Power Of 3 ICT 01 [TradingFinder] AMD ICT & SMC Accumulations🔵 Introduction
The ICT Power of 3 (PO3) strategy, developed by Michael J. Huddleston, known as the Inner Circle Trader, is a structured approach to analyzing daily market activity. This strategy divides the trading day into three distinct phases: Accumulation, Manipulation, and Distribution.
Each phase represents a unique market behavior influenced by institutional traders, offering a clear framework for retail traders to align their strategies with market movements.
Accumulation (19:00 - 01:00 EST) takes place during low-volatility hours, as institutional traders accumulate orders. Manipulation (01:00 - 07:00 EST) involves false breakouts and liquidity traps designed to mislead retail traders. Finally, Distribution (07:00 - 13:00 EST) represents the active phase where significant market movements occur as institutions distribute their positions in line with the broader trend.
This indicator is built upon the Power of 3 principles to provide traders with a practical and visual tool for identifying these key phases. By using clear color coding and precise time zones, the indicator highlights critical price levels, such as highs and lows, helping traders to better understand market dynamics and make more informed trading decisions.
Incorporating the ICT AMD setup into daily analysis enables traders to anticipate market behavior, spot high-probability trade setups, and gain deeper insights into institutional trading strategies. With its focus on time-based price action, this indicator simplifies complex market structures, offering an effective tool for traders of all levels.
🔵 How to Use
The ICT Power of 3 (PO3) indicator is designed to help traders analyze daily market movements by visually identifying the three key phases: Accumulation, Manipulation, and Distribution.
Here's how traders can effectively use the indicator :
🟣 Accumulation Phase (19:00 - 01:00 EST)
Purpose : Identify the range-bound activity where institutional players accumulate orders.
Trading Insight : Avoid placing trades during this phase, as price movements are typically limited. Instead, use this time to prepare for the potential direction of the market in the next phases.
🟣 Manipulation Phase (01:00 - 07:00 EST)
Purpose : Spot false breakouts and liquidity traps that mislead retail traders.
Trading Insight : Observe the market for price spikes beyond key support or resistance levels. These moves often reverse quickly, offering high-probability entry points in the opposite direction of the initial breakout.
🟣 Distribution Phase (07:00 - 13:00 EST)
Purpose : Detect the main price movement of the day, driven by institutional distribution.
Trading Insight : Enter trades in the direction of the trend established during this phase. Look for confirmations such as breakouts or strong directional moves that align with broader market sentiment
🔵 Settings
Show or Hide Phases :mDecide whether to display Accumulation, Manipulation, or Distribution.
Adjust the session times for each phase :
Accumulation: 1900-0100 EST
Manipulation: 0100-0700 EST
Distribution: 0700-1300 EST
Modify Visualization : Customize how the indicator looks by changing settings like colors and transparency.
🔵 Conclusion
The ICT Power of 3 (PO3) indicator is a powerful tool for traders seeking to understand and leverage market structure based on time and price dynamics. By visually highlighting the three key phases—Accumulation, Manipulation, and Distribution—this indicator simplifies the complex movements of institutional trading strategies.
With its customizable settings and clear representation of market behavior, the indicator is suitable for traders at all levels, helping them anticipate market trends and make more informed decisions.
Whether you're identifying entry points in the Accumulation phase, navigating false moves during Manipulation, or capitalizing on trends in the Distribution phase, this tool provides valuable insights to enhance your trading performance.
By integrating this indicator into your analysis, you can better align your strategies with institutional movements and improve your overall trading outcomes.
Educational
Fibonacci Renko Candle Trend - AynetThe " Fibonacci Renko Candle Trend - Aynet" Pine Script is an innovative and customizable indicator that merges the concept of Fibonacci retracement levels with Renko charting, a method designed to filter out market noise by focusing purely on price movement. Below is a detailed, scientific explanation of its structure and functionality:
Key Components
1. ATR-Based Renko Chart
ATR Calculation: The script calculates the Average True Range (ATR) over a user-defined period (atrLength). ATR represents market volatility and dynamically determines the Renko box size.
Box Size: The box size is computed as a product of ATR and a user-defined Fibonacci multiplier (fibMultiplier), making it adaptable to changing market conditions.
2. Fibonacci Integration
Fibonacci Levels: Users manually input Fibonacci ratios (e.g., 0.236, 0.382, 0.618, etc.) that are stored in an array. These ratios define potential retracement or extension levels in the Renko chart.
Dynamic Levels: The script iteratively calculates price levels based on the Renko box size and Fibonacci ratios, identifying the next significant level whenever a price crosses a predefined threshold.
3. Renko Candle Construction
Trend Direction: The script dynamically tracks trend changes by comparing the current close price with previous open and close values.
Renko Candles: When price movement exceeds the box size:
Uptrend: A green candle is drawn if the price rises above the current box.
Downtrend: A red candle is drawn if the price falls below the current box.
Coloring: The Renko candles are colored green (uptrend) or red (downtrend) to visually indicate market momentum.
4. Signal Generation
Trend Change Detection: A trend change is identified when the direction of the Renko box changes from upward to downward or vice versa.
