Stochastic Trendlines with Breakouts [Jamshid] - EnhancedStochastic Trendlines with Breakouts - Enhanced Version
This advanced Stochastic Trendlines with Breakouts script combines several powerful features to provide enhanced breakout detection based on the Stochastic Oscillator and additional confirmation signals. This script is designed to help traders identify key trend reversals, breakout points, and pivot levels with more accuracy by integrating advanced filters such as RSI confirmation, moving average trend filtering, volatility filtering, divergence detection, and multi-timeframe analysis.
Key Features:
Stochastic Oscillator-Based Breakouts:
Automatically detects breakouts based on the smoothed Stochastic Oscillator values (%K and %D), providing insights into overbought and oversold conditions.
Customizable overbought and oversold levels, with a mid-level (50) line for additional reference.
Trendlines on Pivot Points:
Automatically plots dynamic trendlines based on pivot highs and lows of the smoothed Stochastic %K, helping to visualize potential reversal points.
RSI Confirmation (Optional):
Filters breakout signals using the Relative Strength Index (RSI) to confirm breakouts only when the RSI is below 50 for downtrend breakouts and above 50 for uptrend breakouts.
Visual confirmation with a green "RSI Conf." label displayed on the chart when the RSI condition is met.
Moving Average Filter (Optional):
Confirms breakout signals in the direction of a user-defined Moving Average (MA) to trade in the overall market trend direction.
MA length is fully customizable.
Stochastic Divergence Filter (Optional):
Detects bullish or bearish divergence between the price and Stochastic Oscillator values, adding an extra layer of confirmation.
Multi-Timeframe Confirmation (Optional):
Confirms breakouts by checking the Stochastic %K and %D values from a higher timeframe. This helps in avoiding false signals by aligning with the broader market trend.
The higher timeframe can be customized to any timeframe (e.g., daily, weekly, etc.).
Volatility Filter (Optional):
Uses the ATR (Average True Range) to filter out breakouts during periods of low volatility, ensuring signals are only triggered when there is sufficient price movement.
ATR length and multiplier are fully customizable.
Custom Alerts:
Alerts are available for new trendline detections (both pivot high and pivot low) and for confirmed breakout signals. These alerts help traders stay informed in real-time without needing to monitor the chart continuously.
How to Use:
Customize the Stochastic Oscillator settings, such as %K smoothing and %D line parameters, to fit your trading strategy.
Enable or disable additional filtering features (RSI, MA, divergence, MTF, volatility) as needed.
Set up alerts for specific breakout conditions directly in TradingView to stay notified when breakout signals are triggered.
This script is designed for traders who are looking for precision breakout signals with added layers of confirmation to avoid false breakouts and enhance trading accuracy.
Wskaźniki i strategie
Prometheus Fractal WaveThe Fractal Wave is an indicator that uses a fractal analysis to determine where reversals may happen. This is done through a Fractal process, making sure a price point is in a certain set and then getting a Distance metric.
Calculation:
A bullish Fractal is defined by the current bar’s high being less than the last bar’s high, and the last bar’s high being greater than the second to last bar’s high, and the last bar’s high being greater than the third to last bar’s high.
A bearish Fractal is defined by the current low being greater than the last bar’s low, and the last bar’s low being less than the second to last bar’s low, and the last bar’s low being less than the third to last bar’s low.
When there is that bullish or bearish fractal the value we store is either the last bar’s high or low respective to bullish or bearish fractal.
Once we have that value stored we either subtract the last bar’s low from the bullish Fractal value, and subtract the last bar’s high from the bearish Fractal value. Those are our Distances.
Code:
isBullishFractal() =>
high > high and high < high and high > high
isBearishFractal() =>
low < low and low > low and low < low
var float lastBullishFractal = na
var float lastBearishFractal = na
if isBullishFractal() and barstate.isconfirmed
lastBullishFractal := high
if isBearishFractal() and barstate.isconfirmed
lastBearishFractal := low
//------------------------------
//-------CACLULATION------------
//------------------------------
bullWaveDistance = na(lastBullishFractal) ? na : lastBullishFractal - low
bearWaveDistance = na(lastBearishFractal) ? na : high - lastBearishFractal
We then plot the bullish distance and the negative bearish distance.
The trade scenarios come from when one breaks the zero line and then goes back above or below. So if the last bullish distance was below 0 and is now above, or if the last negative bearish distance was above 0 and now below. We plot a green label below a candle for a bullish scenario, or a red label above a candle for a bearish one, you can turn them on or off.
