3 Candle AlertThis is a test for integration using a webhook. I am publishing it so I can share it. Ultimately, this is what we want to do:
1. Trade Entry Rules:
Wait until at least the 3rd bar of the day (15 minutes after market open) before entering the first trade.
Order of Priority for Entry:
Look for two consecutive volume bars of the same color (the second bar must have higher volume than the first).
Look for a “price push” beyond the high or low of the day (as determined in the first 15 minutes).
2. Trading Direction:
If the volume bars are RED, I take a Long Position.
If the volume bars are GREEN, I take a Short Position.
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Dabel MS + FVGThis script is designed to assist traders by identifying market structures, imbalances, and potential trade opportunities using Break of Structure (BOS) and Market Structure Shifts (MSS). It visually highlights imbalances in price action, key pivots, and market structure changes, providing actionable information for making trading decisions.
Key features:
Imbalances Detection: Highlights bullish and bearish price gaps (Fair Value Gaps) using colored boxes. Users can choose the line style (solid, dashed, or dotted) for imbalance midlines.
Market Structure Analysis: Tracks pivot highs and lows to identify BOS and MSS in two separate market structures with adjustable pivot strengths.
Customizable Visualization: Allows users to choose line styles, colors, and display options for both imbalances and market structures.
Alerts: Alerts traders when BOS or MSS occur, helping to monitor the market effectively.
Trading Strategy
Imbalance Trading:
Imbalances (gaps) represent areas where supply or demand was left unfilled. These gaps often act as magnet zones where the price revisits to fill.
Bullish Imbalance: Look for buying opportunities when price enters a green imbalance zone.
Bearish Imbalance: Look for selling opportunities when price enters a red imbalance zone.
Use the midline of the imbalance box as a key reference point for potential reversals.
Break of Structure (BOS) and Market Structure Shift (MSS):
BOS: Indicates a continuation of the existing trend. For example:
Bullish BOS: Look for continuation in the uptrend after a high is broken.
Bearish BOS: Look for continuation in the downtrend after a low is broken.
MSS: Suggests a potential reversal in market structure. For example:
Bullish MSS: Indicates a possible shift from a bearish to bullish market.
Bearish MSS: Indicates a potential shift from a bullish to bearish market.
Multiple Market Structures:
This script provide two sets of market structures, allowing traders to compare short-term and long-term trends.
Adjust the pivot strength to suit your trading style (lower for intraday trading, higher for swing or positional trading).
Entry and Exit:
Entry: Look for entries near imbalances or after confirmed BOS/MSS in line with the overall trend.
Exit: Place stop-loss below/above recent pivots and take profit at nearby support/resistance or imbalance zones.
For New Traders
Focus on Basics: Understand what BOS and MSS mean and how they signal trend direction or reversals.
Use Alerts: Rely on the script's alert system to catch important moments without staring at charts all day.
Start Small: Test this strategy on a demo account before using it live. You can understand it more with practice.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Follow Through Day (FTD) + Sweep [TrendX_]The Follow Through Day (FTD) + Sweep indicator is a Trend-following tool mixing William O'Neil's original FTD concept and Liquidity concept. This indicator helps you identify potential subsequent bullish trends with greater precision by combining volume analysis, price action, and liquidity concepts.
💎 FEATURES
Follow Through Day Candle (FTD Candle)
The FTD, pioneered by William O'Neil, serves as a reliable signal for identifying the beginning of new bull markets. It's particularly valuable because it combines multiple market factors - price action, volume, and timing - to confirm genuine market reversals rather than temporary bounces.
The power of the FTD lies in its ability to distinguish between ordinary market fluctuations and significant trend changes. By requiring specific criteria to be met across multiple sessions, it helps filter out false signals and identifies high-probability reversal points where institutional investors are likely beginning to accumulate positions.
Sweep Area
The Sweep area feature enhances the traditional FTD concept by incorporating modern liquidity analysis. This overlay identifies zones where large market participants are likely to trigger stop losses before continuing the trend. These areas often represent optimal entry points for traders looking to join the new uptrend with reduced risk.
🔎 BREAKDOWN
FTD Candle
The FTD formation process occurs in two distinct phases: Setup and Completion.
Setup Phase
Strong Market Decline
The market must first experience a significant downtrend
This selling pressure helps clear out weak hands and creates oversold conditions
The decline creates the potential energy for a powerful reversal
First Recovery Session
Marks the initial sign of buying pressure emerging
Often characterized by a strong reversal candle
Represents the first indication that selling pressure may be exhausting
Recovery Confirmation
The second and third days must maintain prices above the new pivot low
This consolidation period helps confirm the validity of the initial bounce
Shows that sellers are no longer in control of price action
Completion Phase:
Supply Test Session
Low volume indicates diminishing selling pressure
Price remains above the pivot low
Creates the foundation for institutional buyers to begin accumulating
Breakout Day
Price increase exceeds average profit of bullish candles
Volume increases by at least 15% compared to previous session
Shows strong institutional commitment to the new uptrend
Timing Window
Must occur between the 4th and 8th candle after First Recovery Session
This specific timing helps confirm the sustainability of the reversal
Based on O'Neil's research of historical market bottoms
FTD Sweep
The Post-FTD Phase introduces the Sweep concept, which is crucial for understanding how large market participants operate. This feature leverages the liquidity concept because institutional traders often need to trigger stop losses to accumulate larger positions at better prices. This helps:
Create liquidity pools for large position entries
Shake out weak hands before continuing the trend
Test the strength of the new trend by absorbing selling pressure
⚙️ USAGE
Sweep + TP & SL Strategy
Example: BTCUSDT (1D) - Replay back to 9th November 2024
After an FTD candle forms, traders can adopt a systematic approach to enhance their trading strategy. First, they should determine the swing range and convert the post-FTD zone into concrete stop loss and take profit levels, which are based on the price action during the FTD formation. Next, traders should wait for a sweep formation, as this indicates that institutional players are accumulating positions. A quick price rejection from the sweep level should be observed before executing an entry.
The reasoning behind this strategy is rooted in market microstructure. By waiting for the sweep, traders position themselves alongside institutional players who need to build large positions without causing adverse price movement. The sweep creates the liquidity they need, and the subsequent move often represents the true trend continuation.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Range Channel by Atilla YurtsevenThis script creates a dynamic channel around a user-selected moving average (MA). It calculates the relative difference between price and the MA, then finds the average of the positive differences and the negative differences separately. Using these averages, it plots upper and lower bands around the MA as well as a histogram-like oscillator to show when price moves above or below the average thresholds.
How It Works
Moving Average Selection
The indicator allows you to choose among multiple MA types (SMA, EMA, WMA, Linear Regression, etc.). Depending on your preference, it calculates the chosen MA for the selected lookback period.
