves or selling too low.
1). RSI Buy Filter: Only take buy signals when RSI is below 70 (avoiding overbought conditions).
2). RSI Sell Filter: Only take sell signals when RSI is above 30 (avoiding oversold conditions).
=> MACD (Moving Average Convergence Divergence): Using MACD can help validate the strength of the trend.
1). Buy when the MACD histogram is above the zero line and the Fast EMA crosses above the Slow EMA.
2). Sell when the MACD histogram is below the zero line and the Fast EMA crosses below the Slow EMA.
=> Support/Resistance Levels: Adding support and resistance levels can help you understand market structure and decide whether to enter or exit a trade.
1). Buy when price breaks above a significant resistance level (after a valid buy signal).
2). Sell when price breaks below a major support level (after a valid sell signal).
=> Volume: Consider adding a volume filter to ensure that buy/sell signals are supported by strong market participation. You could only take signals if the volume is above the moving average of volume over a certain period.
=> Trailing Stop Loss: Instead of a fixed stop loss, use a trailing stop based on a percentage or ATR to lock in profits as the trade moves in your favor.
=> Exit Signals: Besides the EMA crossover, consider adding Take Profit or Stop Loss levels, or even using a secondary indicator like RSI to signal an overbought/oversold condition and exit the trade.
Example Usage:
=> Buy Example:
1). Fast EMA (20-period) crosses above the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is below 70, the buy signal is further confirmed as not being overbought.
=> Sell Example:
1). Fast EMA (20-period) crosses below the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is above 30, the sell signal is further confirmed as not being oversold.
Conclusion:
This strategy helps to identify trending markets and filters out sideways or choppy market conditions. By using Fast and Slow EMAs combined with the ATR volatility filter, it provides a reliable approach to catching trending moves while avoiding false signals during low-volatility, sideways markets.
Trendchange Zones Indicator | iSolani
Spotting Reversals Before They Happen: The iSolani Trendshift System
Where RSI Meets Smart Volume Analysis - Your Visual Guide to Market Turns
Core Methodology
RSI-Powered Zones
Identifies critical levels using:
14-period RSI (default) with 70/30 thresholds
Semi-transparent boxes marking overbought (red) and oversold (green) territories
Zone persistence until RSI returns to neutral range
Dynamic Level Tracking
Plots evolving support/resistance using:
Pivot highs/lows with 15-bar lookback (default)
Auto-extending lines that adapt to new price extremes
Volume-Confirmed Breakouts
Flags significant moves with:
5/10 EMA volume oscillator
20% volume threshold (default) for confirmation
Technical Innovation
Three-Layer Confirmation
Unique combination of:
Classic RSI extremes
Price structure through pivot points
Volume-fueled momentum shifts
Adaptive Visualization
Zones maintain historical context at 33% transparency
Dynamic lines extend indefinitely until invalidated
Discreet labels for breakout events
System Workflow
Calculates RSI values in real-time
Draws colored zones when RSI crosses 70/30
Marks pivot points every 15 bars (default)
Updates support/resistance lines on new pivots
Triggers alerts when price breaks levels with volume confirmation
Standard Configuration
RSI Settings : 14-period length
Pivot Detection : 15-bar left/right lookback
Visuals : 33% transparency zones with thin borders
Volume Threshold : 20% oscillator difference
Alerts : Breakout signals with "B" labels
This system transforms the classic RSI into a spatial analysis tool - not just showing when markets are overextended, but where they're likely to reverse. The dynamic lines act as moving barriers that adapt to market structure, while the volume filter ensures only high-conviction breaks get flagged. By layering momentum, price action, and volume dynamics, it creates a multi-spectrum view of potential trend changes.
Crystal Order BlockThe Crystal Order Block Indicator is a powerful tool designed to help traders identify key institutional order blocks with high precision. This indicator is ideal for traders following Smart Money Concepts (SMC) and Institutional Trading Strategies, providing clear insights into potential high-probability trade setups.
🔹 Key Features:
✔ Automatic Order Block Detection: Identifies valid bullish & bearish order blocks.
✔ Unmitigated Order Blocks Highlighted: Focuses on fresh order blocks for improved trade opportunities.
✔ Trend-Focused Trading: Works best when combined with market structure analysis.
✔ Multi-Timeframe Support: Suitable for scalping, swing trading, and intraday trading.
✔ Risk Management Enhancement: Helps traders refine entries and exits based on institutional price movements.
📈 How to Use the Crystal Order Block Indicator:
🔹 Identifying Order Blocks:
➡ The indicator automatically detects order blocks formed by institutional trading activity.
➡ Unmitigated order blocks are highlighted, indicating areas where price may react.
🔹 High-Probability Trade Setups:
➡ Buy Setup: Look for a bullish order block in an uptrend, confirming strength.
➡ Sell Setup: Identify a bearish order block in a downtrend for potential short trades.
🔹 Order Block Mitigation:
➡ The updated version filters out mitigated order blocks, allowing traders to focus on fresh trading opportunities.
📊 Best Practices & Timeframes:
🔸 Works on all timeframes, but higher accuracy is observed on M30 and above.
🔸 Best suited for Smart Money Trading, Institutional Trading, and Price Action Strategies.
🔸 Should be used with liquidity concepts and market structure analysis for enhanced precision.
⚠ Important Note:
This indicator is a technical tool designed to assist traders in market analysis. It does not guarantee success and should be used alongside proper risk management and trading discipline.
RSI Divergence[UgurTash] – Real-Time📈 RSI Divergence – Real-Time, Adaptive, and Intelligent RSI Divergence Detection
🚀 What Does This Indicator Do?
RSI Divergence is a real-time divergence detection tool that helps traders identify bullish and bearish divergences between price and the Relative Strength Index (RSI). Unlike traditional RSI-based indicators, this script offers:
✅ Real-time detection – No need to wait for bar closes or repainting.
✅ Dynamic time-frame adaptation – The script automatically adjusts RSI settings based on the selected chart time frame.
✅ Multi-layered divergence analysis – Supports short-term, medium-term, and long-term divergence detection with an optional all-term mode that dynamically selects the best configuration.
🛠 How Does It Work?
Pivot-Based Divergence Detection:
The script analyzes pivot points on both price and RSI to determine valid divergences.
Bullish divergence occurs when price forms a lower low but RSI trends higher, indicating potential upward momentum.
Bearish divergence occurs when price forms a higher high but RSI trends lower, signaling possible weakness.
Adaptive RSI Calculation:
The RSI length is dynamically adjusted based on the chosen time frame:
Short-Term: RSI (7) for 1-5 min charts.
Medium-Term: RSI (14) for 15-60 min charts.
Long-Term: RSI (28) for 4H+ charts.
In All-Term Mode, the script automatically determines the best RSI length based on the active chart timeframe.
Smart Visualization & Alerts:
Bullish divergences are marked with green lines & labels.
Bearish divergences are highlighted in red.
Users can customize symbol size, divergence labels, and colors.
Instant alerts notify traders as soon as a divergence is detected.
🎯 How to Use This Indicator?
📌 For Trend Reversals: Look for bullish divergences at key support levels and bearish divergences at resistance zones.
📌 For Trend Continuation: Combine divergence signals with moving averages, volume analysis, or price action strategies to confirm trades.
📌 For Scalping & Swing Trading: Adjust the time-frame settings to match your trading style.
🏆 What Makes This Indicator Original?
🔹 Unlike standard RSI divergence indicators, this script features real-time analysis with no repainting, allowing for instant trading decisions.
🔹 The time-frame adaptive RSI makes it dynamic and suitable for any market condition.
🔹 The multi-term divergence detection offers flexibility, giving traders a precise view of both short-term & long-term market structure.
⚠ Note: No indicator guarantees 100% accuracy. Always use additional confirmations and sound risk management strategies.
If you find this tool useful, don’t forget to support & share! 🚀
Opening Score with DivergenceOverview
The Opening Score Indicator is a versatile tool designed to help traders assess market sentiment, trend direction, and potential reversals. By combining Opening Range Breakout (ORB), VWAP, Trend, Volatility, and Divergence Detection, this indicator provides a composite score that adapts to different market conditions.
This version includes divergence detection between the Opening Score and price, which highlights potential trend reversals or continuations before they happen. When a regular divergence occurs, the histogram bar turns orange, signaling an increased probability of a trend change.
