Live Economic CalendarLive Economic Calendar
This TradingView indicator provides real-time economic news events directly on your charts, helping traders stay informed about key market-moving data. Built on the original Forex Factory utility by toodegrees, this version enhances functionality with customizable alerts and improved visualizations.
Key Features:
Real-Time Economic News: Displays upcoming economic events from Forex Factory, categorized by impact level (High, Medium, Low, Holiday).
Custom Alerts: Set alerts before and after news events to stay prepared for market volatility.
Timezone Adjustments: Adjust news event times to match your local timezone for accurate scheduling.
Currency-Specific News: Automatically filters news based on the currency pair you’re viewing, with manual options for specific currencies.
Flexible Display Options: Choose to display news for today, this week, or a custom period. Customize labels, lines, and tables directly on the chart.
Impact Visualization: Visual cues (lines, labels, background shading) for different impact levels to highlight significant market events.
Credits:
• Original Forex Factory Utility by toodegrees
• Alerts and enhancements by Nachodog
This Pine Script™ code is licensed under the Mozilla Public License 2.0: mozilla.org
Educational
Dynamic SL - 1 Pip (Up and Down)The Dynamic SL - 1 Pip Up and Down indicator creates two dynamic lines that follow the price at a distance of 1 pip above and below the closing price. This feature can be particularly useful for traders who want to visualize small stop-loss (SL) levels or track price movement in a highly responsive manner.
Unlike traditional stop-loss indicators, this script ensures that the lines only last for 5 seconds, keeping the chart clean and focusing only on the most relevant price movement.
Key Features
✔ Dynamic Stop-Loss Visualization:
The script draws a green line above the price (+1 pip).
A red line below the price (-1 pip) is also drawn.
✔ Auto-Clearing for a Clean Chart:
Each line lasts for 5 seconds only before automatically disappearing.
This prevents unnecessary clutter on the chart and ensures only the latest price movements are visualized.
✔ Adaptable to Multiple Assets:
Automatically calculates the pip size based on the instrument type:
Forex → Uses 0.0001 per pip.
Futures & Stocks → Uses the minimum tick size.
✔ Ideal for High-Frequency Traders & Scalpers:
Designed for 1-minute (M1) or lower timeframes where traders need to monitor price action closely.
Helps visualize ultra-tight stop-loss levels in scalping strategies.
BTC Future Gamma-Weighted Momentum Model (BGMM)The BTC Future Gamma-Weighted Momentum Model (BGMM) is a quantitative trading strategy that utilizes the Gamma-weighted average price (GWAP) in conjunction with a momentum-based approach to predict price movements in the Bitcoin futures market. The model combines the concept of weighted price movements with trend identification, where the Gamma factor amplifies the weight assigned to recent prices. It leverages the idea that historical price trends and weighting mechanisms can be utilized to forecast future price behavior.
Theoretical Background:
1. Momentum in Financial Markets:
Momentum is a well-established concept in financial market theory, referring to the tendency of assets to continue moving in the same direction after initiating a trend. Any observed market return over a given time period is likely to continue in the same direction, a phenomenon known as the “momentum effect.” Deviations from a mean or trend provide potential trading opportunities, particularly in highly volatile assets like Bitcoin.
Numerous empirical studies have demonstrated that momentum strategies, based on price movements, especially those correlating long-term and short-term trends, can yield significant returns (Jegadeesh & Titman, 1993). Given Bitcoin’s volatile nature, it is an ideal candidate for momentum-based strategies.
2. Gamma-Weighted Price Strategies:
Gamma weighting is an advanced method of applying weights to price data, where past price movements are weighted by a Gamma factor. This weighting allows for the reinforcement or reduction of the influence of historical prices based on an exponential function. The Gamma factor (ranging from 0.5 to 1.5) controls how much emphasis is placed on recent data: a value closer to 1 applies an even weighting across periods, while a value closer to 0 diminishes the influence of past prices.
Gamma-based models are used in financial analysis and modeling to enhance a model’s adaptability to changing market dynamics. This weighting mechanism is particularly advantageous in volatile markets such as Bitcoin futures, as it facilitates quick adaptation to changing market conditions (Black-Scholes, 1973).
Strategy Mechanism:
The BTC Future Gamma-Weighted Momentum Model (BGMM) utilizes an adaptive weighting strategy, where the Bitcoin futures prices are weighted according to the Gamma factor to calculate the Gamma-Weighted Average Price (GWAP). The GWAP is derived as a weighted average of prices over a specific number of periods, with more weight assigned to recent periods. The calculated GWAP serves as a reference value, and trading decisions are based on whether the current market price is above or below this level.
1. Long Position Conditions:
A long position is initiated when the Bitcoin price is above the GWAP and a positive price movement is observed over the last three periods. This indicates that an upward trend is in place, and the market is likely to continue in the direction of the momentum.
2. Short Position Conditions:
A short position is initiated when the Bitcoin price is below the GWAP and a negative price movement is observed over the last three periods. This suggests that a downtrend is occurring, and a continuation of the negative price movement is expected.
Backtesting and Application to Bitcoin Futures:
The model has been tested exclusively on the Bitcoin futures market due to Bitcoin’s high volatility and strong trend behavior. These characteristics make the market particularly suitable for momentum strategies, as strong upward or downward movements are often followed by persistent trends that can be captured by a momentum-based approach.