Relative Difference Calculation
It then computes the percentage difference between the source (typically the closing price) and the MA. (diff = (src / ma - 1) * 100)
Positive & Negative Averages
- Positive differences are averaged and represent how far the price typically moves above the MA.
- Negative differences are similarly averaged for when price moves below the MA.
Range Channel & Oscillator
- The channel is plotted around the MA using the average positive and negative differences (Upper Edge and Lower Edge).
- The “Untrended” histogram plots the difference (diff). Green bars occur when price is above the MA on average, and red bars when below. Two additional lines mark the upper and lower average thresholds on this histogram.
How to Use
Identify Overbought/Oversold Zones: The upper edge can serve as a dynamic overbought level, while the lower edge can suggest potential oversold conditions. When the histogram approaches or crosses these levels, it may signal price extremes relative to its average movement.
Trend Confirmation: Compare price action relative to the channel. If price and the histogram consistently remain above the MA and upper threshold, it could indicate a stronger bullish trend. If they remain below, it might signal a prolonged bearish trend.
Entry/Exit Timings:
- Entry: Traders can look for moments when price breaks back inside the channel from an extreme, anticipating a mean reversion.
- Exit: Watching how price interacts with these dynamic edges can help define stop-loss or take-profit points.
Because these thresholds adapt over time based on actual price behavior, they can be more responsive than fixed-percentage bands. However, like all indicators, it’s most effective when used in conjunction with other technical and fundamental tools.
Disclaimer
This script is provided for educational and informational purposes only. It does not guarantee any specific outcome or profit. Use it at your own discretion and risk.
Trade smart, stay safe.
Atilla Yurtseven
EMA RSI Trend Reversal Ver.1Overview:
The EMA RSI Trend Reversal indicator combines the power of two well-known technical indicators—Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI)—to identify potential trend reversal points in the market. The strategy looks for key crossovers between the fast and slow EMAs, and uses the RSI to confirm the strength of the trend. This combination helps to avoid false signals during sideways market conditions.
How It Works:
Buy Signal:
The Fast EMA (9) crosses above the Slow EMA (21), indicating a potential shift from a downtrend to an uptrend.
The RSI is above 50, confirming strong bullish momentum.
Visual Signal: A green arrow below the price bar and a Buy label are plotted on the chart.
Sell Signal:
The Fast EMA (9) crosses below the Slow EMA (21), indicating a potential shift from an uptrend to a downtrend.
The RSI is below 50, confirming weak or bearish momentum.
Visual Signal: A red arrow above the price bar and a Sell label are plotted on the chart.
Key Features:
EMA Crossovers: The Fast EMA crossing above the Slow EMA signals potential buying opportunities, while the Fast EMA crossing below the Slow EMA signals potential selling opportunities.
RSI Confirmation: The RSI helps confirm trend strength—values above 50 indicate bullish momentum, while values below 50 indicate bearish momentum.
Visual Cues: The strategy uses green arrows and red arrows along with Buy and Sell labels for clear visual signals of when to enter or exit trades.
Signal Interpretation:
Green Arrow / Buy Label: The Fast EMA (9) has crossed above the Slow EMA (21), and the RSI is above 50. This is a signal to buy or enter a long position.
Red Arrow / Sell Label: The Fast EMA (9) has crossed below the Slow EMA (21), and the RSI is below 50. This is a signal to sell or exit the long position.
Strategy Settings:
Fast EMA Length: Set to 9 (this determines how sensitive the fast EMA is to recent price movements).
Slow EMA Length: Set to 21 (this smooths out price movements to identify the broader trend).
RSI Length: Set to 14 (default setting to track momentum strength).
RSI Level: Set to 50 (used to confirm the strength of the trend—above 50 for buy signals, below 50 for sell signals).
Risk Management (Optional):
Use take profit and stop loss based on your preferred risk-to-reward ratio. For example, you can set a 2:1 risk-to-reward ratio (2x take profit for every 1x stop loss).
Backtesting and Optimization:
Backtest the strategy on TradingView by opening the Strategy Tester tab. This will allow you to see how the strategy would have performed on historical data.
Optimization: Adjust the EMA lengths, RSI period, and risk-to-reward settings based on your asset and time frame.
Limitations:
False Signals in Sideways Markets: Like any trend-following strategy, this indicator may generate false signals during periods of low volatility or sideways movement.
Not Suitable for All Market Conditions: This indicator performs best in trending markets. It may underperform in choppy or range-bound markets.
Strategy Example:
XRP/USD Example:
If you're trading XRP/USD and the Fast EMA (9) crosses above the Slow EMA (21), while the RSI is above 50, the indicator will signal a Buy.
Conversely, if the Fast EMA (9) crosses below the Slow EMA (21), and the RSI is below 50, the indicator will signal a Sell.
Bitcoin (BTC/USD):
On the BTC/USD chart, when the indicator shows a green arrow and a Buy label, it’s signaling a potential long entry. Similarly, a red arrow and Sell label indicate a short entry or exit from a previous long position.
Summary:
The EMA RSI Trend Reversal Indicator helps traders identify potential trend reversals with clear buy and sell signals based on the EMA crossovers and RSI confirmations. By using green arrows and red arrows, along with Buy and Sell labels, this strategy offers easy-to-understand visual signals for entering and exiting trades. Combine this with effective risk management and backtesting to optimize your trading performance.
Enigma Liquidity Concept
Enigma Liquidity Concept
Empowering Traders with Multi-Timeframe Analysis and Dynamic Fibonacci Insights
Overview
The Enigma Liquidity Concept is an advanced indicator designed to bridge multi-timeframe price action with Fibonacci retracements. It provides traders with high-probability buy and sell signals by combining higher time frame market direction and lower time frame precision entries. Whether you're a scalper, day trader, or swing trader, this tool offers actionable insights to refine your entries and exits.
What Makes It Unique?
Multi-Timeframe Signal Synchronization:
Higher time frame bullish or bearish engulfing patterns are used to define the directional bias.
Lower time frame retracements are analyzed for potential entry opportunities.
Dynamic Fibonacci Layouts:
Automatically plots Fibonacci retracement levels for the most recent higher time frame signal.
Ensures a clean chart by avoiding clutter from historical signals.
Actionable Buy and Sell Signals:
Sell Signal: When the higher time frame is bearish and the price on the lower time frame retraces above the 50% Fibonacci level before forming a bearish candle.
Buy Signal: When the higher time frame is bullish and the price on the lower time frame retraces below the 50% Fibonacci level before forming a bullish candle.
Customizable Fibonacci Visuals:
Full control over Fibonacci levels, line styles, and background shading to tailor the chart to your preferences.
Integrated Alerts:
Real-time alerts for buy and sell signals on the lower time frame.