Best for Both Intraday & Longer-Term Charts
📊 Optimized for intraday trading → Works well on 1m to 30m timeframes for short-term strategies.
📈 Also effective on longer-term charts → Can be used on 1-hour, 4-hour, daily, or weekly charts to identify macro trends and momentum shifts.
🕰️ Adapts to different market conditions → Whether you’re a day trader, swing trader, or position trader, the Opening Score helps you track trend health and reversals.
How It Works
📊 Composite Opening Score Calculation
• ORB Signal → Detects bullish/bearish breakouts based on the opening range.
• VWAP Signal → Measures price positioning relative to VWAP for trend confirmation.
• Trend Signal → Uses a moving average to determine market direction.
• Volatility Signal → Tracks ATR changes to assess market strength.
• Divergence Detection → Identifies regular and hidden divergences for potential reversals or trend continuation.
🔹 Reversal Alerts with Color-Coded Histogram
• Green Bars → Normal bullish Opening Score.
• Red Bars → Normal bearish Opening Score.
• Orange Bars → Warning! Regular Divergence detected → Possible trend reversal.
🔹 Hidden & Regular Divergence Detection
• Regular Divergence (Reversal Signals)
• 📉 Bearish Regular Divergence → Price makes a Higher High, but Opening Score makes a Lower High → 🔻 Possible Downtrend Reversal.
• 📈 Bullish Regular Divergence → Price makes a Lower Low, but Opening Score makes a Higher Low → 🔼 Possible Uptrend Reversal.
• Hidden Divergence (Trend Continuation Signals)
• 📉 Bearish Hidden Divergence → Price makes a Lower High, but Opening Score makes a Higher High → 🔻 Trend Likely to Continue Down.
• 📈 Bullish Hidden Divergence → Price makes a Higher Low, but Opening Score makes a Lower Low → 🔼 Trend Likely to Continue Up.
How to Use It
✅ Watch for Reversal Alerts (Orange Bars) → These highlight potential market turning points.
✅ Use the Zero Line as a Trend Filter → A score above 0 suggests bullish conditions, while below 0 signals bearish conditions.
✅ Combine with Market Structure & Volume Profile → Works well when paired with support/resistance levels, liquidity zones, and order flow data.
✅ Adjust settings based on timeframe → Increase moving average length & lookback periods for longer-term analysis.
Why Use This Indicator?
🚀 Works for both short-term and long-term traders → Adapts to intraday and higher timeframes.
📊 Multi-Factor Analysis → Combines multiple key market indicators for better accuracy.
🎯 Customizable Weighting → Adjust the influence of each signal to suit your trading style.
✅ No Clutter – Only the Opening Score is plotted → Keeps your chart clean & efficient.
🔔 Recommended for Intraday Trading (1m – 30m) AND Longer-Term Analysis (1H – Weekly) → Use this indicator to enhance your trend detection & reversal strategy! 🚀
STRAW Volume Spike IndicatorThis is basically a:
High-Volume Impulse Detector
The High-Volume Impulse Detector is a refined tool designed to highlight key moments of explosive volume surges in the market, specifically calibrated for assets like Bitcoin on the 15-minute timeframe. Unlike generic volume-based indicators, this script doesn’t just flag high volume—it intelligently adapts to market dynamics by incorporating a custom-moving average baseline and highlighting instances where volume exceeds a significant threshold relative to the average.
Key Features
✅ Adaptive Volume Benchmark – Uses a dynamic moving average to filter out noise and pinpoint meaningful volume spikes.
✅ Impulse Confirmation – Only highlights volume bars that exceed the 50% threshold above the baseline, ensuring signals capture real liquidity shifts.
✅ Smart Color Coding – Differentiates high-impact bullish and bearish volume with distinct visual cues for easy market structure identification.
✅ Designed for Order Block Traders – Helps validate liquidity-driven price movements essential for refining order block and break-of-structure strategies.
Unlike conventional volume overlays, this tool helps traders connect volume surges to key structural shifts, making it an ideal companion for those navigating momentum shifts, market inefficiencies, and institutional footprints.
⚡ Best used on BTC 15m for tracking aggressive volume-driven moves in real-time.
Hyper MA Loop | QuantEdgeBIntroducing Hyper MA Loop by QuantEdgeB
Hyper MA Loop | QuantEdgeB is an advanced trend-following indicator that leverages a custom Hyper Moving Average (HyMA) and an innovative loop-based scoring system to assess trend strength and direction. This tool is designed to provide a dynamic perspective on market momentum, allowing traders to capture trends effectively while filtering out market noise.
Key Features:
1. Hyper Moving Average (HyMA) 🟣
- A weighted moving average that enhances trend responsiveness by applying a custom
weight function.
- Ensures smoother trend detection while maintaining reactivity to price changes.
2. Loop-Based Trend Scoring 🔄
- Utilizes a for-loop function to analyze the movement of HyMA over a specified period.
- Compares current values to past values, generating a cumulative score indicating bullish or
bearish momentum.
- Dynamic thresholds adjust to market conditions for better trend filtering.
3. Threshold-Based Signal System ✅❌
- Long Signals: Triggered when the loop score exceeds the long threshold.
- Short Signals: Activated when the score falls below the short threshold.
- Avoids false signals by requiring sustained strength before confirming a trend.
4. Customizable Visualization & Colors 🎨
- Multiple color modes (Default, Solar, Warm, Cool, Classic) for tailored aesthetics.
- Extra plot options enhance visualization of market structure and volatility.
________
How It Works:
- HyMA Calculation : A unique moving average with a specialized weighting function to
smooth out price action.
- Loop Function : Iterates over past HyMA values, assessing whether price is consistently
higher or lower.
- Threshold Comparison : The loop score is compared against pre-set thresholds to
determine bullish or bearish conditions.
- Signal Generation :
1. Bullish (🔵): If the score crosses the long threshold
2. Bearish (🔴): If the score drops below the short threshold.
- Plotting & Styling : Dynamic candles and gradient overlays provide an intuitive
visualization of rend shifts.
________
Use Cases:
✅ Ideal for trend-following traders looking for solid trends confirmation.
✅ Helps filter out choppy market conditions by adjusting sensitivity dynamically.
✅ Works well with other indicators (e.g., ADX, volume-based filters) for added confirmation.
✅ Suitable for both short-term and long-term trend analysis.
________
Customization Options:
- Adjustable HyMA Length: Modify the responsiveness of the moving average. Default se to 2.
- For-Loop Parameters: Fine-tune how far back the trend analysis should consider. Default se to Start = 1 , End = -1.
- Thresholds for Long & Short: Control signal sensitivity to market fluctuations. Default set to Long = 40, Short = 8.
- Color Modes & Extra Plots: Personalize visualization for better clarity.
________
Conclusion:
The Hyper MA Loop | QuantEdgeB is a powerful, adaptive indicator that combines custom moving averages with loop-based trend analysis to deliver accurate, visually intuitive market signals. Whether you're looking to ride strong trends or filter out weak setups, this tool provides the precision and flexibility needed for effective decision-making. 🚀📈
🔹 Disclaimer: Past performance is not indicative of future results. No trading indicator can guarantee success in financial markets.
🔹 Strategic Consideration: As always, backtesting and strategic adjustments are essential to fully optimize this indicator for real-world trading. Traders should consider risk management practices and adapt settings to their specific market conditions and trading style.
ICT Dealing RangeICT Dealing Range
This indicator identifies and plots ICT (Inner Circle Trader) Dealing Ranges - key institutional areas where smart money accumulates or distributes positions before significant moves.
What is a Dealing Range?
