Modular Range-Trading Strategy (V9.2)# 模块化震荡行情策略 (V9.2)
# Modular Range-Trading Strategy (V9.2)
## 策略简介 | Strategy Overview
该策略基于布林带 (Bollinger Bands)、RSI、MACD、ADX 等经典指标的组合，通过多逻辑模块化结构识别震荡区间的价格反转机会，支持多空双向操作，并在相同逻辑下允许智能加仓，适用于震荡市场的回测和研究。
This strategy combines classic indicators such as Bollinger Bands, RSI, MACD, and ADX to identify price reversal opportunities within ranging markets. It features a modular multi-logic structure, allowing both long and short trades with intelligent pyramiding under the same logic. It is designed for backtesting and research in range-bound conditions.
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## 功能特点 | Key Features
- **多逻辑结构**：支持多套震荡逻辑（动能确认均值回归、布林带极限反转等）。
- **加仓与仓位互斥**：同逻辑下可智能加仓，不同逻辑间自动互斥，避免冲突。
- **回测可调时间范围**：可自定义回测起止时间，精准评估策略表现。
- **指标可视化**：布林带、RSI、MACD 及动态 ATR 止损线实时绘图。
- **K线收盘确认信号**：通过 `barstate.isconfirmed` 控制信号，避免未收盘的虚假信号。
- **Multi-logic structure**: Supports multiple range-trading logics (e.g., momentum-based mean reversion, Bollinger Band reversals).
- **Pyramiding with mutual exclusion**: Allows intelligent pyramiding within the same logic while preventing conflicts between different logics.
- **Adjustable backtesting range**: Customizable start and end dates for accurate performance evaluation.
- **Visual indicators**: Real-time plotting of Bollinger Bands, RSI, MACD, and dynamic ATR stop lines.
- **Close-bar confirmation**: Uses `barstate.isconfirmed` to avoid false signals before bar close.
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## 使用说明 | Usage
1. 将该脚本添加到 TradingView 图表。
2. 在参数中设置回测时间段和指标参数。
3. 仅用于学习与策略研究，请勿直接用于实盘交易。
1. Add this script to your TradingView chart.
2. Configure backtesting dates and indicator parameters as needed.
3. For educational and research purposes only. **Not for live trading.**
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## ⚠️ 免责声明 | Disclaimer
本策略仅供学习和研究使用，不构成任何形式的投资建议。
作者不参与任何实盘交易、资金管理或收益分成，也不保证策略盈利能力。
严禁将本脚本用于任何非法集资、私募募资或与虚拟货币相关的金融违法活动。
使用本策略即表示您自行承担所有风险与法律责任。
This strategy is for educational and research purposes only and does not constitute investment advice.
The author does not participate in live trading, asset management, or profit sharing, nor guarantee profitability.
The use of this script in illegal fundraising, private placements, or cryptocurrency-related financial activities is strictly prohibited.
By using this strategy, you accept all risks and legal responsibilities.
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Cerca negli script per "香港交易所技术指标分析（RSI、MACD、布林带）"
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
Bayesian TrendEnglish Description (primary)
1. Overview
This script implements a Naive Bayesian classifier to estimate the probability of an upcoming bullish, bearish, or neutral move. It combines multiple indicators—RSI, MACD histogram, EMA price difference in ATR units, ATR level vs. its average, and Volume vs. its average—to calculate likelihoods for each market direction. Each indicator is “binned” (categorized into discrete zones) and assigned conditional probabilities for bullish/bearish/neutral scenarios. The script then normalizes these probabilities and paints bars in green if bullish is most likely, red if bearish is most likely, or blue if neutral is most likely. A small table is also displayed in the top-right corner of the chart, showing real-time probabilities.
2. How it works
Indicator Calculations: The script calculates RSI, MACD (line and histogram), EMA, ATR, and Volume metrics.
Binning: Each metric is converted into a discrete category (e.g., low, medium, high). For example, RSI < 30 is binned as “low,” while RSI > 70 is binned as “high.”
Conditional Probabilities: User-defined tables specify the conditional probabilities of each bin under three hypotheses (Up, Down, Neutral).
Naive Bayesian Formula: The script multiplies the relevant conditional probabilities, normalizes them, and derives the final probabilities (Up, Down, or Neutral).
Visualization:
Bar Colors: Bars are green when the Up probability exceeds 50%, red for Down, and blue otherwise.
Table: Displays numeric probabilities of Up, Down, and Neutral in percentage terms.
3. How to use it
Add the script to your chart.
Observe the colored bars:
Green suggests a higher probability for bullish movement.
Red suggests a higher probability for bearish movement.
Blue indicates a higher probability of sideways or uncertain conditions.
Check the table in the top-right corner to see exact probabilities (Up/Down/Neutral).
Use the input settings to adjust thresholds (RSI, MACD, Volume, etc.), define alert conditions (e.g., when Up probability crosses 50%), and decide whether to trigger alerts on bar close or in real-time.
4. Originality and usefulness
Originality: This script uniquely applies a Naive Bayesian approach to a blend of classic and volume-based indicators. It demonstrates how different indicator “zones” can be combined to produce probabilistic insights.
Usefulness: Traders can interpret the probability breakdown to gauge the script’s bias. Unlike single indicators, this approach synthesizes several signals, potentially offering a more holistic perspective on market conditions.
5. Limitations
The conditional probabilities are manually assigned and may not reflect actual market behavior across all instruments or timeframes.
Results depend on the user’s choice of thresholds and indicator settings.
Like any indicator, past performance does not guarantee future results. Always confirm signals with additional analysis.
6. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice. Trading involves significant risk, and you should make decisions based on your own analysis. Neither the script’s author nor TradingView is liable for any financial losses.
Русское описание (Russian translation, optional)
Этот индикатор реализует наивный Байесовский классификатор для оценки вероятности предстоящего роста (Up), падения (Down) или бокового движения (Neutral). Он комбинирует несколько индикаторов—RSI, гистограмму MACD, разницу цены и EMA в единицах ATR, уровень ATR относительно своего среднего значения и объём относительно своего среднего—чтобы вычислить вероятности для каждого направления рынка. Каждый индикатор делится на «зоны» (low, mid, high), которым приписаны условные вероятности для бычьего/медвежьего/нейтрального исхода. Скрипт нормирует эти вероятности и раскрашивает бары в зелёный, красный или синий цвет в зависимости от того, какая вероятность выше. Также в правом верхнем углу отображается таблица с текущими значениями вероятностей.
Confluence StrategyOverview of Confluence Strategy
The Confluence Strategy in trading refers to the combination of multiple technical indicators, support/resistance levels, and chart patterns to identify high-probability trading opportunities. The idea is that when several indicators agree on a price movement, the likelihood of that movement being successful increases.
Key Components
Technical Indicators:
Moving Averages (MA): Commonly used to determine the trend direction. Look for crossovers (e.g., the 50-day MA crossing above the 200-day MA).
Relative Strength Index (RSI): Helps identify overbought or oversold conditions. A reading above 70 may indicate overbought conditions, while below 30 suggests oversold.
MACD (Moving Average Convergence Divergence): Useful for spotting changes in momentum. Look for MACD crossovers and divergence from price.
Support and Resistance Levels:
Identify key levels where price has historically reversed. These can be drawn from previous highs/lows, Fibonacci retracement levels, or psychological price levels.
Chart Patterns:
Patterns like head and shoulders, double tops/bottoms, or flags can indicate potential reversals or continuations in price.
Strategy Implementation
Set Up Your Chart:
Add the desired indicators (e.g., MA, RSI, MACD) to your TradingView chart.
Mark significant support and resistance levels.
Identify Confluence Points:
Look for situations where multiple indicators align. For instance, if the price is near a support level, the RSI is below 30, and the MACD shows bullish divergence, this may signal a buying opportunity.