Code:
plot(bullWaveDistance, color=color.green, title="Bull Wave Distance", linewidth=2)
plot(-bearWaveDistance, color=color.red, title="Bear Wave Distance", linewidth=2)
plot(0, "Zero Line", color=color.gray, display = display.pane)
bearish_reversal = plot_labels ? bullWaveDistance < 0 and bullWaveDistance > 0 : na
bullish_reversal = plot_labels ? -bearWaveDistance > 0 and -bearWaveDistance < 0 : na
plotshape(bullish_reversal, location=location.belowbar, color=color.green, style=shape.labelup, title="Bullish Fractal", text="↑", display = display.all - display.status_line, force_overlay = true)
plotshape(bearish_reversal, location=location.abovebar, color=color.red, style=shape.labeldown, title="Bearish Fractal", text="↓", display = display.all - display.status_line, force_overlay = true)
We can see in this daily NASDAQ:QQQ chart that the indicator gives us marks that can either be used as Reversal signals or as breathers in the trend.
Since it is designed to provide reversals, on something like Gold where the uptrend has been strong, the signals may be just short breathers, not full blown strong reversal signs.
The indicator works just as well intra day as it does on larger timeframes.
We encourage traders to not follow indicators blindly, none are 100% accurate. Please comment on any desired updates, all criticism is welcome!
TS Volatility-Adjusted EWMAThe TS Volatility-Adjusted Exponentially Weighted Moving Average (EWMA) is a dynamic trend-following indicator designed to adapt to changing market volatility. Unlike traditional moving averages, this indicator adjusts its sensitivity based on market conditions, making it more responsive during periods of high volatility and smoother when markets are calmer.
Key Features:
Volatility Adjustment: The EWMA length is dynamically scaled using the Average True Range (ATR), making it adaptive to market volatility. This allows the indicator to react quickly when volatility spikes and remain stable when volatility drops.
User-Controlled Smoothing: The indicator includes an optional smoothing period, allowing you to adjust how smooth or reactive the line is to price changes. If you prefer a more smoothed-out trend, simply increase the smoothing length.
This indicator is perfect for trend-following traders who want an adaptive tool that stays responsive to the market’s volatility. The TS Volatility-Adjusted EWMA helps you confidently follow market trends, whether you’re riding a long-term trend or catching shorter-term movements.
DEB SuperTrend [Mattes]The Dynamic Envelope Based Supertrend integrates two key concepts: dynamic envelopes and the Supertrend, creating a powerful trend-following tool. Understanding its functionality requires a closer look at how the envelopes are constructed and how they interact with price action.
Dynamic Envelopes
>>> Dynamic envelopes are bands that surround a central moving average (MA) which is set by the user. These are then calculated based on the standard deviation of price movements over a specified period. The formula for the upper and lower envelopes is as follows:
Upper Envelope=MA+(Multiplier×STD)
Lower Envelope=MA−(Multiplier×STD)
This dynamic approach ensures that the envelopes expand and contract based on market volatility. In periods of high volatility, the envelopes widen, allowing for more price movement without triggering false signals. Conversely, in low-volatility periods, the envelopes tighten, enhancing sensitivity to price changes.
Interaction with the Supertrend
The Supertrend component is a trend-following indicator that utilizes the concept of Average True Range (ATR) to define its trailing stop levels.
In this indicator however (like I've mentioned before), the ATR bands have been replaced with the STD envelopes, as they offer a better performance compared to ATR bands.
Trend Direction
The Supertrend indicator generates buy and sell signals based on price crossing the calculated upper and lower envelopes:
>>> Buy Signal: Triggered when the price closes above the upper envelope, indicating a potential upward trend.
>>> Sell Signal: Triggered when the price closes below the lower envelope, suggesting a downward trend.
Adaptive Nature:
The dynamic envelopes effectively serve as dynamic support and resistance levels, which adapt to price movements and volatility, while the Supertrend tracks these levels to confirm the trend direction and adjust accordingly to changes, making it an enhanced version of ATR Based Supertrends.
Unique Aspects and Advantages
->>>> The Dynamic Envelope Based Supertrend is unique for several reasons:
>>> Volatility Responsiveness: The indicator adjusts its sensitivity based on market conditions, reducing the likelihood of false signals during quiet market phases and improving reliability during volatile periods. This is reasoned by the STD envelope bands contracting and expanding relative to the tickers performance.
>>> Trend Confirmation: By integrating the Supertrend logic, the indicator not only provides entry signals but also guides traders on when to exit, maintaining a focus on trend-following rather than mean reversion.
