[TehThomas] - ICT Volume ImbalanceThis script is a Volume Imbalance (VI) detector and visualizer for use on the TradingView platform. The goal of the script is to automatically identify areas where there are significant imbalances in the volume of trades between consecutive candlesticks and visually highlight these areas. These imbalances can provide traders with valuable insights about the market’s current condition, often signaling potential reversal or continuation points based on price and volume action.
ICT (Inner Circle Trader) Concept of Volume Imbalances
Volume imbalances are a critical concept in the ICT trading methodology. They refer to situations where there is an unusual or significant difference in volume between two consecutive candlesticks, which might indicate institutional or large player activity. According to ICT principles, these imbalances can show us areas of market inefficiency or potential price manipulation. By identifying these imbalances, traders can gain an edge in understanding where the market is likely to move next.
Bullish and Bearish Volume Imbalances:
Bullish Volume Imbalance: This occurs when there is a strong increase in buying pressure, typically indicated by a higher volume on a candle that closes significantly above the previous one, often leaving a gap or larger price movement. The market could be preparing to push higher, and the volume shows a clear shift in buying demand.
Bearish Volume Imbalance:
Conversely, a bearish imbalance occurs when there is a strong increase in selling pressure, typically signaled by a candle that closes significantly lower than the previous one, again with higher volume. This could indicate that large players are offloading positions, and the price is likely to drop further.
Key Features and Functions of the Script
The script automates the process of detecting these volume imbalances and visually marking them on a price chart. Let’s explore its functionality in detail.
1. Inputs Section
The script allows for significant customization through its input options, which help traders adjust the detection and visualization of volume imbalances based on their individual preferences and trading style. Below are the details:
lookback (250 bars): This input specifies the number of bars (or candles) the script should look back when analyzing the volume imbalance. By setting this to 250, the user is looking at the last 250 bars on the chart to detect any significant volume imbalances. This period is adjustable between 50 to 500 bars.
volumeThreshold (1.0 multiplier): This input helps set the sensitivity for identifying volume imbalances. The script compares the volume of the current candle with the previous one, and if the current volume exceeds the previous volume by this threshold multiplier (in this case, 1.0 means at least equal to the previous volume), then it triggers an imbalance. Users can adjust the multiplier to suit different market conditions.
showBoxes (true/false): This toggle determines whether the boxes representing volume imbalances are drawn on the chart. When enabled, the script visually highlights the imbalances with colored boxes.
fillBaseColor (orange with 80% opacity): This is the color setting for the background of the imbalance boxes. A softer color (like orange with opacity) ensures the imbalance is highlighted without obscuring the price action.
borderColor (gray): The color of the border around the imbalance boxes. This adds a visual distinction to make the imbalance areas more visible.
borderWidth (1 pixel): This controls the width of the box's border to adjust how prominent it appears.
rightOffset (30 bars): This input controls how far the imbalance box extends to the right on the chart. It helps users anticipate the potential continuation of the imbalance beyond the current candle.
allowWickOverlap (true/false): This setting allows imbalances to be identified even if the wicks of the two consecutive candlesticks overlap. If set to false, only imbalances where the bodies of the candlesticks don’t overlap are considered.
showBrokenBoxes (true/false): If enabled, once a volume imbalance no longer holds true (i.e., the price breaks through the box), the box is marked as "broken." If disabled, the box is deleted when the imbalance condition no longer applies.
brokenBoxColor (red): This controls the color of the box when it is broken, which can be used as a visual cue that the imbalance was invalidated or no longer valid for analysis.
2. Volume Imbalance Function
This is the core function of the script, where the logic to detect bullish and bearish volume imbalances is implemented.
Bullish Imbalance Condition:
The first condition checks if the low of the current candle is greater than the high of the previous candle. This suggests that the market is moving upward with buying pressure.
The second condition checks whether the volume of the current candle is higher than the previous candle by the volumeThreshold multiplier. If both conditions are satisfied, a bullish imbalance is detected.
Bearish Imbalance Condition:
The first condition checks if the high of the current candle is lower than the low of the previous candle. This suggests downward price action with selling pressure.
The second condition checks whether the current volume exceeds the previous volume by the threshold
Allow Wick Overlap: If allowWickOverlap is set to true, the script will still detect imbalances if the wicks of the two candles overlap (common in volatile markets). If false, imbalances are only considered if the wicks do not overlap.
3. Box Creation and Management
When a volume imbalance is detected, the script creates a box on the chart:
The bullish imbalance box is drawn using the minimum of the open and close of the current bar as the top boundary and the maximum of the open and close of the previous bar as the bottom boundary.
Conversely, the bearish imbalance box is drawn in reverse, using the maximum of the current bar’s open and close as the top boundary and the minimum of the previous bar’s open and close as the bottom boundary.
Once the box is created, it is displayed on the chart with the specified background color, border color, and width.
4. Processing Existing Boxes
After detecting a new imbalance and drawing a box, the script checks whether the box should still remain on the chart:
If the price moves beyond the boundaries of the imbalance box, the box is marked as broken (if showBrokenBoxes is enabled), and its color is changed to red, signifying that the imbalance is no longer valid.
If the box remains intact (i.e., the price has not broken the defined boundaries), the script keeps the box extended to the right as the market continues to evolve.
5. Removing Outdated Boxes
Lastly, the script removes boxes that are older than the specified lookback period. For example, if a box was created 250 bars ago, it will be deleted after that period. This ensures the chart stays clean and only focuses on relevant imbalances.
Why This Script is Useful for Traders
This script is extremely valuable for traders, especially those following the ICT methodology, because it automates the process of detecting market inefficiencies or imbalances that might signal future price action. Here’s why it’s particularly useful:
Identifying Key Areas of Interest: Volume imbalances often point to areas where institutional or large-scale traders have entered the market. These areas could provide clues about the next significant move in the market.
Visualizing Market Structure: By automatically drawing boxes around volume imbalances, the script helps traders visually identify potential areas of support, resistance, or turning points, enabling them to make informed trading decisions.
Time Efficiency: Instead of manually analyzing each candlestick and volume spike, this script does the heavy lifting, saving traders valuable time and allowing them to focus on other aspects of their strategy.
Enhanced Trade Entries and Exits: By understanding where volume imbalances are occurring, traders can time their entries (buying during bullish imbalances and selling during bearish ones) and exits (as imbalances break) more effectively, thus improving their chances of success.
Conclusion
In summary, this script is a powerful tool for traders looking to implement volume imbalance strategies based on the ICT methodology. It automates the identification and visualization of significant imbalances in price and volume, offering traders a clear visual representation of potential market turning points. By customizing the settings, traders can tailor the script to their preferred timeframes and sensitivity, making it a flexible and effective tool for any trading strategy.
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Opening Range BoxIndicator Name: Opening Range Box with Extensions
Author: YanivBull
Description:
The Opening Range Box with Extensions is a powerful tool designed to visualize the trading range established during the first 30 minutes of a market session, a critical period for setting the day's trend. This indicator plots a box representing the high and low prices formed within this opening range, with dashed extension lines projecting these levels forward throughout the session.