Alerts for bullish and bearish signals on the higher time frame.
How It Works
Higher Time Frame Analysis:
The indicator identifies bullish and bearish engulfing patterns to detect key reversals or continuation points.
Fibonacci retracement levels are calculated and plotted dynamically for the most recent signal:
Bullish Signal: 100% starts at the low, 0% at the high.
Bearish Signal: 100% starts at the high, 0% at the low.
Lower Time Frame Execution:
Monitors retracements relative to the higher time frame Fibonacci levels.
Provides visual and alert-based buy/sell signals when conditions align for a high-probability entry.
How to Use It
Setup:
Select your higher and lower time frames in the settings.
Customize Fibonacci levels, line styles, and background visuals for clarity.
Trade Execution:
Use the higher time frame signals to determine directional bias.
Watch for actionable buy/sell signals on the lower time frame:
Enter short trades on red triangle sell signals.
Enter long trades on green triangle buy signals.
Alerts:
Enable alerts for real-time notifications of buy/sell signals on lower time frames and higher time frame directional changes.
Concepts Underlying the Calculations
Engulfing Patterns: Represent key reversals or continuations in price action, making them reliable for defining directional bias on higher time frames.
Fibonacci Retracements: Fibonacci levels are used to identify critical zones for potential price reactions during retracements.
Multi-Timeframe Analysis: Combines the strength of higher time frame trends with the precision of lower time frame signals to enhance trades.
Important Notes
This indicator is best used in conjunction with your existing trading strategy and risk management plan.
It does not repaint signals and ensures clarity by displaying Fibonacci levels only for the most recent signal.
Ideal For:
Swing traders, day traders, and scalpers looking to optimize entries and exits with Fibonacci retracements.
Traders who prefer clean charts with actionable insights and customizable visuals.
Dynamic Signal EngineDynamic Signal Engine
The Dynamic Signal Engine is a powerful and versatile indicator, designed to help traders make informed decisions by combining trend analysis with key support and resistance levels. This tool is inspired by the Linear Regression Oscillator , which laid the foundation for this enhanced implementation. By building on the original concept, this script introduces additional features, customization, and integration with dynamic trading strategies to suit diverse trading styles.
Key Features
Inspiration and Foundation
This indicator draws inspiration from the Linear Regression Oscillator , leveraging its robust trend detection capabilities while adding custom enhancements for broader functionality and user adaptability.
Trading Style Customization
Adaptable for Scalping, Intraday, and Swing Trading with dynamic parameter adjustments for each style.
User-defined inputs for thresholds, lookback periods, and visualization options provide further control.
Enhanced Linear Regression Oscillator (LRO)
A refined implementation of the LRO calculates deviations from a regression line, normalized for improved trend detection.
Identifies bullish and bearish crossovers with added alerts and visual markers.
Includes proximity alerts for critical thresholds to help traders anticipate key market movements.
Dynamic Support and Resistance Integration
Incorporates ENIGMA Signal Logic to identify swing highs and lows, dynamically marking them as fractal support and resistance levels.
When a sell signal from ENIGMA is generated, traders can choose to sell immediately or use the low of the previous candle as the entry point. Similarly, for a buy signal, traders can buy immediately or use the high of the previous candle for entry. These signals are visually indicated by a green triangle for buy signals, ensuring clear and actionable insights.
Advanced Visualization
Displays key levels with customizable horizontal lines (solid, dashed, or dotted) and labels for clarity.
Candle colours and mini arrows highlight trends and potential trading opportunities.
Real-Time Alerts
Alerts for LRO threshold crossings and swing-level breaches keep you updated without the need for constant monitoring.
Optimized for Usability
Designed to keep charts clean by limiting displayed trades and signals to recent activity.
Adjustable parameters ensure flexibility and a user-friendly experience.
How It Works
Trend Detection with Enhanced LRO
The indicator builds on the Linear Regression Oscillator , calculating oscillations of price movements and normalizing them for trend analysis. Crossovers and threshold proximity are visualized on the chart and trigger alerts for potential market shifts.
Dynamic Support and Resistance Levels
The ENIGMA Signal Logic identifies recent swing highs and lows, marking them as key levels. These levels are dynamically updated as new swing points are detected, providing actionable support and resistance zones.
Signal Confirmation
Buy or sell signals are confirmed when:
Price breaches the swing levels.
The LRO aligns with directional bias (e.g., bearish crossover for sell signals).
Signals are further clarified by ENIGMA's green triangle indicators, showing key buy and sell opportunities.
Visualization and Alerts
Signals are displayed using arrows, labelled horizontal lines, and optional candle colours. Alerts notify traders of key events, such as LRO threshold crossings or swing-level breaches.
How to Use
Choose your Trading Style: Scalping, Intraday, or Swing Trading. The indicator adjusts its default settings automatically.
Fine-tune parameters like LRO thresholds, line lengths, and the number of visible trades to suit your preferences.
Observe the chart for signals:
Green arrows and lines indicate buy opportunities.
Red arrows and lines signal sell opportunities.
Use the alert system to stay informed about LRO thresholds and signal confirmations.
Integrate the indicator with your existing trading strategy for better decision-making.
Acknowledgement
This script was inspired by the Linear Regression Oscillator . While it builds on the core concept, this implementation introduces unique enhancements, such as dynamic signal integration, trading style adaptability, and advanced visualization tools, making it a highly customizable and versatile tool for traders.
Disclaimer
This indicator is intended for educational purposes only and should not be considered financial advice. Always perform due diligence and apply appropriate risk management when trading.
IPO Lifecycle Sell Strategy [JARUTIR]IPO Lifecycle Sell Strategy with Dynamic Buy Date and Multiple Sell Rules
This custom TradingView script is designed for traders looking to capitalize on dynamic strategies for IPOs and growth stocks, by implementing several sell rules based on price action and technical indicators. It provides a set of sell rules that are applied dynamically depending on the stock's lifecycle and price action, allowing users to lock in profits and minimize drawdowns based on key technical thresholds.
The four sell strategies incorporated into this script are inspired by the book "The Lifecycle Trade", a resource that focuses on capturing profits while managing risk in different phases of a stock's lifecycle, from IPO to high-growth stages.
Key Features:
Buy Price and Buy Date: You can either manually input your buy price and date or let the script automatically detect the buy date based on the specified buy price.
Multiple Sell Strategies: Choose from 4 predefined sell strategies:
Ascender Rule : Captures strong momentum from IPO stocks by selling portions at specific price levels or technical conditions.
Midterm Rule : Focuses on holding for longer periods, with defensive sell signals triggered when the stock deviates significantly from peak price or key moving averages.
40 Week Rule : Designed for long-term holds, this rule triggers a sell when the stock closes below the 40-week moving average.