Entry and Exit Points:
Entry: Place a trade when your confluence conditions are met. Use limit orders for better prices.
Exit: Set profit targets based on resistance levels or use trailing stops. Consider the risk-reward ratio to ensure your trades are favorable.
Risk Management:
Always implement stop-loss orders to protect against unexpected market moves. Position size should reflect your risk tolerance.
Example of a Confluence Trade
Setup:
Price approaches a strong support level.
RSI shows oversold conditions (below 30).
The 50-day MA is about to cross above the 200-day MA (bullish crossover).
Action:
Enter a long position as the conditions align.
Set a stop loss just below the support level and a take profit at the next resistance level.
Conclusion
The Confluence Strategy can significantly enhance trading accuracy by ensuring that multiple indicators support a trade decision. Traders on TradingView can customize their indicators and charts to fit their personal trading styles, making it a flexible approach to technical analysis.
Swiss Knife [MERT]Introduction
The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format.
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Key Features
Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes.
Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection.
Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score.
Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart.
Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots.
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Explanation of Each Indicator
Moving Average Convergence Divergence (MACD)
- Purpose : Measures the relationship between two moving averages of price.
- Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum.
Awesome Oscillator (AO)
- Purpose : Gauges market momentum by comparing recent market movements to historic ones.
- Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum.
Parabolic SAR (SAR)
- Purpose : Identifies potential reversal points in price direction.
- Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend.
SuperTrend
- Purpose : Determines the prevailing market trend.
- Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line.
Detrended Price Oscillator (DPO)
- Purpose : Removes trend from price to identify cycles.
- Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below.
Relative Strength Index (RSI)
- Purpose : Measures the speed and change of price movements.
- Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum.
Stochastic Oscillator
- Purpose : Compares a particular closing price to a range of its prices over a certain period.
- Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions.
Bollinger Bands (BB)
- Purpose : Measures market volatility and provides relative price levels.
- Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness.
Ichimoku Cloud
- Purpose : Provides support and resistance levels, trend direction, and momentum.
- Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud.
Chande Momentum Oscillator (CMO)
- Purpose : Measures momentum on both up and down days.
- Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum.
Donchian Channels
- Purpose : Identifies volatility and potential breakouts.
- Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout.
Average Directional Index (ADX)
- Purpose : Measures the strength of a trend.
- Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend.
Volume Momentum Indicators (VolMom, CumVolMom, POCMom)
- Purpose : Analyze volume to assess buying and selling pressure.
- Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum.
Fractals
- Purpose : Identify potential reversal points in the market.
- Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend.
Divergence Detection
- Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line).
- Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal.
- Note : This functionality utilizes the library from Divergence Indicator .
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Coloring Scheme
Background Color
- Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes.
- Interpretation :
- Green Shades : Indicate bullish market sentiment.
- Red Shades : Indicate bearish market sentiment.
- Intensity : The strength of the color corresponds to the strength of the sentiment score.
Sentiment Table
- Purpose : Displays the status of each indicator across different timeframes.
- Interpretation :
- Green Cell : The indicator suggests a bullish signal.
- Red Cell : The indicator suggests a bearish signal.
- Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe.
Exponential Moving Averages (EMAs)
- Purpose : Provide dynamic support and resistance levels.
- Colors :
- EMA 10 : Lime
- EMA 20 : Yellow
- EMA 50 : Orange
- EMA 100 : Red
- EMA 200 : Purple
Trendlines
- Purpose : Visual representation of support and resistance levels based on pivot points.
- Interpretation :
- Upward Trendlines : Colored green , indicating support levels.
- Downward Trendlines : Colored red , indicating resistance levels.
- Note : Trendlines are drawn using the library from Simple Trendlines .
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Utility of Market Sentiment
The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by:
Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend.
Identifying Reversals : Divergences and fractals can signal potential turning points.
Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades.
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Divergences
Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal.
- Bullish Divergence : Price makes a lower low, but the indicator makes a higher low.
- Bearish Divergence : Price makes a higher high, but the indicator makes a lower high.
The indicator detects divergences for:
RSI
MACD
Stochastic Oscillator
On-Balance Volume (OBV)
Money Flow Index (MFI)
Accumulation/Distribution Line (A/D Line)
By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly.
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Trendlines
Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points:
- Upward Trendlines (Support) : Connect higher lows, indicating an uptrend.
- Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend.
These trendlines help traders visualize the trend direction and potential breakout or reversal points.
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Super Trend Reversals (ST Reversal)
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders:
Engage Early : Enter the market as reversal momentum builds up.
Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes.
By capturing these reversal points, traders can enhance their trading performance.
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Conclusion
The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions.
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Citations
- Divergence Detection Library : Divergence Indicator by DevLucem
- Trendline Drawing Library : Simple Trendlines by HoanGhetti
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Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions.
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OneThingToRuleThemAll [v1.4]This script was created because I wanted to be able to display a contextual chart of commonly used indicators for scalping and swing traders, with the ability to control the visual representation on the charts as their cross-overs, cross-unders, or changes of state happen in real time. Additionally, I wanted the ability to control how or when they are displayed. While looking through other community projects, I found they lacked the ability to full customize the output controls and values used for these indicators.
The script leverages standard RSI/MACD/VWAP/MVWAP/EMA calculations to help a trader visually make more informed decisions on entering or exiting a trade, depending on their understanding on what the indicators represent. Paired with a table directly on the chart, it allows a trader to quickly reference values to make more informed decisions without having to look away from the price action or look through multiple indicator outputs.
The main functionality of the indicator is controlled within the settings directly on the chart. There a user can enable the visual representations, or disable, and configure how they are displayed on the charts by altering their values or style types.
Users have the ability to enable/disable visual representations of:
The indicator chart
RSI Cross-over and RSI Reversals
MACD Uptrends and Downtrends
VWAP Cross-overs and Cross-unders
VWAP Line
MVWAP Cross-overs and Cross-unders
MVWAP Line
EMA Cross-overs and Cross-unders
EMA Line
Some traders like to use these visual indications as thresholds to enter or exit trades. Its best to find out which ones work the best with the security you are trying to trade. Personally, I use the table as a reference in conjunction with the RSI chart indicators to help me decide a logical trailing stop if I am scalping. Some users might like the track EMA200 crossovers, and have visual representations on the chart for when that happens. However, users may use the other indicators in other methods, and this script provides the ability to be able to configure those both visually and by value.
The pine script code is open source and itself is fairly straightforward, it is mostly written to provide the ultimate level of control the the user of the various indicators. Please reach out to me directly if you would like a further understanding of the code and an explanation on anything that may be unclear.
Enjoy :)
-dead1.
McClellan Indicators (Oscillator, Summation Index w/ RSI & MACD)Four indicators in one based on the McClellan Oscillator for both the NYSE and Nasdaq exchanges. Designed to be used in conjunction with each other- plot the Oscillator (Osc), Summation Index (MSI), and RSI/MACD of the MSI on both your SPX and Nasdaq chart. Select the exchange and indicator within the settings. These tools are secondary- but when the signals are combined with the action of the index and stocks can be helpful in identifying market turns and trend strength.
McClellan Oscillator--
The Osc is a market breadth tool that uses a fast and slow EMA based on the difference between advancing and declining stocks on the exchange. Used primarily to identify breadth thrusts, divergences, and extremes (oversold/overbought). Plot horizontal levels to see when the market internals are extremely overbought or oversold, and take note of when the Osc is declining while the market is advancing or vice versa.
McClellan Summation Index--
For intermediate trends the MSI is a running total of the Osc which can be used to confirm the strength of a trend, and spot potential reversals. A 10 period ema is included on this indicator, where crossovers can aid in spotting the change in trend of market internals, and divergences can identify when market internals are not in line with the trend. Shading is applied for when the internals are in a bullish or bearish trend.