Signal Labels: If a trend change occurs, the script generates "LONG" or "SHORT" signals with associated Fibonacci levels. These labels are positioned near the respective candles and displayed with customizable transparency for clarity.
5. Fibonacci Visualization
The script dynamically plots Fibonacci levels as horizontal dashed lines:
Each line corresponds to a specific Fibonacci ratio scaled by the box size.
These lines act as potential support or resistance zones, offering a roadmap for market behavior.
6. User Interface and Customization
Parameters: Users can configure:
ATR period (atrLength).
Fibonacci multipliers and ratios.
Signal label transparency and display settings.
Info Panel: A compact information table displays the computed Renko box size for reference.
Scientific and Trading Use Cases
Noise Filtering: By using Renko charts, the script eliminates time-based noise, allowing traders to focus solely on price action.
Volatility-Based Adaptation: The ATR-based dynamic box size ensures the indicator adapts to market volatility, making it robust across asset classes and market conditions.
Fibonacci-Based Strategy: Incorporating Fibonacci levels provides a structured framework to predict key support and resistance levels, commonly used in retracement and extension strategies.
Signal Precision: By combining Renko and Fibonacci levels, the script identifies trend changes with high precision, aiding traders in timing their entries and exits.
Improvements for Advanced Use
Multi-Timeframe Support: Extend the script to compute Renko levels and Fibonacci ratios across multiple timeframes.
Alert Integration: Add alerts for when price crosses specific Fibonacci levels or when trend changes occur.
Statistical Validation: Enhance the script by integrating a success rate tracker for signals, helping traders evaluate its reliability.
This script is a powerful tool for traders looking for a balance between simplicity and accuracy, leveraging advanced concepts like Fibonacci and Renko to deliver actionable insights.
Buy When There's Blood in the Streets StrategyStatistical Analysis of Drawdowns in Stock Markets
Drawdowns, defined as the decline from a peak to a trough in asset prices, are an essential measure of risk and market dynamics. Their statistical properties provide insights into market behavior during extreme stress periods.
Distribution of Drawdowns: Research suggests that drawdowns follow a power-law distribution, implying that large drawdowns, while rare, are more frequent than expected under normal distributions (Sornette et al., 2003).
Impacts of Extreme Drawdowns: During significant drawdowns (e.g., financial crises), the average recovery time is significantly longer, highlighting market inefficiencies and behavioral biases. For example, the 2008 financial crisis led to a 57% drawdown in the S&P 500, requiring years to recover (Cont, 2001).
Using Standard Deviations: Drawdowns exceeding two or three standard deviations from their historical mean are often indicative of market overreaction or capitulation, creating contrarian investment opportunities (Taleb, 2007).
Behavioral Finance Perspective: Investors often exhibit panic-selling during drawdowns, leading to oversold conditions that can be exploited using statistical thresholds like standard deviations (Kahneman, 2011).
Practical Implications: Studies on mean reversion show that extreme drawdowns are frequently followed by periods of recovery, especially in equity markets. This underpins strategies that "buy the dip" under specific, statistically derived conditions (Jegadeesh & Titman, 1993).
References:
Sornette, D., & Johansen, A. (2003). Stock market crashes and endogenous dynamics.
Cont, R. (2001). Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance.
Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable.
Kahneman, D. (2011). Thinking, Fast and Slow.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.
Global Index Spread RSI StrategyThis strategy leverages the relative strength index (RSI) to monitor the price spread between a global benchmark index (such as AMEX) and the currently opened asset in the chart window. By calculating the spread between these two, the strategy uses RSI to identify oversold and overbought conditions to trigger buy and sell signals.
Key Components:
Global Benchmark Index: The strategy compares the current asset with a predefined global index (e.g., AMEX) to measure relative performance. The choice of a global benchmark allows the trader to analyze the current asset's movement in the context of broader market trends.
Spread Calculation:
The spread is calculated as the percentage difference between the current asset's closing price and the global benchmark index's closing price:
Spread=Current Asset Close−Global Index CloseGlobal Index Close×100
Spread=Global Index CloseCurrent Asset Close−Global Index Close×100
This metric provides a measure of how the current asset is performing relative to the global index. A positive spread indicates the asset is outperforming the benchmark, while a negative spread signals underperformance.
RSI of the Spread: The RSI is then calculated on the spread values. The RSI is a momentum oscillator that ranges from 0 to 100 and is commonly used to identify overbought or oversold conditions in asset prices. An RSI below 30 is considered oversold, indicating a potential buying opportunity, while an RSI above 70 is overbought, suggesting that the asset may be due for a pullback.
Strategy Logic:
Entry Condition: The strategy enters a long position when the RSI of the spread falls below the oversold threshold (default 30). This suggests that the asset may have been oversold relative to the global benchmark and might be due for a reversal.
Exit Condition: The strategy exits the long position when the RSI of the spread rises above the overbought threshold (default 70), indicating that the asset may have become overbought and a price correction is likely.
Visual Reference:
The RSI of the spread is plotted on the chart for visual reference, making it easier for traders to monitor the relative strength of the asset in relation to the global benchmark.