>>> Stability: Due to its use of Standard deviation envelopes, it is very ressistant in periods of uncertainty, Rather than buy bottom and selling tops, it stays long/short for the complete period of mean reverting environments, which is based on the bigger and fuller trend direction on the larger timescales.
>>> Clear Signals: The indicator simplifies decision-making by offering visual cues through its envelopes and trend signals, making it accessible to traders of all experience levels.
Summary:
The Dynamic Envelope Based Supertrend is a sophisticated trend-following indicator that intelligently combines dynamically adjusted STD envelopes with Supertrend logic. By incorporating volatility metrics, it offers a clear and actionable framework for traders, enhancing their ability to identify and follow trends effectively.
DSL Trend Analysis [ChartPrime]The DSL Trend Analysis indicator utilizes Discontinued Signal Lines (DSL) deployed directly on price, combined with dynamic bands, to analyze the trend strength and momentum of price movements. By tracking the high and low price values and comparing them to the DSL bands, it provides a visual representation of trend momentum, highlighting both strong and weakening phases of market direction.
⯁ KEY FEATURES AND HOW TO USE
⯌ DSL-Based Trend Detection :
This indicator uses Discontinued Signal Lines (DSL) to evaluate price action. When the high stays above the upper DSL band, the line turns lime, indicating strong upward momentum. Similarly, when the low stays below the lower DSL band, the line turns orange, indicating strong downward momentum. Traders can use these visual signals to identify strong trends in either direction.
⯌ Bands for Trend Momentum :
The indicator plots dynamic bands around the DSL lines based on ATR (Average True Range). These bands provide a range within which price can fluctuate, helping to distinguish between strong and weakening trends. If the high remains within the upper band, the lime-colored line becomes transparent, showing weakening upward momentum. The same concept applies for the lower band, where the line turns orange with transparency, indicating weakening downward momentum.
If high and low stays between bands line has no color
to make sure indicator catches only strong momentum of price
⯌ Real-Time Band Price Labels :
The indicator places two labels on the chart, one at the upper DSL band and one at the lower DSL band, displaying the real-time price values of these bands. These labels help traders track the current price relative to the key bands, which are essential in determining potential breakout or reversal zones.
⯌ Visual Confirmation of Momentum Shifts :
By monitoring the relationship between the high and low values of the price relative to the DSL bands, this indicator provides a reliable way to confirm whether the trend is gaining or losing strength. This allows traders to act accordingly, whether it's to enter or exit positions based on trend strength or weakness.
⯁ USER INPUTS
Length : Defines the period used to calculate the DSL lines, influencing the sensitivity of the trend detection.
Offset : Adjusts the offset applied to the upper and lower DSL bands, affecting how the thresholds for strong or weak momentum are set.
Width (ATR Multiplier) : Determines the width of the DSL bands based on an ATR multiplier, providing a dynamic range around the price for momentum analysis.
⯁ CONCLUSION
The DSL Trend Analysis indicator is a powerful tool for assessing price momentum and trend strength. By combining Discontinued Signal Lines with dynamically calculated bands, traders can easily spot key moments when momentum shifts from strong to weak or vice versa. The color-coded lines and real-time price labels provide valuable insights for trading decisions in both trending and ranging markets.
FVG Order Blocks [BigBeluga]This indicator is an advanced tool designed to detect and visualize market FVGs with order blocks, where the price action has created gaps due to strong buying or selling pressure. These FVG often act as critical support and resistance levels, giving traders strategic points for potential entries and exits. The indicator not only identifies these imbalances but also displays their relative strength by size %, helping traders prioritize order blocks that are more likely to hold or break.
The indicator works on various pairs and stocks, it also works on charts that do not provide volume data
Forex (JPY/USD):
Stocks (NVDA):
🔵 KEY FEATURES & USAGE
● FVGs Detection and Visualization:
The indicator detects bullish and bearish FVGs. Bullish FVG occur when there is significant buying, and order block is plotted below the FVG zone:
Conversely, bearish FVG are plotted with an order block above the zone, indicating potential resistance.
Traders can use these order blocks to anticipate price reactions when the market revisits these areas, making them ideal for setting up trades.
● FVG Filtering:
The indicator includes a FVG % filter that allows traders to only display strong order blocks. This ensures that only significant FVG order blocks are shown, reducing noise and focusing on the most impactful areas.
● Highlighting Broken Levels:
When an imbalance level is broken—either breached by price action or no longer relevant—the indicator can either delete the level or mark it with a gray color areas. This provides a clear visual cue that the level has been compromised, allowing traders to adjust their strategies accordingly.