Everest Rule : Aggressive strategy for selling into strength based on parabolic moves or gap downs, ideal for high momentum stocks.
Interactive Features:
Horizontal Green Line showing the buy price level from the buy date.
Visual Sell Signals appear only after the buy date to ensure that your analysis is relevant to the stock lifecycle.
Customizable settings, allowing you to choose your preferred sell rule strategy and automate buy date detection.
This script is perfect for traders using a strategic, systematic approach to IPOs and high-growth stocks, whether you're looking for quick exits during momentum phases or holding for longer-term growth.
Usage:
Input your Buy Price and Buy Date, or allow the script to automate the buy date detection.
Select a Sell Rule strategy based on your risk profile and trading style.
View visual signals for selling when specific conditions are met.
Frequently Asked Questions (FAQs):
Q1: How do I input my Buy Price and Buy Date?
The script allows you to either manually input the Buy Price and Buy Date or use the automated detection. If you choose automated detection, the script will automatically assign the buy date when the price crosses above your set Buy Price.
Q2: What is the purpose of the "Sell Rules"?
The script offers four sell strategies to help manage different types of stocks in varying phases of their lifecycle:
Ascender Rule: Targets IPO stocks showing positive momentum.
Midterm Rule: A defensive strategy for stocks in a steady uptrend.
40 Week Rule: Long-term hold strategy designed to ride stocks through extended growth.
Everest Rule: Aggressive strategy to capture profits during parabolic price moves.
Q3: What is the significance of the Green Line at Buy Price?
The Green Line represents your entry point (Buy Price) on the chart. It will appear from the buy date onwards, helping you track the performance of your stock relative to your entry.
Q4: Can I customize the Sell Strategy?
Yes! You can choose from the available Sell Rules (Ascender Rule, Midterm Rule, 40 Week Rule, Everest Rule) via an input option in the script. Each strategy has its own unique triggers based on price action, moving averages, and time-based conditions.
Q5: Does this script work for stocks and crypto?
Yes, this script is designed for both stocks and cryptocurrencies. It works on any asset where price data and timeframes are available.
Q6: How do the Weekly Moving Averages (WSMA) work in this strategy?
The script uses weekly moving averages (WSMA) to track longer-term trends. These are essential for some of the sell rules, such as the Midterm Rule and 40 Week Rule, which rely on the stock's movement relative to the 40-week moving average.
Q7: Will the script plot a Sell Signal immediately after the Buy Date?
No, sell signals will only be plotted after the Buy Date. This ensures that the sell strategy is relevant to your actual holding period and avoids premature triggers.
Q8: How do I interpret the Sell Signal?
The script will plot a Red Sell Signal above the bar when the sell conditions are met, based on the selected strategy. This indicates that it may be a good time to exit the position according to your chosen rule.
Q9: Can I use this strategy on different timeframes?
Yes, you can apply the script to any timeframe. However, some sell strategies, like the Midterm Rule and 40 Week Rule, are designed to work best with weekly data, so it's recommended to use these strategies with longer timeframes.
Q10: Does this script have any alerts?
Yes! The script supports alert conditions that will notify you when the sell conditions are met according to your selected rule. You can set up alerts to stay informed without needing to watch the chart constantly.
Q11: What if I want to disable some of the sell rules?
You can select your preferred sell rule using the "Select Sell Rule" dropdown. If you don’t want to use a particular rule, simply choose a different strategy or leave it inactive.
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Disclaimer:
This strategy is intended for educational purposes only. It should not be considered financial advice. Always perform your own research and consult with a professional before making any trading decisions. Trading involves significant risk, and you should never trade with money you cannot afford to lose.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
Candlestick Strength and Volatility ReadoutDisplays a readout on the top right corner of the screen displaying a two basic calculations (volatility and strength; i.e. candlestick size and how close to the highs or lows it closed) for more convenient candlestick (price action) analysis.
Due to restrictions with Pine Script (or my knowledge thereof) only the current and previous candlestick data is shown, rather than the one currently hovered over.
The data is derived via two simple calculations; volatility being division between the range of the candlestick's high and low by the ATR; 'strength' (what I like to call it) being the range of the body by the range of the open to high or low, depending on the facing direction (positive or negative candlestick). These are expressed as percentages and will turn green depending on the set threshold.
Using this, one can effectively automate calculations you'd have to do by hand otherwise. I personally use these as entry filters in my trading, so it helps to not have to measure, remeasure, and divide before each potential entry.
Settings are implemented to change certain variables to your liking.
PSP Indicator [Elbaz]Precision Swing Point or PSP is a unique technical analysis tool designed to compare the price action of three tickers that are in sync.
It highlights moments when the price structure diverges between the markets, identifying ideal entry points for trades - We would like to enter a trade when we found PSP and one of the tickers took the wick while others didn't.
This strategy provides an edge by focusing on periods of desynchronization between the indices, where one index may be showing strength while another is lagging. The idea is to find the moments where the candle colors (bullish or bearish) differ across the markets, then wait for one of the tickers to "take" the wick of the PSP while other didn't and enter a trade.
Once a divergence is detected, the indicator plots an arrow on the chart, signaling a potential trade entry. To minimize risk, a good place to put stop loss will at the end of the wick of the PSP — the high or low wick of the candle where the divergence occurs.
The PSP Indicator allows for several custom inputs:
- Tickers: Customize the tickers to compare. The default values are S&P 500 E-mini, NASDAQ E-mini, and Dow Jones E-mini, if you trade Crypto you might want to use BTC, ETH, TOTAL3.
- Lookback Period: The lookback input defines how far back the indicator should evaluate to calculate the price structure point.
- Highlight Bar Times: Users can specify particular times during the trading day to highlight, such as the market open or significant news events. This helps traders focus on key trading windows.
Max Pain StrategyThe Max Pain Strategy uses a combination of volume and price movement thresholds to identify potential "pain zones" in the market. A "pain zone" is considered when the volume exceeds a certain multiple of its average over a defined lookback period, and the price movement exceeds a predefined percentage relative to the price at the beginning of the lookback period.
Here’s how the strategy functions step-by-step:
Inputs:
length: Defines the lookback period used to calculate the moving average of volume and the price change over that period.
volMultiplier: Sets a threshold multiplier for the volume; if the volume exceeds the average volume multiplied by this factor, it triggers the condition for a potential "pain zone."
priceMultiplier: Sets a threshold for the minimum percentage price change that is required for a "pain zone" condition.
Calculations:
averageVolume: The simple moving average (SMA) of volume over the specified lookback period.
priceChange: The absolute difference in price between the current bar's close and the close from the lookback period (length).