A Dealing Range is a significant price area where institutional traders accumulate or distribute their positions. These ranges form through a specific sequence of price movements that indicate institutional order flow:
Bullish Dealing Range Sequence:
1. Initial High (H)
2. Initial Low (L)
3. Higher High (HH)
4. Lower Low (LL)
5. Break above HH (confirmation)
Bearish Dealing Range Sequence:
1. Initial Low (L)
2. Initial High (H)
3. Lower Low (LL)
4. Higher High (HH)
5. Break below LL (confirmation)
My Trading Strategy
Entry Methods:
1. Range Extreme Retests:
- After range formation, wait for price to return to either extreme
- Long entries at range bottom with stops below
- Short entries at range top with stops above
2. Mid-Line Strategy:
- Use the mid-line as a pivot point for reversals
- Long entries on mid-line bounce with stops below
- Short entries on mid-line rejection with stops above
Stop Loss Placement:
- When entering at extremes: Place stops beyond the mid
- When entering at mid-line: Place stops beyond the opposing extreme
- Always respect the structure's boundaries
Take Profit Targets:
- Minimum 2:1 Risk-Reward ratio
- For extreme entries: Target the opposite extreme
- For mid-line entries: Target the nearest extreme
Risk Management
- Never enter without a clear invalidation point
- Maintain minimum 2:1 RR ratio
- Consider market structure and higher timeframe context
Indicator Features
- Auto-detection of dealing range patterns
- Color-coded boxes (green for bullish, red for bearish)
- Optional mid-line display
- Customizable colors and styles
- Adjustable pivot lookback periods
Notes
This tool is based on ICT concepts but should be used in conjunction with other forms of analysis. The dealing range provides a framework for understanding institutional order flow, but proper risk management and market context are essential for successful trading.
Remember: The best trades often come from clean retests of these ranges after their initial formation. Patience in waiting for proper setups is key to successful implementation.
ELC Indicator**ELC Indicator – Enigma Liquidity Concept**
The ELC Indicator is a cutting-edge tool designed for traders who want to leverage price action and liquidity concepts for high-precision trading opportunities. Unlike conventional indicators that rely purely on trend-following or oscillatory methods, ELC incorporates a unique combination of market structure, Fibonacci retracement levels, and dynamic EMA filtering to detect key buy and sell zones. This original approach helps traders capture the most relevant market movements and anticipate potential reversals with higher confidence.
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### **What the ELC Indicator Does**
The primary goal of the ELC Indicator is to identify liquidity zones and plot Fibonacci-based levels around detected buy or sell signals. It continuously monitors price action to identify instances where significant liquidity grabs occur, signaled by breakouts beyond recent highs or lows. Once a signal is detected, the indicator plots horizontal lines at key Fibonacci ratios (0%, 25%, 50%, 75%, 100%, 120%, and 180%) to give traders a clear visual framework for potential retracement or extension levels.
Additionally, the indicator includes a dynamic EMA filter, which ensures that buy signals are only triggered when the price is above the EMA and sell signals when the price is below the EMA. This filtering mechanism helps reduce false signals in choppy markets and aligns trades with the broader trend direction.
---
### **Key Features**
1. **Buy & Sell Signals**
- Buy signals are generated when a liquidity grab occurs below the previous low, and the closing price is above the candle body midpoint and the EMA.
- Sell signals are triggered when a liquidity grab occurs above the previous high, and the closing price is below the candle body midpoint and the EMA.
- Visual cues are provided via small upward (green) and downward (red) triangles on the chart.
2. **Fibonacci Levels**
- For each buy or sell signal, the indicator plots multiple horizontal lines at key Fibonacci levels. These levels can help traders set realistic profit targets and stop-loss levels.
- The plotted lines can be customized in terms of style (solid, dotted, dashed) and color (buy and sell line colors).
3. **Dynamic EMA Filtering**
- A customizable EMA filter is integrated into the logic to align trades with the prevailing trend.
- The EMA length is adjustable, allowing traders to fine-tune the indicator based on their trading style and market conditions.
4. **Alert System**
- Alerts can be enabled for both buy and sell signals, ensuring traders never miss an opportunity even when away from the screen.
- Alerts are triggered once per bar, ensuring timely notifications without excessive noise.
5. **Customizable Signal Visibility**
- Traders can toggle the visibility of the last 9 buy and sell signals. When this option is disabled, only the most recent signal is displayed, helping to declutter the chart.
---
### **How to Use the ELC Indicator**
- **Trend Following**: The ELC Indicator works well in trending markets by filtering signals based on the EMA direction. Traders can use the plotted Fibonacci levels to enter trades, set profit targets, and manage risk.
- **Reversal Trading**: The liquidity grab detection mechanism allows traders to capture potential market reversals. By waiting for price retracements to key Fibonacci levels after a signal, traders can enter trades with a favorable risk-to-reward ratio.
- **Scalping & Day Trading**: With its ability to plot key intraday levels and generate real-time alerts, the ELC Indicator is particularly useful for scalpers and day traders looking to exploit short-term market inefficiencies.
---
### **Concepts Underlying the Calculations**
1. **Liquidity Grabs**: The ELC Indicator’s core logic is based on detecting instances where the market moves beyond a recent high or low, triggering a liquidity grab. This often signals a potential reversal or continuation, depending on broader market conditions.
2. **Fibonacci Ratios**: Once a signal is detected, key Fibonacci levels are plotted to provide traders with actionable zones for trade entries, profit targets, or stop-loss placements.
3. **EMA Filtering**: The EMA acts as a dynamic trend filter, ensuring that signals are aligned with the dominant market direction. This reduces the likelihood of entering trades against the prevailing trend.
---
### **Why ELC is Unique**
The ELC Indicator stands out by combining multiple powerful trading concepts—liquidity, Fibonacci ratios, and EMA filtering—into a single tool that provides actionable and visually intuitive information. Unlike traditional trend-following indicators that lag behind price action, ELC proactively identifies key market turning points based on liquidity events. Its customizable features, real-time alerts, and comprehensive plotting of Fibonacci levels make it a versatile tool for traders across various styles and timeframes.
Whether you're a scalper looking for intraday opportunities or a swing trader aiming to capture larger moves, the ELC Indicator offers a robust framework for identifying and executing high-probability trades.
---
### **How to Get Started**
1. Add the ELC Indicator to your chart.
2. Customize the EMA length, line colors, and style based on your preference.
3. Enable alerts to receive real-time notifications of buy and sell signals.
4. Use the plotted Fibonacci levels to plan your trade entries, profit targets, and stop-loss levels.
5. Combine the signals from ELC with your existing market analysis for optimal results.
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This unique approach makes the ELC Indicator a valuable tool for traders seeking precision, clarity, and consistency in their trading decisions.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Zigzag3 -Invincible3Description:
Zigzag3 - Invincible3 is a powerful and flexible support and resistance indicator for TradingView. Utilizing an enhanced ZigZag algorithm and Dow Theory principles, it detects price pivots, higher highs (HH), lower highs (LH), higher lows (HL), and lower lows (LL). The indicator draws lines and labels to visualize these pivots, making it easier to identify market structure, trends, and potential reversal points.
The Length input allows traders to control the sensitivity of pivot detection.
Support and Resistance Lines:
Displays dotted and solid SR lines based on significant pivots to highlight key market zones.
Option to extend support/resistance lines dynamically with real-time progression for the latest pivot.
Labels for Dow Theory Points:
Mark higher highs, lower highs, higher lows, and lower lows with customizable colors.
Identifies market direction and potential breakout levels with visual clarity.
ZigZag Line Visualization:
Toggle the ZigZag lines to connect pivots for a better understanding of price movement.
Dynamic Dotted Line Progression:
A dotted line extends in real-time from the most recent significant pivot point, aiding in quick analysis.
This indicator is ideal for traders looking to analyze market structure, identify trends, and spot potential reversals. It can be used as a standalone tool or in combination with other strategies for enhanced precision.
Order blocksHi all!
This indicator will show you found order blocks that can be used as supply or demand. It's my take on trying to create good order blocks and I hope it makes sense.
First off I suggest to verify the current trend before using an order block. This can be done in a variety of ways, one way could be to use my other script "Market structure" () which I use and suggest.
You can configure the indicator to behave differently depending on settings. These are the settings available:
• The order blocks created can be found in any higher timeframe defined in "Timeframe"
• The number of active order blocks are defined in "Count". If an order block is found the earliest order block will be replaced
• You can choose the type of order blocks that are found ("Bullish", "Bearish " or "Both") in "Type"
• The old order blocks can be kept if "Keep history" is checked
• Order blocks that are found are not removed when mitigated (entered) but when a new one appears. They can be removed when they are broken by price if "Remove broken zones" are checked
There is also a setting section called "Requirements" that defines what is required for an order block to be created. These are the settings:
• "Take out"
Check this if you want the base of the order block (the candle where the zone is drawn from (high and low)) to have to take out the previous candle (be higher or lower depending if the order block is bullish or bearish).