● Order Blocks Signals:
When price retest the blocks, indicator display potential sell or buy signals. Which can be an opportunity for trades
🔵 CUSTOMIZATION
● FVG Filter:
Adjust the strength filter to control which FVGs are displayed based on their percentage size. This filter helps in focusing only on significant blocks that are likely to impact price action.
● Order Blocks Amount Displayed:
Set the maximum number of Order Blocks to be displayed on the chart. This customization helps keep the chart clean and ensures that only the most important blocks are in view.
● Broken Order Blocks Display:
Choose whether to display order blocks that have been broken by the price. This feature helps in maintaining a focus on blocks that are still valid while filtering out those that are no longer relevant.
● Color Customization:
You can customize the colors for bullish and bearish Order Blocks to match your chart's overall color scheme. Additionally, strength bars can be color-coded based on their percentage to quickly identify high-priority order blocks.
Traders who are confident in the settings of the indicator can confidently use it on various types of markets
Options Series - Dynamic Support & Resistance
🌟 Key Features & How It Works:
⭐ Dynamic Support and Resistance Management:
The script dynamically calculates and draws support and resistance lines based on pivot highs and pivot lows. Unlike static levels that remain unchanged, these lines are updated in real-time. When a support or resistance level is breached, the corresponding line is automatically deleted, keeping the chart clean and relevant. This feature ensures that the trader is always looking at valid support and resistance levels based on the current price action.
⭐ Use of Arrays for Line Management:
The script utilizes arrays to store and manage support and resistance lines (array.new_line(0)). This is a more advanced feature of Pine Script v5, allowing for efficient handling of multiple lines on the chart. By using arrays, the script can easily track and manipulate multiple lines (adding, removing, updating), ensuring that the chart remains optimized for real-time analysis.
⭐ Customizable Inputs for Flexibility:
The script includes user inputs for the pivot length and the line width, making it adaptable to different trading styles and preferences. The pivot length determines how sensitive the indicator is to price changes, while the line width allows traders to customize the visual representation of support and resistance levels. These inputs add flexibility and make the script accessible to a broad range of traders.
⭐ Efficient Breach Detection Mechanism:
The isBreached function is a key part of the script. It checks whether the current price has breached any of the existing support or resistance levels. If a breach is detected (i.e., the price crosses below a support or above a resistance), the respective line is deleted, ensuring that only active and valid lines remain on the chart. This automatic update feature reduces the need for manual intervention, helping traders stay focused on key price levels.
⭐ Visual Clarity and Chart Cleanliness:
By deleting breached lines, the script ensures that the chart does not become cluttered with outdated or irrelevant lines. This visual clarity is crucial for traders who rely on clean, simple charts for decision-making. Removing unnecessary information helps traders make faster, more confident decisions based on the current market structure.
⭐ Scalability for Multiple Timeframes:
The use of pivot points makes the script adaptable to different timeframes, from intraday scalping to longer-term swing trading. By changing the pivot length, traders can optimize the indicator for different market environments, ensuring that it can be applied across various asset classes and timeframes.
⭐ Practical for Range-bound and Breakout Trading:
This script is particularly effective for traders who focus on range-bound markets or breakout strategies. It allows them to quickly identify areas where price is likely to reverse (support/resistance) or break out (when support/resistance is breached), providing real-time insight into market dynamics.
⭐ Simplification of Price Action Analysis:
By automating the calculation of pivots and management of support/resistance levels, the script simplifies price action analysis. Traders no longer need to manually draw or monitor these levels, which is a common task in technical analysis. This provides an edge, as it reduces the time spent on chart preparation and helps focus on executing trades.
⭐ Originality:
The script "Options Series - Pivot Based Support & Resistance" is an original approach to generating support and resistance levels using pivot points. Pivot-based techniques are popular, but the script introduces an automated dynamic way of drawing support and resistance lines, tracking breaches, and deleting lines when they are no longer valid. This aspect adds a refreshing layer of interactivity and functionality that sets it apart from basic pivot point scripts. The use of arrays to store and manage multiple support and resistance lines is also a good application of Pine Script’s newer array functionalities.
⭐ Uniqueness of the Script:
The script stands out due to its dynamic management of support and resistance lines. Unlike traditional scripts that simply plot static pivot points, this one evolves with the market by removing broken levels, ensuring only valid support and resistance lines are visible on the chart. This is particularly useful for traders who focus on clean charting. The use of arrays to store and manage the lines, alongside the efficient deletion of lines when breached, demonstrates a solid understanding of Pine Script v5's advanced features, such as array manipulation.