Pain Zone Condition:
The condition for entering a position is triggered if both the volume is higher than the average volume by the volMultiplier and the price change exceeds the price at the length-period ago by the priceMultiplier. This is an indication of significant market activity that could result in a price move.
Position Entry:
A long position is entered when the "pain zone" condition is met.
Exit Strategy:
The position is closed after the specified holdPeriods, which defines how many periods the position will be held after being entered.
Visualization:
A small triangle is plotted on the chart where the "pain zone" condition is met.
The background color changes to a semi-transparent red when the "pain zone" is active.
Scientific Explanation of the Components
Volume Analysis and Price Movement: These are two critical factors in trading strategies. Volume often serves as an indicator of market strength (or weakness), and price movement is a direct reflection of market sentiment. Higher volume with significant price movement may suggest that the market is entering a phase of increased volatility or trend formation, which the strategy aims to exploit.
Volume analysis: The study of volume as an indicator of market participation, with increased volume often signaling stronger trends (Murphy, J. J., Technical Analysis of the Financial Markets).
Price movement thresholds: A large price change over a short period may be interpreted as a breakout or a potential reversal point, aligning with volatility and liquidity analysis (Schwager, J. D., Market Wizards).
Repainting Check: This strategy does not involve any repainting because it is based on current and past data, and there is no reference to future values in the decision-making process. However, any strategy that uses lagging indicators or conditions based on historical bars, like close , is inherently a lagging strategy and might not predict real-time price action accurately until after the fact.
Risk Management: The position hold duration is predefined, which adds an element of time-based risk control. This duration ensures that the strategy does not hold a position indefinitely, which could expose it to unnecessary risk.
Potential Issues and Considerations
Repainting:
The strategy does not utilize future data or conditions that depend on future bars, so it does not inherently suffer from repainting issues.
However, since the strategy relies on volume and price change over a set lookback period, the decision to enter or exit a trade is only made after the data for the current bar is complete, meaning the trade decisions are somewhat delayed, which could be seen as a lagging feature rather than a repainting one.
Lagging Nature:
As with many technical analysis-based strategies, this one is based on past data (moving averages, price changes), meaning it reacts to market movements after they have already occurred, rather than predicting future price actions.
Overfitting Risk:
With parameters like the lookback period and multipliers being user-adjustable, there is a risk of overfitting to historical data. Adjusting parameters too much based on past performance can lead to poor out-of-sample results (Gauthier, P., Practical Quantitative Finance).
Conclusion
The Max Pain Strategy is a simple approach to identifying potential market entries based on volume spikes and significant price changes. It avoids repainting by relying solely on historical and current bar data, but it is inherently a lagging strategy that reacts to price and volume patterns after they have occurred. Therefore, the strategy can be effective in trending markets but may struggle in highly volatile, sideways markets.
Silver Bullet ICT Strategy [TradingFinder] 10-11 AM NY Time +FVG🔵 Introduction
The ICT Silver Bullet trading strategy is a precise, time-based algorithmic approach that relies on Fair Value Gaps and Liquidity to identify high-probability trade setups. The strategy primarily focuses on the New York AM Session from 10:00 AM to 11:00 AM, leveraging heightened market activity within this critical window to capture short-term trading opportunities.
As an intraday strategy, it is most effective on lower timeframes, with ICT recommending a 15-minute chart or lower. While experienced traders often utilize 1-minute to 5-minute charts, beginners may find the 1-minute timeframe more manageable for applying this strategy.
This approach specifically targets quick trades, designed to take advantage of market movements within tight one-hour windows. By narrowing its focus, the Silver Bullet offers a streamlined and efficient method for traders to capitalize on liquidity shifts and price imbalances with precision.
In the fast-paced world of forex trading, the ability to identify market manipulation and false price movements is crucial for traders aiming to stay ahead of the curve. The Silver Bullet Indicator simplifies this process by integrating ICT principles such as liquidity traps, Order Blocks, and Fair Value Gaps (FVG).
These concepts form the foundation of a tool designed to mimic the strategies of institutional players, empowering traders to align their trades with the "smart money." By transforming complex market dynamics into actionable insights, the Silver Bullet Indicator provides a powerful framework for short-term trading success
Silver Bullet Bullish Setup :
Silver Bullet Bearish Setup :
🔵 How to Use
The Silver Bullet Indicator is a specialized tool that operates within the critical time windows of 9:00-10:00 and 10:00-11:00 in the forex market. Its design incorporates key principles from ICT (Inner Circle Trader) methodology, focusing on concepts such as liquidity traps, CISD Levels, Order Blocks, and Fair Value Gaps (FVG) to provide precise and actionable trade setups.
🟣 Bullish Setup
In a bullish setup, the indicator starts by marking the high and low of the session, serving as critical reference points for liquidity. A typical sequence involves a liquidity grab below the low, where the price manipulates retail traders into selling positions by breaching a key support level.
This movement is often orchestrated by smart money to accumulate buy orders. Following this liquidity grab, a market structure shift (MSS) occurs, signaled by the price breaking the CISD Level—a confirmation of bullish intent. The indicator then highlights an Order Block near the CISD Level, representing the zone where institutional buying is concentrated.
Additionally, it identifies a Fair Value Gap, which acts as a high-probability area for price retracement and trade entry. Traders can confidently take long positions when the price revisits these zones, targeting the next significant liquidity pool or resistance level.
Bullish Setup in CAPITALCOM:US100 :
🟣 Bearish Setup
Conversely, in a bearish setup, the price manipulates liquidity by creating a false breakout above the high of the session. This move entices retail traders into long positions, allowing institutional players to enter sell orders.
Once the price reverses direction and breaches the CISD Level to the downside, a change of character (CHOCH) becomes evident, confirming a bearish market structure. The indicator highlights an Order Block near this level, indicating the origin of the institutional sell orders, along with an associated FVG, which represents an imbalance zone likely to be revisited before the price continues downward.
By entering short positions when the price retraces to these levels, traders align their strategies with the anticipated continuation of bearish momentum, targeting nearby liquidity voids or support zones.
Bearish Setup in OANDA:XAUUSD :
🔵 Settings
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The Silver Bullet Indicator is a cutting-edge tool designed specifically for forex traders who aim to leverage market dynamics during critical liquidity windows. By focusing on the highly active 9:00-10:00 and 10:00-11:00 timeframes, the indicator simplifies complex market concepts such as liquidity traps, Order Blocks, Fair Value Gaps (FVG), and CISD Levels, transforming them into actionable insights.
What sets the Silver Bullet Indicator apart is its precision in detecting false breakouts and market structure shifts (MSS), enabling traders to align their strategies with institutional activity. The visual clarity of its signals, including color-coded zones and directional arrows, ensures that both novice and experienced traders can easily interpret and apply its findings in real-time.