• "Consecutive rising/falling"
Each following candle in the reaction (the 3 reaction candles) needs to reach higher or lower (depending on bullish or bearish). Check this if you want that to be true.
• "Reaction"
Some sort of reaction is needed from the 3 candles creating the order block. This reaction is based on the value of the Average True Length (ATR) of length 14. You can here define a factor of the value from the ATR that these 3 candles needs to move in price. A higher need for a reaction (higher factor of the ATR) will create lesser zones. You can also choose to show this limit with the checkbox.
• "Fair Value Gap"
The reaction needs to create a gap (imbalance) in price. This gap is known as a "Fair Value Gap" and is created when the last candle's wick does not meet with the base candle's wick. Check this if you want this to be needed.
After these settings you can also choose the colors of the created zones. The ones that are active (called "Zones"), the ones that are replaced ("Replaced zones") and the ones that are broken ("Broken zones") (if this is enabled in "Remove broken zones").
I'm using my library "Touched" to be able to show you labels when the order blocks have a retest, false breakout and breakout. These labels can be hidden if you disable the labels under the style tab in the indicator settings.
The concept of order blocks is widely used among traders and can provide you with good supply or demand zones. I hope that this indicator makes sense.
My todo-list has a few things, but top of that list is adding alerts for zone interactions or creations. Please feel free to say what you want to be coded!
The order blocks in the publication chart are found in weekly timeframe but are shown on the daily timeframe. Other than that the image shows you zones from the default settings (which are based on the daily timeframe).
Best of luck trading!
Fibonacci Levels Strategy with High/Low Criteria-AYNETThis code represents a TradingView strategy that uses Fibonacci levels in conjunction with high/low price criteria over specified lookback periods to determine buy (long) and sell (short) conditions. Below is an explanation of each main part of the code:
Explanation of Key Sections
User Inputs for Higher Time Frame and Candle Settings
Users can select a higher time frame (timeframe) for analysis and specify whether to use the "Current" or "Last" higher time frame (HTF) candle for calculating Fibonacci levels.
The currentlast setting allows flexibility between using real-time or the most recent closed higher time frame candle.
Lookback Periods for High/Low Criteria
Two lookback periods, lowestLookback and highestLookback, allow users to set the number of bars to consider when finding the lowest and highest prices, respectively.
This determines the criteria for entering trades based on how recent highs or lows compare to current prices.
Fibonacci Levels Configuration
Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, and 100%) are configurable. These are used to calculate price levels between the high and low of the higher time frame candle.
Each level represents a retracement or extension relative to the high/low range of the HTF candle, providing important price levels for decision-making.
HTF Candle Calculation
HTF candle data is calculated based on the higher time frame selected by the user, using the newbar check to reset htfhigh, htflow, and htfopen values.
The values are updated with each new HTF bar or as prices move within the same HTF bar to track the highest high and lowest low accurately.
Set Fibonacci Levels Array
Using the calculated HTF candle's high, low, and open, the Fibonacci levels are computed by interpolating these values according to the user-defined Fibonacci levels.
A fibLevels array stores these computed values.
Plotting Fibonacci Levels
Each Fibonacci level is plotted on the chart with a different color, providing visual indicators for potential support/resistance levels.
High/Low Price Criteria Calculation
The lowest and highest prices over the specified lookback periods (lowestLookback and highestLookback) are calculated and plotted on the chart. These serve as dynamic levels to trigger long or short entries.
Trade Signal Conditions
longCondition: A long (buy) signal is generated when the price crosses above both the lowest price criteria and the 50% Fibonacci level.
shortCondition: A short (sell) signal is generated when the price crosses below both the highest price criteria and the 50% Fibonacci level.
Executing Trades
Based on the longCondition and shortCondition, trades are entered with the strategy.entry() function, using the labels "Long" and "Short" for tracking on the chart.
Strategy Use
This strategy allows traders to utilize Fibonacci retracement levels and recent highs/lows to identify trend continuation or reversal points, potentially providing entry points aligned with larger market structure. Adjusting the lowestLookback and highestLookback along with Fibonacci levels enables a customizable approach to suit different trading styles and market conditions.
ICT Setup 03 [TradingFinder] Judas Swing NY 9:30am + CHoCH/FVG🔵 Introduction
Judas Swing is an advanced trading setup designed to identify false price movements early in the trading day. This advanced trading strategy operates on the principle that major market players, or "smart money," drive price in a certain direction during the early hours to mislead smaller traders.
This deceptive movement attracts liquidity at specific levels, allowing larger players to execute primary trades in the opposite direction, ultimately causing the price to return to its true path.
The Judas Swing setup functions within two primary time frames, tailored separately for Forex and Stock markets. In the Forex market, the setup uses the 8:15 to 8:30 AM window to identify the high and low points, followed by the 8:30 to 8:45 AM frame to execute the Judas move and identify the CISD Level break, where Order Block and Fair Value Gap (FVG) zones are subsequently detected.
In the Stock market, these time frames shift to 9:15 to 9:30 AM for identifying highs and lows and 9:30 to 9:45 AM for executing the Judas move and CISD Level break.
Concepts such as Order Block and Fair Value Gap (FVG) are crucial in this setup. An Order Block represents a chart region with a high volume of buy or sell orders placed by major financial institutions, marking significant levels where price reacts.
Fair Value Gap (FVG) refers to areas where price has moved rapidly without balance between supply and demand, highlighting zones of potential price action and future liquidity.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The Judas Swing setup enables traders to pinpoint entry and exit points by utilizing Order Block and FVG concepts, helping them align with liquidity-driven moves orchestrated by smart money. This setup applies two distinct time frames for Forex and Stocks to capture early deceptive movements, offering traders optimized entry or exit moments.
🟣 Bullish Setup
In the Bullish Judas Swing setup, the first step is to identify High and Low points within the initial time frame. These levels serve as key points where price may react, forming the basis for analyzing the setup and assisting traders in anticipating future market shifts.
In the second time frame, a critical stage of the bullish setup begins. During this phase, the price may create a false break or Fake Break below the low level, a deceptive move by major players to absorb liquidity. This false move often causes smaller traders to enter positions incorrectly. After this fake-out, the price reverses upward, breaking the CISD Level, a critical point in the market structure, signaling a potential bullish trend.
Upon breaking the CISD Level and reversing upward, the indicator identifies both the Order Block and Fair Value Gap (FVG). The Order Block is an area where major players typically place large buy orders, signaling potential price support. Meanwhile, the FVG marks a region of supply-demand imbalance, signaling areas where price might react.
Ultimately, after these key zones are identified, a trader may open a buy position if the price reaches one of these critical areas—Order Block or FVG—and reacts positively. Trading at these levels enhances the chance of success due to liquidity absorption and support from smart money, marking an opportune time for entering a long position.
🟣 Bearish Setup
In the Bearish Judas Swing setup, analysis begins with marking the High and Low levels in the initial time frame. These levels serve as key zones where price could react, helping to signal possible trend reversals. Identifying these levels is essential for locating significant bearish zones and positioning traders to capitalize on downward movements.
In the second time frame, the primary bearish setup unfolds. During this stage, price may exhibit a Fake Break above the high, causing a brief move upward and misleading smaller traders into incorrect positions. After this false move, the price typically returns downward, breaking the CISD Level—a crucial bearish trend indicator.
With the CISD Level broken and a bearish trend confirmed, the indicator identifies the Order Block and Fair Value Gap (FVG). The Bearish Order Block is a region where smart money places significant sell orders, prompting a negative price reaction. The FVG denotes an area of supply-demand imbalance, signifying potential selling pressure.
When the price reaches one of these critical areas—the Bearish Order Block or FVG—and reacts downward, a trader may initiate a sell position. Entering trades at these levels, due to increased selling pressure and liquidity absorption, offers traders an advantage in profiting from price declines.
🔵 Settings
Market : The indicator allows users to choose between Forex and Stocks, automatically adjusting the time frames for the "Opening Range" and "Trading Permit" accordingly: Forex: 8:15–8:30 AM for identifying High and Low points, and 8:30–8:45 AM for capturing the Judas move and CISD Level break. Stocks: 9:15–9:30 AM for identifying High and Low points, and 9:30–9:45 AM for executing the Judas move and CISD Level break.