Two additional indicators are the RSI and MACD of the Summation Index. An overbought or oversold MSI RSI generally indicates a strong trend in the market internals, however you may want to take note when the RSI stalls and begins to "hook" in the opposite direction. This indicator has signals to show when the market internals may be turning and to be on lookout for trend change.
Similarly- the MACD of the MSI identifies the strength of the trend, and crossovers can be used to help spot reversals. Shading is included in this indicator to spot the bullish/bearish trend of internals.
OBV with Volume/Momentum DivergenceCredits go to vyperphi696 and LazyBear for the original OBV with Divergence script.
This indicator has the new option to check for momentum divergence, which I have done by adding RSI and MACD data.
Hence the indicator allows combined testing of volume and momentum divergence. This feature aims to improve trend reversal detection by reducing false positives.
In summary, 3 divergence categories are shown by default as lines:
Volume + RSI + MACD (dark green/red)
Volume + RSI / Volume + MACD (light green/red)
Volume (gray)
Line colors can be adjusted via plot settings. Therefore it is also possible to distinguish Volume + RSI and Volume + MACD divergence if necessary.
Lastly, I edited the indicator scaling mechanism when changing from one timeframe to another; the transitions are smoother now. This only applies when auto-scaling is off.
Panel RSI MACD DMI//RSI
//--Default length : 14
//--RSI > 70 : Background is RED
//--RSI < 30 : Background is GREEN
//--RSI Between 30 and 70 : Background is BLUE
//MACD
//--Default: 12,26,9
//--MACD cross above Zero Line / Signal Line : Background is GREEN
//--MACD cross below Zero Line / Signal Line : Background is RED
//--Others condition : Background is BLUE
//DMI
//--Default: 14, 14
//--ADX > 20 : Text is GREEN
//--ADX < 20 : Text is RED
//--DI+ > DI- : Background is BLUE
//--DI- > DI+ : Background is YELLOW
Forex scalper 2xEMA + SRSI + MACDThis is a forex scalping strategy designed for the most liquid pairs, like major forex pairs.
Its made of
1 EMA 50
1 EMA 100
Stochastic RSI
MACD
Rules
For long :close of the candle is above moving average 50, moving average 50> moving average 100, macd histogram is positive and cross over of stochastic rsi with the oversold level.
For short :close of the candle is below moving average 50, moving average 50 < moving average 100, macd histogram is negative and cross under of stochastic rsi with the overbought level.
Exit
For exit we have take profit and stop loss using fixed pip points.
For this example on EURUSD we use 20 pips for both tp and sl
IF you have any questions let me know !
{INDYAN} RSI + MACDModded RSI and MACD for intraday use. If rsi above 60 and macd is above zero line then go for buy and if rsi is below 40 and macd below zero line then go for sell side. use it in small timeframe i.e. 3 minute or less.
better for scalp trading
Happy Trading
Love INDYAN
#It can be used best with INDYAN Go With Trend
Multi momentum indicatorScript contains couple momentum oscillators all in one pane
List of indicators:
RSI
Stochastic RSI
MACD
CCI
WaveTrend by LazyBear
MFI
Default active indicators are RSI and Stochastic RSI
Other indicators are disabled by default
RSI, StochRSI and MFI are modified to be bounded to range from 100 to -100. That's why overbought is 40 and 60 instead 70 and 80 while oversold -40 and -60 instead 30 and 20.
MACD and CCI as they are not bounded to 100 or 200 range, they are limited to 100 - -100 by default when activated (extras are simply hidden) but there is an option to show full indicator.
In settings there are couple more options like show crosses or show only histogram.
Default source for all indicators is close (except WaveTrend and MFI which use hlc3) and it could be changed but for all indicators.
There is an option for 2nd RSI which can be set for any timeframe and background calculated by Fibonacci levels.
MACD and RSI divergence by Rexio v2Hi everyone!
I wrote this indicator for intraday trading and it cannot be use only by itself you need to at least draw some S/R lines to make it useful. It is based at MACD histogram and gives signal when it sees divergence on MACD/RSI/MACD's Histogram (or all at once - settings) when macd's histogram switchs trend. Im using it to playing with a trend most of the time looking for hidden divergence at higher time frame and after that looking for regular divergence at lower time frame.
Im not a computer programist nor professional trader so it is only for educational purposes only.
Strategy Chameleon [theUltimator5]Have you ever looked at an indicator and wondered to yourself "Is this indicator actually profitable?" Well now you can test it out for yourself with the Strategy Chameleon!
Strategy Chameleon is a versatile, signal-agnostic trading strategy designed to adapt to any external indicator or trading system. Like a chameleon changes colors to match its environment, this strategy adapts to match any buy/sell signals you provide, making it the ultimate backtesting and automation tool for traders who want to test multiple strategies without rewriting code.
🎯 Key Features
1) Connects ANY external indicator's buy/sell signals
Works with RSI, MACD, moving averages, custom indicators, or any Pine Script output
Simply connect your indicator's signal output to the strategy inputs
2) Multiple Stop Loss Types:
Percentage-based stops
ATR (Average True Range) dynamic stops
Fixed point stops
3) Advanced Trailing Stop System:
Percentage trailing
ATR-based trailing
Fixed point trailing
4) Flexible Take Profit Options:
Risk:Reward ratio targeting
Percentage-based profits
ATR-based profits
Fixed point profits
5) Trading Direction Control
Long Only - Bull market strategies
Short Only - Bear market strategies
Both - Full market strategies
6) Time-Based Filtering
Optional trading session restrictions
Customize active trading hours
Perfect for day trading strategies
📈 How It Works
Signal Detection: The strategy monitors your connected buy/sell signals
Entry Logic: Executes trades when signals trigger during valid time periods
Risk Management: Automatically applies your chosen stop loss and take profit levels
Trailing System: Dynamically adjusts stops to lock in profits
Performance Tracking: Real-time statistics table showing win rate and performance
⚙️ Setup Instructions
0) Add indicator you want to test, then add the Strategy to your chart
Connect Your Signals:
imgur.com
Go to strategy settings → Signal Sources
1) Set "Buy Signal Source" to your indicator's buy output
2) Set "Sell Signal Source" to your indicator's sell output
3) Choose table position - This simply changes the table location on the screen
4) Set trading direction preference - Buy only? Sell only? Both directions?
imgur.com
5) Set your preferred stop loss type and level
You can set the stop loss to be either percentage based or ATR and fully configurable.
6) Enable trailing stops if desired
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7) Configure take profit settings
8) Toggle time filter to only consider specific time windows or trading sessions.
🚀 Use Cases
Test various indicators to determine feasibility and/or profitability.
Compare different signal sources quickly
Validate trading ideas with consistent risk management
Portfolio Management
Apply uniform risk management across different strategies
Standardize stop loss and take profit rules
Monitor performance consistently
Automation Ready
Built-in alert conditions for automated trading
Compatible with trading bots and webhooks
Easy integration with external systems
⚠️ Important Notes
This strategy requires external signals to function
Default settings use 10% of equity per trade
Pyramiding is disabled (one position at a time)
Strategy calculates on bar close, not every tick
🔗 Integration Examples
Works perfectly with:
RSI strategies (connect RSI > 70 for sells, RSI < 30 for buys)
Moving average crossovers
MACD signal line crosses
Bollinger Band strategies
Custom oscillators and indicators
Multi-timeframe strategies
📋 Default Settings
Position Size: 10% of equity
Stop Loss: 2% percentage-based
Trailing Stop: 1.5% percentage-based (enabled)
Take Profit: Disabled (optional)
Trade Direction: Both long and short
Time Filter: Disabled
Universal Renko Bars by SiddWolfUniversal Renko Bars or UniRenko Bars is an overlay indicator that applies the logic of Renko charting directly onto a standard candlestick chart. It generates a sequence of price-driven bricks, where each new brick is formed only when the price moves a specific amount, regardless of time. This provides a clean, price-action-focused visualization of the market's trend.