By integrating ICT principles, the indicator empowers traders to identify high-probability entry and exit points, minimize risk, and optimize trade execution. Whether you are capturing short-term price movements or navigating complex market conditions, the Silver Bullet Indicator offers a robust framework to enhance your trading performance.
Ultimately, this tool is more than just an indicator; it is a strategic ally for traders who seek to decode the movements of smart money and capitalize on institutional strategies. With the Silver Bullet Indicator, traders can approach the market with greater confidence, precision, and profitability.
Scalp System# Scalp System
A premium scalping system designed specifically for 2-minute charts, combining multiple timeframe analysis with trend-based trading decisions. This indicator helps identify high-probability scalping opportunities through color-coded moving averages and their crossovers.
## Strategy Overview
### Entry Signals
- ONLY trade LONG when price is above RED line
- ONLY trade SHORT when price is below RED line
- Primary entry: BLUE/GREEN crosses
- Strong trend confirmation: YELLOW/PURPLE crosses
### Best Practices
1. Trade with the trend (follow RED line direction)
2. Wait for price pullbacks of faster lines
3. Combine crosses with support/resistance levels
4. Use smaller targets
5. Quick exits on failed breakouts
6. Monitor volume for confirmation
### Color Guide
- YELLOW: Fast trend identifier
- BLUE: Very short-term momentum (1min)
- GREEN: Short-term momentum (3min)
- RED: Trend filter
- PURPLE: Strong trend baseline
### Risk Management
- Place stops beyond the RED line
- Scale out at key levels
- Use 1:1.5 minimum risk/reward
- Avoid trading during major news
- Reduce position size in choppy markets
### Best Trading Hours
- Most effective during first 2 hours after market open
- Good opportunities during power hour (last hour)
- Avoid lunch hour chop (11:30-1:30 EST)
## Tips
- Less is more - wait for clean setups
- Respect the RED line as your trend filter
- Multiple timeframe confirmation increases success rate
- Use crosses as triggers, not absolute signals
- Practice in simulator before live trading
Easy CotHow to Use the Commitment of Traders (COT) Report for Market Analysis
The Commitment of Traders (COT) report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that breaks down the open interest in various futures markets. It categorizes traders into three main groups: Commercials, Non-Commercials, and Retail Traders (Non-Reportable positions). Understanding and analyzing the COT report can provide insights into market sentiment and potential reversals, especially in commodity, currency, and stock index futures.
Key Components of the COT Report
Commercials (Hedgers)
These are entities involved in the production or consumption of the underlying asset. For example, oil producers might hedge by selling oil futures to lock in prices, while airlines might buy futures to hedge against rising prices.
Commercials typically act as hedgers, so their positions can indicate the need for protection rather than speculative intent. Because they are less price-sensitive, their positions are usually opposite to the trend near market reversals.
Non-Commercials (Large Speculators)
This group includes hedge funds, asset managers, and large traders who take speculative positions to profit from price movements.
Non-Commercials are often trend-followers, meaning they increase long positions in an uptrend and short positions in a downtrend. When Non-Commercials become extremely bullish or bearish, it may signal a potential market reversal.
Retail Traders (Non-Reportable Positions)
These are smaller individual traders whose positions are too small to be reported individually.
Retail traders tend to be less experienced and are often on the wrong side of major market moves, so extreme positions by retail traders can sometimes signal a market turning point.
How to Interpret the COT Data
1. Identify Extreme Positions
Extreme Long or Short Positions: When a group reaches a historically extreme level of long or short positions, it often signals a potential reversal. For instance, if Non-Commercials are overwhelmingly long, it may indicate that the uptrend is overextended, and a reversal could be near.
Contrarian Indicator: Since Retail Traders are often on the wrong side, you may look for signals where they are extremely long or short, indicating a possible reversal in the opposite direction.
2. Look for Divergences
Divergence Between Groups: If Non-Commercials (speculators) and Retail Traders are moving in opposite directions, it could indicate that a trend is losing momentum and a reversal is possible.
Commercials vs. Non-Commercials: Commercials are often positioned opposite to Non-Commercials. If there’s a divergence where Non-Commercials are highly bullish, but Commercials are increasingly bearish, it might suggest a coming reversal.
3. Trend Confirmation and Reversal Signals
Trend Confirmation: If both Non-Commercials and Retail Traders are aligned in one direction, it might confirm the trend. However, keep in mind that such alignment may signal the later stages of a trend.
Reversal Signals: Look for signs when Non-Commercials are reaching a peak in one direction while Retail Traders peak in the opposite. Such situations can often indicate that the current trend is close to exhaustion.
Using the COT Report in Trading Strategies
Contrarian Trading Strategy
Extreme Positions as Reversal Signals: Use COT data to identify extreme positions. For instance, if Non-Commercials have a very high long position in a commodity, it might suggest that a bullish trend is overextended and a bearish reversal could be near.
Retail Trader Extremes: If Retail Traders are heavily long or short, consider taking the opposite position once you have additional confirmation signals (e.g., technical indicators).
Following the Trend with Large Speculators
Non-Commercials tend to be trend-followers, so if you see them increasingly long (or short) on an asset, it could be a signal to follow the trend until extreme levels are reached.
Using Divergences for Entry and Exit Points
Entry: If Non-Commercials are long, but Retail Traders are heavily short, consider entering a long position as it may confirm the trend.
Exit: If Non-Commercials begin to reduce their positions while Retail Traders increase theirs, it might be time to consider exiting, as the trend could be losing momentum.
VOLUME DIRECTION INDICATORDesigned for the 1-hour chart, this indicator shows:
Green Line: Volume when price rises, suggesting buying.
Red Line: Volume when price falls, indicating selling.
How to Use:
Watch for Crossover: When the Green Line moves above the Red, it might signal a budding uptrend.
Check Retracement: If the Green Line pulls back but stays above the Red, the uptrend could be strengthening.
Price Check: Look for a small price drop but not a reversal.
Trade Entry:
Enter at the high of the retracement candle.
Or wait for the Green Line to rise again.
For Precision: Draw a line at the retracement peak and switch to a shorter timeframe to find entry patterns above this line.
Remember: Use this with other tools for better trading decisions.
The Volume Direction Indicator provides a visual representation of market activity by assuming volume can be attributed to buying or selling based on price action within each bar. When the price closes higher than it opened, the volume for that period is considered as 'Bought Shares', plotted in green. Conversely, if the price closes lower, the volume is treated as 'Sold Shares', shown in red. This indicator resets daily to give a fresh perspective on trading activity each day.
Key Features:
Buying Pressure: Green line represents the cumulative volume during periods where the price increased.
Selling Pressure: Red line indicates the cumulative volume during price decreases.
Daily Reset: Accumulated values reset at the start of each new trading day, focusing on daily market sentiment.