Backtests of the BGMM on the Bitcoin futures market indicate that the model achieves above-average returns during periods of strong momentum, especially when the Gamma factor is optimized to suit the specific dynamics of the Bitcoin market. The high volatility of Bitcoin, combined with adaptive weighting, allows the model to respond quickly to price changes and maximize trading opportunities.
Scientific Citations and Sources:
• 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.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637–654.
• Fama, E. F., & French, K. R. (1992). The Cross-Section of Expected Stock Returns. The Journal of Finance, 47(2), 427–465.
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.
Multiple Candlestick Patterns - AlgomaxxA comprehensive candlestick pattern detection indicator that identifies seven major Japanese candlestick patterns in real-time. This indicator helps traders identify potential reversal and continuation patterns with customizable visual alerts and labels.
Features
Detects 7 major candlestick patterns:
Doji
Hammer
Shooting Star
Bullish Engulfing
Bearish Engulfing
Morning Star
Evening Star
Color-coded candlesticks for easy pattern identification
Customizable pattern indicators above/below candles
Optional pattern labels with adjustable position
Alert conditions for each pattern
Grouped settings for easy customization
Settings
General Settings
Lookback Period: Number of candles to analyze (default: 20)
Body Size Threshold: Minimum relative size for candle body (default: 0.6)
Pattern Settings
Toggle visibility for each pattern type:
Doji Pattern
Hammer Pattern
Shooting Star Pattern
Bullish Engulfing Pattern
Bearish Engulfing Pattern
Morning Star Pattern
Evening Star Pattern
Label Settings
Show Labels: Toggle pattern labels on/off
Label Text Color: Customize label color
Label Position: Choose between Left/Center/Right alignment
Label Offset: Adjust distance of labels from candles
Pattern Descriptions
Doji: Shows indecision when open and close prices are very close
Yellow color
Cross symbol below candle
Hammer: Potential bullish reversal with long lower shadow
Green color
Triangle up symbol below candle
Shooting Star: Potential bearish reversal with long upper shadow
Red color
Triangle down symbol above candle
Bullish Engulfing: Bullish reversal pattern where current green candle completely engulfs previous red candle
Light green color
Triangle up symbol below candle
Bearish Engulfing: Bearish reversal pattern where current red candle completely engulfs previous green candle
Light red color
Triangle down symbol above candle
Morning Star: Three-candle bullish reversal pattern
Seafoam green color
Triangle up symbol below candle
Evening Star: Three-candle bearish reversal pattern
Pink red color
Triangle down symbol above candle
How to Use
Add the indicator to your chart
Customize the settings based on your preferences:
Enable/disable specific patterns you want to monitor
Adjust label settings for better visibility
Set up alerts for patterns you want to be notified about
Pattern Recognition:
Watch for color changes in candlesticks indicating pattern formation
Look for shape indicators above/below candles
Read pattern labels for quick pattern identification
Trading Suggestions:
Use in conjunction with other technical indicators
Consider overall trend and support/resistance levels
Confirm patterns with volume and price action
Wait for pattern completion before making trading decisions
Tips
Patterns work best when used with multiple timeframes
Combine with trend lines and support/resistance levels
Use volume to confirm pattern strength
Consider market context and overall trend
Larger timeframes typically produce more reliable signals
Use alerts to avoid missing important pattern formations
Disclaimer
This indicator is for informational and educational purposes only. No guarantee is made regarding the accuracy of pattern detection or potential future price movements. Always use proper risk management and consider multiple factors before making trading decisions.
Ultimate Volatility Scanner by NHBprod - Requested by Client!Hey Everyone!
I created another script to add to my growing library of strategies and indicators that I use for automated crypto and stock trading! This strategy is for BITCOIN but can be used on any stock or crypto. This was requested by a client so I thought I should create it and hopefully build off of it and build variants!
This script gets and compares the 14-day volatility using the ATR percentage for a list of cryptocurrencies and stocks. Cryptocurrencies are preloaded into the script, and the script will show you the TOP 5 coins in terms of volatility, and then compares it to the Bitcoin volatility as a reference. It updates these values once per day using daily timeframe data from TradingView. The coins are then sorted in descending order by their volatility.
If you don't want to use the preloaded set of coins, you have the option of inputting your own coins AND/OR stocks!
Let me know your thoughts.
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.
Buyable Gap Ups (BGU) ScreenerBuyable Gap Ups (BGU) Screener
This custom indicator detects Buyable Gap Ups (BGU), designed to identify stocks with significant price movements driven by gap-ups, often signaling strong bullish momentum. It helps traders spot potential opportunities where a stock has gapped up above the previous day's high with increased volume, suggesting the possibility of continued price strength.
Key Features:
Gap Percentage Threshold: Set a minimum gap percentage required for a valid buyable gap-up.
Volume Change Threshold: Identifies gap-ups accompanied by a significant increase in volume compared to the 50-day average.
ATR-Based Gap Detection (Optional): Use Average True Range (ATR) to determine whether the gap is large enough, factoring in recent volatility.
Customizable Lookback Period: Adjust the number of recent bars to track the frequency of BGU occurrences.
Volume Confirmation: Only signals buyable gaps when volume surpasses a defined threshold above the 50-day average.
Input Parameters:
Gap Percentage Threshold: Adjusts the minimum percentage gap for a valid signal.
Volume Change Threshold: Determines the minimum percentage increase in volume compared to the 50-day moving average.
Use ATR Gap: Option to use ATR to determine the minimum gap size instead of the percentage gap.
ATR Multiplier for Gap: Customizes the gap size based on the ATR.