Its primary purpose is to identify the boundaries of the initial trend at the start of trading. When these boundaries are breached, it serves as a trigger for potential trading opportunities: a breakout above the box high signals a possible long entry, while a breakdown below the box low indicates a potential short entry. The indicator also includes historical boxes for up to 5 previous days (configurable), allowing traders to analyze past opening ranges and their extensions for context and pattern recognition.
Key Features:
Customizable session start time (hour and minute) to adapt to various markets (e.g., NYSE, DAX, etc.).
Displays the current session's opening range box in blue and historical boxes in gray.
Plots dashed extension lines from the high and low of each box, limited to 500 bars or the end of the trading day.
Adjustable number of historical days (1-20, default 5).
Usage:
Set the Session Start Hour and Session Start Minute according to your market's opening time (relative to your chart's timezone, e.g., UTC+2). Watch for price action around the box boundaries—breakouts above the high or below the low can be used as signals for initiating long or short trades, respectively. Combine with other technical analysis tools for confirmation.
This indicator is ideal for day traders looking to capitalize on early session momentum and breakout strategies.
Astro: Moon SizeThe Astro: Moon Size indicator, built using AstroLib , calculates the distance and visualizes the apparent size of the Moon based on astronomical positioning. This script is tailored for the 1D timeframe and provides insights into lunar perigees (closest approach) and apogees (farthest distance), making it useful for astrologically-informed trading strategies.
New Astro Indicators Feature:
By setting the Julian Date to X number of days in the future, and offsetting the plot by X number of bars accordingly, it is now possible to visualize future projections of TradingView indicators that reference the AstroLib . This feature has been long requested and is far overdue, so thank you to everyone who pushed for this feature release. Enjoy, time travelers from the future!!
Key Features:
Moon Size Calculation: Uses Julian Date (J2000) conversion and AstroLib functions to determine the Moon's apparent distance.
Future Projection: Displays the Moon's distance from 28 up to 500 days ahead, with color gradients indicating proximity/size.
Pivot Identification: Marks local maxima (apogees) and minima (perigees) with labeled date stamps for easy reference.
Dynamic Labeling: Adapts label positioning and size based on the Moon's current trend and relative size.
Usage Notes:
⚠️ Timeframe Restriction: For now, the script only functions on the 1D timeframe and will prompt an error otherwise.
⚠️ Asset Restriction: This script is meant to be loaded on charts for assets that trade 24/7, like BTCUSD historical index.
Multi-Ticker RS vs SPYThis Pine Script, titled "Multi-Ticker RS vs SPY," is a clean and efficient indicator designed for TradingView, enabling traders to monitor the relative strength (RS) of up to 10 ticker symbols compared to the S&P 500 ETF (SPY) on a single chart. Ideal for options traders, such as those managing a $1,400 account, it provides a simple way to assess which stocks are outperforming or underperforming the broader market. As of February 26, 2025, the script supports any chart timeframe, such as 5-minute or daily intervals, and calculates RS based on a user-defined lookback period, defaulting to 1 bar for real-time insights.
Users can input ticker symbols via customizable settings, with defaults set to popular stocks like AAPL, TSLA, NVDA, GOOGL, AMZN, MSFT, FB, NFLX, INTC, and PYPL. The script fetches closing prices for each ticker and SPY, computes their percentage changes over the lookback period, and determines RS as the ratio of each ticker’s change to SPY’s change, handling division by zero gracefully. It displays each ticker’s current RS score in a vertical column of labels on the chart’s top-left corner, updated on the last bar to avoid clutter. Users can adjust label size (tiny, small, normal, large) and text color for visibility, ensuring a tailored, error-free experience for quick market analysis.
Gann & Fibonacci Analysis for MSTRYes! Below is a step-by-step guide to performing Gann Analysis on MSTR in TradingView for the last year.
Step 1: Set Up the Chart
Open TradingView and search for MSTR (MicroStrategy).
Select the 1-day (D) timeframe to analyze the past year.
Set your chart to logarithmic scale (⚙ Settings → Scale → Log).
Enable grid lines for alignment (⚙ Settings → Appearance → Grid Lines).
Step 2: Identify Key Highs and Lows (Last Year)
Find the 52-week high and 52-week low for MSTR.
As of now:
52-Week High: ~$999 (March 2024).
52-Week Low: ~$280 (October 2023).
Step 3: Plot Gann Angles
Using TradingView's Gann Fan Tool:
Select "Gann Fan" (Press / and type “Gann Fan” to find it).
Start at the 52-week low (~$280, October 2023) and drag upwards.
Adjust the angles to match key levels:
1x1 (45°) → Main trendline
2x1 (26.5°) → Strong uptrend
4x1 (15°) → Weak trendline
1x2 (63.75°) → Strong resistance
Repeat the process from the 52-week high (~$999, March 2024) downward to see bearish angles.
Step 4: Apply Fibonacci & Gann Retracement Levels
Using Fibonacci Retracement:
Select "Fibonacci Retracement" tool.
Draw from 52-week high ($999) to 52-week low ($280).
Enable key Fibonacci levels:
23.6% ($816)
38.2% ($678)
50% ($640)
61.8% ($550)
78.6% ($430)
Watch for price reactions near these levels.
Using Gann Retracement Levels:
Select "Gann Box" in TradingView.
Draw from 52-week high ($999) to low ($280).
Enable key Gann retracement levels:
12.5% ($912)
25% ($850)
37.5% ($768)
50% ($640)
62.5% ($550)
75% ($480)
87.5% ($350)
Identify confluences with Gann angles and Fibonacci levels.
Step 5: Identify Significant Dates & Time Cycles
Use "Date Range" Tool in TradingView.
Mark major turning points:
High → Low: ~180 days (Half-year cycle).
Low → High: ~90 days (Quarter cycle).
Use Square-Outs (Time = Price method):
Example: If MSTR hit $500, check 500 days from key events.
Mark key anniversaries of past highs/lows for possible reversals.
Step 6: Analyze and Trade Execution
✅ If MSTR is at a Gann angle + Fibonacci level + key date → Expect a reaction.
✅ Use RSI, MACD, and Volume for extra confirmation.
✅ Set Stop-Loss at nearest Gann support/resistance.
Standardized Leveraged ETF Fund of FlowsThis indicator tracks and standardizes the 3-month fund flows of major leveraged ETFs across different asset classes, including equities, gold, and bonds.
The fund flows are summed over a 3-month period (63 trading days) and then standardized using a 500-day rolling mean and standard deviation.
The resulting normalized fund flow values are plotted in three distinct colors:
Blue for Equities Fund Flows
Yellow for Gold Fund Flows
Green for Bond Fund Flows
SL Hunting Detector📌 Step 1: Identify Liquidity Zones
The script plots high-liquidity zones (red) and low-liquidity zones (green).
These are areas where big players target stop-losses before reversing the price.
Example:
If price is near a red liquidity zone, expect a potential stop-loss hunt & reversal downward.
If price is near a green liquidity zone, expect a potential stop-loss hunt & reversal upward.
📌 Step 2: Watch for Stop-Loss Hunts (Fakeouts)
The indicator marks stop-loss hunts with red (bearish) or green (bullish) arrows.
When do stop-loss hunts occur?
✅ A long wick below support (with high volume) = Stop hunt before reversal upward.
✅ A long wick above resistance (with high volume) = Stop hunt before reversal downward.