Note: This indicator simplifies market dynamics by linking volume directly to price changes. It does not account for complex trading scenarios like short selling or market manipulations. Use this indicator as a tool to gauge general market direction and activity, not for precise transaction data.
Advanced Multi-Seasonality StrategyThe Multi-Seasonality Strategy is a trading system based on seasonal market patterns. Seasonality refers to recurring market trends driven by predictable calendar-based events. These patterns emerge due to economic cycles, corporate activities (e.g., earnings reports), and investor behavior around specific times of the year. Studies have shown that such effects can influence asset prices over defined periods, leading to opportunities for traders who exploit these patterns (Hirshleifer, 2001; Bouman & Jacobsen, 2002).
How the Strategy Works:
The strategy allows the user to define four distinct periods within a calendar year. For each period, the trader selects:
Entry Date (Month and Day): The date to enter the trade.
Holding Period: The number of trading days to remain in the trade after the entry.
Trade Direction: Whether to take a long or short position during that period.
The system is designed with flexibility, enabling the user to activate or deactivate each of the four periods. The idea is to take advantage of seasonal patterns, such as buying during historically strong periods and selling during weaker ones. A well-known example is the "Sell in May and Go Away" phenomenon, which suggests that stock returns are higher from November to April and weaker from May to October (Bouman & Jacobsen, 2002).
Seasonality in Financial Markets:
Seasonal effects have been documented across different asset classes and markets:
Equities: Stock markets tend to exhibit higher returns during certain months, such as the "January effect," where prices rise after year-end tax-loss selling (Haugen & Lakonishok, 1987).
Commodities: Agricultural commodities often follow seasonal planting and harvesting cycles, which impact supply and demand patterns (Fama & French, 1987).
Forex: Currency pairs may show strength or weakness during specific quarters based on macroeconomic factors, such as fiscal year-end flows or central bank policy decisions.
Scientific Basis:
Research shows that market anomalies like seasonality are linked to behavioral biases and institutional practices. For example, investors may respond to tax incentives at the end of the year, and companies may engage in window dressing (Haugen & Lakonishok, 1987). Additionally, macroeconomic factors, such as monetary policy shifts and holiday trading volumes, can also contribute to predictable seasonal trends (Bouman & Jacobsen, 2002).
Risks of Seasonal Trading:
While the strategy seeks to exploit predictable patterns, there are inherent risks:
Market Changes: Seasonal effects observed in the past may weaken or disappear as market conditions evolve. Increased algorithmic trading, globalization, and policy changes can reduce the reliability of historical patterns (Lo, 2004).
Overfitting: One of the risks in seasonal trading is overfitting the strategy to historical data. A pattern that worked in the past may not necessarily work in the future, especially if it was based on random chance or external factors that no longer apply (Sullivan, Timmermann, & White, 1999).
Liquidity and Volatility: Trading during specific periods may expose the trader to low liquidity, especially around holidays or earnings seasons, leading to slippage and larger-than-expected price swings.
Economic and Geopolitical Shocks: External events such as pandemics, wars, or political instability can disrupt seasonal patterns, leading to unexpected market behavior.
Conclusion:
The Multi-Seasonality Strategy capitalizes on the predictable nature of certain calendar-based patterns in financial markets. By entering and exiting trades based on well-established seasonal effects, traders can potentially capture short-term profits. However, caution is necessary, as market dynamics can change, and seasonal patterns are not guaranteed to persist. Rigorous backtesting, combined with risk management practices, is essential to successfully implementing this strategy.
References:
Bouman, S., & Jacobsen, B. (2002). The Halloween Indicator, "Sell in May and Go Away": Another Puzzle. American Economic Review, 92(5), 1618-1635.
Fama, E. F., & French, K. R. (1987). Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage. Journal of Business, 60(1), 55-73.
Haugen, R. A., & Lakonishok, J. (1987). The Incredible January Effect: The Stock Market's Unsolved Mystery. Dow Jones-Irwin.
Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. Journal of Finance, 56(4), 1533-1597.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Sullivan, R., Timmermann, A., & White, H. (1999). Data-Snooping, Technical Trading Rule Performance, and the Bootstrap. Journal of Finance, 54(5), 1647-1691.
This strategy harnesses the power of seasonality but requires careful consideration of the risks and potential changes in market behavior over time.
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.
RSI Crossover Strategy with Compounding (Monthly)Explanation of the Code:
Initial Setup:
The strategy initializes with a capital of 100,000.
Variables track the capital and the amount invested in the current trade.
RSI Calculation:
The RSI and its SMA are calculated on the monthly timeframe using request.security().
Entry and Exit Conditions:
Entry: A long position is initiated when the RSI is above its SMA and there’s no existing position. The quantity is based on available capital.
Exit: The position is closed when the RSI falls below its SMA. The capital is updated based on the net profit from the trade.
Capital Management:
After closing a trade, the capital is updated with the net profit plus the initial investment.
Plotting:
The RSI and its SMA are plotted for visualization on the chart.
A label displays the current capital.
Notes:
Test the strategy on different instruments and historical data to see how it performs.
Adjust parameters as needed for your specific trading preferences.
This script is a basic framework, and you might want to enhance it with risk management, stop-loss, or take-profit features as per your trading strategy.
Feel free to modify it further based on your needs!
Comprehensive Market Overview1. What is this indicator about?
The "Comprehensive Market Overview" indicator provides a holistic view of the market by incorporating several key metrics:
Close Price: Displays the current close price below each candle.
Percent from All-Time High: Calculates how far the current close price is from the highest high observed over a specified period.
RSI (Relative Strength Index): Measures the momentum of price movements to assess whether a stock is overbought or oversold.
Volume Gain: Computes the current volume relative to its 20-period simple moving average (SMA), indicating volume strength or weakness.
Volatility: Quantifies market volatility by calculating the ratio of the Bollinger Bands' width (difference between upper and lower bands) to the SMA.
2. How it works?
Close Price Label: This label is displayed below each bar, showing the current close price.
Percent from All-Time High: Calculates the percentage difference between the highest high observed (all-time high) and the current close price.
RSI Calculation: Computes the RSI using a 14-period setting, providing insight into whether a stock is potentially overbought or oversold.
Volume Strength: Computes the current volume divided by its 20-period SMA, indicating whether volume is above or below average.
Volatility Calculation: Calculates the width of the Bollinger Bands (based on a 20-period SMA and 2 standard deviations) and expresses it as a percentage of the SMA, providing a measure of market volatility
3.Correct Trend Identification with Indicators
All-Time High (ATH) Levels:
Low Value (Near ATH): When the percent from ATH is low (close to 0%), it indicates that the current price is near the all-time high zone. This suggests strong bullish momentum and potential resistance levels.