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The Judas Swing indicator helps traders spot reliable trading opportunities by detecting false price movements and key levels such as Order Block and FVG. With a focus on early market movements, this tool allows traders to align with major market participants, selecting entry and exit points with greater precision, thereby reducing trading risks.
Its extensive customization options enable adjustments for various market types and trading conditions, giving traders the flexibility to optimize their strategies. Based on ICT techniques and liquidity analysis, this indicator can be highly effective for those seeking precision in their entry points.
Overall, Judas Swing empowers traders to capitalize on significant market movements by leveraging price volatility. Offering precise and dependable signals, this tool presents an excellent opportunity for enhancing trading accuracy and improving performance
Multi Deviation VWAP [OmegaTools]The Multi Deviation VWAP is an original variation of the traditional VWAP indicator, designed to enhance your trading experience by providing more precise market insights. While the conventional VWAP calculates a single price level based on volume and price over a given period, the Multi Deviation VWAP goes a step further by introducing dynamic upper and lower bands that adapt to market conditions. These bands give traders a more comprehensive understanding of volatility and price action, making it an ideal tool for various trading strategies, especially for identifying potential price reversals or trend continuations.
Key Features:
Separate Calculation of Deviation Bands:
Unlike traditional VWAP bands, where both the upper and lower bands are symmetrically calculated using a single deviation value, the Multi Deviation VWAP calculates the deviations independently for the upper and lower bands. This allows for a more accurate reflection of market dynamics.
The upper deviation band is based on the average distance of closing prices above the VWAP, while the lower deviation band considers the average distance of closing prices below the VWAP.
This separation provides a more tailored approach, adapting to whether the market is showing bullish or bearish momentum, as opposed to a fixed, equal deviation in both directions.
Internal and External Bands:
Two sets of deviation bands are plotted: Internal Bands and External Bands, controlled by user inputs (factorone for internal and factortwo for external). These bands offer multiple levels of support and resistance based on market volatility.
The Internal Bands are closer to the VWAP and act as the first level of support/resistance, suitable for short-term or tighter trading ranges.
The External Bands are further from the VWAP and capture more significant market swings, useful for identifying larger trends or setting wider stop-losses.
Timeframe Flexibility:
The indicator allows traders to select the desired timeframe (1D by default) over which the VWAP and its deviation bands are calculated. This flexibility enables users to adapt the indicator to different trading styles, from intraday scalping to longer-term trend analysis.
Visual Enhancements:
Bullish and Bearish Colors: The bands are color-coded for quick visual interpretation. Bullish bands (lower deviations) are colored blue, while bearish bands (upper deviations) are colored red, making it easy to differentiate between market conditions at a glance.
Plot Fill: The area between the internal and external bands is shaded, providing clear visual zones of potential price containment, aiding in understanding the market structure and anticipating price movements.
How It Differs from a Standard VWAP:
Traditional VWAP provides a single price line that represents the volume-weighted average price over a given period, often used to identify general price trends.
In contrast, the Multi Deviation VWAP introduces upper and lower bands calculated separately based on price deviations above and below the VWAP, giving a more nuanced view of market volatility.
Symmetrical bands in traditional VWAP may not always accurately reflect the market's true behavior, especially in trending markets, where upward and downward price movements aren't always equal. By splitting the deviation calculations, this tool provides a more dynamic and realistic view of price action, adapting to whether the market is showing stronger upward or downward pressure.
Use Cases:
Trend Identification: The VWAP line acts as a central trend line, while the deviation bands offer levels of potential support and resistance. When price moves beyond the external bands, it may indicate overextension and potential reversal.
Volatility Trading: Traders can use the internal and external bands to set dynamic take-profit or stop-loss levels, allowing for flexible risk management depending on market conditions.
Range Trading: In consolidating markets, the Multi Deviation VWAP can help traders identify optimal buy and sell zones as the price oscillates between the upper and lower bands.
By incorporating independent deviation bands, this indicator provides traders with a more responsive tool that reflects market behavior more accurately, helping them make informed trading decisions with enhanced precision.
Wyckoff Method IndicatorThe Wyckoff Method Market Cycle Indicator is a powerful tool designed to help traders identify the current market phase based on the principles of the Wyckoff Method. This indicator analyzes price action and volume patterns to determine whether the market is in an accumulation, markup, distribution, or markdown phase.
The Wyckoff Method, developed by Richard D. Wyckoff, is a time-tested approach to understanding market dynamics and identifying potential trading opportunities. By studying the interaction between price and volume, the Wyckoff Method aims to provide insight into the actions of market participants and the potential direction of the market.
This indicator automatically detects the key market phases as defined by the Wyckoff Method:
Accumulation: This phase occurs when large institutional investors are quietly accumulating positions, often leading to a period of consolidation with low volatility and decreasing volume.
Markup: Following the accumulation phase, the markup phase is characterized by a breakout above the accumulation range, accompanied by increasing volume. This indicates a potential bullish trend.
Distribution: After a significant price advance, the distribution phase emerges. It is marked by high volatility and increasing volume as large investors begin to distribute their holdings to the public.
Markdown: The markdown phase follows the distribution phase and is characterized by a breakdown below the distribution range, accompanied by increasing volume. This suggests a potential bearish trend.
The indicator plots the detected market phases on the chart using the following signals:
Green triangle pointing upwards: Accumulation phase
Blue triangle pointing downwards: Markup phase
Red triangle pointing downwards: Distribution phase
Orange triangle pointing upwards: Markdown phase
By utilizing this indicator, traders can gain valuable insights into the underlying market structure and make more informed trading decisions. However, it is important to note that the Wyckoff Method Market Cycle Indicator should be used in conjunction with other technical analysis tools and risk management strategies.
The indicator provides two input parameters:
Lookback Period: The number of bars used to calculate the volatility and determine the market phases. The default value is 50.
Volume Condition Multiple: The multiple used to compare the current volume with the volume of the lookback period. The default value is 2.
Traders can adjust these parameters to suit their specific trading style and the characteristics of the asset being analyzed.
Please note that this indicator is intended for educational and informational purposes only. It does not constitute financial advice. Always conduct your own analysis and exercise proper risk management when trading.
Happy trading!
ATR Bands (Keltner Channel), Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of ATR Bands, candle wicks crossing the ATR upper and lower bands, and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from the lower band when using phi * multiplier
B2 Signal - Potential pivot up from the lower band when using 1/2 * multiplier
B3 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the upper band when using
S2 Signal - Potential pivot down from the upper band when using 1/2 * multiplier
S3 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional B1, B2, and S1, and S2 signals can be displayed that use the bands based on a multiplier that is half that of the primary one, and phi (0.618) times the primary multiplier as a way to quickly check for signals occurring along different, but related, bands.
Calculations
ATR Bands, or Keltner Channels, are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. ATR Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of ATRs to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of ATRs from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Settings
CHANNEL SETTINGS
Baseline EMA Period (Default: 21): Period length of the moving average basis line.
ATR Period (Default: 21): The number of periods over which the Average True Range (ATR) is calculated.
Basis MA Type (Default: SMA): The moving average type for the basis line.
Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
ADDITIONAL CHANNELS
Half of Multiplier Offset (Default: True): Toggles the display of the ATR bands that are set a distance of half of the ATR multiplier.
Quarter of Multiplier Offset (Default: false): Toggles the display of the ATR bands that are set a distance of one quarter of the ATR multiplier.
Phi (Φ) Offset (Default: false): Toggles the display of the ATR bands that are set a distance of phi (Φ) times the ATR multiplier.
WICK SETTINGS FOR CANDLE FILTERS
Wick Ratio for Bands (Default: 0.4): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.4): The ratio of wick size to total candle size for use at baseline.
Use Candle Body (rather than full candle size) (Default: false): Determines whether wick calculations use the candle body or the entire candle size.
VISUAL PREFERENCES - SIGNALS
Show Signals (Default: true): Allows signal labels to be shown.
Show Signals from 1/2 Band Offset (Default: false): Toggle signals originating from 1/2 offset upper and lower bands.