Overbought and oversold levels are also drawn as horizontal reference lines (70 and 30), along with a neutral level at 50 to show market equilibrium.
Theoretical Basis:
The strategy is built on the mean reversion principle, which suggests that asset prices tend to revert to a long-term average over time. When prices move too far from this mean—either being overbought or oversold—they are likely to correct back toward equilibrium. By using RSI to identify these extremes, the strategy aims to profit from price reversals.
Mean Reversion: According to financial theory, asset prices oscillate around a long-term average, and any extreme deviation (overbought or oversold conditions) presents opportunities for price corrections (Poterba & Summers, 1988).
Momentum Indicators (RSI): The RSI is widely used in technical analysis to measure the momentum of an asset. Its application to the spread between the asset and a global benchmark allows for a more nuanced view of relative performance and potential turning points in the asset's price trajectory.
Practical Application:
This strategy works best in markets where relative strength is a key factor in decision-making, such as in equity indices, commodities, or forex markets. By assessing the performance of the asset relative to a global benchmark and utilizing RSI to identify extremes in price movements, the strategy helps traders to make more informed decisions based on potential mean reversion points.
While the "Global Index Spread RSI Strategy" offers a method for identifying potential price reversals based on relative strength and oversold/overbought conditions, it is important to recognize that no strategy is foolproof. The strategy assumes that the historical relationship between the asset and the global benchmark will hold in the future, but financial markets are subject to a wide array of unpredictable factors that can lead to sudden changes in price behavior.
Risk of False Signals:
The strategy relies heavily on the RSI to trigger buy and sell signals. However, like any momentum-based indicator, RSI can generate false signals, particularly in highly volatile or trending markets. In such conditions, the strategy may enter positions too early or exit too late, leading to potential losses.
Market Context:
The strategy may not account for macroeconomic events, news, or other market forces that could cause sudden shifts in asset prices. External factors, such as geopolitical developments, monetary policy changes, or financial crises, can cause a divergence between the asset and the global benchmark, leading to incorrect conclusions from the strategy.
Overfitting Risk:
As with any strategy that uses historical data to make decisions, there is a risk of overfitting the model to past performance. This could result in a strategy that works well on historical data but performs poorly in live trading conditions due to changes in market dynamics.
Execution Risks:
The strategy does not account for slippage, transaction costs, or liquidity issues, which can impact the execution of trades in real-market conditions. In fast-moving markets, prices may move significantly between order placement and execution, leading to worse-than-expected entry or exit prices.
No Guarantee of Profit:
Past performance is not necessarily indicative of future results. The strategy should be used with caution, and risk management techniques (such as stop losses and position sizing) should always be implemented to protect against significant losses.
Traders should thoroughly test and adapt the strategy in a simulated environment before applying it to live trades, and consider seeking professional advice to ensure that their trading activities align with their risk tolerance and financial goals.
References:
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Arvind - Gap Up/Down Alerts with Buy, Sell, CoverStrategy Description: Gap Up/Down Alerts with Buy, Sell, and Cover Conditions
This strategy identifies gap trading opportunities for both long (buy) and short (sell) setups, along with precise exit conditions for each, leveraging moving averages (MAs) and price action. The strategy is designed to dynamically work on any stock chart and provides clear visual and alert-based indications.
Core Logic
Buy Setup:
The strategy identifies bullish momentum for buying when:
The stock has gapped up (open price is significantly higher than the previous day's close by the user-defined percentage, e.g., 5%).
The price touches and bounces off either the 9-period moving average (MA) or the 21-period MA.
The 9 MA is above the 21 MA, indicating a bullish trend.
The price crosses the prior bar's high after bouncing.
Exit Condition for Buy:
The buy position is exited if the next bar's low drops below the buy bar's low.
Sell (Short) Setup:
The strategy identifies bearish momentum for short selling when:
The stock has either gapped up or gapped down.
The price is below both the 9-period MA and the 21-period MA.
The 9 MA is below the 21 MA, indicating a bearish trend.
The price touches the 9 MA but fails to stay above it, followed by the next bar breaking below the prior bar's low.
Cover Condition for Sell:
The short position is covered if the next bar's high rises above the sell bar's high.
Visual Indicators
Green Triangle Below the Bar: Signals a buy entry.
Orange Triangle Above the Bar: Indicates a buy exit.
Red Triangle Above the Bar: Signals a short sell entry.
Black Triangle Above the Bar: Indicates a cover (exit short).
Alerts
Custom alerts are included for real-time notifications of:
Buy Signal: Notifies when a buy condition is met.
Buy Exit: Alerts when the buy exit condition is triggered.
Sell Signal: Notifies when a short sell condition is met.
Cover Signal: Alerts when the short position should be covered.
Benefits of the Strategy
Dynamic Gap Detection: Identifies stocks that show significant gaps up or down, signaling high volatility and potential trading opportunities.
Trend Confirmation: Uses the alignment of moving averages (9 MA and 21 MA) to confirm bullish or bearish trends.
Clear Entry/Exit Rules: Ensures disciplined trading by using defined entry and exit criteria.