High Value (Below ATH): A high percentage from ATH indicates how much the current price is below the all-time high. This could signal potential support levels or opportunities for price recovery towards previous highs.
RSI (Relative Strength Index):
Overbought (High RSI): RSI values above 70 typically indicate that the asset is overbought, suggesting a potential reversal or correction in price.
Oversold (Low RSI): RSI values below 30 indicate oversold conditions, suggesting a potential rebound or price increase.
Swing Trading Strategies
Confirmation with Visual Analysis: Visualizing the chart to confirm ATH levels and RSI readings can provide strong indications of market sentiment and potential trading opportunities:
Bullish Signals: Look for prices near ATH with RSI confirming strength (not yet overbought), indicating potential continuation or breakout.
Bearish Signals: Prices significantly below ATH with RSI showing weakness (not yet oversold), indicating potential for a bounce or reversal.
Volume Confirmation: Comparing current volume to its SMA helps confirm the strength of price movements. Higher current volume relative to the SMA suggests strong price action.
Volatility Assessment: Monitoring volatility through the Bollinger Bands' width ratio helps assess potential price swings. Narrow bands suggest low volatility, while wide bands indicate higher volatility and potential trading opportunities.
4.Entry and Exit Points:
Entry: Consider entering long positions near support levels when prices are below ATH and RSI is oversold. Conversely, enter short positions near resistance levels when prices are near ATH and RSI is overbought.
Exit: Exit long positions near resistance or ATH levels when prices show signs of resistance or RSI becomes overbought. Exit short positions near support levels or when prices rebound from oversold conditions.
Risk Management: Always incorporate risk management techniques such as setting stop-loss orders based on support and resistance levels identified through ATH and RSI analysis.
Implementation Example
Sessions KillZones Library [TradingFinder]🔵 Introduction
"The Forex Trading Sessions" highlight the active periods across different markets where significant trading volume and influence on the forex market are evident. The primary trading sessions globally include the "Asian Session," "London Session," and "New York Session."
A "Kill Zone" refers to a segment within a session characterized by high trading volume and notably sharper price movements. Consequently, there's a higher probability of encountering price action setups within these zones. Traders capitalize on this phenomenon in pursuit of more successful trading outcomes.
If you aim to integrate sessions or kill zones into your indicators or strategies, utilizing this library can amplify the precision and efficiency of your Python script development.
🔵 How to Use
First, you can add the library to your code as shown in the example below:
import TFlab/SessionAndKillZoneLibrary_TradingFinder/1
🟣 Parameters
SessionDetector(Session_Name, Session_Time, KillZone_Time, Session_Show, KillZone_Show, AreaUpdate, MoreInfo, Session_Color, Info_Color) =>
Parameters:
•Session_Name (string)
•Session_Time (string)
•KillZone_Time (string)
•Session_Show (bool)
•KillZone_Show (bool)
•AreaUpdate (string)
•MoreInfo (bool)
•Session_Color (color)
•Info_Color (color)
Session_Name : You must enter the session name in this parameter.
Session_Time : Enter here the start and end time of the session, which should be based on the UTC time zone.
KillZone_Time : Enter the start and end times of the kill zone, which should be based on the UTC time zone, here.
Session_Show : You can control whether or not to show the session using this entry. You must set true to display and false to not display.
KillZone_Show : Using this input you can control whether the kill zone is displayed or not. You must set true to display and false to not display.
AreaUpdate : If you want the session to be determined based on the time and high and low of the session itself, you must enter "Session" and if you want the area to be determined based on the time and high and low of the kill zone, you must enter "Kill Zone".
MoreInfo : If you want more information, you should set this entry to true, otherwise set to false. This information includes the number of candles in the area, the length of time in the area and the volume of transactions in the area.
Session_Color : Enter your desired color to display the session at this section. It is recommended to use bright and sharp colors.
Info_Color : Enter your desired color to display more information in this section.
🔵 Function Outputs
The outputs of this function are direct and indirect.
🟣 Indirect outputs
These outputs include session display, kill zone display, and time and volume information of session or kill zone.
🟣 Direct outputs
There are 8 direct outputs, which are:
Session Time : If the Session is active, it outputs 1, and if the Session is inactive, it outputs 0.
Kill Zone Time : If the Kill Zone is active, it outputs 1, and if the Kill Zone is inactive, it outputs 0.
Open : Session opening price.
High : The highest price of the session.
Low : The lowest price of the session.
Close : The last price of the session.
Low Touch Alert : If "Area Update" is in "Kill Zone" mode, if the price reaches the lowest price of the kill zone in the same session after the end of the kill zone, this output will be true. You can use this output to create an alert.
High Touch Alert : If "Area Update" is in "Kill Zone" mode, if the price reaches the highest price of the kill zone in the same session after the end of the kill zone, this output will be true. You can use this output to create an alert.
Important : To use "Open", "High", "Low" and "Close", "Area Update" must be in "Session" mode.
Support and Resistance Polynomial Regressions | Flux ChartsOverview
This script is a dynamic form of support and resistance. Support and resistance plots areas where price commonly reverses its direction or “pivots”. A resistance line for instance is typically found by locating a price point where multiple high pivots occur. A high pivot is where a price increases for a number of bars then decreases for a number of bars creating a local maximum. This script takes the high pivots points but rather than using a horizontal line a polynomial regressed line is used.
It is common to see consecutive higher highs or lower lows or a mixed pattern of both so a classical support or resistance line can be insufficient. This script lets users find a polynomial of best fit for high pivots and low pivots creating a resistance and support line respectively.
Here are the same two sets of high and low pivots the first using linear regressed support and resistance lines the second using quadratic.
Here are the predicted results:
The Quadratic regression gives a much more accurate prediction of future pivot areas and the increase in variance of the data.
Quick Start
Add the script to the chart. Then select a left point and right point on the chart. This will be the data the script uses to calculate a best fit resistance line. Then select another left and right point that will be for the support line.
Now you can confirm your basic settings like the type of regression: Linear Regression, Quadratic Regression, Cubic Regression or Custom Regression.
After confirming the lines will be plotted on the graph.
Custom Polynomial Regression Setting
Polynomials follow the form:
The degree of a polynomial is the highest exponent in the equation. For example the polynomial ax^2 + bx + c has a degree of 2.
Here are the default polynomial options and their equivalent custom polynomial entry:
This allows us to create regressions with a custom number of inflection points. An inflection point is a point where the graph changes from concave up to concave down or vice versa. The maximum number of inflection points a polynomial can have is the degree - 2. Having multiple inflection points in our regression allows for having a closer fit minimizing error.
It should be noted that having a closer fit is not inherently better; this can cause overfitting. Overfitting is when a model is too closely fit to the training data and not generalizable to the population data.