Show Signals from Phi (Φ) Band Offset (Default: false): Toggle signals originating from phi (Φ) offset upper and lower bands.
Show Baseline Signals (Default: false): Toggle Baseline signals.
VISUAL PREFERENCES - BANDS
Show ATR (Keltner) Bands (Default: true): Use a background color inside the Bollinger Bands.
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
Bollinger Band Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of Bollinger Bands, candle wicks crossing the upper and lower Bollinger Bands and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional, B1 and S1 signals can be displayed that use the baseline as the pivot level.
Settings
SIGNALS
Show Bollinger Band Signals (Default: True): Allows signal labels to be shown.
Hide Baseline Signals (Default: False): Baseline signals are on by default. This will turn them off.
Show Wick Signals (Defau
lt: True): Displays signals when wicking occurs.
BOLLINGER BAND SETTINGS
Period length for Bollinger Band Basis (Default: 21): Length of the Bollinger Band (BB) moving average basis line.
Basis MA Type (Default: SMA): The moving average type for the BB Basis line.
Source (Default: “close”): The source of time series data.
Standard Deviation Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
WICK SETTINGS FOR BOLLINGER BANDS
Wick Ratio for Bands (Default: 0.3): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.3): The ratio of wick size to total candle size for use at baseline.
WICK SETTINGS FOR CANDLE SIGNALS
Upper Wick Threshold (Default: 50): The percent of upper wick compared to the full candle size or candle body size.
Lower Wick Threshold (Default: 50): The percent of lower wick compared to the full candle size or candle body size.
Use Candle Body (Default: false): Toggles the use of the full candle size versus the candle body size when calculating the wick signal.
VISUAL PREFERENCES
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
Show Signals (Default: true): Toggle the Bollinger Band upper band, lower band, and baseline signals.
Show Bollinger Bands (Default: true): Show the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Calculations
Bollinger Bands are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. Bollinger Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of standard deviations to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of standard deviations from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
BAERMThe Bitcoin Auto-correlation Exchange Rate Model: A Novel Two Step Approach
THIS IS NOT FINANCIAL ADVICE. THIS ARTICLE IS FOR EDUCATIONAL AND ENTERTAINMENT PURPOSES ONLY.
If you enjoy this software and information, please consider contributing to my lightning address
Prelude
It has been previously established that the Bitcoin daily USD exchange rate series is extremely auto-correlated
In this article, we will utilise this fact to build a model for Bitcoin/USD exchange rate. But not a model for predicting the exchange rate, but rather a model to understand the fundamental reasons for the Bitcoin to have this exchange rate to begin with.
This is a model of sound money, scarcity and subjective value.
Introduction
Bitcoin, a decentralised peer to peer digital value exchange network, has experienced significant exchange rate fluctuations since its inception in 2009. In this article, we explore a two-step model that reasonably accurately captures both the fundamental drivers of Bitcoin’s value and the cyclical patterns of bull and bear markets. This model, whilst it can produce forecasts, is meant more of a way of understanding past exchange rate changes and understanding the fundamental values driving the ever increasing exchange rate. The forecasts from the model are to be considered inconclusive and speculative only.
Data preparation
To develop the BAERM, we used historical Bitcoin data from Coin Metrics, a leading provider of Bitcoin market data. The dataset includes daily USD exchange rates, block counts, and other relevant information. We pre-processed the data by performing the following steps:
Fixing date formats and setting the dataset’s time index
Generating cumulative sums for blocks and halving periods
Calculating daily rewards and total supply
Computing the log-transformed price
Step 1: Building the Base Model
To build the base model, we analysed data from the first two epochs (time periods between Bitcoin mining reward halvings) and regressed the logarithm of Bitcoin’s exchange rate on the mining reward and epoch. This base model captures the fundamental relationship between Bitcoin’s exchange rate, mining reward, and halving epoch.
where Yt represents the exchange rate at day t, Epochk is the kth epoch (for that t), and epsilont is the error term. The coefficients beta0, beta1, and beta2 are estimated using ordinary least squares regression.
Base Model Regression
We use ordinary least squares regression to estimate the coefficients for the betas in figure 2. In order to reduce the possibility of over-fitting and ensure there is sufficient out of sample for testing accuracy, the base model is only trained on the first two epochs. You will notice in the code we calculate the beta2 variable prior and call it “phaseplus”.
The code below shows the regression for the base model coefficients:
\# Run the regression
mask = df\ < 2 # we only want to use Epoch's 0 and 1 to estimate the coefficients for the base model
reg\_X = df.loc\ [mask, \ \].shift(1).iloc\
reg\_y = df.loc\ .iloc\
reg\_X = sm.add\_constant(reg\_X)
ols = sm.OLS(reg\_y, reg\_X).fit()
coefs = ols.params.values
print(coefs)
The result of this regression gives us the coefficients for the betas of the base model:
\
or in more human readable form: 0.029, 0.996869586, -0.00043. NB that for the auto-correlation/momentum beta, we did NOT round the significant figures at all. Since the momentum is so important in this model, we must use all available significant figures.
Fundamental Insights from the Base Model
Momentum effect: The term 0.997 Y suggests that the exchange rate of Bitcoin on a given day (Yi) is heavily influenced by the exchange rate on the previous day. This indicates a momentum effect, where the price of Bitcoin tends to follow its recent trend.
Momentum effect is a phenomenon observed in various financial markets, including stocks and other commodities. It implies that an asset’s price is more likely to continue moving in its current direction, either upwards or downwards, over the short term.
The momentum effect can be driven by several factors:
Behavioural biases: Investors may exhibit herding behaviour or be subject to cognitive biases such as confirmation bias, which could lead them to buy or sell assets based on recent trends, reinforcing the momentum.
Positive feedback loops: As more investors notice a trend and act on it, the trend may gain even more traction, leading to a self-reinforcing positive feedback loop. This can cause prices to continue moving in the same direction, further amplifying the momentum effect.
Technical analysis: Many traders use technical analysis to make investment decisions, which often involves studying historical exchange rate trends and chart patterns to predict future exchange rate movements. When a large number of traders follow similar strategies, their collective actions can create and reinforce exchange rate momentum.
Impact of halving events: In the Bitcoin network, new bitcoins are created as a reward to miners for validating transactions and adding new blocks to the blockchain. This reward is called the block reward, and it is halved approximately every four years, or every 210,000 blocks. This event is known as a halving.
The primary purpose of halving events is to control the supply of new bitcoins entering the market, ultimately leading to a capped supply of 21 million bitcoins. As the block reward decreases, the rate at which new bitcoins are created slows down, and this can have significant implications for the price of Bitcoin.
The term -0.0004*(50/(2^epochk) — (epochk+1)²) accounts for the impact of the halving events on the Bitcoin exchange rate. The model seems to suggest that the exchange rate of Bitcoin is influenced by a function of the number of halving events that have occurred.
Exponential decay and the decreasing impact of the halvings: The first part of this term, 50/(2^epochk), indicates that the impact of each subsequent halving event decays exponentially, implying that the influence of halving events on the Bitcoin exchange rate diminishes over time. This might be due to the decreasing marginal effect of each halving event on the overall Bitcoin supply as the block reward gets smaller and smaller.
This is antithetical to the wrong and popular stock to flow model, which suggests the opposite. Given the accuracy of the BAERM, this is yet another reason to question the S2F model, from a fundamental perspective.
The second part of the term, (epochk+1)², introduces a non-linear relationship between the halving events and the exchange rate. This non-linear aspect could reflect that the impact of halving events is not constant over time and may be influenced by various factors such as market dynamics, speculation, and changing market conditions.
The combination of these two terms is expressed by the graph of the model line (see figure 3), where it can be seen the step from each halving is decaying, and the step up from each halving event is given by a parabolic curve.
NB - The base model has been trained on the first two halving epochs and then seeded (i.e. the first lag point) with the oldest data available.
Constant term: The constant term 0.03 in the equation represents an inherent baseline level of growth in the Bitcoin exchange rate.
In any linear or linear-like model, the constant term, also known as the intercept or bias, represents the value of the dependent variable (in this case, the log-scaled Bitcoin USD exchange rate) when all the independent variables are set to zero.