Versatile Application: Works on any chart and timeframe, making it suitable for intraday, swing, or positional trading.
Visual and Alert-Based Signals: Provides actionable insights with visual markers on the chart and real-time alerts.
Use Cases
This strategy is ideal for traders looking to capitalize on:
Stocks that exhibit high momentum after a gap up or down.
Trend-following setups for long and short trades.
Quick and disciplined exits based on well-defined criteria.
Trend Following Strategy with KNN
### 1. Strategy Features
This strategy combines the K-Nearest Neighbors (KNN) algorithm with a trend-following strategy to predict future price movements by analyzing historical price data. Here are the main features of the strategy:
1. **Dynamic Parameter Adjustment**: Uses the KNN algorithm to dynamically adjust parameters of the trend-following strategy, such as moving average length and channel length, to adapt to market changes.
2. **Trend Following**: Captures market trends using moving averages and price channels to generate buy and sell signals.
3. **Multi-Factor Analysis**: Combines the KNN algorithm with moving averages to comprehensively analyze the impact of multiple factors, improving the accuracy of trading signals.
4. **High Adaptability**: Automatically adjusts parameters using the KNN algorithm, allowing the strategy to adapt to different market environments and asset types.
### 2. Simple Introduction to the KNN Algorithm
The K-Nearest Neighbors (KNN) algorithm is a simple and intuitive machine learning algorithm primarily used for classification and regression problems. Here are the basic concepts of the KNN algorithm:
1. **Non-Parametric Model**: KNN is a non-parametric algorithm, meaning it does not make any assumptions about the data distribution. Instead, it directly uses training data for predictions.
2. **Instance-Based Learning**: KNN is an instance-based learning method that uses training data directly for predictions, rather than generating a model through a training process.
3. **Distance Metrics**: The core of the KNN algorithm is calculating the distance between data points. Common distance metrics include Euclidean distance, Manhattan distance, and Minkowski distance.
4. **Neighbor Selection**: For each test data point, the KNN algorithm finds the K nearest neighbors in the training dataset.
5. **Classification and Regression**: In classification problems, KNN determines the class of a test data point through a voting mechanism. In regression problems, KNN predicts the value of a test data point by calculating the average of the K nearest neighbors.
### 3. Applications of the KNN Algorithm in Quantitative Trading Strategies
The KNN algorithm can be applied to various quantitative trading strategies. Here are some common use cases:
1. **Trend-Following Strategies**: KNN can be used to identify market trends, helping traders capture the beginning and end of trends.
2. **Mean Reversion Strategies**: In mean reversion strategies, KNN can be used to identify price deviations from the mean.
3. **Arbitrage Strategies**: In arbitrage strategies, KNN can be used to identify price discrepancies between different markets or assets.
4. **High-Frequency Trading Strategies**: In high-frequency trading strategies, KNN can be used to quickly identify market anomalies, such as price spikes or volume anomalies.
5. **Event-Driven Strategies**: In event-driven strategies, KNN can be used to identify the impact of market events.
6. **Multi-Factor Strategies**: In multi-factor strategies, KNN can be used to comprehensively analyze the impact of multiple factors.
### 4. Final Considerations
1. **Computational Efficiency**: The KNN algorithm may face computational efficiency issues with large datasets, especially in real-time trading. Optimize the code to reduce access to historical data and improve computational efficiency.
2. **Parameter Selection**: The choice of K value significantly affects the performance of the KNN algorithm. Use cross-validation or other methods to select the optimal K value.
3. **Data Standardization**: KNN is sensitive to data standardization and feature selection. Standardize the data to ensure equal weighting of different features.
4. **Noisy Data**: KNN is sensitive to noisy data, which can lead to overfitting. Preprocess the data to remove noise.
5. **Market Environment**: The effectiveness of the KNN algorithm may be influenced by market conditions. Combine it with other technical indicators and fundamental analysis to enhance the robustness of the strategy.
GoldenTradz EMA+SMA Insight Multi Timeframe - [TilakBala]GoldenTradz EMA+SMA Insight Multi-Timeframe
📊 Indicator By: TilakBala from GoldenTradz — Revolutionize your trading approach with precision and insight!
Unlock the full potential of moving averages with the GoldenTradz EMA+SMA Insight indicator. This feature-packed tool combines the strength of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA), offering unmatched flexibility and clarity for traders. Whether you're a beginner or a pro, this indicator empowers you to make well-informed trading decisions across multiple timeframes.
Key Features & Advantages:
Multi-Timeframe Analysis: Seamlessly analyze market trends using EMAs and SMAs from different timeframes on a single chart.
Gain a broader perspective by comparing short-term and long-term trends.
Customizable Settings:
Adjust EMA and SMA lengths, sources, and timeframes to fit your trading strategy perfectly.
Enable or disable specific moving averages for a clutter-free chart view.
Enhanced Trend Detection:
Identify bullish and bearish trends quickly using visually distinct EMAs and SMAs.
Use shorter EMAs for faster signals and longer SMAs for reliable trend confirmation.
Overlay Design:
Plots moving averages directly on the price chart for effortless analysis.