Confirmation:
Volume must spike (volume > 1.5x the average volume).
ATR-based wicks must be longer than usual (showing a stop-hunt trap).
📌 Step 3: Enter a Trade After a Stop-Hunt
🔹 Bullish Trade (Buying a Dip)
If a green arrow appears (stop-hunt below support):
✅ Enter a long (buy) trade at or just above the wick’s recovery level.
✅ Stop-loss: Below the wick’s low (avoid getting hunted again).
✅ Take-profit: Next resistance level or mid-range of the liquidity zone.
🔹 Bearish Trade (Shorting a Fakeout)
If a red arrow appears (stop-hunt above resistance):
✅ Enter a short (sell) trade at or just below the wick’s rejection level.
✅ Stop-loss: Above the wick’s high (avoid getting stopped out).
✅ Take-profit: Next support level or mid-range of the liquidity zone.
📌 Step 4: Set Alerts & Automate
✅ The indicator triggers alerts when a stop-hunt is detected.
✅ You can set TradingView to notify you instantly when:
A bullish stop-hunt occurs → Look for long entry.
A bearish stop-hunt occurs → Look for short entry.
📌 Example Trade Setup
Example (BTC Long Trade on Stop-Hunt)
BTC is near $40,000 support (green liquidity zone).
A long wick drops to $39,800 with a green arrow (bullish stop-hunt signal).
Volume spikes, and price recovers quickly back above $40,000.
Trade entry: Buy at $40,050.
Stop-loss: Below wick ($39,700).
Take-profit: $41,500 (next resistance).
Result: BTC pumps, stop-loss remains safe, and trade profits.
🔥 Final Tips
Always wait for confirmation (don’t enter blindly on signals).
Use higher timeframes (15m, 1H, 4H) for better accuracy.
Combine with Order Flow tools (like Bookmap) to see real liquidity zones.
🚀 Now try it on TradingView! Let me know if you need adjustments. 📈🔥
GWAP (Gamma Weighted Average Price)Gamma Weighted Average Price (GWAP) Indicator
The Gamma Weighted Average Price (GWAP) is a dynamic financial indicator that applies exponentially decaying weights to historical prices to calculate a weighted average. The method leverages the exponential decay function, controlled by a gamma factor, to prioritize recent price data while gradually diminishing the influence of older observations. This approach builds upon techniques commonly found in time-series analysis, including Exponentially Weighted Moving Averages (EWMA), which are extensively used in financial modeling (Campbell, Lo & MacKinlay, 1997).
Theoretical Context and Justification
The gamma-weighted approach follows principles similar to those in Exponentially Weighted Moving Averages (EWMA), often used in volatility modeling, where weights decay exponentially over time. The exponential decay model can improve signal responsiveness compared to simple moving averages (Hyndman & Athanasopoulos, 2018). This design helps capture recent market dynamics without ignoring past trends, a common requirement in high-frequency trading systems (Bandi & Russell, 2006).
Practical Applications
1. Trend Detection:
The GWAP can help identify bullish and bearish trends:
• When the price is above GWAP, the market exhibits bullish momentum.
• Conversely, when the price is below GWAP, bearish momentum prevails.
2. Volatility Filtering:
Because of the gamma weighting mechanism, GWAP reduces the noise commonly seen in volatile markets, making it a useful tool for traders looking to smooth price fluctuations while retaining actionable signals.
3. Crossovers for Trade Signals:
Similar to moving average strategies, traders can use price crossovers with the GWAP as trade signals:
• Buy Signal: When the price crosses above the GWAP.
• Sell Signal: When the price crosses below the GWAP.
4. Adaptive Gamma Weighting:
The gamma factor allows for further customization.
• Higher gamma values (>1) place greater emphasis on older data, suitable for long-term trend analysis.
• Lower gamma values (<1) heavily weight recent price movements, ideal for fast-moving markets.
Example Use Case
A trader analyzing the S&P 500 may use a gamma factor of 0.92 with a 14-period GWAP to detect shifts in market sentiment during periods of heightened volatility. When the index price crosses above the GWAP, this could signal a potential recovery, prompting a buy entry. Conversely, when the price moves below the GWAP during a correction, it may suggest a short-selling opportunity.
Scientific References
• Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets. Princeton University Press.
• Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice. OTexts.
• Bandi, F. M., & Russell, J. R. (2006). Microstructure Noise, Realized Variance, and Optimal Sampling. Econometrica.
Volatility Arbitrage Spread Oscillator Model (VASOM)The Volatility Arbitrage Spread Oscillator Model (VASOM) is a systematic approach to capitalizing on price inefficiencies in the VIX futures term structure. By analyzing the differential between front-month and second-month VIX futures contracts, we employ a momentum-based oscillator (Relative Strength Index, RSI) to signal potential market reversion opportunities. Our research builds upon existing financial literature on volatility risk premia and contango/backwardation dynamics in the volatility markets (Zhang & Zhu, 2006; Alexander & Korovilas, 2012).
Volatility derivatives have become essential tools for managing risk and engaging in speculative trades (Whaley, 2009). The Chicago Board Options Exchange (CBOE) Volatility Index (VIX) measures the market’s expectation of 30-day forward-looking volatility derived from S&P 500 option prices (CBOE, 2018). Term structures in VIX futures often exhibit contango or backwardation, depending on macroeconomic and market conditions (Alexander & Korovilas, 2012).
This strategy seeks to exploit the spread between the front-month and second-month VIX futures as a proxy for term structure dynamics. The spread’s momentum, quantified by the RSI, serves as a signal for entry and exit points, aligning with empirical findings on mean reversion in volatility markets (Zhang & Zhu, 2006).
• Entry Signal: When RSI_t falls below the user-defined threshold (e.g., 30), indicating a potential undervaluation in the spread.
• Exit Signal: When RSI_t exceeds a threshold (e.g., 70), suggesting mean reversion has occurred.
Empirical Justification
The strategy aligns with findings that suggest predictable patterns in volatility futures spreads (Alexander & Korovilas, 2012). Furthermore, the use of RSI leverages insights from momentum-based trading models, which have demonstrated efficacy in various asset classes, including commodities and derivatives (Jegadeesh & Titman, 1993).
References
• Alexander, C., & Korovilas, D. (2012). The Hazards of Volatility Investing. Journal of Alternative Investments, 15(2), 92-104.
• CBOE. (2018). The VIX White Paper. Chicago Board Options Exchange.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
• Zhang, C., & Zhu, Y. (2006). Exploiting Predictability in Volatility Futures Spreads. Financial Analysts Journal, 62(6), 62-72.
• Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
ELHAI Futures Trend Checker (ES, NQ, YM)The ELHAI Futures Trend Checker is a powerful TradingView indicator designed for futures traders who want to monitor the trend synchronization of the three major U.S. futures indices:
✅ E-mini S&P 500 (ES1!)
✅ E-mini Nasdaq 100 (NQ1!)
✅ E-mini Dow Jones (YM1!)
This indicator checks whether all three futures indices are bullish or bearish during each candle formation. If one of them is out of sync (e.g., two indices are bullish while one is bearish), the indicator triggers an alert and highlights the background in red, helping traders identify potential market indecision or divergence.
Key Features
📌 Designed for Futures Traders – Focuses on ES, NQ, and YM futures contracts.