The constant term indicates that even without considering the effects of the previous day’s exchange rate or halving events, there is a baseline growth in the exchange rate of Bitcoin. This baseline growth could be due to factors such as the network’s overall growth or increasing adoption, or changes in the market structure (more exchanges, changes to the regulatory environment, improved liquidity, more fiat on-ramps etc).
Base Model Regression Diagnostics
Below is a summary of the model generated by the OLS function
OLS Regression Results
\==============================================================================
Dep. Variable: logprice R-squared: 0.999
Model: OLS Adj. R-squared: 0.999
Method: Least Squares F-statistic: 2.041e+06
Date: Fri, 28 Apr 2023 Prob (F-statistic): 0.00
Time: 11:06:58 Log-Likelihood: 3001.6
No. Observations: 2182 AIC: -5997.
Df Residuals: 2179 BIC: -5980.
Df Model: 2
Covariance Type: nonrobust
\==============================================================================
coef std err t P>|t| \
\------------------------------------------------------------------------------
const 0.0292 0.009 3.081 0.002 0.011 0.048
logprice 0.9969 0.001 1012.724 0.000 0.995 0.999
phaseplus -0.0004 0.000 -2.239 0.025 -0.001 -5.3e-05
\==============================================================================
Omnibus: 674.771 Durbin-Watson: 1.901
Prob(Omnibus): 0.000 Jarque-Bera (JB): 24937.353
Skew: -0.765 Prob(JB): 0.00
Kurtosis: 19.491 Cond. No. 255.
\==============================================================================
Below we see some regression diagnostics along with the regression itself.
Diagnostics: We can see that the residuals are looking a little skewed and there is some heteroskedasticity within the residuals. The coefficient of determination, or r2 is very high, but that is to be expected given the momentum term. A better r2 is manually calculated by the sum square of the difference of the model to the untrained data. This can be achieved by the following code:
\# Calculate the out-of-sample R-squared
oos\_mask = df\ >= 2
oos\_actual = df.loc\
oos\_predicted = df.loc\
residuals\_oos = oos\_actual - oos\_predicted
SSR = np.sum(residuals\_oos \*\* 2)
SST = np.sum((oos\_actual - oos\_actual.mean()) \*\* 2)
R2\_oos = 1 - SSR/SST
print("Out-of-sample R-squared:", R2\_oos)
The result is: 0.84, which indicates a very close fit to the out of sample data for the base model, which goes some way to proving our fundamental assumption around subjective value and sound money to be accurate.
Step 2: Adding the Damping Function
Next, we incorporated a damping function to capture the cyclical nature of bull and bear markets. The optimal parameters for the damping function were determined by regressing on the residuals from the base model. The damping function enhances the model’s ability to identify and predict bull and bear cycles in the Bitcoin market. The addition of the damping function to the base model is expressed as the full model equation.
This brings me to the question — why? Why add the damping function to the base model, which is arguably already performing extremely well out of sample and providing valuable insights into the exchange rate movements of Bitcoin.
Fundamental reasoning behind the addition of a damping function:
Subjective Theory of Value: The cyclical component of the damping function, represented by the cosine function, can be thought of as capturing the periodic fluctuations in market sentiment. These fluctuations may arise from various factors, such as changes in investor risk appetite, macroeconomic conditions, or technological advancements. Mathematically, the cyclical component represents the frequency of these fluctuations, while the phase shift (α and β) allows for adjustments in the alignment of these cycles with historical data. This flexibility enables the damping function to account for the heterogeneity in market participants’ preferences and expectations, which is a key aspect of the subjective theory of value.
Time Preference and Market Cycles: The exponential decay component of the damping function, represented by the term e^(-0.0004t), can be linked to the concept of time preference and its impact on market dynamics. In financial markets, the discounting of future cash flows is a common practice, reflecting the time value of money and the inherent uncertainty of future events. The exponential decay in the damping function serves a similar purpose, diminishing the influence of past market cycles as time progresses. This decay term introduces a time-dependent weight to the cyclical component, capturing the dynamic nature of the Bitcoin market and the changing relevance of past events.
Interactions between Cyclical and Exponential Decay Components: The interplay between the cyclical and exponential decay components in the damping function captures the complex dynamics of the Bitcoin market. The damping function effectively models the attenuation of past cycles while also accounting for their periodic nature. This allows the model to adapt to changing market conditions and to provide accurate predictions even in the face of significant volatility or structural shifts.
Now we have the fundamental reasoning for the addition of the function, we can explore the actual implementation and look to other analogies for guidance —
Financial and physical analogies to the damping function:
Mathematical Aspects: The exponential decay component, e^(-0.0004t), attenuates the amplitude of the cyclical component over time. This attenuation factor is crucial in modelling the diminishing influence of past market cycles. The cyclical component, represented by the cosine function, accounts for the periodic nature of market cycles, with α determining the frequency of these cycles and β representing the phase shift. The constant term (+3) ensures that the function remains positive, which is important for practical applications, as the damping function is added to the rest of the model to obtain the final predictions.
Analogies to Existing Damping Functions: The damping function in the BAERM is similar to damped harmonic oscillators found in physics. In a damped harmonic oscillator, an object in motion experiences a restoring force proportional to its displacement from equilibrium and a damping force proportional to its velocity. The equation of motion for a damped harmonic oscillator is:
x’’(t) + 2γx’(t) + ω₀²x(t) = 0
where x(t) is the displacement, ω₀ is the natural frequency, and γ is the damping coefficient. The damping function in the BAERM shares similarities with the solution to this equation, which is typically a product of an exponential decay term and a sinusoidal term. The exponential decay term in the BAERM captures the attenuation of past market cycles, while the cosine term represents the periodic nature of these cycles.
Comparisons with Financial Models: In finance, damped oscillatory models have been applied to model interest rates, stock prices, and exchange rates. The famous Black-Scholes option pricing model, for instance, assumes that stock prices follow a geometric Brownian motion, which can exhibit oscillatory behavior under certain conditions. In fixed income markets, the Cox-Ingersoll-Ross (CIR) model for interest rates also incorporates mean reversion and stochastic volatility, leading to damped oscillatory dynamics.
By drawing on these analogies, we can better understand the technical aspects of the damping function in the BAERM and appreciate its effectiveness in modelling the complex dynamics of the Bitcoin market. The damping function captures both the periodic nature of market cycles and the attenuation of past events’ influence.
Conclusion
In this article, we explored the Bitcoin Auto-correlation Exchange Rate Model (BAERM), a novel 2-step linear regression model for understanding the Bitcoin USD exchange rate. We discussed the model’s components, their interpretations, and the fundamental insights they provide about Bitcoin exchange rate dynamics.
The BAERM’s ability to capture the fundamental properties of Bitcoin is particularly interesting. The framework underlying the model emphasises the importance of individuals’ subjective valuations and preferences in determining prices. The momentum term, which accounts for auto-correlation, is a testament to this idea, as it shows that historical price trends influence market participants’ expectations and valuations. This observation is consistent with the notion that the price of Bitcoin is determined by individuals’ preferences based on past information.
Furthermore, the BAERM incorporates the impact of Bitcoin’s supply dynamics on its price through the halving epoch terms. By acknowledging the significance of supply-side factors, the model reflects the principles of sound money. A limited supply of money, such as that of Bitcoin, maintains its value and purchasing power over time. The halving events, which reduce the block reward, play a crucial role in making Bitcoin increasingly scarce, thus reinforcing its attractiveness as a store of value and a medium of exchange.
The constant term in the model serves as the baseline for the model’s predictions and can be interpreted as an inherent value attributed to Bitcoin. This value emphasizes the significance of the underlying technology, network effects, and Bitcoin’s role as a medium of exchange, store of value, and unit of account. These aspects are all essential for a sound form of money, and the model’s ability to account for them further showcases its strength in capturing the fundamental properties of Bitcoin.
The BAERM offers a potential robust and well-founded methodology for understanding the Bitcoin USD exchange rate, taking into account the key factors that drive it from both supply and demand perspectives.
In conclusion, the Bitcoin Auto-correlation Exchange Rate Model provides a comprehensive fundamentally grounded and hopefully useful framework for understanding the Bitcoin USD exchange rate.