WHAT IS UNIVERSAL RENKO BARS?
For years, traders have faced a stark choice: the clean, noise-free world of Renko charts, or the rich, time-based context of Candlesticks. Choosing Renko meant giving up your favorite moving averages, volume profiles, and the fundamental sense of time. Choosing Candlesticks meant enduring the market noise that often clouds true price action.
But what if you didn't have to choose?
Universal Renko Bars is a revolutionary indicator that ends this dilemma. It's not just another charting tool; it's a powerful synthesis that overlays the pure, price-driven logic of Renko bricks directly onto your standard candlestick chart. This hybrid approach gives you the best of both worlds:
❖ The Clarity of Renko: By filtering out the insignificant noise of time, Universal Renko reveals the underlying trend with unparalleled clarity. Up trends are clean successions of green bricks; down trends are clear red bricks. No more guesswork.
❖ The Context of Candlesticks: Because the Renko logic is an overlay, you retain your time axis, your volume data, and full compatibility with every other time-based indicator in your arsenal (RSI, MACD, Moving Averages, etc.).
The true magic, however, lies in its live, Unconfirmed Renko brick. This semi-transparent box is your window into the current bar's real-time struggle. It grows, shrinks, and changes color with every tick, showing you exactly how close the price is to confirming the trend or forcing a reversal. It’s no longer a lagging indicator; it’s a live look at the current battle between buyers and sellers.
Universal Renko Bars unifies these two powerful charting methods, transforming your chart into a more intelligent, noise-free, and predictive analytical canvas.
HOW TO USE
To get the most out of Universal Renko Bars, here are a few tips and a full breakdown of the settings.
Initial Setup for the Best Experience
For the cleanest possible view, it's highly recommended that you hide the body of your standard candlesticks, that shows only the skelton of the candle. This allows the Renko bricks to become the primary focus of your chart.
→ Double click on the candles and uncheck the body checkbox.
Settings Breakdown
The indicator is designed to be powerful yet intuitive. The settings are grouped to make customization easy.
First, What is a "Tick"?
Before we dive in, it's important to understand the concept of a "Tick." In Universal Renko, a Tick is not the same as a market tick. It's a fundamental unit of price movement that you define. For example, if you set the Tick Size to $0.50, then a price move of $1.00 is equal to 2 Ticks. This is the core building block for all Renko bricks. Tick size here is dynamically determined by the settings provided in the indicator.
❖ Calculation Method (The "Tick Size" Engine)
This section determines the monetary value of a single "Tick."
`Calculation Method` : Choose your preferred engine for defining the Tick Size.
`ATR Based` (Default): The Tick Size becomes dynamic, based on market volatility (Average True Range). Bricks will get larger in volatile markets and smaller in quiet ones. Use the `ATR 14 Multiplier` to control the sensitivity.
`Percentage` : The Tick Size is a simple percentage of the current asset price, controlled by the `Percent Size (%)` input.
`Auto` : The "set it and forget it" mode. The script intelligently calculates a Tick Size based on the asset's price. Use the `Auto Sensitivity` slider to make these automatically calculated bricks thicker (value > 1.0) or thinner (value < 1.0).
❖ Parameters (The Core Renko Engine)
This group controls how the bricks are constructed based on the Tick Size.
`Tick Trend` : The number of "Ticks" the price must move in the same direction to print a new continuation brick. A smaller value means bricks form more easily.
`Tick Reversal` : The number of "Ticks" the price must move in the opposite direction to print a new reversal brick. This is typically set higher than `Tick Trend` (e.g., double) to filter out minor pullbacks and market noise.
`Open Offset` : Controls the visual overlap of the bricks. A value of `0` creates gapless bricks that start where the last one ended. A value of `2` (with a `Tick Reversal` of 4) creates the classic 50% overlap look.
❖ Visuals (Controlling What You See)
This is where you tailor the chart to your visual preference.
`Show Confirmed Renko` : Toggles the solid-colored, historical bricks. These are finalized and will never change. They represent the confirmed past trend.
`Show Unconfirmed Renko` : This is the most powerful visual feature. It toggles the live, semi-transparent box that represents the developing brick. It shows you exactly where the price is right now in relation to the levels needed to form the next brick.
`Show Max/Min Levels` : Toggles the horizontal "finish lines" on your chart. The green line is the price target for a bullish brick, and the red line is the target for a bearish brick. These are excellent for spotting breakouts.
`Show Info Label` : Toggles the on-chart label that provides key real-time stats:
🧱 Bricks: The total count of confirmed bricks.
⏳ Live: How many chart bars the current live brick has been forming. These bars forms the Renko bricks that aren't confirmed yet. Live = 0 means the latest renko brick is confirmed.
🌲 Tick Size: The current calculated value of a single Tick.
Hover over the label for a tooltip with live RSI(14), MFI(14), and CCI(20) data for additional confirmation.
TRADING STRATEGIES & IDEAS
Universal Renko Bars isn't just a visual tool; it's a foundation for building robust trading strategies.
Trend Confirmation: The primary use is to instantly identify the trend. A series of green bricks indicates a strong uptrend; a series of red bricks indicates a strong downtrend. Use this to filter out trades that go against the primary momentum.
Reversal Spotting: Pay close attention to the Unconfirmed Brick . When a strong trend is in place and the live brick starts to fight against it—changing color and growing larger—it can be an early warning that a reversal is imminent. Wait for the brick to be confirmed for a higher probability entry.
Breakout Trading: The `Max/Min Levels` are your dynamic breakout zones. A long entry can be considered when the price breaks and closes above the green Max Level, confirming a new bullish brick. A short entry can be taken when price breaks below the red Min Level.
Confluence & Indicator Synergy: This is where Universal Renko truly shines. Overlay a moving average (e.g., 20 EMA). Only take long trades when the green bricks are forming above the EMA. Combine it with RSI or MACD; a bearish reversal brick forming while the RSI shows bearish divergence is a very powerful signal.
A FINAL WORD
Universal Renko Bars was designed to solve a fundamental problem in technical analysis. It brings together the best elements of two powerful methodologies to give you a clearer, more actionable view of the market. By filtering noise while retaining context, it empowers you to make decisions with greater confidence.
Add Universal Renko Bars to your chart today and elevate your analysis. We welcome your feedback and suggestions for future updates!
Follow me to get notified when I publish New Indicator.
~ SiddWolf
Logistic Regression ICT FVG🚀 OVERVIEW
Welcome to the Logistic Regression Fair Value Gap (FVG) System — a next-gen trading tool that blends precision gap detection with machine learning intelligence.
Unlike traditional FVG indicators, this one evolves with each bar of price action, scoring and filtering gaps based on real market behavior.
🔧 CORE FEATURES
✨ Smart Gap Detection
Automatically identifies bullish and bearish Fair Value Gaps using volatility-aware candle logic.
📊 Probability-Based Filtering
Uses logistic regression to assign each gap a confidence score (0 to 1), showing only high-probability setups.
🔁 Real-Time Retest Tracking
Continuously watches how price interacts with each gap to determine if it deserves respect.
📈 Multi-Factor Assessment
Evaluates RSI, MACD, and body size at gap formation to build a full context snapshot.
🧠 Self-Learning Engine
The logistic regression model updates on each bar using gradient descent, refining its predictions over time.
📢 Built-In Alerts
Get instant alerts when a gap forms, gets retested, or breaks.
🎨 Custom Display Options
Control the color of bullish/bearish zones, and toggle on/off probability labels for cleaner charts.