🚀 Conclusion:
This script stands out for its real-time adaptability, dynamic support/resistance management, and efficient use of Pine Script’s advanced features. It a powerful tool for both novice and advanced traders.
The script is an indicator designed to draw support and resistance levels based on pivot highs and lows, dynamically removing lines when they are breached. If a price crosses a support or resistance level, the respective line is deleted, ensuring the chart reflects the current state of support and resistance accurately.
MomentumSignal Kit RSI-MACD-ADX-CCI-CMF-TSI-EStoch// ----------------------------------------
// Description:
// ----------------------------------------
// MomentumKit RSI/MACD-ADX-CCI-CMF-TSI-EStoch Suite is a comprehensive momentum indicator suite designed to provide robust buy and sell signals through the consensus of multiple normalized momentum indicators. This suite integrates the following indicators:
// - **Relative Strength Index (RSI)**
// - **Stochastic RSI**
// - **Moving Average Convergence Divergence (MACD)** with enhanced logic
// - **True Strength Index (TSI)**
// - **Commodity Channel Index (CCI)**
// - **Chaikin Money Flow (CMF)**
// - **Average Directional Index (ADX)**
// - **Ehlers' Stochastic**
//
// **Key Features:**
// 1. **Normalization:** Each indicator is normalized to a consistent scale, facilitating easier comparison and interpretation across different momentum metrics. This uniform scaling allows traders to seamlessly analyze multiple indicators simultaneously without the confusion of differing value ranges.
//
// 2. **Consensus-Based Signals:** By combining multiple indicators, MomentumKit generates buy and sell signals based on the agreement among various momentum measurements. This multi-indicator consensus approach enhances signal reliability and reduces the likelihood of false positives.
//
// 3. **Overlap Analysis:** The normalization process aids in identifying overlapping signals, where multiple indicators point towards a potential change in price or momentum. Such overlaps are strong indicators of significant market movements, providing traders with timely and actionable insights.
//
// 4. **Enhanced Logic for MACD:** The MACD component within MomentumKit utilizes enhanced logic to improve its responsiveness and accuracy in detecting trend changes.
//
// 5. **Debugging Features:** MomentumKit includes advanced debugging tools that display individual buy and sell signals generated by each indicator. These features are intended for users with technical and programming skills, allowing them to:
// - **Visualize Signal Generation:** See real-time buy and sell signals for each integrated indicator directly on the chart.
// - **Adjust Signal Thresholds:** Modify the criteria for what constitutes a buy or sell signal for each indicator, enabling tailored analysis based on specific trading strategies.
// - **Filter and Manipulate Signals:** Enable or disable specific indicators' contributions to the overall buy and sell signals, providing flexibility in signal generation.
// - **Monitor Indicator Behavior:** Utilize debug plots and labels to understand how each indicator reacts to market movements, aiding in strategy optimization.
//
// **Work in Progress:**
// MomentumKit is continuously evolving, with ongoing enhancements to its algorithms and user interface. Current debugging features are designed to offer deep insights for technically adept users, allowing for extensive customization and fine-tuning. Future updates aim to introduce more user-friendly interfaces and automated optimization tools to cater to a broader audience.
//
// **Usage Instructions:**
// - **Visibility Controls:** Users can toggle the visibility of individual indicators to focus on specific momentum metrics as needed.
// - **Parameter Adjustments:** Each indicator comes with customizable parameters, allowing traders to fine-tune the suite according to their trading strategies and market conditions.
// - **Debugging Features:** Enable the debugging mode to visualize individual indicator signals and adjust their contribution to the overall buy/sell signals. This requires a basic understanding of the underlying indicators and their operational thresholds.
//
// **Benefits:**
// - **Simplified Analysis:** Normalization simplifies the process of analyzing multiple indicators, making it easier to identify consistent signals across different momentum measurements.
// - **Improved Decision-Making:** Consensus-based signals backed by multiple normalized indicators provide a higher level of confidence in trading decisions.
// - **Versatility:** Suitable for various trading styles and market conditions, MomentumKit offers a versatile toolset for both novice and experienced traders.
//
// **Technical Requirements:**
// - **Programming Knowledge:** To fully leverage the debugging and signal manipulation features, users should possess a foundational understanding of Pine Script and the mechanics of momentum indicators.
// - **Customization Skills:** Ability to adjust indicator parameters and debug filters to align with specific trading strategies.