ATR Length: Adjusts the lookback period for calculating ATR.
Lookback Period for BGU: Set the number of bars over which to calculate the BGU count.
Alerts & Signals:
The script will plot signals below bars where a valid BGU condition is met.
Alerts can be set for when a BGU is detected, giving real-time notifications for potential trading opportunities.
This indicator is designed to help traders find stocks showing strong bullish momentum, especially after earnings or other market-moving events, with the potential for continued uptrend. It is ideal for those looking to incorporate gap-based strategies in their trading.
Walk Forward PatternsINTRO
In Euclidean geometry, every mathematical output has a planar projection. 'Walk Forward Patterns' can be considered a practical example of this concept. On the other hand, this indicator might also be viewed as an experiment in 'how playing with Lego as a child contributes to time series analysis' :)
OVERVIEW
This script dynamically generates the necessary optimization and testing ranges for Walk Forward Analysis based on user-defined bar count and length inputs. It performs automatic calculations for each step, offers 8 different window options depending on the inputs, and visualizes the results dynamically. I should also note that most of the window models consist of original patterns I have created.
ADDITIONAL INFO : WHAT IS WALK FORWARD ANALYSIS?
Although it is not the main focus of this indicator, providing a brief definition of Walk Forward Analysis can be helpful in correctly interpreting the results it generates. Walk Forward Analysis (WFA) is a systematic method for optimizing parameters and validating trading strategies. It involves dividing historical data into variable segments, where a strategy is first optimized on an in-sample period and then tested on an out-of-sample period. This process repeats by shifting the windows forward, ensuring that each test evaluates the strategy on unseen data, helping to assess its robustness and adaptability in real market conditions.
ORIGINALITY
There are very few studies on Walk Forward Analysis in TradingView. Even worse, there are no any open-source studies available. Someone has to start somewhere, I suppose. And in my personal opinion, determining the optimization and backtest intervals is the most challenging part of WFA. These intervals serve as a prerequisite for automated parameter optimization. I felt the need to publish this pattern module, which I use in my own WFA models, partly due to this gap on community scripts.
INDICATOR MECHANICS
To use the indicator effectively, you only need to perform four simple tasks:
Specify the total number of bars in your chart in the 'Bar Index' parameter.
Define the optimization (In-Sample Test) length.
Define the testing (Out-Of-Sample Test) length.
Finally, select the window type.
The indicator automatically models everything else (including the number of steps) based on your inputs. And the result; you now have a clear idea of which bars to use for your Walk Forward tests!
A COMMONLY USED WINDOW SELECTION METHOD: ROLLING
A more concrete definition of Walk Forward Analysis, specifically for the widely used Rolling method, can be described as follows:
Parameters that have performed well over a certain period are identified (Optimization: In-Sample).
These parameters are then tested on a shorter, subsequent period (Backtest: Out-of-Sample).
The process is repeated forward in time (At each step, the optimization and backtest periods are shifted by the backtest length).
If the cumulative percentage profit obtained from the backtest results is greater than half of the historical optimization profit, the strategy is considered "successful."
If the strategy is successful, the most recent (untested) optimization values are used for live trading.
OTHER WINDOW OPTIONS
ANCHORED: That's a pattern based on progressively expanding optimization ranges at each step. Backtest ranges move forward in a staircase-like manner.
STATIC: Optimization ranges remain fixed, while backtest ranges are shifted forward.
BLOCKED: Optimization ranges are shifted forward in groups of three blocks. Backtest ranges are also shifted in a staircase manner, even at the cost of creating gaps from the optimization end bars.
TRIANGULAR: Optimization ranges are shifted forward in triangular regions, while backtest ranges move in a staircase pattern.
RATIO: The optimization length increases by 25% of the initial step’s fixed length at each step. In other words, the length grows by 25% of the first step's length incrementally. Backtest ranges always start from the bar where the optimization ends.
FIBONACCI: A variation of the Ratio method, where the optimization shift factor is set to 0.618
RANDOM WALK
Unlike the window models explained above, we can also generate optimization and backtest ranges completely randomly—offering almost unlimited variations! When you select the "Random" option in the "Window" parameter on the indicator interface, random intervals are generated based on various trigonometric calculations. By changing the numerical value in the '🐒' parameter, you can create entirely unique patterns.
WHY THE 🐒 EMOJI?
Two reasons.
First, I think that as humanity, we are a species of tailless primates who become happy when we understand things :). At least evolutionarily. The entire history of civilization is built on the effort to express the universe in a scale we can comprehend. 'Knowledge' is an invention born from this effort, which is why we feel happiness when we 'understand'. Second, I can't think of a better metaphor for randomness than a monkey sitting at a keyboard. See: Monkey Test.
Anyway, I’m rambling :)
NOTES
The indicator generates results for up to 100 steps. As the number of steps increases, the table may extend beyond the screen—don’t forget to zoom out!
FINAL WORDS
I haven’t published a Walk Forward script yet . However, there seem to be examples that can perform parameter optimization in the true sense of the word, producing more realistic results without falling into overfitting in my library. Hopefully, I’ll have the chance to publish one in the coming weeks. Sincerely thanks to Kıvanç Özbilgiç, Robert Pardo, Kevin Davey, Ernest P. Chan for their inspiring publishments.
DISCLAIMER
That's just a script, nothing more. I hope it helps everyone. Do not forget to manage your risk. And trade as safely as possible. Best of luck!