📌 Live Market Monitoring – Works in real-time and updates dynamically with each tick.
📌 Bullish/Bearish Trend Confirmation – Detects when all three indices are in sync.
📌 Mismatch Detection – Alerts you when at least one index is out of trend.
📌 Custom Alerts – Set up TradingView alerts to be notified instantly when a trend mismatch occurs.
📌 Visual Background Highlight – A red background warns of a market divergence.
How It Works
The script retrieves open and close prices for ES, NQ, and YM.
Determines whether each futures index is bullish (close > open) or bearish (close < open).
If all three indices are bullish or all are bearish, it remains neutral.
If one index is different, an alert is triggered and the background turns red.
How to Use
Apply the indicator to your TradingView chart.
Choose any timeframe – Works well on intraday, daily, or higher timeframes.
Enable alerts: Go to Alerts → Create Alert, select "Futures Trend Mismatch", and set your preferred alert frequency.
Use alongside other indicators like moving averages, RSI, or MACD for better trade confirmation.
Best Use Cases
✔ Day traders & scalpers – Quickly spot market divergence in live trading.
✔ Swing traders – Identify when futures markets lose synchronization.
✔ Trend followers – Confirm if all major futures markets are aligned before making a move.
Final Notes
This indicator was built for Elhai to provide real-time trend analysis across major U.S. futures indices. Use it as a confirmation tool to improve market timing and decision-making.
Enhanced Volume Profile█ OVERVIEW
The Enhanced Volume Profile (EVP) is an indicator designed to plot a volume profile on the chart based on either the visible chart range or a fixed lookback period. The script helps analyze the distribution of volume at different price levels over time, providing insights into areas of high trading activity and potential support/resistance zones.
█ KEY FEATURES
1. Visible Chart Range vs. Fixed Lookback Depth
Visible Chart Range
- Default analysis mode
- Calculates profile based on visible portion of the chart
- Dynamically updates with chart view changes
Fixed Lookback Depth
- Optional alternative to visible range
- Uses specified number of bars (10-3000)
- Provides consistent analysis depth
- Independent of chart view
2. Custom Resolution
Auto-Resolution Mode
Automatically selects timeframes based on chart's current timeframe:
≤ 1 minute: Uses 1-minute resolution
≤ 5 minutes: Uses 1-minute resolution
≤ 15 minutes: Uses 5-minute resolution
≤ 1 hour: Uses 5-minute resolution
≤ 4 hours: Uses 15-minute resolution
≤ 12 hours: Uses 15-minute resolution
≤ 1 day: Uses 1-hour resolution
≤ 3 days: Uses 2-hours resolution
≤ 1 week: Uses 4-hours resolution
Custom Resolution Override
Optional override of auto-resolution system
Provides control over data granularity
Must be lower than or equal to chart's timeframe
Falls back to auto-resolution if validation fails
3. Volume Profile Resolution
Adjustable number of points (10-400)
Controls profile granularity
Higher resolution provides more detail
Balance between precision and performance
4. Point of Control (PoC)
Identifies price level with highest traded volume
Optional display with customizable appearance
Adjustable line thickness (1-30)
Configurable color
5. Value Area (VA)
Shows price range of majority trading volume
Adjustable coverage (5-95%), default is 68%
Customizable boundary lines
Configurable lines color and thickness (1-20)
█ INPUT PARAMETERS
Lookback Settings
Use Visible Chart Range
- Default: true
- Calculates profile based on visible bars
- Ideal for focused analysis
Fixed Lookback Bars
- Range: 10-3000
- Default: 200
- Used when visible range is disabled
Resolution Settings
Enable Custom Resolution
- Default: false
- Overrides auto-resolution
Custom Resolution
- Default: 1-minute
- Changes automatically when "Enable Custom Resolution" is disabled
Volume Profile Appearance
Profile Resolution
- Range: 10-400
- Default: 200
- Controls detail level
Profile Width Scale
- Range: 1-50
- Default: 15
- Adjusts profile width
Right Offset
- Range: 0-500
- Default: 20
- Controls spacing from price bars
Profile Fill Color
- Default: #5D606B (70% transparency)
Point of Control Settings
Show Point of Control
- Default: true
- Toggles PoC visibility
PoC Line Thickness
- Range: 1-30
- Default: 1
PoC Line Color
- Default: Red
Value Area Settings
Show Value Area
- Default: true
- Toggles VA lines
Value Area Coverage
- Range: 5-95%
- Default: 68%
Value Area Line Color
- Default: Blue
Value Area Line Thickness
- Range: 1-20
- Default: 1
█ TECHNICAL IMPLEMENTATION DETAILS
Exceeding Bars Management
The script dynamically adjusts the number of bars used in the volume profile calculation based on the selected timeframe and the maximum allowed bars (max_bars_back).
If the total number of bars exceeds the predefined threshold (6000 bars), the script reduces the lookback period (lookback_bars) by trimming some of the historical data, ensuring the chart does not become overloaded with data.
The adjustment is made based on the ratio of bars per candle (bars_per_candle), ensuring that the volume profile remains computationally efficient while maintaining its relevance.
█ EXAMPLE USE CASES
1. Visible Range Mode
For analyzing a recent trend and focusing on only the visible part of the chart, enabling the "Use Visible Chart Range" option calculates the profile based on the current view, without considering historical data outside the visible area.
2. Fixed Lookback Depth
For analyzing a specific period in the past (e.g., the last 200 bars), disabling the visible range and setting a fixed lookback depth of 200 bars ensures the profile always considers the last 200 bars, regardless of the visible range.
3. Custom Resolution
If there’s a need for greater control over the timeframe used for volume profile calculations (e.g., using a 5-minute resolution on a 15-minute chart), enabling custom resolution and setting the desired timeframe provides this control.
HAPPY TRADING ✌️
Thin Liquidity Zones [PhenLabs]Thin Liquidity Zones with Volume Delta
Our advanced volume analysis tool identifies and visualizes significant liquidity zones using real-time volume delta analysis. This indicator helps traders pinpoint and monitor critical price levels where substantial trading activity occurs, providing precise volume flow measurement through lower timeframe analysis.
The tool works by leveraging the fact that hedge funds, institutions, and other large market participants strategically fill their orders in areas of thin liquidity to minimize slippage and market impact. By detecting these zones, traders gain valuable insights into potential areas of accumulation, distribution, and liquidity traps, allowing for more informed trading decisions.
🔍 Key Features
Real-time volume delta calculation using lower timeframe data
Dynamic zone creation based on volume spikes
Automatic timeframe optimization
Size-filtered zones to avoid noise
Custom delta timeframe scanning
Flexible analysis period selection
📊 Visual Demonstration
💡 How It Works
The indicator continuously scans for high-volume areas where trading activity exceeds the specified threshold (default 6.0x average volume). When detected, it creates zones that display the net volume delta, showing whether buying or selling pressure dominated that price level.