Multi VWAP from Gaps [MW]Multi VWAP from Gaps
Introduction
The Multi VWAP from Gaps tool extends the concept of using the Anchored Volume Weighted Average Price, popularized by its founder, Brian Shannon, founder of AlphaTrends. It creates automatic AVWAPS for anchor points originating at the biggest gaps of the week, month, quarter and year. Currently, most standard VWAP tools allow users to place custom anchored VWAPs, but the routine of doing this for every equity being watched can become cumbersome. This tool makes that process multi-times easier. Considering that large gaps can represent a shift in market structure, this tool provides unique and immediate insight into how past daily price gaps can and have affected price action.
Settings
LABEL SETTINGS
Show Biggest Gap of Week | Month | Quarter : Toggle labels that identify the location of the biggest gaps for the selected time period.
Show Big Labels : Toggle labels from showing the date and gap size to just showing a single letter (W/M/Q/Y) designating the time period that the gap is from.
Hide All Labels : Turn labels off and on.
MAX VWAP LINES
Max Weekly | Monthly | Quarterly | Yearly Lines : How many VWAP lines, starting from today, should be shown for the specified time period. Max: 5
SHOW VWAP LINES
Show Weekly | Monthly | Quarterly | Yearly Lines : This feature allows you to remove lines for the specified time period.
Calculations
This indicator does not provide buy or sell signals. It is simply the VWAP calculated starting from an “anchor point”, or start time. It is calculated by the summation of Price x Volume / Volume for the period starting at the anchor point.
How to Interpret
According to Brian Shannon, VWAP is an objective measure of what the average trader has paid for a particular equity over a given period, and is the value that large institutional investors frequently use as a trade signal. Therefore, by definition, when the price is above an AVWAP, buyers are in control for that period of time. Likewise, if the price is below the AVWAP, sellers are in control for that period of time.
VWAPs that coincide with important events, such as FOMC meetings, CPI reports, earnings reports, have added significance. In many cases, these events can cause gaps to happen in day-to-day price movement, and can affect market structure going forward.
Practically speaking, price action can tend to change direction when a significant VWAP is hit, voiding buy and sell signals. Like moving averages, this indicator can show, in real-time, how a buy or sell signal should be interpreted. A significant AVWAP line is a point of interest, and can serve as strong support or resistance, because large institutions may be using those values for entries or exits. For a great analysis of how to use AVWAP, visit the AlphaTrends channel on Youtube here or you can buy Brian Shannon’s “Anchored VWAP” book on Amazon.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Additionally, in order to build the VWAP calculations, past data is needed that may not be available on shorter timeframes. The workaround is that for some longer-term VWAP lines on shorter timeframes, you may see less than the total of lines that you selected in settings. This is particularly the case with quarterly VWAP lines on the 5 minute timeframe for some equities.
Acknowledgements
This script uses the MarketHolidays library by @Protervus. Also, for debugging, the JavaScript-style Debug Console by @algotraderdev was invaluable. Special thanks to @antsmuzic for helping review and debug the script. And, of course, without Brian Shannon's books, videos, and interviews, this indicator would would not have happened.
Order Blocks Finder [TradingFinder] Major OB | Supply and Demand🔵 Introduction
Drawing all order blocks on the path, especially in range-bound or channeling markets, fills the chart with lines, making it confusing rather than providing the trader with the best entry and exit points.
🔵 Reason for Indicator Creation
For traders familiar with market structure and only need to know the main accumulation points (best entry or exit points), and primary order blocks that act as strong sources of power.
🟣 Important Note
All order blocks, both ascending and descending, are identified and displayed on the chart when the structure of "BOS" or "CHOCH" is broken, which can also be identified with "MSS."
🔵 How to Use
When the indicator is installed, it plots all order blocks (active order blocks) and continues until the price reaches them. This continuation happens in boxes to have a better view in the TradingView chart.
Green Range : Ascending order blocks where we expect a price increase in these areas.
Red Range : Descending order blocks where we expect a price decrease in these areas.
🔵 Settings
Order block refine setting : When Order block refine is off, the supply and demand zones are the entire length of the order block (Low to High) in their standard state and cannot be improved. If you turn on Order block refine, supply and demand zones will improve using the error correction algorithm.
Refine type setting : Improving order blocks using the error correction algorithm can be done in two ways: Defensive and Aggressive. In the Aggressive method, the largest possible range is considered for order blocks.
🟣 Important
The main advantage of the Aggressive method is minimizing the loss of stops, but due to the widening of the supply or demand zone, the reward-to-risk ratio decreases significantly. The Aggressive method is suitable for individuals who take high-risk trades.
In the Defensive method, the range of order blocks is minimized to their standard state. In this case, fewer stops are triggered, and the reward-to-risk ratio is maximized in its optimal state. It is recommended for individuals who trade with low risk.
Show high level setting : If you want to display major high levels, set show high level to Yes.
Show low level setting : If you want to display major low levels, set show low level to Yes.
🔵 How to Use
The general view of this indicator is as follows.
When the price approaches the range, wait for the price reaction to confirm it, such as a pin bar or divergence.
If the price passes with a strong candle (spike), especially after a long-range or at the beginning of sessions, a powerful event is happening, and it is outside the credibility level.
An Example of a Valid Zone
An Example of Breakout and Invalid Zone. (My suggestion is not to use pending orders, especially when the market is highly volatile or before and after news.)
After reaching this zone, expect the price to move by at least the minimum candle that confirmed it or a price ceiling or floor.
🟣 Important : These factors can be more accurately measured with other trend finder indicators provided.
🔵 Auxiliary Tools
There is much talk about not using trend lines, candlesticks, Fibonacci, etc., in the web space. However, our suggestion is to create and use tools that can help you profit from this market.
• Fibonacci Retracement
• Trading Sessions
• Candlesticks
🔵 Advantages
• Plotting main OBs without additional lines;
• Suitable for timeframes M1, M5, M15, H1, and H4;
• Effective in Tokyo, Sydney, and London sessions;
• Plotting the main ceiling and floor to help identify the trend.
Implied Orderblock Breaker (Zeiierman)█ Overview
The Implied Order Block Breaker (Zeiierman) is a tool designed to identify enhanced order blocks with imbalances. These enhanced order blocks represent areas where there is a rapid price movement. Essentially, this indicator uses order blocks and suggests that a swift price movement away from these levels, breaking the current market structure, could indicate an area that the market has not correctly valued. This technique offers traders a unique method to identify potential market inefficiencies and imbalances, serving as a guide for potential price revisits.
The indicator doesn't scan for imbalances in the traditional sense — where there's an absence of trades between two price levels — but instead, it identifies quick movements away from key levels that suggest where an imbalance might exist. Relying on crossovers and cross-unders in conjunction with pivot points and examining the high/low within the same period provides an innovative method for traders to spot these potentially undervalued or overvalued areas in the market. These inferred imbalances can be crucial for traders looking for price levels where the market might make significant moves.
█ How It Works
Bullish
Crossover: The closing price of a bar crosses above a pivot high, which is an indication that buyers are in control and pushing the price upwards.
New Low Within Period: There is a lower low within the same period as the pivot high. This suggests that after setting a high, the market pulled back to set a new low, potentially leaving a price gap on the way up as the price quickly recovers.
Bearish
Crossunder: The closing price of a bar crosses under a pivot low, indicating that sellers are taking control and driving the price down.
New High Within Period: There is a higher high within the same period as the pivot low. This condition suggests that the market rallied to a new high before falling back below the pivot low, potentially leaving a gap on the way down.
█ How to Use
The enhanced order blocks are often revisited, and the price may aim to 'fill' the potential imbalance created by the rapid price movement, thereby presenting traders with potential entry or exit points. This approach aligns with the idea that imbalances are frequently revisited by the market, and when combined with the context of Order Blocks, it provides even more confluence.
Example
Here, if the price drops rapidly after setting a new high—crossing under the pivot low—it may skip over certain price levels, creating a 'gap' that signifies an area where the price might have been overvalued (imbalance), which the market may revisit for a potential price correction or revaluation.
█ Settings
Period: Determines the number of bars used for identifying pivot highs and lows. A higher value gives more significant but less frequent signals, while a lower value increases sensitivity but might give more false positives.
Pivot Surrounding: Specifies the number of candles to analyze around a pivot point. Increasing this value broadens the analysis range, potentially capturing more setups but possibly including less significant ones.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