🚩 WHAT MAKES IT DIFFERENT
This isn’t just another box-drawing indicator.
While others mark every imbalance, this system thinks before it draws — using statistical modeling to filter out noise and prioritize high-impact zones.
By learning from how price behaves around gaps (not just how they form), it helps you trade only what matters — not what clutters.
⚙️ HOW IT WORKS
1️⃣ Detection
FVGs are identified using ATR-based thresholds and sharp wick imbalances.
2️⃣ Behavior Monitoring
Every gap is tracked — and if respected enough times, it becomes part of the elite training set.
3️⃣ Context Capture
Each new FVG logs RSI, MACD, and body size to provide a feature-rich context for prediction.
4️⃣ Prediction (Logistic Regression)
The model predicts how likely the gap is to be respected and assigns it a probability score.
5️⃣ Classification & Alerts
Gaps above the threshold are plotted with score labels, and alerts trigger for entry/respect/break.
⚙️ CONFIGURATION PANEL
🔧 System Inputs
• Max Retests – How many times a gap must be respected to train the model
• Prediction Threshold – Minimum score to show a gap on the chart
• Learning Rate – Controls how fast the model adapts (default: 0.009)
• Max FVG Lifetime – Expiration duration for unused gaps
• Show Historic Gaps – Show/hide expired or invalidated gaps
🎨 Visual Options
• Bullish/Bearish Colors – Set gap colors to fit your chart style
• Confidence Labels – Show probability scores next to FVGs
• Alert Toggles – Enable alerts for:
– New FVG detected
– FVG respected (entry)
– FVG invalidated (break)
💡 WHY LOGISTIC REGRESSION?
Traditional FVG tools rely on candle shapes.
This system relies on probability — by training on RSI, MACD, and price behavior, it predicts whether a gap will act as a true liquidity zone.
Logistic regression lets the system continuously adapt using new data, making it more accurate the longer it runs.
That means smarter signals, fewer false positives, and a clearer view of where real opportunities lie.
real_time_candlesIntroduction
The Real-Time Candles Library provides comprehensive tools for creating, manipulating, and visualizing custom timeframe candles in Pine Script. Unlike standard indicators that only update at bar close, this library enables real-time visualization of price action and indicators within the current bar, offering traders unprecedented insight into market dynamics as they unfold.
This library addresses a fundamental limitation in traditional technical analysis: the inability to see how indicators evolve between bar closes. By implementing sophisticated real-time data processing techniques, traders can now observe indicator movements, divergences, and trend changes as they develop, potentially identifying trading opportunities much earlier than with conventional approaches.
Key Features
The library supports two primary candle generation approaches:
Chart-Time Candles: Generate real-time OHLC data for any variable (like RSI, MACD, etc.) while maintaining synchronization with chart bars.
Custom Timeframe (CTF) Candles: Create candles with custom time intervals or tick counts completely independent of the chart's native timeframe.
Both approaches support traditional candlestick and Heikin-Ashi visualization styles, with options for moving average overlays to smooth the data.
Configuration Requirements
For optimal performance with this library:
Set max_bars_back = 5000 in your script settings
When using CTF drawing functions, set max_lines_count = 500, max_boxes_count = 500, and max_labels_count = 500
These settings ensure that you will be able to draw correctly and will avoid any runtime errors.
Usage Examples
Basic Chart-Time Candle Visualization
// Create real-time candles for RSI
float rsi = ta.rsi(close, 14)
Candle rsi_candle = candle_series(rsi, CandleType.candlestick)
// Plot the candles using Pine's built-in function
plotcandle(rsi_candle.Open, rsi_candle.High, rsi_candle.Low, rsi_candle.Close,
"RSI Candles", rsi_candle.candle_color, rsi_candle.candle_color)
Multiple Access Patterns
The library provides three ways to access candle data, accommodating different programming styles:
// 1. Array-based access for collection operations
Candle candles = candle_array(source)
// 2. Object-oriented access for single entity manipulation
Candle candle = candle_series(source)
float value = candle.source(Source.HLC3)
// 3. Tuple-based access for functional programming styles
= candle_tuple(source)
Custom Timeframe Examples
// Create 20-second candles with EMA overlay
plot_ctf_candles(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 20,
timezone = -5,
tied_open = true,
ema_period = 9,
enable_ema = true
)
// Create tick-based candles (new candle every 15 ticks)
plot_ctf_tick_candles(
source = close,
candle_type = CandleType.heikin_ashi,
number_of_ticks = 15,
timezone = -5,
tied_open = true
)
Advanced Usage with Custom Visualization
// Get custom timeframe candles without automatic plotting
CandleCTF my_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 30
)
// Apply custom logic to the candles
float ema_values = my_candles.ctf_ema(14)
// Draw candles and EMA using time-based coordinates
my_candles.draw_ctf_candles_time()
ema_values.draw_ctf_line_time(line_color = #FF6D00)
Library Components
Data Types
Candle: Structure representing chart-time candles with OHLC, polarity, and visualization properties
CandleCTF: Extended candle structure with additional time metadata for custom timeframes
TickData: Structure for individual price updates with time deltas
Enumerations
CandleType: Specifies visualization style (candlestick or Heikin-Ashi)
Source: Defines price components for calculations (Open, High, Low, Close, HL2, etc.)
SampleType: Sets sampling method (Time-based or Tick-based)
Core Functions
get_tick(): Captures current price as a tick data point
candle_array(): Creates an array of candles from price updates
candle_series(): Provides a single candle based on latest data
candle_tuple(): Returns OHLC values as a tuple
ctf_candles_array(): Creates custom timeframe candles without rendering
Visualization Functions
source(): Extracts specific price components from candles
candle_ctf_to_float(): Converts candle data to float arrays
ctf_ema(): Calculates exponential moving averages for candle arrays
draw_ctf_candles_time(): Renders candles using time coordinates
draw_ctf_candles_index(): Renders candles using bar index coordinates
draw_ctf_line_time(): Renders lines using time coordinates
draw_ctf_line_index(): Renders lines using bar index coordinates
Technical Implementation Notes
This library leverages Pine Script's varip variables for state management, creating a sophisticated real-time data processing system. The implementation includes:
Efficient tick capturing: Samples price at every execution, maintaining temporal tracking with time deltas
Smart state management: Uses a hybrid approach with mutable updates at index 0 and historical preservation at index 1+
Temporal synchronization: Manages two time domains (chart time and custom timeframe)
The tooltip implementation provides crucial temporal context for custom timeframe visualizations, allowing users to understand exactly when each candle formed regardless of chart timeframe.
Limitations
Custom timeframe candles cannot be backtested due to Pine Script's limitations with historical tick data
Real-time visualization is only available during live chart updates
Maximum history is constrained by Pine Script's array size limits
Applications
Indicator visualization: See how RSI, MACD, or other indicators evolve in real-time
Volume analysis: Create custom volume profiles independent of chart timeframe
Scalping strategies: Identify short-term patterns with precisely defined time windows
Volatility measurement: Track price movement characteristics within bars
Custom signal generation: Create entry/exit signals based on custom timeframe patterns
Conclusion
The Real-Time Candles Library bridges the gap between traditional technical analysis (based on discrete OHLC bars) and the continuous nature of market movement. By making indicators more responsive to real-time price action, it gives traders a significant edge in timing and decision-making, particularly in fast-moving markets where waiting for bar close could mean missing important opportunities.
Whether you're building custom indicators, researching price patterns, or developing trading strategies, this library provides the foundation for sophisticated real-time analysis in Pine Script.
Implementation Details & Advanced Guide
Core Implementation Concepts
The Real-Time Candles Library implements a sophisticated event-driven architecture within Pine Script's constraints. At its heart, the library creates what's essentially a reactive programming framework handling continuous data streams.