Key zone characteristics:
Size filtering prevents noise from large price swings
Volume delta shows actual buying/selling pressure
Zones automatically expire based on lookback period
Real-time updates as new volume data arrives
⚙️ Settings
Time Settings
Analysis Timeframe: 15M to 1W options
Custom Period: User-defined bar count
Delta Timeframe: Automatic or manual selection
Volume Analysis
Volume Threshold: Minimum spike multiple
Volume MA Length: Averaging period
Maximum Zone Size: Size filter percentage
Display Options
Zone Color: Customizable with transparency
Delta Display: On/Off toggle
Text Position: Left/Center/Right alignment
📌 Tips for Best Results
Adjust volume threshold based on instrument volatility
Monitor zone clusters for potential support/resistance
Consider reducing max zone size in volatile markets
Use in conjunction with price action and other indicators
⚠️ Important Notes
Requires volume data from your data provider
Lower timeframe scanning may impact performance
Maximum 500 zones maintained for optimization
Zone creation is filtered by both volume and size
🔧 Volume Delta Calculation
The indicator uses TradingView’s advanced volume delta calculation, which:
Scans lower timeframe data for precision
Measures actual buying vs selling pressure
Updates in real-time with new data
Provides clear positive/negative flow indication
This tool is ideal for traders focusing on volume analysis and order flow. It helps identify key levels where significant trading activity has occurred and provides insight into the nature of that activity through volume delta analysis.
Note: Performance may vary based on your chart’s timeframe. Adjust settings according to your trading style and the instrument’s characteristics. Past performance is not indicative of future results, DYOR.
BTC-SPX Momentum Gauge + EMA SignalHere's an explanation of the market dynamics and signal benefits of this script:
Momentum and Sentiment Indicator:
The script uses the momentum of the S&P 500 to change the chart's background color, providing a quick visual cue of market sentiment. Green indicates potential bullish momentum in the broader market, while red suggests bearish momentum. This can help traders gauge overall market direction at a glance.
Bitcoin Trend Analysis:
By plotting the scaled TEMA of Bitcoin (BTC), traders can see how Bitcoin's trend correlates or diverges from the current asset being analyzed. Since Bitcoin is often viewed as a hedge against traditional financial systems or inflation, its trend can signal broader economic shifts or investor sentiment towards alternative investments.
Dual Trend Confirmation:
The script offers two trend lines: one for Bitcoin and one for the current ticker. When these lines move in tandem, it might indicate a strong market trend across both traditional and crypto markets. Divergence between these lines can highlight potential market anomalies or opportunities for arbitrage or hedging.
Smoothness vs. Reactivity:
The use of TEMA for Bitcoin provides a smoother signal than a simple moving average, reducing lag while still reacting to price changes. This can be particularly useful for identifying longer-term trends in Bitcoin's volatile market. The 20-period EMA for the current ticker, on the other hand, gives a quicker response to price changes in the asset you're directly trading.
Cross-Asset Correlation:
By overlaying Bitcoin's trend on another asset's chart, traders can analyze how these markets might influence each other. For instance, if Bitcoin is in an uptrend while a traditional asset is declining, it might suggest capital rotation into cryptocurrencies.
Trading Signals:
Crossovers or divergences between the TEMA of Bitcoin and the EMA of the current ticker could be used as signals for entry or exit points. For example, if the BTC TEMA crosses above the current ticker's EMA, it might suggest a shift towards crypto assets.
Risk Management:
The visual cues from the background color and moving averages can aid in risk management. For example, trading in the direction of the momentum indicated by the background color might be seen as going with the market flow, potentially reducing risk.
Macro-Economic Insights:
The relationship between Bitcoin and traditional markets can offer insights into macroeconomic conditions, particularly related to inflation, monetary policy, and investor sentiment towards fiat currencies.
Headwind and tailwind:
Currently BTC correlated trade instruments experience headwind or tailwind from the broader market. This indicator lets the user see it to help their trade decision process.
Additional Statement:
As the market realizes the dangers of the fiat that its construct is built upon and evolves and migrates into stable money, incorruptible by inflation, this indicator will reveal the external influence of that corruptible and the internal influence of the incorruptible; having diminishing returns as the rise of stable money overtakes the treasuries of the fiat construct.
Timed Ranges [mktrader]The Timed Ranges indicator helps visualize price ranges that develop during specific time periods. It's particularly useful for analyzing market behavior in instruments like NASDAQ, S&P 500, and Dow Jones, which often show reactions to sweeps of previous ranges and form reversals.
### Key Features
- Visualizes time-based ranges with customizable lengths (30 minutes, 90 minutes, etc.)
- Tracks high/low range development within specified time periods
- Shows multiple cycles per day for pattern recognition
- Supports historical analysis across multiple days
### Parameters
#### Settings
- **First Cycle (HHMM-HHMM)**: Define the time range of your first cycle. The duration of this range determines the length of all subsequent cycles (e.g., "0930-1000" creates 30-minute cycles)
- **Number of Cycles per Day**: How many consecutive cycles to display after the first cycle (1-20)
- **Maximum Days to Display**: Number of historical days to show the ranges for (1-50)
- **Timezone**: Select the appropriate timezone for your analysis
#### Style
- **Box Transparency**: Adjust the transparency of the range boxes (0-100)
### Usage Example
To track 30-minute ranges starting at market open:
1. Set First Cycle to "0930-1000" (creates 30-minute cycles)
2. Set Number of Cycles to 5 (will show ranges until 11:30)
3. The indicator will display:
- Range development during each 30-minute period
- Visual progression of highs and lows
- Color-coded cycles for easy distinction
### Use Cases
- Identify potential reversal points after range sweeps
- Track regular time-based support and resistance levels
- Analyze market structure within specific time windows
- Monitor range expansions and contractions during key market hours
### Tips
- Use in conjunction with volume analysis for better confirmation
- Pay attention to breaks and sweeps of previous ranges
- Consider market opens and key session times when setting cycles
- Compare range sizes across different time periods for volatility analysis
Rolling Angled Volume Profile [Trendoscope®]🎲 Volume Profile Indicators
🎯Traditional Volume Profile
Volume profile indicators visually represent the distribution of volume across price levels. These indicators typically operate on horizontal price levels, making them effective in identifying supply and demand zones in ranging markets. However, they are less useful in trending markets where price movements follow a slope.
🎯The Need for Angled Volume Profiles
Just as support and resistance levels differ from trendlines, volume profile indicators require an equivalent method to account for volume distribution along a sloped trajectory. This would enable more accurate volume analysis in trending markets.
We identified the need of Angled Volume profile and have already published few indicators that implements the concept.
Angled Volume Profile calculates volume distribution along a slope. Users interact with the indicator by selecting the starting point, after which the volume profile is calculated for the selected trajectory.
Volume Forks is another tool that extends angled volume profile analysis, aligning volume profiles along the trajectory of pitchforks.
🎲 Rolling Volume Profile Indicator
The Rolling Volume Profile offers a new approach to angled volume profile calculations, addressing some limitations of earlier implementations:
🎯 Rolling Calculation
The volume profile is calculated for the last N bars of the instrument
The slope of the profile lines is determined by the closing prices of the starting and ending bars
Profiles are drawn in the direction of price movement between the start and end bars.
🎯 Dynamic Updates
As new bars are added, the calculations are updated, and the profile is redrawn based on the latest data.
This dynamic behavior earns it the name "Rolling Volume Profile."
🎯 Advantages Over Earlier Versions
Unlimited Profile Lines : Unlike previous implementations limited to 500 profile lines, this indicator uses polyline objects, overcoming the restriction.