© dg_factor
USDT.D + USDT.C ALL TIMEFRAMESThis indicator combines the dominance of USDT (USDT.D) and USDC (USDC.D) to track total stablecoin market share across all timeframes. It displays the combined dominance as candlesticks, providing a clearer view of market liquidity shifts and investor sentiment.
📌 How to Use:
Green candles indicate rising stablecoin dominance (potential risk-off sentiment).
Red candles indicate declining stablecoin dominance (potential risk-on sentiment).
Works on all timeframes, from intraday scalping to macro trend analysis.
This tool is essential for traders looking to analyze stablecoin liquidity flow, identify market turning points, and refine trading strategies based on stablecoin dominance behavior. 🚀
Optimized Dynamic SupertrendDetailed Explanation of the Optimized Dynamic Supertrend Script
This Supertrend script is designed to dynamically adapt to different market conditions using ATR expansion, volume confirmation, and trend filtering. Below is a step-by-step breakdown of how it works and its functions.
1 ATR-Based Supertrend Calculation
📌 Key Purpose:
The script calculates an adaptive ATR-based Supertrend line, which acts as a dynamic support or resistance level for trend direction.
📌 How it Works:
ATR (Average True Range) is used to measure market volatility.
A dynamic ATR multiplier is applied based on price standard deviation (instead of a fixed value).
The Supertrend is calculated as:
Upper Band: SMA(close, ATR length) + (ATR Multiplier * ATR Value)
Lower Band: SMA(close, ATR length) - (ATR Multiplier * ATR Value)
The Supertrend flips when price crosses and holds beyond the Supertrend line.
🔹 Dynamic Adjustment:
Instead of using a fixed ATR multiplier, the script adjusts it using:
pinescript
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dynamicFactor = ta.stdev(close, atrLength) / ta.sma(close, atrLength)
atrMultiplier = input(1.5, title="Base ATR Multiplier") * dynamicFactor
High volatility → Wider Supertrend bands (to avoid false signals).
Low volatility → Tighter Supertrend bands (for faster detection).
2 Trend Detection Logic
📌 Key Purpose:
Determines if the market is in a bullish or bearish trend based on price action.
Uses volume sensitivity and ATR expansion to reduce false signals.
📌 How it Works:
pinescript
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var float supertrend = na
supertrend := close > nz(supertrend , lowerBand) ? lowerBand : upperBand
The Supertrend value updates dynamically.
If price is above the Supertrend line, the trend is bullish (green).
If price is below the Supertrend line, the trend is bearish (red).
3 Volume Sensitivity Confirmation
📌 Key Purpose:
Avoid false trend flips by confirming with volume (approximated using a CVD proxy).
📌 How it Works:
pinescript
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priceChange = close - close
volumeWeightedTrend = priceChange * volume // Approximate CVD Behavior
trendConfirmed = volumeWeightedTrend > 0 ? close > supertrend : close < supertrend
Positive price change + High volume → Confirms bullish momentum.
Negative price change + High volume → Confirms bearish momentum.
If there’s low volume, the trend change is ignored to avoid false breakouts.
4 Noise Reduction (Final Trend Confirmation)
📌 Key Purpose:
Filter out weak or choppy price movements using ATR expansion.
📌 How it Works:
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trendUp = trendConfirmed and ta.atr(atrLength) > ta.atr(atrLength)
trendDown = not trendUp
Trend only flips when confirmed by volume + ATR expansion.
If ATR is not expanding, the script ignores weak price movements.
This ensures Supertrend signals align with strong market moves.
5 Can This Be Used on All Timeframes?
✅ YES! This Supertrend is adaptive, meaning it adjusts dynamically based on:
Volatility: Uses ATR expansion to adjust for different market conditions.
Timeframe Sensitivity: Works on any timeframe (1M, 5M, 15M, 1H, 4H, 1D, 1W).
Market Structure: Confirms trend flips using volume & price movement strength.
🚀 Best Timeframes for Trading:
For Scalping (1M - 15M) → Quick execution, best with order flow confirmation.
For Swing Trading (1H - 4H - 1D) → Stronger trend signals, reduced noise.
For High Timeframes (3D - 1W) → Identifies major market shifts.
🔥 Advantages & Disadvantages in Your Trading Setup
✅ Advantages:
✔ Fully Dynamic & Adaptive → Adjusts to different timeframes & volatility.
✔ Reduces False Signals → Uses ATR expansion & volume confirmation.
✔ Precise Trend Reversals → Labels LONG & SHORT entries clearly.
✔ Works on Any Market → Crypto, Forex, Stocks, Commodities.
✔ No Extra Indicators → Pure Supertrend-based (fits your setup).
❌ Disadvantages:
⚠ Lagging Indicator → ATR & volume confirmation add slight delay.
⚠ Needs High Volume to Confirm → Weak volume → no trend flip.
⚠ Choppy Market = Late Entries → Sideways movement can cause delays.
🚀 Final Thoughts:
It’s fully dynamic & adaptive (unlike traditional static Supertrends).
No extra indicators → Uses only Supertrend logic
Refines entry points using volume & ATR confirmation (removes noise).
This ensures you get high-probability trend signals while filtering out weak breakouts! 🎯
BullDozz MA-CandlesticksBullDozz MA-Candlesticks 🏗️📊
The BullDozz MA-Candlesticks indicator transforms traditional candlesticks by replacing their Open, High, Low, and Close values with various types of Moving Averages (MAs). This helps traders visualize market trends with smoother price action, reducing noise and enhancing decision-making.