//
// **Disclaimer:**
// This indicator suite is intended for educational and analytical purposes only and does not constitute financial advice. Trading involves significant risk, and past performance is not indicative of future results. Always conduct your own analysis or consult a qualified financial advisor before making trading decisions.
Stochastics Confluences 4 in 1Description of the Pine Script:
This script plots the Full Stochastic indicator for four different time periods, and highlights conditions where potential buy or sell signals can be identified. The Stochastic indicator measures the position of the current closing price relative to the range of high and low prices over a defined period, helping traders identify overbought and oversold conditions.
Key Features:
Stochastic Calculation for 4 Different Periods:
The script calculates the Stochastic for four separate lookback periods: 9, 14, 40, and 60 bars.
Each Stochastic value is smoothed by a Simple Moving Average (SMA) to reduce noise and provide a clearer signal.
Visual Representation:
It plots each Stochastic value on the chart using different colors, allowing the user to see how the different periods of the indicator behave relative to each other.
Horizontal lines are drawn at 80 (Upper Bound) and 20 (Lower Bound), commonly used to identify overbought and oversold regions.
Highlighting Buy and Sell Conditions:
Green Highlight (Potential Buy Signal):
When all four Stochastic values (for the four different periods) are below 20, this suggests that the asset is in an oversold condition across multiple timeframes. The green background highlight appears when the Stochastic lines converge below 20, indicating a potential buy signal, as the price may be preparing to move upward from an oversold state.
Red Highlight (Potential Sell Signal):
When all four Stochastic values are above 80, the asset is in an overbought condition across multiple timeframes. The red background highlight appears when the Stochastic lines converge above 80, indicating a potential sell signal, as the price may soon reverse downward from an overbought state.
How to Interpret the Signals:
Buy Signals (Green Highlight):
When the chart is highlighted in green, it means the Stochastic indicators for all four periods are below 20, signaling that the asset is oversold and may be nearing a potential upward reversal. This condition suggests a possible buying opportunity, especially when other indicators confirm the potential for an upward trend.
Sell Signals (Red Highlight):
When the chart is highlighted in red, it indicates that the Stochastic indicators for all four periods are above 80, meaning the asset is overbought. This condition signals a possible downward reversal, suggesting a potential selling opportunity if the price begins to show signs of weakness.
By using this script, traders can visually identify periods of strong confluence across different timeframes when the Stochastic indicators are in extreme oversold or overbought conditions, which are traditionally seen as strong buy or sell signals.
This approach helps filter out weaker signals and focuses on moments when all timeframes align, increasing the probability of a successful trade.
Adjusted CoT IndexAdjusted COT Index
Improves upon: "COT Index Commercials vs large and small Speculators" by SystematicFutures
How: CoT Indexes are adjusted by Open Interest to normalise data over time, and threshold background colours are in-line with Larry Williams recommendations from his book.
Note: This indicator is **only** accurate on the Daily time-frame due to the mid-week release date for CoT data.
This script calculates and plots the Adjusted Commitment of Traders (COT) Index for Commercial, Large Speculator, and Retail (Small Speculator) categories.
The CoT Index is adjusted by Open Interest to normalise data through time, following the methodology of Larry Williams, providing insights into how these groups are positioned in the market with an arguably more historically accurate context.
COT Categories
-------------------
- Commercials (Producers/Hedgers): Large entities hedging against price changes in the underlying asset.
- Large Speculators (Non-commercials): Professional traders and funds speculating on price movements.
- Retail Traders (Nonreportable/Small Speculators): Small individual traders, typically less informed.
Features
----------
- Open Interest Adjustment
- The net positions for each category are normalized by Open Interest to account
for varying contract sizes.
- Customisable Look-back Period
- You can adjust the number of weeks for the index calculation to control the
historical range used for comparison.
- Thresholds for Extremes
- Upper and lower thresholds (configurable) are provided to mark overbought and
oversold conditions.
- Defaults
- Overbought: <=20
- Oversold: >= 80
- Hide Current Week Option
- Optionally hide the current week's data until market close for more accurate comparison.
- Visual Aids
- Plot the Commercials, Large Speculators, and Retail indexes, and optionally highlight extreme positioning.
Inputs
--------
- weeks
- Number of weeks for historical range comparison.
- upperExtreme and lowerExtreme
- Thresholds to identify overbought/oversold conditions (default 80/20).
- hideCurrentWeek
- Option to hide current week's data until market close.
- markExtremes
- Highlight extremes where any index crosses the upper or lower thresholds.