Live Updates : Previous angled volume profile tools lacked real-time updates when new bars appeared. This limitation is resolved in the Rolling Volume Profile Indicator.
The Rolling Volume Profile provides an efficient and scalable solution for analyzing volume in trending markets.
🎯 Indicator Settings
Simple settings include few customisable options
Internals Elite NYSE [Beta]Overview:
This indicator is designed to provide traders with a quick overview of key market internals and metrics in a single, easy-to-read table displayed directly on the chart. It incorporates a variety of metrics that help gauge market sentiment, momentum, and overall market conditions.
The table dynamically updates in real-time and uses color-coding to highlight significant changes or thresholds, allowing traders to quickly interpret the data and make informed trading decisions.
Features:
Market Internals:
TICK: Measures the difference between the number of stocks ticking up versus those ticking down on the NYSE. Green or red background indicates if it crosses a user-defined threshold.
Advance/Decline (ADD): Shows the net number of advancing versus declining stocks on the NYSE. Color-coded to show positive, negative, or neutral conditions.
Volatility Metrics:
VIX Change (%): Displays the percentage change in the Volatility Index (VIX), a key gauge of market fear or complacency. Color-coded for direction.
VIX Price: Displays the current VIX price with thresholds to indicate low, medium, or high volatility.
Other Market Metrics:
DXY Change (%): Percentage change in the US Dollar Index (DXY), indicating dollar strength or weakness.
VWAP Deviation (%): Percentage of stocks above VWAP (Volume Weighted Average Price), helping traders assess intraday buying and selling pressure.
Asset-Specific Metrics:
BTCUSD Change (%): Percentage change in Bitcoin (BTC) price, useful for monitoring cryptocurrency sentiment.
SPY Change (%): Percentage change in the S&P 500 ETF (SPY), a proxy for the overall stock market.
Current Ticker Change (%): Percentage change in the currently selected ticker on the chart.
US10Y Change (%): Percentage change in the yield of the 10-Year US Treasury Note (TVC:US10Y), an important macroeconomic indicator.
Customizable Appearance:
Adjustable text size to suit your chart layout.
User-defined thresholds for key metrics (e.g., TICK, ADD, VWAP, VIX).
Dynamic Table Placement:
You can position the table anywhere on the chart: top-right, top-left, bottom-right, bottom-left, middle-right, or middle-left.
How to Use:
Add the Indicator to Your Chart:
Apply the indicator to your chart from the Pine Script editor in TradingView.
Customize the Inputs:
Adjust the thresholds for TICK, ADD, VWAP, and VIX according to your trading style.
Enable or disable the metrics you want to see in the table by toggling the display options for each metric (e.g., Show TICK, Show BTC, Show SPY).
Set the table placement to your preferred position on the chart.
Interpret the Table:
Look for color-coded cells to quickly identify significant changes or breaches of thresholds.
Positive values are typically shown in green, negative values in red, and neutral/insignificant changes in gray.
Use metrics like TICK and ADD to gauge market breadth and momentum.
Refer to VWAP deviation to assess intraday buying or selling pressure.
Monitor the VIX and US10Y changes to stay aware of macroeconomic and volatility shifts.
Incorporate Into Your Strategy:
Use the indicator alongside technical analysis to confirm setups or identify areas of caution.
Keep an eye on correlated metrics (e.g., VIX and SPY) for broader market context.
Use BTCUSD or DXY as additional indicators of risk-on/risk-off sentiment.
Ideal Users:
Day Traders: Quickly gauge intraday market conditions and momentum.
Swing Traders: Identify broader sentiment shifts using metrics like ADD, DXY, and US10Y.
Macro Investors: Stay updated on key macroeconomic indicators like the 10-Year Treasury yield (US10Y) and the US Dollar Index (DXY).
This indicator serves as a comprehensive tool for understanding market conditions at a glance, enabling traders to act decisively based on the latest data.
Implied and Historical VolatilityAbstract
This TradingView indicator visualizes implied volatility (IV) derived from the VIX index and historical volatility (HV) computed from past price data of the S&P 500 (or any selected asset). It enables users to compare market participants' forward-looking volatility expectations (via VIX) with realized past volatility (via historical returns). Such comparisons are pivotal in identifying risk sentiment, volatility regimes, and potential mispricing in derivatives.
Functionality
Implied Volatility (IV):
The implied volatility is extracted from the VIX index, often referred to as the "fear gauge." The VIX represents the market's expectation of 30-day forward volatility, derived from options pricing on the S&P 500. Higher values of VIX indicate increased uncertainty and risk aversion (Whaley, 2000).
Historical Volatility (HV):
The historical volatility is calculated using the standard deviation of logarithmic returns over a user-defined period (default: 20 trading days). The result is annualized using a scaling factor (default: 252 trading days). Historical volatility represents the asset's past price fluctuation intensity, often used as a benchmark for realized risk (Hull, 2018).
Dynamic Background Visualization:
A dynamic background is used to highlight the relationship between IV and HV:
Yellow background: Implied volatility exceeds historical volatility, signaling elevated market expectations relative to past realized risk.
Blue background: Historical volatility exceeds implied volatility, suggesting the market might be underestimating future uncertainty.
Use Cases
Options Pricing and Trading:
The disparity between IV and HV provides insights into whether options are over- or underpriced. For example, when IV is significantly higher than HV, options traders might consider selling volatility-based derivatives to capitalize on elevated premiums (Natenberg, 1994).
Market Sentiment Analysis:
Implied volatility is often used as a proxy for market sentiment. Comparing IV to HV can help identify whether the market is overly optimistic or pessimistic about future risks.
Risk Management:
Institutional and retail investors alike use volatility measures to adjust portfolio risk exposure. Periods of high implied or historical volatility might necessitate rebalancing strategies to mitigate potential drawdowns (Campbell et al., 2001).
Volatility Trading Strategies:
Traders employing volatility arbitrage can benefit from understanding the IV/HV relationship. Strategies such as "long gamma" positions (buying options when IV < HV) or "short gamma" (selling options when IV > HV) are directly informed by these metrics.
Scientific Basis
The indicator leverages established financial principles:
Implied Volatility: Derived from the Black-Scholes-Merton model, implied volatility reflects the market's aggregate expectation of future price fluctuations (Black & Scholes, 1973).
Historical Volatility: Computed as the realized standard deviation of asset returns, historical volatility measures the intensity of past price movements, forming the basis for risk quantification (Jorion, 2007).
Behavioral Implications: IV often deviates from HV due to behavioral biases such as risk aversion and herding, creating opportunities for arbitrage (Baker & Wurgler, 2007).
Practical Considerations
Input Flexibility: Users can modify the length of the HV calculation and the annualization factor to suit specific markets or instruments.
Market Selection: The default ticker for implied volatility is the VIX (CBOE:VIX), but other volatility indices can be substituted for assets outside the S&P 500.
Data Frequency: This indicator is most effective on daily charts, as VIX data typically updates at a daily frequency.
Limitations
Implied volatility reflects the market's consensus but does not guarantee future accuracy, as it is subject to rapid adjustments based on news or events.
Historical volatility assumes a stationary distribution of returns, which might not hold during structural breaks or crises (Engle, 1982).