🔹 Features:
✅ Choose from multiple MA types: SMA, EMA, WMA, DEMA, TEMA, LSMA
✅ Customizable MA period for flexibility
✅ Candlestick colors based on trend: Green for bullish, Red for bearish
✅ Works on any market and timeframe
This indicator is perfect for traders who want a clearer perspective on price movement using moving average-based candlesticks. 🚀 Try it now and refine your market analysis! 📈🔥
3x Supertrend (for Vietnamese stock market and vn30f1m)The 4Vietnamese 3x Supertrend Strategy is an advanced trend-following trading system developed in Pine Script™ and designed for publication on TradingView as an open-source strategy under the Mozilla Public License 2.0. This strategy leverages three Supertrend indicators with different ATR lengths and multipliers to identify optimal trade entries and exits while dynamically managing risk.
Key Features:
Option to build and hold long term positions with entry stop order. Try this to avoid market complex movement and retain long term investment style's benefits.
Advanced Entry & Exit Optimization: Includes configurable stop-loss mechanisms, pyramiding, and exit conditions tailored for different market scenarios.
Dynamic Risk Management: Implements features like selective stop-loss activation, trade window settings, and closing conditions based on trend reversals and loss management.
This strategy is particularly suited for traders seeking a systematic and rule-based approach to trend trading. By making it open-source, we aim to provide transparency, encourage community collaboration, and help traders refine and optimize their strategies for better performance.
License:
This script is released under the Mozilla Public License 2.0, allowing modifications and redistribution while maintaining open-source integrity.
Happy trading!
Anti-Martingale Position Sizing 6500$ Trailing DrawdownReady reckoner to let you know how much to risk as a function of your drawdown when trading NQ.
Combined SmartComment & Dynamic S/R LevelsDescription:
The Combined SmartComment & Dynamic S/R Levels script is designed to provide valuable insights for traders using TradingView. It integrates dynamic support and resistance levels with a powerful Intelligent Comment system to enhance decision-making. The Intelligent Comment feature generates market commentary based on key technical indicators, delivering real-time actionable feedback that helps optimize trading strategies.
Intelligent Comment Feature:
The Intelligent Comment function continuously analyzes market conditions and offers relevant insights based on combinations of various technical indicators such as RSI, ATR, MACD, WMA, and others. These comments help traders identify potential price movements, highlighting opportunities to buy, sell, or wait.
Examples of the insights provided by the system include:
RSI in overbought/oversold and price near resistance/support: Indicates potential price reversal points.
Price above VAH and volume increasing: Suggests a strengthening uptrend.
Price near dynamic support/resistance: Alerts when price approaches critical support or resistance zones.
MACD crossovers and RSI movements: Provide signals for potential trend shifts or continuations.
Indicators Used:
RSI (Relative Strength Index)
ATR (Average True Range)
MACD (Moving Average Convergence Divergence)
WMA (Weighted Moving Average)
POC (Point of Control)
Bollinger Bands
SuperSignal
Volume
EMA (Exponential Moving Average)
Dynamic Support/Resistance Levels
How It Works:
The script performs real-time market analysis, assessing multiple technical indicators to generate Intelligent Comments. These comments provide traders with timely guidance on potential market movements, assisting with decision-making in a dynamic market environment. The script also integrates dynamic support and resistance levels to further enhance trading accuracy.
Support and Resistance all in one The Support and Resistance Indicator (v4) is designed to identify and track key price levels in financial markets. Here's how it works:
Core Functionality
Level Detection
Uses pivot points to identify significant price levels
Looks for swing highs (resistance) and swing lows (support)
Requires price action to pivot over a specified period (default 10 bars)
Dynamic Level Management
Maintains separate arrays for support and resistance levels
Limits maximum displayed levels (default 10) to prevent chart clutter
Removes oldest levels when maximum is reached
Ensures new levels are sufficiently distant from existing ones (minimum 1% separation)
Touch Detection System
Monitors price interaction with established levels
Counts when price comes within 0.1% of any level
Updates touch count and strength classification
Categories: "New" (1 touch), "Moderate" (2 touches), "Strong" (3+ touches)
Visual Representation
Draws horizontal lines at each level
Updates line width based on strength (thicker for stronger levels)
Shows labels with price and strength information
Color coding: Red (new/moderate levels), Green (strong levels)
Displays triangles (▼▲) at pivot points
Trading Applications
Support/Resistance Trading
Strong levels (3+ touches) suggest reliable trading zones
More touches indicate higher probability reversal points
Use for stop loss and target placement
Breakout Trading
Monitor breaks of strong levels
Higher touch count suggests more significant breakouts
Watch for false breakouts at weaker levels
Risk Management
Place stops beyond strong levels
Use level strength to adjust position size
Consider multiple timeframe analysis
Best Practices
Use with other indicators for confirmation
Consider market context and trend
Monitor level strength development
Don't rely solely on touch count
Watch for price reaction at levels
Customization Options
Adjust pivot length for different timeframes
Modify minimum distance between levels
Change required touches for "Strong" classification
Toggle strength labels display
Choose line style (Solid/Dashed/Dotted)
This indicator helps identify key price levels where market participants have shown interest, making it valuable for trade planning and risk management
BullDozz Fibo ZigZagFibo ZigZag - Advanced Fibonacci Retracement Tool 🔥
📌 Overview
The Fibo ZigZag indicator is a powerful tool for trend structure analysis using the ZigZag pattern and Fibonacci retracement levels. It automatically identifies swing highs & lows, draws ZigZag lines, and overlays Fibonacci levels with price labels at the right end for better readability.