Distinct colors and line thicknesses ensure clear identification of each moving average.
Versatile Applications:
Suitable for scalping, day trading, swing trading, and long-term investments.
Works flawlessly with stocks, forex, cryptocurrencies, commodities, indices, and more.
Decision-Making Support:
Crossovers between EMAs and SMAs help identify potential buy or sell opportunities.
Monitor key support and resistance levels dynamically.
Efficiency in Market Noise:
EMAs provide rapid responsiveness in volatile markets.
SMAs help smooth out market noise for clearer long-term trends.
Adaptable to Any Strategy:
Perfect for breakout, trend-following, and mean-reversion strategies.
Combine with other indicators for a comprehensive trading system.
User-Friendly:
Intuitive interface with clear input fields for quick setup.
Suitable for traders of all experience levels.
📊 Indicator By: TilakBala from GoldenTradz — Revolutionize your trading approach with precision and insight!
Transform your trading with GoldenTradz EMA+SMA Insight — the ultimate tool for trend and momentum analysis.
Gupta TradersThis is completely failed strategy,
Trades taken in opposite direction is more worth it than in forward direction.
Color Candle - Time Algo- Script para colorir as barrar de um minuto especifico do gráfico afim de identificar levels importantes do tempo e preço.
- Script to color the bars of a specific minute on the chart in order to identify important time and price levels.
- all based on GB TIME.
- still under development.
Request from a friend and teacher, tactile, true enigma in person.
Solotov, você é viaxx mas é meu amigo.
Igor, ta marolando.
Com os comentários de solotov,
- não precisa mais de relógio.
Sri Yantra MTF - AynetSri Yantra MTF - Aynet Script Overview
This Pine Script generates a Sri Yantra-inspired geometric pattern overlay on price charts. The pattern is dynamically updated based on multi-timeframe (MTF) inputs, utilizing high and low price ranges, and adjusting its size relative to a chosen multiplier.
The Sri Yantra is a sacred geometric figure used in various spiritual and mathematical contexts, symbolizing the interconnectedness of the universe. Here, it is applied to visualize structured price levels.
Scientific and Technical Explanation
Multi-Timeframe Integration:
Base Timeframe (baseRes): This is the primary timeframe for the analysis. The opening price and ATR (Average True Range) are calculated from this timeframe.
Pattern Timeframe (patternRes): Defines the granularity of the pattern. It ensures synchronization with price movements on specific time intervals.
Geometric Construction:
ATR-Based Scaling: The script uses ATR as a volatility measure to dynamically size the geometric pattern. The sizeMult input scales the pattern relative to price volatility.
Pattern Width (barOffset): Defines the horizontal extent of the pattern in terms of bars. This ensures the pattern is aligned with price movements and scales appropriately.
Sri Yantra-Like Geometry:
Outer Square: A bounding box is drawn around the price level.
Triangles: Multiple layers of triangles (primary, secondary, and tertiary) are calculated and drawn to mimic the structure of the Sri Yantra. These triangles converge and diverge based on price levels.
Horizontal Lines: Added at key levels to provide additional structure and aesthetic alignment.
Dynamic Updates:
The pattern recalculates and redraws itself on the last bar of the selected timeframe, ensuring it adapts to real-time price data.
A built-in check identifies new bars in the chosen timeframe (patternRes), ensuring accurate updates.
Information Table:
Displays the selected base and pattern timeframes in a table format on the top-right corner of the chart.
Allows traders to see the active settings for quick adjustments.
Key Inputs
Style Settings:
Pattern Color: Customize the color of the geometric patterns.
Size Multiplier (sizeMult): Adjusts the size of the pattern relative to price movements.
Line Width: Controls the thickness of the geometric lines.
Timeframe Settings:
Base Resolution (baseRes): Timeframe for calculating the pattern's anchor (default: daily).
Pattern Resolution (patternRes): Timeframe granularity for the pattern’s formation.
Geometric Adjustments:
Pattern Width (barOffset): Horizontal width in bars.
ATR Multiplier (rangeSize): Vertical size adjustment based on price volatility.
Scientific Concepts
Volatility Representation:
ATR (Average True Range): A standard measure of market volatility, representing the average range of price movements over a defined period. Here, ATR adjusts the vertical height of the geometric figures.
Geometric Symmetry:
The script emulates symmetry similar to the Sri Yantra, aligning with the principles of sacred geometry, which often appear in nature and mathematical constructs. Symmetry in financial data visualizations can aid in intuitive interpretation of price movements.
Multi-Timeframe Fusion:
Synchronizing patterns with multiple timeframes enhances the relevance of overlays for different trading strategies. For example, daily trends combined with hourly patterns can help traders optimize entries and exits.
Visual Features
Outer Square:
Drawn to encapsulate the geometric structure.
Represents the broader context of price levels.
Triangles:
Three layers of interlocking triangles create a fractal pattern, providing a visual alignment to price dynamics.
Horizontal Lines:
Emphasize critical levels within the pattern, offering visual cues for potential support or resistance areas.