- Options to display or hide indexes for Commercials, Large Speculators, and Small Speculators.
Outputs
----------
- The script plots the COT Index for each of the three categories and highlights periods of extreme positioning with customisable thresholds.
Usage
-------
- This tool is useful for traders who want to track the positioning of different market participants over time.
- By identifying the extreme positions of Commercials, Large Speculators, and Retail traders, it can give insights into market sentiment and potential reversals.
- Reversals of trend can be confirmed with RSI Divergence (daily), for example
- Continuation can be confirmed with RSI overbought/oversold conditions (daily), and/or hidden RSI Hidden Divergence, for example
Vektorkerzen HighlightThe indicator highlights candles when:
The volume is at least twice the 20-period moving average.
The range (difference between high and low prices) is at least twice the 20-period average range.
*2.2 Aggregated (Raw Z-scores with MA)***To be used with other 2.2 indicator***
Key Indicators Used:
Oscillating Indicators: RSI, TSI, Stochastic, MACD, CCI, Vortex Indicator, Williams %R.
Perpetual Trend Indicators: EMA, ADX, Parabolic SAR, Supertrend, Donchian Channel, Ichimoku Cloud, RVGI.
How to Use the Indicator:
Raw Z-Score (Blue Line): This represents the real-time aggregated Z-score of all the indicators. It shows how far the current market conditions are from their average, helping you identify trends.
Moving Average of Z-Score (Orange Line): A smoothed version of the Z-score that helps confirm trends and eliminate noise.
Shaded Area: The area between the Z-score and its moving average is shaded green if the Z-score is above the moving average (bullish), and red if below the moving average (bearish).
Zero Line (Gray Line): Serves as a reference point. A Z-score crossing above zero could signal a bullish market, while crossing below zero could indicate bearish conditions.
This indicator helps in identifying market extremes and trend reversals by combining various technical indicators into a single aggregate score, ideal for spotting overbought or oversold conditions and possible trend shifts
*2.2 Aggregate Signal Indicator (trial)How to Use the Indicator:
Trend Detection:
The aggregate trend score will plot above 0 for bullish conditions and below 0 for bearish conditions.
When the trend score is green, it indicates a positive (bullish) trend, while red indicates a negative (bearish) trend.
Visual Representation:
The blue line represents the aggregate trend score, while the grey line at 0 shows the neutral point.
The area between the trend score and the 0-line is filled with green (bullish) or red (bearish) based on the score's direction.
Confirming Trends:
Look for consistency in the trend score remaining above or below 0 to confirm a lasting trend.
Use this indicator alongside other trading strategies to filter out false signals and gain confirmation of market direction.
Customizable Inputs:
The indicator allows you to customize the settings for each individual indicator (e.g., lengths for EMA, ADX, RSI, MACD, etc.) to fine-tune the system to your preference or specific market conditions.
Farley's Accumulation-Distribution Accelerator (ADA)Farley's ADA (From The Master Swing Trader)
What it is :
ADA is designed to track volume oscillations in the market and reduce the impact of shock events.
It observes the supply-demand dynamics within the market, which can trigger natural levels of price reversals.
How It Works
Volume and Price Relationship: ADA measures the lag between price and volume movements. It highlights when volume leads or lags behind price changes, helping traders identify potential reversals or trends.
Signal Generation: ADA can generate faster and cleaner signals compared to traditional indicators like On-Balance Volume (OBV).
Usage
Support and Resistance: ADA formations can help identify support and resistance levels and trendlines.
detect natural levels where price reversals might occur.
Trend Identification: Look for significant divergences between ADA and price action to identify potential trend reversals.
Volume Analysis: Use ADA to anticipate pauses in price movements when volume leads, and expect dynamic trends when ADA significantly moves ahead of price action.
Time Based 3 Candle Model CRT FrameworkThe 3 Candle Model Overview:
The 3 Candle Model serves as a sophisticated framework for traders to navigate the complexities of financial markets, particularly within futures and forex trading. This guide not only elaborates on the model's key features but also emphasizes its originality and practical usefulness in the TradingView community. The core principle of the 3 Candle Model revolves around understanding how candle patterns can represent significant price ranges, offering valuable insights into potential market movements. By integrating the model with other critical trading concepts such as the Power of Three (PO3), Open-High-Low-Close (OHLC), and Turtle Soup setups, traders can enhance their ability to identify high-probability trades and achieve better trading outcomes.