This indicator is designed for traders who use price action, trend reversal strategies, and support/resistance analysis.
🛠 Features
✅ Automatic ZigZag detection with customizable depth, deviation, and backstep
✅ Fibonacci retracement levels (0%, 23.6%, 38.2%, 50%, 61.8%, 100%, 161.8%, 261.8%, 423.6%)
✅ Price labels at Fibonacci levels (placed at the right end of the levels)
✅ Alerts for new swing highs & lows
✅ Customizable line colors, text colors, and label sizes
✅ Lightweight and optimized for fast performance
📊 How It Works
1️⃣ The script detects ZigZag structure points based on price swings
2️⃣ It connects recent highs & lows with a ZigZag line
3️⃣ Fibonacci retracement levels are calculated and drawn between the last two significant swing points
4️⃣ Each Fibo level is labeled with its percentage & exact price, placed at the right end for clarity
5️⃣ Alerts trigger automatically when a new swing high or low is detected
⚙ Customization Options
🔹 ZigZag Settings: Adjust Depth, Deviation, BackStep, and Leg length
🔹 Fibonacci Levels: Modify line colors, label text colors, and visibility
🔹 Alerts: Enable/disable trend change alerts
📈 Best Use Cases
🚀 Identifying Trend Reversals – Detect key turning points using Fibonacci levels
📉 Support & Resistance Trading – Use retracement levels as entry/exit points
📊 Swing Trading & Scalping – Combine ZigZag with price action for effective strategies
🔔 Alert-Based Trading – Get notified when new swing highs/lows form
🚀 How to Use
📌 Add the indicator to your chart
📌 Adjust the settings to match your trading strategy
📌 Use the Fibonacci levels & ZigZag lines to analyze trend direction & key price zones
📌 Wait for alerts or manually enter trades based on price reaction to Fibo levels
📢 Final Thoughts
The Fibo ZigZag is an essential tool for traders who rely on price action, trend reversals, and Fibonacci levels. Whether you're a beginner or a pro, this indicator helps you spot high-probability trading opportunities with ease.
⚡ Try it now & enhance your trading strategy! 🚀
💬 Let us know your feedback & suggestions in the comments! Happy trading! 📊🔥
Kalman FilterKalman Filter Indicator Description
This indicator applies a Kalman Filter to smooth the selected price series (default is the close) and help reveal the underlying trend by filtering out market noise. The filter is based on a recursive algorithm consisting of two main steps:
Prediction Step:
The filter predicts the next state using the last estimated value and increases the uncertainty (error covariance) by adding the process noise variance (Q). This step assumes that the price follows a random walk, where the last known estimate is the best guess for the next value.
Update Step:
The filter computes the Kalman Gain, which determines the weight given to the new measurement (price) versus the prediction. It then updates the state estimate by combining the prediction with the measurement error (using the measurement noise variance, R). The error covariance is also updated accordingly.
Key Features:
Customizable Input:
Source: Choose any price series (default is the closing price) for filtering.
Measurement Noise Variance (R): Controls the sensitivity to new measurements (default is 0.1). A higher R makes the filter less responsive.
Process Noise Variance (Q): Controls the assumed level of inherent price variability (default is 0.01). A higher Q allows the filter to adapt more quickly to changes.
Visual Trend Indication:
The filtered trend line is plotted directly on the chart:
When enabled, the line is colored green when trending upward and red when trending downward.
If color option is disabled, the line appears in blue.
This indicator is ideal for traders looking to smooth price data and identify trends more clearly by reducing the impact of short-term volatility.
75th-25th Percentile Momentum | QuantumResearchIntroducing QuantumResearch’s 75th-25th Percentile Momentum Indicator
The 75th-25th Percentile Momentum indicator is a cutting-edge tool that combines percentile rank analysis with ATR-based deviation to detect significant bullish and bearish momentum in the market. By analyzing price movements relative to the 75th and 25th percentiles of recent data, the indicator provides traders with clear and dynamic signals for long and short opportunities.
How It Works
Percentile Analysis:
The 75th and 25th percentiles are calculated over a user-defined lookback period, representing the upper and lower thresholds for price action.
ATR-Based Adjustment:
ATR (Average True Range) is used to account for market volatility, dynamically adjusting the thresholds with user-defined multipliers.
Signal Generation:
Long Signal: Triggered when the price exceeds the 75th percentile plus the ATR-based adjustment (default multiplier: 1.3).
Short Signal: Triggered when the price falls below the 25th percentile minus the ATR-based adjustment (default multiplier: 1.3).
Visual Representation
The indicator offers a clear and customizable visual interface:
Green Bars: Indicate a bullish trend, signaling a potential long opportunity when the price surpasses the adjusted 75th percentile.
Red Bars: Indicate a bearish trend, signaling a potential short opportunity when the price drops below the adjusted 25th percentile.
Additional visuals include:
A dynamically colored 54-period EMA line, representing trend direction:
Green Line: Indicates a bullish trend.
Red Line: Indicates a bearish trend.
A filled area between the EMA line and the midpoint (HL2), offering enhanced trend visibility.
Customization & Parameters
The 75th-25th Percentile Momentum indicator includes several adjustable parameters to suit different trading styles:
Source: Defines the input price (default: close).
Percentile Length: Default set to 25, determines the lookback period for percentile calculations.
