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. 🚀
Educational
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:
pinescript
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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.
Moving Average Hamming-RKMoving Average Hamming
Description:
A Moving Average using a Hamming window is a technique used in technical analysis to smooth price data. The Hamming window applies weighted smoothing, reducing sharp variations and edge effects in the data. This helps in identifying trends more effectively while minimizing noise.
It can be used in combination with other technical indicators for better market analysis.
Technical Use:
The Hamming Moving Average reduces high-frequency noise, making trends clearer.
It applies different weights to data points, giving more importance to the center of the window while reducing the impact of abrupt changes.
This method is particularly useful in trend-following strategies as it minimizes false breakouts.
It can also be integrated into algorithmic trading systems for improved price fluctuation filtering.
When to Take a Position:
Buy Signal: When the price crosses above the Hamming Moving Average, indicating a potential uptrend.
Sell Signal: When the price crosses below the Hamming Moving Average, signaling a possible downtrend.
Confirmation: Combine with other indicators like RSI or MACD to confirm the trend before entering a trade.
Avoid Choppy Markets: The indicator works best in trending markets; avoid using it in sideways or ranging conditions.
This approach helps traders refine their analysis, making informed decisions while reducing market noise.
Classic Nacked Z-Score ArbitrageThe “Classic Naked Z-Score Arbitrage” strategy employs a statistical arbitrage model based on the Z-score of the price spread between two assets. This strategy follows the premise of pair trading, where two correlated assets, typically from the same market sector, are traded against each other to profit from relative price movements (Gatev, Goetzmann, & Rouwenhorst, 2006). The approach involves calculating the Z-score of the price spread between two assets to determine market inefficiencies and capitalize on short-term mispricing.
Methodology
Price Spread Calculation:
The strategy calculates the spread between the two selected assets (Asset A and Asset B), typically from different sectors or asset classes, on a daily timeframe.
Statistical Basis – Z-Score:
The Z-score is used as a measure of how far the current price spread deviates from its historical mean, using the standard deviation for normalization.
Trading Logic:
• Long Position:
A long position is initiated when the Z-score exceeds the predefined threshold (e.g., 2.0), indicating that Asset A is undervalued relative to Asset B. This signals an arbitrage opportunity where the trader buys Asset B and sells Asset A.
• Short Position:
A short position is entered when the Z-score falls below the negative threshold, indicating that Asset A is overvalued relative to Asset B. The strategy involves selling Asset B and buying Asset A.
Theoretical Foundation
This strategy is rooted in mean reversion theory, which posits that asset prices tend to return to their long-term average after temporary deviations. This form of arbitrage is widely used in statistical arbitrage and pair trading techniques, where investors seek to exploit short-term price inefficiencies between two assets that historically maintain a stable price relationship (Avery & Sibley, 2020).
Further, the Z-score is an effective tool for identifying significant deviations from the mean, which can be seen as a signal for the potential reversion of the price spread (Braucher, 2015). By capturing these inefficiencies, traders aim to profit from convergence or divergence between correlated assets.
Practical Application
The strategy aligns with the Financial Algorithmic Trading and Market Liquidity analysis, emphasizing the importance of statistical models and efficient execution (Harris, 2024). By utilizing a simple yet effective risk-reward mechanism based on the Z-score, the strategy contributes to the growing body of research on market liquidity, asset correlation, and algorithmic trading.
The integration of transaction costs and slippage ensures that the strategy accounts for practical trading limitations, helping to refine execution in real market conditions. These factors are vital in modern quantitative finance, where liquidity and execution risk can erode profits (Harris, 2024).
References
• Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 1317-1343.
• Avery, C., & Sibley, D. (2020). Statistical Arbitrage: The Evolution and Practices of Quantitative Trading. Journal of Quantitative Finance, 18(5), 501-523.
• Braucher, J. (2015). Understanding the Z-Score in Trading. Journal of Financial Markets, 12(4), 225-239.
• Harris, L. (2024). Financial Algorithmic Trading and Market Liquidity: A Comprehensive Analysis. Journal of Financial Engineering, 7(1), 18-34.