Information Table:
Displays the active timeframe settings, helping traders quickly verify configurations.
Applications
Trend Visualization:
Patterns overlay on price movements provide a clearer view of trend direction and potential reversals.
Volatility Mapping:
ATR-based scaling ensures the pattern adjusts to varying market conditions, making it suitable for different asset classes and trading strategies.
Multi-Timeframe Analysis:
Integrates higher and lower timeframes, enabling traders to spot confluences between short-term and long-term price levels.
Potential Enhancements
Add Fibonacci Levels: Overlay Fibonacci retracements within the pattern for deeper price level insights.
Dynamic Alerts: Include alert conditions when price intersects key geometric lines.
Custom Labels: Add text descriptions for critical intersections or triangle centers.
This script is a unique blend of technical analysis and sacred geometry, providing traders with an innovative way to visualize market dynamics.
Double RSI with MA & MFIThis Pine Script creates an indicator combining two RSI calculations (short and long) with a Money Flow Index (MFI). It includes customizable settings for each RSI and MFI, and plots them with dynamic colors. The script also adds optional smoothing using various types of moving averages. Visual enhancements like gradient fills for overbought and oversold zones are included. Overall, it provides a comprehensive tool for analyzing market momentum.
Indicator Overview
Title: Double RSI with MA & MFI
Short Title: RSI with MA & MFI
Version: 5
Inputs
Short RSI Settings: Length, Source, Timeframe
Long RSI Settings: Length, Source, Timeframe
MFI Settings: Length
Moving Average Settings: Type, Length
Calculations
Short RSI:
Uses the specified length, source, and timeframe.
Calculates RSI based on price changes.
Colors: Green (>= 60), Red (<= 40), Yellow (in between).
Long RSI:
Similar to Short RSI but with its own length, source, and timeframe.
Single color: Blue.
Money Flow Index (MFI):
Calculated using the typical price (hlc3) and specified length.
Plotted in purple.
Plotting
Short RSI: Plotted with dynamic colors.
Long RSI: Plotted in blue.
MFI: Plotted in purple.
RSI Levels: Upper (80), Mid Upper (60), Mid Lower (40), Lower (20) with dotted lines.
Gradient Fill: Overbought (green) and Oversold (red) areas.
Moving Average (MA)
Types: SMA, EMA, SMMA (RMA), WMA, VWMA.
Calculation: Based on the selected type and length.
Plotting: Plotted if enabled, in light grey.
This script combines two RSI indicators with different settings, a Money Flow Index, and an optional moving average for smoothing the RSI values. It also includes visual enhancements like dynamic coloring and gradient fills for better readability
TICKFLOW_FUTURES-ATR-ZONESThe TICKFLOW_FUTURES-ATR-ZONES script is a dynamic indicator designed to help traders identify key zones of price action based on ATR (Average True Range) and Bollinger Bands. This script combines customizable moving averages, volatility-based bands, and trend slope calculations to provide a clear visual framework for analyzing trends, detecting potential reversals, and identifying high-probability buy/sell zones.
Key Features:
Dynamic ATR Zones:
Upper and lower bands are calculated using ATR and adjusted dynamically based on the visible price range, ensuring alignment with current market conditions.
Slope-Based Color Coding:
The middle line (moving average) dynamically changes its color based on the slope to indicate bullish, bearish, or neutral trends.
Bollinger Band Squeeze Detection:
Highlights periods of price contraction using Bollinger Band width, helping identify potential breakout setups.
Buy and Sell Signals:
Displays visual markers (BUY/SELL) based on slope changes and price action relative to the dynamic middle line.
Customizable Inputs:
Includes options to adjust ATR multiplier, Bollinger Band settings, moving average type, slope lookback period, and color preferences.
Visual Zones:
Shaded areas representing ATR-based upper and lower zones for a clear and intuitive price action framework.
Usage Instructions:
Clean Chart:
Use the script on a clean chart for best results. This ensures that the plotted zones, lines, and markers are easily interpretable without interference.
Understanding the Components:
The middle line represents the selected moving average type, providing the directional bias.
Upper and lower zones indicate potential reversal or continuation levels based on ATR.
BUY/SELL markers suggest trend initiation points but should be confirmed with additional analysis.
Customization:
Adjust input parameters (e.g., ATR multiplier, Bollinger Band settings) to fit your trading style and market conditions.
Important Notes:
This script works as a standalone tool and does not require other indicators to function.
Avoid using it with additional scripts on the same chart unless explicitly needed and described in your analysis.
Heikin-Ashi + SSL + TDI + Supertrend IndicatorPrimary Confirmation (15-Minute):
Bullish Signal:
Heikin-Ashi candle is green (close > open).
MACD Line crosses above the Signal Line, and the histogram is positive.
Bearish Signal:
Heikin-Ashi candle is red (close < open).
MACD Line crosses below the Signal Line, and the histogram is negative.
Secondary Confirmation (1-Minute):
Bullish Signal:
Price is above the SSL Channel (upper line).
Supertrend is bullish.
TDI Green Line is above the Red Line.
Bearish Signal:
Price is below the SSL Channel (lower line).