ATR Length: Default set to 14, adjusts the sensitivity of volatility measurement.
Multiplier for 75th Percentile: Default set to 1.3, adjusts the threshold for long signals.
Multiplier for 25th Percentile: Default set to 1.3, adjusts the threshold for short signals.
Color Modes: Choose from eight visual themes to personalize the appearance of trend signals.
Trading Applications
This indicator is versatile and can be applied across various markets and strategies:
Momentum Trading: Highlights when price action demonstrates strong upward or downward momentum relative to recent percentiles.
Volatility-Adaptive Strategies: By incorporating ATR-based thresholds, the indicator adjusts dynamically to market conditions.
Reversal Detection: Identifies potential turning points when the price moves significantly beyond the 75th or 25th percentiles.
Final Note
QuantumResearch’s 75th-25th Percentile Momentum indicator is a powerful tool for traders looking to capture momentum and trend opportunities in the market.
Its combination of percentile analysis, volatility adjustment, and visual clarity offers a robust framework for making informed trading decisions. As with all indicators, it is recommended to backtest thoroughly and integrate this tool into a comprehensive trading strategy.
LRLR [TakingProphets]LRLR (Low Resistance Liquidity Run) Indicator
This indicator identifies potential liquidity runs in areas of low resistance, based on ICT (Inner Circle Trader) concepts. It specifically looks for a series of unmitigated swing highs in a downtrend that form without any bearish fair value gaps (FVGs) between them.
What is an LRLR?
- A Low Resistance Liquidity Run occurs when price creates a series of lower highs without any bearish fair value gaps in between
- The absence of bearish FVGs indicates there is no significant resistance in the area
- These formations often become targets for smart money to collect liquidity above the swing highs
How to Use the Indicator:
1. The indicator will draw a diagonal line connecting a series of qualifying swing highs
2. A small "LRLR" label appears to mark the pattern
3. These areas often become targets for future price moves, as they represent zones of accumulated liquidity with minimal resistance
Key Points:
- Minimum of 4 consecutive lower swing highs
- No bearish fair value gaps can exist between these swing highs
- The diagonal line helps visualize the liquidity run formation
- Can be used for trade planning and identifying potential reversal zones
Settings:
- Show Labels: Toggle the "LRLR" label visibility
- LRLR Line Color: Customize the appearance of the diagonal line
Best Practices:
1. Use in conjunction with other ICT concepts and market structure analysis
2. Pay attention to how price reacts when returning to these levels
3. Consider these areas as potential targets for smart money liquidity grabs
4. Most effective when used on higher timeframes (4H and above)
Note: This is an educational tool and should be used as part of a complete trading strategy, not in isolation.
Fair Value Gap (FVG) by AlgoMaxxFair Value Gap (FVG) by AlgoMaxx
Advanced Fair Value Gap (FVG) detector with dynamic support/resistance lines. This professional-grade tool helps traders identify and track important market inefficiencies through Fair Value Gaps.
Features:
• Auto-detection of bullish and bearish FVGs
• Dynamic dotted extension lines for latest FVGs
• Smart gap filtering system
• Color-coded visualization
• Customizable parameters
• Clean, optimized code
Key Functions:
• Detects imbalance zones between candlesticks
• Marks FVGs with color-coded boxes
• Extends dotted lines for active reference levels
• Automatically updates with new gap formations
• Tracks gap fills in real-time
Inputs:
• Lookback Period: Historical gaps to display
• Minimum Gap Size %: Filter for gap significance
• Bullish/Bearish Colors: Visual customization
• Show Filled Gaps: Toggle filled gap visibility
Practical Applications:
1. Support/Resistance Levels
2. Mean Reversion Trading
3. Trend Continuation Setups
4. Market Structure Analysis
5. Price Action Trading
Usage Tips:
• Higher timeframes (1H+) provide more reliable signals
• Multiple FVGs in one zone indicate stronger levels
• Use in conjunction with other technical tools
• Monitor price reactions at FVG levels
• Consider gaps as zones rather than exact prices
Note: This is a premium-grade indicator designed for serious traders. Works best on higher timeframes where price inefficiencies are more significant.
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By Algomaxx
Version: 1.0
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Disclaimer:
This indicator is for informational purposes only. Trade at your own risk and always use proper risk management.
#FVG #technical #trading #algomaxx #premium
Twitter Model ICT [TradingFinder] MMXM ERL D + FVG + M15 MSS/SMT🔵 Introduction
The Twitter Model ICT is a trading approach based on ICT (Inner Circle Trader) models, focusing on price movement between external and internal liquidity in lower timeframes. This model integrates key concepts such as Market Structure Shift (MSS), Smart Money Technique (SMT) divergence, and CISD level break to identify precise entry points in the market.
The primary goal of this model is to determine key liquidity levels, such as the previous day’s high and low (PDH/PDL) and align them with the Fair Value Gap (FVG) in the 1-hour timeframe. The overall strategy involves framing trades around the 1H FVG and using the M15 Market Structure Shift (MSS) for entry confirmation.
The Twitter Model ICT is designed to utilize external liquidity levels, such as PDH/PDL, as key entry zones. The model identifies FVG in the 1-hour timeframe, which acts as a magnet for price movement. Additionally, traders confirm entries using M15 Market Structure Shift (MSS) and SMT divergence.
Bullish Twitter Model :
In a bullish setup, the price sweeps the previous day’s low (PDL), and after confirming reversal signals, buys are executed in internal liquidity zones. Conversely, in a bearish setup, the price sweeps the previous day’s high (PDH), and after confirming weakness signals, sells are executed.