References
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy, 81(3), 637-654.
Whaley, R. E. (2000). "The Investor Fear Gauge." The Journal of Portfolio Management, 26(3), 12-17.
Hull, J. C. (2018). Options, Futures, and Other Derivatives. Pearson Education.
Natenberg, S. (1994). Option Volatility and Pricing: Advanced Trading Strategies and Techniques. McGraw-Hill.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2001). The Econometrics of Financial Markets. Princeton University Press.
Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk. McGraw-Hill.
Baker, M., & Wurgler, J. (2007). "Investor Sentiment in the Stock Market." Journal of Economic Perspectives, 21(2), 129-151.
Candle VolumeThis indicator gives gives candle volume represented in X.Y format for simplicity.
100% = 1.0
20% = 0.2
Anything 10X is represented by an arrow up or down based on candle price delta open to close.
By default, a 500 candle lookback of volume is used excluding exteem outliers of 50.
You can adjust these in settings.
Dynamic Volatility Differential Model (DVDM)The Dynamic Volatility Differential Model (DVDM) is a quantitative trading strategy designed to exploit the spread between implied volatility (IV) and historical (realized) volatility (HV). This strategy identifies trading opportunities by dynamically adjusting thresholds based on the standard deviation of the volatility spread. The DVDM is versatile and applicable across various markets, including equity indices, commodities, and derivatives such as the FDAX (DAX Futures).
Key Components of the DVDM:
1. Implied Volatility (IV):
The IV is derived from options markets and reflects the market’s expectation of future price volatility. For instance, the strategy uses volatility indices such as the VIX (S&P 500), VXN (Nasdaq 100), or RVX (Russell 2000), depending on the target market. These indices serve as proxies for market sentiment and risk perception (Whaley, 2000).
2. Historical Volatility (HV):
The HV is computed from the log returns of the underlying asset’s price. It represents the actual volatility observed in the market over a defined lookback period, adjusted to annualized levels using a multiplier of \sqrt{252} for daily data (Hull, 2012).
3. Volatility Spread:
The difference between IV and HV forms the volatility spread, which is a measure of divergence between market expectations and actual market behavior.
4. Dynamic Thresholds:
Unlike static thresholds, the DVDM employs dynamic thresholds derived from the standard deviation of the volatility spread. The thresholds are scaled by a user-defined multiplier, ensuring adaptability to market conditions and volatility regimes (Christoffersen & Jacobs, 2004).
Trading Logic:
1. Long Entry:
A long position is initiated when the volatility spread exceeds the upper dynamic threshold, signaling that implied volatility is significantly higher than realized volatility. This condition suggests potential mean reversion, as markets may correct inflated risk premiums.
2. Short Entry:
A short position is initiated when the volatility spread falls below the lower dynamic threshold, indicating that implied volatility is significantly undervalued relative to realized volatility. This signals the possibility of increased market uncertainty.
3. Exit Conditions:
Positions are closed when the volatility spread crosses the zero line, signifying a normalization of the divergence.
Advantages of the DVDM:
1. Adaptability:
Dynamic thresholds allow the strategy to adjust to changing market conditions, making it suitable for both low-volatility and high-volatility environments.
2. Quantitative Precision:
The use of standard deviation-based thresholds enhances statistical reliability and reduces subjectivity in decision-making.
3. Market Versatility:
The strategy’s reliance on volatility metrics makes it universally applicable across asset classes and markets, ensuring robust performance.
Scientific Relevance:
The strategy builds on empirical research into the predictive power of implied volatility over realized volatility (Poon & Granger, 2003). By leveraging the divergence between these measures, the DVDM aligns with findings that IV often overestimates future volatility, creating opportunities for mean-reversion trades. Furthermore, the inclusion of dynamic thresholds aligns with risk management best practices by adapting to volatility clustering, a well-documented phenomenon in financial markets (Engle, 1982).
References:
1. Christoffersen, P., & Jacobs, K. (2004). The importance of the volatility risk premium for volatility forecasting. Journal of Financial and Quantitative Analysis, 39(2), 375-397.
2. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007.
3. Hull, J. C. (2012). Options, Futures, and Other Derivatives. Pearson Education.
4. Poon, S. H., & Granger, C. W. J. (2003). Forecasting volatility in financial markets: A review. Journal of Economic Literature, 41(2), 478-539.
5. Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
This strategy leverages quantitative techniques and statistical rigor to provide a systematic approach to volatility trading, making it a valuable tool for professional traders and quantitative analysts.
Volatility IndicatorThe volatility indicator presented here is based on multiple volatility indices that reflect the market’s expectation of future price fluctuations across different asset classes, including equities, commodities, and currencies. These indices serve as valuable tools for traders and analysts seeking to anticipate potential market movements, as volatility is a key factor influencing asset prices and market dynamics (Bollerslev, 1986).
Volatility, defined as the magnitude of price changes, is often regarded as a measure of market uncertainty or risk. Financial markets exhibit periods of heightened volatility that may precede significant price movements, whether upward or downward (Christoffersen, 1998). The indicator presented in this script tracks several key volatility indices, including the VIX (S&P 500), GVZ (Gold), OVX (Crude Oil), and others, to help identify periods of increased uncertainty that could signal potential market turning points.
Volatility Indices and Their Relevance
Volatility indices like the VIX are considered “fear gauges” as they reflect the market’s expectation of future volatility derived from the pricing of options. A rising VIX typically signals increasing investor uncertainty and fear, which often precedes market corrections or significant price movements. In contrast, a falling VIX may suggest complacency or confidence in continued market stability (Whaley, 2000).
The other volatility indices incorporated in the indicator script, such as the GVZ (Gold Volatility Index) and OVX (Oil Volatility Index), capture the market’s perception of volatility in specific asset classes. For instance, GVZ reflects market expectations for volatility in the gold market, which can be influenced by factors such as geopolitical instability, inflation expectations, and changes in investor sentiment toward safe-haven assets. Similarly, OVX tracks the implied volatility of crude oil options, which is a crucial factor for predicting price movements in energy markets, often driven by geopolitical events, OPEC decisions, and supply-demand imbalances (Pindyck, 2004).
Using the Indicator to Identify Market Movements
The volatility indicator alerts traders when specific volatility indices exceed a defined threshold, which may signal a change in market sentiment or an upcoming price movement. These thresholds, set by the user, are typically based on historical levels of volatility that have preceded significant market changes. When a volatility index exceeds this threshold, it suggests that market participants expect greater uncertainty, which often correlates with increased price volatility and the possibility of a trend reversal.
For example, if the VIX exceeds a pre-determined level (e.g., 30), it could indicate that investors are anticipating heightened volatility in the equity markets, potentially signaling a downturn or correction in the broader market. On the other hand, if the OVX rises significantly, it could point to an upcoming sharp movement in crude oil prices, driven by changing market expectations about supply, demand, or geopolitical risks (Geman, 2005).
Practical Application
To effectively use this volatility indicator in market analysis, traders should monitor the alert signals generated when any of the volatility indices surpass their thresholds. This can be used to identify periods of market uncertainty or potential market turning points across different sectors, including equities, commodities, and currencies. The indicator can help traders prepare for increased price movements, adjust their risk management strategies, or even take advantage of anticipated price swings through options trading or volatility-based strategies (Black & Scholes, 1973).