Tick Processing System
The foundation of the library is the get_tick() function, which captures price updates as they occur:
export get_tick(series float source = close, series float na_replace = na)=>
varip float price = na
varip int series_index = -1
varip int old_time = 0
varip int new_time = na
varip float time_delta = 0
// ...
This function:
Samples the current price
Calculates time elapsed since last update
Maintains a sequential index to track updates
The resulting TickData structure serves as the fundamental building block for all candle generation.
State Management Architecture
The library employs a sophisticated state management system using varip variables, which persist across executions within the same bar. This creates a hybrid programming paradigm that's different from standard Pine Script's bar-by-bar model.
For chart-time candles, the core state transition logic is:
// Real-time update of current candle
candle_data := Candle.new(Open, High, Low, Close, polarity, series_index, candle_color)
candles.set(0, candle_data)
// When a new bar starts, preserve the previous candle
if clear_state
candles.insert(1, candle_data)
price.clear()
// Reset state for new candle
Open := Close
price.push(Open)
series_index += 1
This pattern of updating index 0 in real-time while inserting completed candles at index 1 creates an elegant solution for maintaining both current state and historical data.
Custom Timeframe Implementation
The custom timeframe system manages its own time boundaries independent of chart bars:
bool clear_state = switch settings.sample_type
SampleType.Ticks => cumulative_series_idx >= settings.number_of_ticks
SampleType.Time => cumulative_time_delta >= settings.number_of_seconds
This dual-clock system synchronizes two time domains:
Pine's execution clock (bar-by-bar processing)
The custom timeframe clock (tick or time-based)
The library carefully handles temporal discontinuities, ensuring candle formation remains accurate despite irregular tick arrival or market gaps.
Advanced Usage Techniques
1. Creating Custom Indicators with Real-Time Candles
To develop indicators that process real-time data within the current bar:
// Get real-time candles for your data
Candle rsi_candles = candle_array(ta.rsi(close, 14))
// Calculate indicator values based on candle properties
float signal = ta.ema(rsi_candles.first().source(Source.Close), 9)
// Detect patterns that occur within the bar
bool divergence = close > close and rsi_candles.first().Close < rsi_candles.get(1).Close
2. Working with Custom Timeframes and Plotting
For maximum flexibility when visualizing custom timeframe data:
// Create custom timeframe candles
CandleCTF volume_candles = ctf_candles_array(
source = volume,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 60
)
// Convert specific candle properties to float arrays
float volume_closes = volume_candles.candle_ctf_to_float(Source.Close)
// Calculate derived values
float volume_ema = volume_candles.ctf_ema(14)
// Create custom visualization
volume_candles.draw_ctf_candles_time()
volume_ema.draw_ctf_line_time(line_color = color.orange)
3. Creating Hybrid Timeframe Analysis
One powerful application is comparing indicators across multiple timeframes:
// Standard chart timeframe RSI
float chart_rsi = ta.rsi(close, 14)
// Custom 5-second timeframe RSI
CandleCTF ctf_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 5
)
float fast_rsi_array = ctf_candles.candle_ctf_to_float(Source.Close)
float fast_rsi = fast_rsi_array.first()
// Generate signals based on divergence between timeframes
bool entry_signal = chart_rsi < 30 and fast_rsi > fast_rsi_array.get(1)
Final Notes
This library represents an advanced implementation of real-time data processing within Pine Script's constraints. By creating a reactive programming framework for handling continuous data streams, it enables sophisticated analysis typically only available in dedicated trading platforms.
The design principles employed—including state management, temporal processing, and object-oriented architecture—can serve as patterns for other advanced Pine Script development beyond this specific application.
------------------------
Library "real_time_candles"
A comprehensive library for creating real-time candles with customizable timeframes and sampling methods.
Supports both chart-time and custom-time candles with options for candlestick and Heikin-Ashi visualization.
Allows for tick-based or time-based sampling with moving average overlay capabilities.
get_tick(source, na_replace)
Captures the current price as a tick data point
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
na_replace (float) : Optional - Value to use when source is na
Returns: TickData structure containing price, time since last update, and sequential index
candle_array(source, candle_type, sync_start, bullish_color, bearish_color)
Creates an array of candles based on price updates
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
sync_start (simple bool) : Optional - Whether to synchronize with the start of a new bar
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of Candle objects ordered with most recent at index 0
candle_series(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides a single candle based on the latest price data
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: A single Candle object representing the current state
candle_tuple(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides candle data as a tuple of OHLC values
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Tuple representing current candle values
method source(self, source, na_replace)
Extracts a specific price component from a Candle
Namespace types: Candle
Parameters:
self (Candle)
source (series Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
na_replace (float) : Optional - Value to use when source value is na
Returns: The requested price value from the candle
method source(self, source)
Extracts a specific price component from a CandleCTF
Namespace types: CandleCTF
Parameters:
self (CandleCTF)
source (simple Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
Returns: The requested price value from the candle as a varip
method candle_ctf_to_float(self, source)
Converts a specific price component from each CandleCTF to a float array
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
Returns: Array of float values extracted from the candles, ordered with most recent at index 0
method ctf_ema(self, ema_period)
Calculates an Exponential Moving Average for a CandleCTF array
Namespace types: array
Parameters:
self (array)
ema_period (simple float) : Period for the EMA calculation
Returns: Array of float values representing the EMA of the candle data, ordered with most recent at index 0
method draw_ctf_candles_time(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar time coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using time-based x-coordinates
method draw_ctf_candles_index(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar index coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using index-based x-coordinates
method draw_ctf_line_time(self, source, line_size, line_color)
Renders a line representing a price component from the candles using time coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_time(self, line_size, line_color)
Renders a line from a varip float array using time coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_index(self, source, line_size, line_color)
Renders a line representing a price component from the candles using index coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
method draw_ctf_line_index(self, line_size, line_color)
Renders a line from a varip float array using index coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots tick-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots tick-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots time-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots time-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_candles(source, candle_type, sample_type, number_of_ticks, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, enable_ema, line_width, ema_color, use_time_indexing)
Unified function for plotting candles with comprehensive options
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Optional - Type of candle chart to display
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
ema_period (simple float) : Optional - Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
enable_ema (bool) : Optional - Whether to display the EMA overlay
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with optional EMA overlay
ctf_candles_array(source, candle_type, sample_type, number_of_ticks, number_of_seconds, tied_open, bullish_color, bearish_color)
Creates an array of custom timeframe candles without rendering them
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to create (candlestick or Heikin-Ashi)
sample_type (simple SampleType) : Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of CandleCTF objects ordered with most recent at index 0
Candle
Structure representing a complete candle with price data and display properties
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
candle_color (series color) : Color to use when rendering the candle
ready (series bool) : Boolean indicating if candle data is valid and ready for use
TickData
Structure for storing individual price updates
Fields:
price (series float) : The price value at this tick
time_delta (series float) : Time elapsed since the previous tick in milliseconds
series_index (series int) : Sequential index identifying this tick
CandleCTF
Structure representing a custom timeframe candle with additional time metadata
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
open_time (series int) : Timestamp marking when the candle was opened (in Unix time)
time_delta (series float) : Duration of the candle in milliseconds
candle_color (series color) : Color to use when rendering the candle
[MAD] Weighted Trend Detector--> Purpose
The Weighted Trend Detector evaluates market direction by combining multiple technical indicators (RSI, MACD, Moving Averages, ADX, and Volume) across up to three different timeframes.
It calculates an overall trend score to help visualize whether conditions are bullish, bearish, or neutral.