Bearish Twitter Model :
In short setups, entries are only executed above the Midnight Open, while in long setups, entries are taken below the Midnight Open. Adhering to these principles allows traders to define precise entry and exit points and analyze price movement with greater accuracy based on liquidity and market structure.
🔵 How to Use
The Twitter Model ICT is a liquidity-based trading strategy that analyzes price movements relative to the previous day’s high and low (PDH/PDL) and Fair Value Gap (FVG). This model is applicable in both bullish and bearish directions and utilizes the 1-hour (1H) and 15-minute (M15) timeframes for entry confirmation.
The price first sweeps an external liquidity level (PDH or PDL) and then provides an entry opportunity based on Market Structure Shift (MSS) and SMT divergence. Additionally, the entry should be positioned relative to the Midnight Open, meaning long entries should occur below the Midnight Open and short entries above it.
🟣 Bullish Twitter Model
In a bullish setup, the price first sweeps the previous day’s low (PDL) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bullish Fair Value Gap (FVG) forms, which serves as the price target.
To confirm the entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should be observed, signaling a trend reversal to the upside. Additionally, SMT divergence with correlated assets can indicate weakness in selling pressure.
Under these conditions, a long position is taken below the Midnight Open, with a stop-loss placed at the lowest point of the recent bearish move. The price target for this trade is the FVG in the 1-hour timeframe.
🟣 Bearish Twitter Model
In a bearish setup, the price first sweeps the previous day’s high (PDH) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bearish Fair Value Gap (FVG) is identified, serving as the trade target.
To confirm entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should form, signaling a trend shift to the downside. If an SMT divergence is present, it can provide additional confirmation for the trade.
Once these conditions are met, a short position is taken above the Midnight Open, with a stop-loss placed at the highest level of the recent bullish move. The trade's price target is the FVG in the 1-hour timeframe.
🔵 Settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
Daily Position : Determines whether only the first signal of the day is considered or if signals are evaluated throughout the entire day.
Session : Specifies in which trading sessions the indicator will be active.
Second Symbol : This setting allows you to select another asset for comparison with the primary asset. By default, "XAUUSD" (Gold) is set as the second symbol, but you can change it to any currency pair, stock, or cryptocurrency. For example, you can choose currency pairs like EUR/USD or GBP/USD to identify divergences between these two assets.
Divergence Fractal Periods : This parameter defines the number of past candles to consider when identifying divergences. The default value is 2, but you can change it to suit your preferences. This setting allows you to detect divergences more accurately by selecting a greater number of candles.
The indicator allows displaying sessions based on various time zones. The user can select one of the following options :
UTC (Coordinated Universal Time)
Local Time of the Session
User’s Local Time
Show Open Price : Displays the New York market opening price.
Show PDH / PDL : Displays the previous day’s high and low to identify potential entry points.
Show SMT Divergence : Displays lines and labels for bullish ("+SMT") and bearish ("-SMT") divergences.
🔵 Conclusion
The Twitter Model ICT is an effective approach for analyzing and executing trades in financial markets, utilizing a combination of liquidity principles, market structure, and SMT confirmations to identify optimal entry and exit points.
By analyzing the previous day’s high and low (PDH/PDL), Fair Value Gaps (FVG), and Market Structure Shift (MSS) in the 1H and M15 timeframes, traders can pinpoint liquidity-driven trade opportunities. Additionally, considering the Midnight Open level helps traders avoid random entries and ensures better trade placement.
By applying this model, traders can interpret market movements based on liquidity flow and structural changes, allowing them to fine-tune their trading decisions with higher precision. Ultimately, the Twitter Model ICT provides a structured and logical approach for traders who seek to trade based on liquidity behavior and trend shifts in the market.
E9 MM Nuke signalScript identifies wickless candles on a specified higher timeframe and plots them on a lower timeframe (If desired), such as 15 minutes. It includes options to adjust the margin for error (e.g. 5 tick wick), higher timeframe, and toggle the volume filter with period adjustment.
Wickless candles signal strong market sentiment shifts, indicating areas of significant buying or selling pressure. These areas can become key levels of support or resistance, making them crucial to monitor for potential price revisits.
Why Price Revisits Wickless Areas
Manipulators often create artificial wickless candles to deceive traders. However, genuine market movements can also produce wickless candles, indicating a strong consensus among market participants. In either case, the price is likely to revisit these areas as traders and investors react to the perceived market sentiment shift.
Key Features:
Margin Input:
Description: Allows users to specify the margin in 0.01 tick increments to account for small wicks due to spread issues.
Example: A margin of 0.05 ticks means the script will consider candles wickless if the high is within 0.05 ticks of the open and the low is within 0.05 ticks of the open.
Volume Filter:
Description: Users can enable or disable a volume filter to consider only candles with a volume greater than the average volume over a specified period.
Default: Enabled by default.
Volume Period Input: Users can specify the period for calculating the average volume (e.g., 9 periods).
Higher Timeframe Input:
Description: Allows users to select the higher timeframe on which to identify wickless candles.
Options: H4 ("240"), Daily ("D"), Weekly ("W"), Monthly ("M").
Plotting:
Bearish Wickless Candles: Plotted with a red circle and a "🐻" emoji above the bar.
Bullish Wickless Candles: Plotted with a green circle and a "🐂" emoji below the bar.