Supertrend is bearish.
TDI Green Line is below the Red Line.
Trade Execution:
A buy or sell signal is plotted on the chart when both the 15-minute and 1-minute conditions align.
9 EMA and 15 EMA Rejection and Pullbackashif ali 9 EMA and 15 EMA Rejection and Pullback and 9 EMA and 15 EMA Rejection and Pullback and 9 EMA and 15 EMA Rejection and Pullback
Gains and Drawdowns with Standard DeviationsThis “Gains and Drawdowns with Standard Deviations” indicator helps in analyzing and visualizing the percentage gains and drawdown phases of a market or asset relative to its historical range. By calculating gains from the lowest low and drawdowns from the highest high over a specified lookback period, this indicator provides deeper insights into price movements and risk.
Key Features and Applications:
1. Gain and Drawdown Calculation:
• Gains: The indicator calculates the percentage gain from the lowest price point within a specific lookback period (e.g., 250 days).
• Drawdowns: Drawdowns are calculated as the percentage change from the highest point in the same period. This helps in identifying the maximum loss phases.
2. Standard Deviation:
• The indicator computes the standard deviation of both gains and drawdowns over a specified period (e.g., 250 days), allowing you to quantify volatility.
• Three bands (1st, 2nd, and 3rd standard deviations) are plotted for both gains and drawdowns, representing the frequency and magnitude of price movements within the normal volatility range.
3. Extreme Movements Highlighting:
• The indicator highlights extreme gains and drawdowns when they exceed user-defined thresholds. This helps in identifying significant market events or turning points.
4. Customizable Thresholds:
• Users can adjust the thresholds for extreme gains and drawdowns, as well as the lookback period for calculating gains, drawdowns, and standard deviations, making the indicator highly adaptable to specific needs.
Application in Portfolio Management:
The use of standard deviation in portfolio management is essential for assessing the risk and volatility of a portfolio. According to Modern Portfolio Theory (MPT) by Harry Markowitz, diversification of assets in a portfolio helps to minimize overall risk (especially the standard deviation), while maximizing returns. The standard deviation of a portfolio measures the volatility of its returns, with higher standard deviation indicating higher risk.
Scientific Source: Markowitz, H. M. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91.
Markowitz’s theory suggests that an optimized portfolio, by minimizing the standard deviation of returns and combining a diversified asset allocation, can achieve better risk-adjusted returns.
Conclusion:
This indicator is particularly useful for traders and portfolio managers who want to understand and visualize market risk and extreme events. By using gains, drawdowns, and volatility metrics, it allows for systematic monitoring and evaluation of price movements, leading to more informed decisions in trading or portfolio management. A comprehensive understanding of price behavior and volatility helps in optimizing risk management and making strategic market entries.
Key Features:
• Visualization of Gains and Drawdowns with color-coded highlights for extreme movements.
• Standard Deviation Calculations for detailed volatility analysis.
• Customizable Thresholds for identifying extreme market events.
This indicator is a valuable tool for analyzing market data from a scientific standpoint, improving risk management, and making data-driven decisions based on historical performance.
EMA Crossover with Support and ResistanceBuy Signal: When the 9 EMA crosses above the 20 EMA, it's a potential bullish signal, indicating the price might continue upward.
Sell Signal: When the 9 EMA crosses below the 20 EMA, it's a potential bearish signal, indicating the price might continue downward.
RSI on Price Indicator Advanced Multi-Level RSIRSI on Price Indicator | Advanced Multi-Level RSI with Customizable Levels & Background Fill (Free Pine Script for TradingView)
Unlock the full potential of your TradingView charts with the 'RSI on Price NEW' indicator. This free Pine Script offers multi-level RSI bands, customizable overbought/oversold levels, and eye-catching background fills. Perfect for intraday, daily, weekly, or monthly analysis. Enhance your trading strategy today!
Take your trading analysis to the next level with the 'RSI on Price NEW' indicator for TradingView. This powerful and free Pine Script overlay brings the RSI directly onto your price chart, combining multiple levels of RSI calculations for detailed insights. With fully customizable settings for RSI periods, overbought/oversold thresholds, and dynamic color-coded background fills, this script is perfect for traders who want precision and clarity. Whether you're trading intraday, daily, weekly, or monthly charts, this script offers unparalleled versatility. Optimize your trading strategy today with this innovative RSI tool!
Black Line 50 RSI in center
above that 3 line is 60, 70, 80
below black line is 40, 30, 20 RSI
MegaGas Bollinger Bands with Divergence and Circle SignalsIndicator: MegaGas Bollinger Bands with Divergence and Circle Signals
This script provides a powerful combination of Bollinger Bands, RSI Divergence detection, and signal visualization tools. Designed with flexibility and precision in mind, it aims to assist traders in identifying trend reversals, volatility zones, and divergence-based trading opportunities. The script is well-suited for swing trading, momentum trading, and even scalping when adapted to lower timeframes.
How It Works:
Bollinger Bands:
Bollinger Bands are used to detect price volatility and overbought/oversold conditions. The script calculates:
Basis Line: A 34-period Simple Moving Average (SMA) as the core trend line.