--> Scaling & Weightings
Each component indicator contributes a score between -1.0 and +1.0. User-defined weights (e.g., 0.2 for RSI, 0.3 for MACD) determine how much each indicator influences the final score. An adaptive scaling mechanism ensures extreme values remain in view by dynamically setting the minimum and maximum of the score range over a specified lookback period.
--> Basic Parameters of Individual Indicators
RSI Period: Number of bars for the Relative Strength Index calculation; higher values smooth out noise but may lag.
MACD Fast/Slow/Signal: EMA-based periods to identify momentum shifts. A shorter “Fast” length reacts quickly, while a longer “Slow” length is smoother.
Moving Averages (Short & Long Lengths): Simple Moving Averages used to gauge shorter- vs. longer-term price direction.
ADX Length: Defines how many bars are considered when measuring trend strength. Higher values produce smoother ADX lines.
Volume MA Length: Period over which the average volume is calculated to compare against current volume.
--> Colors & How They Are Mixed
The background color scales from a negative color (for lower scores) to a positive color (for higher scores).
Near the highest or lowest parts of the score range, additional blending occurs if the slope (change in score) reverses:
Turning Down: Mixes with a user-chosen “warning” color if the score is high but moving lower.
Turning Up: Mixes with a user-chosen “recovery” color if the score is low but moving higher.
All colors (including line and label text) can be adjusted in the script’s inputs to suit personal preferences.colors are customizable via inputs.
Have fun :-)
Prediction Based on Linreg & Atr
We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈.
How Does the Linreg & ATR Prediction Work?
1. Trend Calculation and Signals:
o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script).
o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉.
2. Predicting Future Prices:
o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮.
o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍.
3. Adjusting the Prediction:
o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍.
4. Visualization:
o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈.
5. EMA Cross Signals:
o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉.
6. Additional Considerations:
o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented).
Confidence Interpretation:
• High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥.
• Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️.
Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀.
Español
Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈.
¿Cómo Funciona la Predicción con Linreg & ATR?
Cálculo de Tendencias y Señales:
Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script).
Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉.
Predicción de Precios Futuros:
Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮.
Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍.
Ajuste de la Predicción:
El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍.
Visualización:
Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈.
Señales de Cruce de EMAs:
Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉.
Consideraciones Adicionales:
Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente).
Interpretación de la Confianza:
Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥.
Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️.
La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
Ultimate Multi-Physics Financial IndicatorThe Ultimate Multi-Physics Financial Indicator is an advanced Pine Script designed to combine various complex theories from physics, mathematics, and statistical mechanics to create a holistic, multi-dimensional approach to market analysis. Let’s break down the core concepts and how they’re applied in this script:
1. Fractal Geometry: Recursive Pattern Recognition
Purpose: This part of the script uses fractal geometry to recursively analyze price pivots (highs and lows) for detecting patterns.
Fractals: The fractalHigh and fractalLow signals represent key turning points in the market. The script goes deeper by recursively analyzing layers of pivot sequences, adding "depth" to the recognition of patterns.
Recursive Depth: It breaks down each detected pivot into smaller components, giving more nuance to market pattern recognition. This provides a broader context for how prices have behaved historically at various levels of recursion.
2. Quantum Mechanics: Adaptive Probabilistic Monte Carlo with Correlation
Purpose: This component integrates randomness (from Monte Carlo simulations) with current market behavior using correlation.
Randomness Weighted by Correlation: By generating random probabilities and weighting them based on how well the market aligns with recent trends, it creates a probabilistic signal. The random values are scaled by a correlation factor (close prices and their moving average), adding adaptive elements where randomness is adjusted by current market conditions.
3. Thermodynamics: Adaptive Efficiency Ratio (Entropy-Like Decay)
Purpose: This section uses principles from thermodynamics, where efficiency in price movement is dynamically adjusted by recent volatility and changes.
Efficiency Ratio: It calculates how efficiently the market is moving over a certain period. The "entropy decay factor" reflects how stable the market is. Higher entropy (chaos) results in lower efficiency, while stable periods maintain higher efficiency.
4. Chaos Theory: Lorenz-Driven Market Oscillation
Purpose: Instead of using a basic Average True Range (ATR) indicator, this section applies chaos theory (using a Lorenz attractor analogy) to describe complex market oscillations.
Lorenz Attractor: This models market behavior with a chaotic system that depends on the historical price changes at different time intervals. The attractor value quantifies the level of "chaos" or unpredictability in the market.
5. String Theory: Multi-Layered Dimensional Analysis of RSI and MACD
Purpose: Combines traditional indicators like the RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) with momentum for multi-dimensional analysis.
Interaction of Layers: Each layer (RSI, MACD, and momentum) is treated as part of a multi-dimensional structure, where they influence one another. The final signal is a blended outcome of these key metrics, weighted and averaged for complexity.
6. Fluid Dynamics: Adaptive OBV (Pressure-Based)
Purpose: This section uses fluid dynamics to understand how price movement and volume create pressure over time, similar to how fluids behave under different forces.
Adaptive OBV: Traditional OBV (On-Balance Volume) is adapted by using statistical smoothing to measure the "pressure" exerted by volume over time. The result is a signal that shows where there might be building momentum or pressure in the market based on volume dynamics.
7. Recursive Synthesis of Signals
Purpose: After calculating all the individual signals (fractal, quantum, thermodynamic, chaos, string, and fluid), the script synthesizes them into one cohesive signal.
Recursive Feedback Loop: Each signal is recursively influenced by others, forming a feedback loop that allows the indicator to continuously learn from new data and self-adjust.
8. Signal Smoothing and Final Output
Purpose: To avoid noise in the output, the final combined signal is smoothed using an Exponential Moving Average (EMA), which helps stabilize the output for easier interpretation.
9. Dynamic Color Coding Based on Signal Extremes
Purpose: Visual clarity is enhanced by using color to highlight different levels of signal strength.
Color Coding: The script dynamically adjusts colors (green, orange, red) based on the strength of the final signal relative to its percentile ranking in historical data, making it easier to spot bullish, neutral, or bearish signals.
The "Ultimate Multi-Physics Financial Indicator" integrates a diverse array of scientific principles — fractal geometry, quantum mechanics, thermodynamics, chaos theory, string theory, and fluid dynamics — to provide a comprehensive market analysis tool. By combining probabilistic simulations, multi-dimensional technical indicators, and recursive feedback loops, this indicator adapts dynamically to evolving market conditions, giving traders a holistic view of market behavior across various dimensions. The result is an adaptive and flexible tool that responds to both short-term and long-term market changes
MACD Bands - Multi Timeframe [TradeMaster Lite]We present a customizable MACD indicator, with the following features:
Multi-timeframe
Deviation bands to spot unusual volatility
9 Moving Average types
Conditional coloring and line crossings
👉 What is MACD?
MACD is a classic, trend-following indicator that uses moving averages to identify changes in momentum. It can be used to identify trend changes, overbought and oversold conditions, and potential reversals.
👉 Multi-timeframe:
This feature allows to analyze the same market data on multiple time frames, which can be in help to identify trends and patterns that would not be visible on a single time frame. When using the multi-timeframe feature, it is important to start with the higher time frame and then look for confirmation on the lower time frames. This will help you to avoid false signals. Please note that only timeframes higher than the chart timeframe is supported currently with this feature enabled. Might get updated in the future.
👉 Deviation bands to spot unusual volatility:
Deviation bands are plotted around the Signal line that can be in help to identify periods of unusual volatility. When the MACD line crosses outside of the deviation bands, it suggests that the market is becoming more volatile and a strong trend may form in that direction.
👉 9 Moving Average types can be used in the script. Each type of moving average offers a unique perspective and can be used in different scenarios to identify market trends.
SMA (Simple Moving Average): This calculates the average of a selected range of values, by the number of periods in that range.
SMMA (Smoothed Moving Average): This takes into account all data available and assigns equal weighting to the values.