Traders may also use this indicator in conjunction with other technical analysis tools to validate the potential for significant market movements. For example, if the VIX exceeds its threshold and the market is simultaneously approaching a critical technical support or resistance level, the trader might consider entering a position that capitalizes on the anticipated price breakout or reversal.
Conclusion
This volatility indicator is a robust tool for identifying market conditions that are conducive to significant price movements. By tracking the behavior of key volatility indices, traders can gain insights into the market’s expectations of future price fluctuations, enabling them to make more informed decisions regarding market entries and exits. Understanding and monitoring volatility can be particularly valuable during times of heightened uncertainty, as changes in volatility often precede substantial shifts in market direction (French et al., 1987).
References
• Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Christoffersen, P. F. (1998). Evaluating Interval Forecasts. International Economic Review, 39(4), 841-862.
• Whaley, R. E. (2000). Derivatives on Market Volatility. Journal of Derivatives, 7(4), 71-82.
• Pindyck, R. S. (2004). Volatility and the Pricing of Commodity Derivatives. Journal of Futures Markets, 24(11), 973-987.
• Geman, H. (2005). Commodities and Commodity Derivatives: Modeling and Pricing for Agriculturals, Metals and Energy. John Wiley & Sons.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
• French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987). Expected Stock Returns and Volatility. Journal of Financial Economics, 19(1), 3-29.
Economic RegimeThis indicator, "Economic Regime" , provides a comprehensive analysis of market conditions by combining multiple asset classes and financial metrics. It uses normalized scores and trend analysis to classify the current economic regime into one of four categories: Goldilocks, Reflation, Inflation, or Deflation. The classification is based on inputs like S&P 500 performance, bond yields, commodity prices, volatility indices, and sector ETFs. Additionally, it plots key financial spreads, including the yield spread (10Y-2Y) and credit spread (HYG-LQD), to offer deeper insights into liquidity and market sentiment. The background color dynamically reflects the identified economic regime, facilitating quick visual interpretation.
Heikin Ashi Candles - [Better Overlay]Heikin Ashi Candles - Better Overlay
Heikin Ashi candles are a unique charting technique designed to smooth price data, making it easier to identify trends and potential reversals. The "Heikin Ashi Candles - Better Overlay" indicator takes this concept further by introducing enhancements like a moving average based on the Heikin Ashi values and an overlay of actual price dynamics. This blog explores the functionality and features of this indicator.
Key Features
1. Heikin Ashi Candle Plotting
The indicator calculates Heikin Ashi values (open, high, low, and close) to plot candles directly on the chart. These candles provide a clearer view of market trends by reducing noise commonly seen in standard candlesticks.
- Heikin Ashi Close: The average of open, high, low, and close prices.
- Heikin Ashi Open: A smoothed value derived from the previous Heikin Ashi open and close values.
- Heikin Ashi High/Low: The highest and lowest prices between the Heikin Ashi open, close, and the actual high/low of the period.
The candle colors are intuitive:
- Green: Indicates bullish movement.
- Red: Indicates bearish movement.
The indicator uses semi-transparent candle bodies to ensure better visibility of the actual price chart underneath.
2. Heikin Ashi Moving Average
The indicator includes an optional moving average calculated from the Heikin Ashi values. This moving average helps traders identify the overall trend direction and its strength.
- The length of the moving average is adjustable via input settings.
- The color of the moving average line reflects its trend:
- Green: Uptrend.
- Red: Downtrend.
3. Dynamic Actual Price Line
To maintain a connection with real-time price data, the indicator overlays a dashed line representing the actual closing price of the asset. This feature provides valuable context when analyzing Heikin Ashi data, ensuring traders do not lose sight of the actual price levels.
Customization Options
The indicator offers several customization settings for better usability:
- Heikin Ashi Moving Average:
- Toggle to show or hide the moving average.
- Adjustable length for the moving average, ranging from 1 to 500 periods.
- Candle Styling:
- The colors and transparency levels of the candles are predefined to maintain chart clarity.
- Users can visually distinguish Heikin Ashi data from the actual price chart.
Practical Use Cases
1. Trend Identification
Heikin Ashi candles smooth out noise, making it easier to identify trends. Bullish and bearish candle coloring provides a quick visual cue for market sentiment.
2. Trend Strength and Reversals
The Heikin Ashi moving average serves as a reliable indicator of trend strength. A change in the color of the moving average can indicate a potential trend reversal.
3. Real-Time Price Reference
The dynamic price line ensures traders have a clear reference to the actual closing price, which is crucial for making informed decisions in real-time markets.
Conclusion
The "Heikin Ashi Candles - Better Overlay" indicator is a versatile tool for traders looking to combine the smoothing benefits of Heikin Ashi candles with the precision of real-time price data. Its additional features, like the Heikin Ashi moving average and dynamic price line, make it a comprehensive solution for both trend-following and real-time trading strategies.
This indicator is a great addition to any trader's toolkit, offering clarity and actionable insights without overcomplicating the chart. Give it a try to explore its potential in your trading journey.
Average Trading Volume per Minute & Suitable Position SizeDescription:
This indicator calculates an average trading volume per minute for the specified lookback period (default 377 bars). It then estimates a suitable position size in USD (or contracts on specific exchanges) by multiplying the average volume by a user-defined percentage (default 8%). The script discards extreme data points (top and bottom 20%) before finding the median, so it provides a more robust measure of typical volume.
How It Works:
1. Each bar’s volume is converted to a USD-based figure, either by taking volume directly (if the exchange quotes in USD) or multiplying volume by the midpoint price.
2. Values are stored in an array, which is then sorted to remove the most extreme 40% (20% from each tail). The remaining 60% is used to calculate a median.
3. You enter a position size percentage (e.g. 8%), and the script multiplies the median volume-per-minute by this percentage to get your recommended position size.
4. For certain exchanges like BitMEX/Deribit, the script adapts how it treats volume (in quotes vs. base), so it can display the final position size properly (USD or contracts).
5. The script displays the result in a small table on the chart, showing the recommended position size in USD (or, for some perpetual contracts, in contract units). If no valid data is available, it indicates “Data Invalid.”
Usage Tips:
• The default Position Size Percentage is 8%. You can adjust it higher for more aggressive trading or lower for smaller exposure.
• The default lookback (Average Calculation Period) is 377 bars. Experiment with different values (e.g. 200 or 500) to capture more or fewer historical bars.
• On certain exchanges and symbols (e.g. BitMEX or Deribit’s “.P” pairs), the script automatically switches how it calculates volume (USD vs. coin-based).
• If you see “Data Invalid,” it likely means the current symbol or timeframe lacks sufficient volume info, or you’re running it on a symbol like BTC.D.
Why This Helps:
• Many traders size positions by guesswork or a fixed fraction of their account. This script instead ties position size to actual average trading volume, ensuring your position is neither too large (risk of poor fills) nor too small (wasting leverage potential).
• Removing top/bottom outliers and using the median aims to give a stable volume measure—less influenced by sudden spikes or extremely quiet bars.
Feel free to tweak the inputs and experiment with different timeframes or pairs. By aligning your position size with typical market liquidity, you can potentially improve overall trade execution and manage risk more effectively.