Upper Bands: Bands positioned 1x and 2x the standard deviation above the SMA.
Lower Bands: Bands positioned 1x and 2x the standard deviation below the SMA. These levels provide dynamic support and resistance zones, highlighting breakout and reversion opportunities.
RSI Divergence Detection:
The indicator detects bullish divergence (when RSI forms a higher low while price forms a lower low) and bearish divergence (when RSI forms a lower high while price forms a higher high). These divergences often precede significant reversals or momentum shifts.
Bullish divergence is displayed with blue triangles (up).
Bearish divergence is displayed with orange triangles (down).
Buy and Sell Signals:
Circle Signals are generated when price crosses key Bollinger Bands levels:
A green circle appears when the price crosses above the lower band (potential buy signal).
A red circle appears when the price crosses below the upper band (potential sell signal).
These signals help identify potential entry and exit points for trades, particularly in trend-following or mean-reversion strategies.
Trend Reference (Moving Average):
A 50-period Simple Moving Average (SMA) is included as a trend reference, helping traders gauge the overall market direction. Use this to confirm divergence signals and avoid trades against the prevailing trend.
Why This Indicator Is Unique:
This script integrates multiple tools in a meaningful way, emphasizing contextual trading signals. Unlike standalone Bollinger Bands or RSI indicators, it introduces:
Advanced Divergence Analysis: Enhancing traditional RSI with divergence-based alerts.
Dynamic Signal Filtering: Preventing repetitive signals by introducing state-based logic for circles and divergence signals.
Trend Alignment: Combining Bollinger Bands with an SMA to filter trades based on the prevailing trend.
How to Use:
Setup:
Apply the indicator to any chart and timeframe. For swing trading, higher timeframes like 4H or 1D are recommended.
Adjust the RSI, Bollinger Bands, and Moving Average lengths to match your strategy and asset.
Signals:
Look for divergence signals (triangles) as early warnings of trend reversals. Confirm these with price action or other tools.
Use circle signals (green/red) to time potential entries/exits around Bollinger Band extremes.
Confirmation:
Combine divergence and circle signals with the SMA line to avoid counter-trend trades. For example, take bullish signals when the price is above the SMA and bearish signals when it is below.
Chart Clarity:
The script is published with a clean chart for clarity. It visualizes all signals with distinct shapes (triangles and circles) and colors, ensuring they are easily recognizable. Bollinger Bands and the SMA are plotted with transparency to avoid clutter.
Originality:
This script is a thoughtful blend of Bollinger Bands and RSI divergence detection, carefully designed to provide traders with actionable insights. It introduces state-based logic to manage repetitive signals and seamlessly integrates trend filtering, making it a valuable tool for both novice and experienced traders.
Custom Ratio IndicatorThis indicator allows users to compare the price ratio of two customizable trading pairs. By dividing the closing price of the first trading pair by the second, it calculates and plots the resulting ratio on the chart. It is designed for traders who want to analyze correlations or relative performance between two assets. The default pairs are ETHUSDT and BTCUSDT, and users can customize these inputs. The indicator supports high precision to ensure accurate representation of small or large ratios. Additionally, the current ratio is dynamically displayed on the chart for easy reference.
Forward Price Performance TableThis calculates the percentage price changes for three key timeframes:
1 week (5 trading days ago)
1 month (17 trading days ago),
3 months (45 trading days ago).
This is to show a forward looking performance based on earlier timeframes that traditionally used. This is the framework I team uses to calculate performance metrics.
Custom Text Box - MOJE_SMALLHere Ive tuned an already good indicator for daily bias, just by lowering the text fond from normal to small. So you can write down more info and still se the chart clearly!
Monthly RSI Crossing 60 with ExitPrash
Take entry when Monthly RSI Crossing 60. Exit when 10 week low is breached.
Global vs National Index Spread RSIThe Global vs National Index Spread RSI indicator visualizes the relative strength of national stock indices compared to a global benchmark (e.g., AMEX). It calculates the percentage spread between the closing prices of each national index and the global index, applying the Relative Strength Index (RSI) to each spread.
How It Works
Spread Calculation: The spread represents the percentage difference between a national index and the global index.
RSI Application: RSI is applied to these spreads to identify overbought or oversold conditions in the relative performance of the national indices.
Reference Lines: Overbought (70), oversold (30), and neutral (50) levels help guide interpretation.
Insights from Research
The correlation between global and national indices provides insights into market integration and interdependence. Studies such as Forbes & Rigobon (2002) emphasize the importance of understanding these linkages during periods of financial contagion. Observing spread trends with RSI can aid in identifying shifts in investor sentiment and regional performance anomalies.
Use Cases
- Detect divergences between national and global markets.
- Identify overbought or oversold conditions for specific indices.
- Complement portfolio management strategies by monitoring geographic performance.
References
Forbes, K. J., & Rigobon, R. (2002). "No contagion, only interdependence: Measuring stock market co-movements." Journal of Finance.
Eun, C. S., & Shim, S. (1989). "International transmission of stock market movements." Journal of Financial and Quantitative Analysis.