EMA (Exponential Moving Average): This places a greater weight and significance on the most recent data points.
DEMA (Double Exponential Moving Average): This is a faster-moving average that uses a proprietary calculation to reduce the lag in data points.
TEMA (Triple Exponential Moving Average): This is even quicker than the DEMA, helping traders respond more quickly to changes in trend.
LSMA (Least Squares Moving Average): This moving average applies least squares regression method to determine the future direction of the trend.
HMA (Hull Moving Average): This moving average is designed to reduce lag and improve smoothness, providing quicker signals for short-term market movements.
VWMA (Volume Weighted Moving Average): This assigns more weight to candles with a high volume, reflecting the true average values more accurately in high volume periods.
WMA (Weighted Moving Average): This assigns more weight to the latest data, but not as much as the EMA.
👉 Conditional coloring :
This feature colors the MACD line line based on it's direction and fills the area between the MACD line and Deviation band edges to highlight the potential volatility and the strength of the momentum. This can be useful to identify when the market is trending strongly and when it is in a more neutral or choppy state.
👉 MACD Line - Signal Line crossings:
This is a classic MACD trading signal that occurs when the MACD line crosses above or below the signal line. Crossovers can be used to identify potential trend reversals. This can be a bullish or bearish signal, depending on the direction of the crossover.
👉 General advice
Confirming Signals with other indicators:
As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade.
Use proper risk management:
When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing.
Combining with other technical indicators:
The indicator can be effectively used alongside other technical indicators to create a comprehensive trading strategy and provide additional confirmation.
Keep in Mind:
Thorough research and backtesting are essential before making any trading decisions. Furthermore, it's crucial to have a solid understanding of the indicator and its behavior. Additionally, incorporating fundamental analysis and considering market sentiment can be vital factors to take into account in your trading approach.
Limitations:
This is a lagging indicator. Please note that the indicator is using moving averages, which are lagging indicators.
The indicators within the TradeMaster Lite package aim for simplicity and efficiency, while retaining their original purpose and value. Some settings, functions or visuals may be simpler than expected.
⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. Our aim is to offer useful features that meet the needs of the 21st century and that we actually use.
🛑 Risk Notice:
Everything provided by trademasterindicator – from scripts, tools, and articles to educational materials – is intended solely for educational and informational purposes. Past performance does not assure future returns.
Major and Minor Trend Indicator by Nikhil34a V 2.2Title: Major and Minor Trend Indicator by Nikhil34a V 2.2
Description:
The Major and Minor Trend Indicator v2.2 is a comprehensive technical analysis script designed for use with the TradingView platform. This powerful tool is developed in Pine Script version 5 and helps traders identify potential buying and selling opportunities in the stock market.
Features:
SMA Trend Analysis: The script calculates two Simple Moving Averages (SMAs) with user-defined lengths for major and minor trends. It displays these SMAs on the chart, allowing traders to visualize the prevailing trends easily.
Surge Detection: The indicator can detect buying and selling surges based on specific conditions, such as volume, RSI, MACD, and stochastic indicators. Both Buying and Selling surges are marked in black on the chart.
Option Buy Zone Detection: The script identifies the option buy zone based on SMA crossovers, RSI, and MACD values. The buy zone is categorized as "CE Zone" or "PE Zone" and displayed in the table along with the trigger time.
Two-Day High and Low Range: The script calculates the highest high and lowest low of the previous two trading days and plots them on the chart. The area between these points is shaded in semi-transparent green and red colors.
Crossover Analysis: The script analyzes moving average crossovers on multiple timeframes (2-minute, 3-minute, and 5-minute) and displays buy and sell signals accordingly.
Trend Identification: The script identifies the major and minor trends as either bullish or bearish, providing valuable insights into the overall market sentiment.
Usage:
Customize Major and Minor SMA Periods: Adjust the lengths of major and minor SMAs through input parameters to suit your trading preferences.
Enable/Disable Moving Averages: Choose which SMAs to display on the chart by toggling the "showXMA" input options.
Set Surge and Option Buy Zone Thresholds: Modify the surgeThreshold, volumeThreshold, RSIThreshold, and StochThreshold inputs to refine the surge and buy zone detection.
Analyze Crossover Signals: Monitor the crossover signals in the table, categorized by timeframes (2-minute, 3-minute, and 5-minute).
Explore Market Bias and Distance to 2-Day High/Low: The table provides information on market bias, current price movement relative to the previous two-day high and low, and the option buy zone status.
Additional Use Cases:
Surge Indicator:
The script includes a Surge Indicator that detects sudden buying or selling surges in the market. When a buying surge is identified, the "BSurge" label will appear below the corresponding candle with black text on a white background. Similarly, a selling surge will display the "SSurge" label in white text on a black background. These indicators help traders quickly spot strong buying or selling activities that may influence their trading decisions. These surges can be used to identify sudden premium dump zones.
Option Buy Zone:
The Option Buy Zone is an essential feature that identifies potential zones for buying call options (CE Zone) or put options (PE Zone) based on specific technical conditions. The indicator evaluates SMA crossovers, RSI, and MACD values to determine the current market sentiment. When the option buy zone is triggered, the script will display the respective zone ("CE Zone" or "PE Zone") in the table, highlighted with a white background. Additionally, the time when the buy zone was triggered will be shown under the "Option Buy Zone Trigger Time" column.
Price Movement Relative to 2-Day High/Low:
The script calculates the highest high and lowest low of the previous two trading days (high2DaysAgo and low2DaysAgo) and plots these points on the chart. The area between these two points is shaded in semi-transparent green and red colors. The green region indicates the price range between the highpricetoconsider (highest high of the previous two days) and the lower value between highPreviousDay and high2DaysAgo. Similarly, the red region represents the price range between the lowpricetoconsider (lowest low of the previous two days) and the higher value between lowPreviousDay and low2DaysAgo.
Entry Time and Current Zone:
The script identifies potential entry times for trades within the option buy zone. When a valid buy zone trigger occurs, the script calculates the entryTime by adding the durationInMinutes (user-defined) to the startTime. The entryTime will be displayed in the "Entry Time" column of the table. Depending on the comparison between optionbuyzonetriggertime and entryTime, the background color of the entry time will change. If optionbuyzonetriggertime is greater than entryTime, the background color will be yellow, indicating that a new trigger has occurred before the specified duration. Otherwise, the background color will be green, suggesting that the entry time is still within the defined duration.
Current Zone Indicator:
The script further categorizes the current zone as either "CE Zone" (call option zone) or "PE Zone" (put option zone). When the market is trending upwards and the minor SMA is above the major SMA, the currentZone will be set to "CE Zone." Conversely, when the market is trending downwards and the minor SMA is below the major SMA, the currentZone will be "PE Zone." This information is displayed in the "Current Zone" column of the table.
These additional use cases empower traders with valuable insights into market trends, buying and selling surges, option buy zones, and potential entry times. Traders can combine this information with their analysis and risk management strategies to make informed and confident trading decisions.
Note:
The script is optimized for identifying trends and potential trade opportunities. It is crucial to perform additional analysis and risk management before executing any trades based on the provided signals.
Happy Trading!
Bull Club BiasThe script intends to eliminate noise from the chart. It uses a combination of multiple indicators into 1.
For long bias:
Close is greater than the ADX
15 Period EMA on close is greater than SMA on high
13 period RSI is greater than 25 periods RSI
MACD is greater than 0
For short bias:
Close is lower than the ADX
15 Period EMA on close is lower than SMA on high
13 period RSI is lower than 25 periods RSI
MACD is lower than 0
For every other combination, it is a range-bound bias. NSE:BANKNIFTY
A green background indicates long bias
A Red background indicates short bias
An Orange background indicates range-bound bias