Indicator includes:
3 Customizable Timeframe choices to fractally frame 3 candle models for precision
Live Timers for each timeframe to always be aware of the models timing
Parent Candle tracking on every preffered timeframe until new models parent candle is printed
Key Features of the 3 Candle Model
The 3 Candle Model primarily utilizes a three-candle structure, where the first candle establishes a price range, the second candle may act as a confirmation (often termed a "turtle soup"), and the third candle provides the breakout or continuation. This structure is pivotal in determining entry and exit points for trades, ensuring that each trading decision is backed by solid price action analysis.
OHLC Principle:
The Open-High-Low-Close (OHLC) concept is integral to the 3 Candle Model, allowing traders to analyze price action more effectively. Understanding the relationship between these four price points helps traders gauge market sentiment and potential reversals. By incorporating OHLC into the model, traders can develop a deeper understanding of market structure and its implications for future price movements.
Delivery States:
The 3 Candle Model emphasizes the importance of delivery states, which refer to the market's phase during specific time frames. Recognizing these states aids traders in determining the appropriate conditions for entering trades, particularly when combined with the power of three and candle range patterns. This understanding is crucial for positioning trades in alignment with market momentum.
High Probability Setups:
By aligning the 3 Candle Model with inside bar setups, traders can optimize their strategies for high-probability outcomes. This approach capitalizes on the inherent fractal nature of price movements, where previous patterns repeat at different scales. The combination of the model and inside bar setups enhances the trader's toolkit, allowing for more strategic trade placements.
Turtle Soup Formation:
The 3 Candle Model intricately connects with the Turtle Soup concept, which focuses on false breakouts. Identifying these formations at critical levels enhances the trader's ability to anticipate reversals or continuation patterns. The timing of these setups, particularly during specified times like 3:00 AM, 6:00 AM, 9:00 AM, and 1:00 PM, is crucial for maximizing trade success.
Using the 3 Candle Model in Trading
Integration with PO3:
The Power of Three (PO3) is a fundamental aspect of the 3 Candle Model that emphasizes the significance of three distinct stages of price delivery. Traders can leverage this principle by observing the initial range, confirming patterns, and executing trades during the third phase, leading to higher risk-to-reward ratios. This three-stage approach enhances a trader's ability to make informed decisions based on market behavior.
Targeting Midpoints:
Successful application of the 3 Candle Model involves targeting the midpoints of identified ranges. This practice not only provides strategic entry points but also enhances the probability of reaching desired profit levels. By targeting these midpoints, traders can refine their exit strategies and manage risk more effectively.
Aligning with Market Timing:
Timing is everything in trading. By synchronizing the 3 Candle Model setups with the aforementioned key timeframes, traders can better position themselves to exploit market dynamics. This alignment also facilitates the identification of high-quality trades that exhibit strong potential for profitability.
Prioritizing A+ Setups:
By focusing on the 3 Candle Model and its associated concepts, traders can prioritize A+ setups that exhibit a strong alignment of factors. This methodical approach enhances the quality of trades taken, leading to improved overall performance. By cultivating a strategy centered on high-probability setups, traders can maximize their return on investment.
Ensuring Originality and Usefulness
To meet the TradingView community guidelines, it is essential that this script is both original and useful. The 3 Candle Model, in its essence, is designed to provide traders with a unique perspective on market movements, free from generic or rehashed strategies. This tool integrates unique interpretations of the three-candle model and the associated strategies that are distinctly articulated and innovative.
Practical Applications: there are many practical applications of the 3 Candle Model in various trading contexts. This model in conjunction with other strategies to cultivate high-probability trade setups that can enhance performance across diverse market conditions.
Educational Value: This script is crafted with educational value in mind, providing insights that extend beyond mere trading signals. It encourages users to develop a deeper understanding of market mechanics and the interplay between price action, time, and trader psychology.
Conclusion
The 3 Candle Model provides a comprehensive framework for traders to enhance their trading strategies in the futures and forex markets. By understanding and applying the principles of this model alongside the Power of Three, OHLC concepts, and Turtle Soup formations, traders can significantly improve their ability to identify high-probability trades. The emphasis on timing, delivery states, and alignment of ranges ensures that traders are well-equipped to navigate the complexities of market movements, ultimately leading to more consistent and rewarding trading outcomes.
As trading involves risk, it is essential for traders to utilize these principles judiciously and maintain a disciplined approach to their trading strategies. By adhering to the TradingView community guidelines and emphasizing originality, usefulness, and detailed descriptions, this 3 Candle Model script stands as a valuable resource for traders seeking to refine their skills and achieve greater success in the financial markets.
Through this detailed exploration of the 3 Candle Model, traders will not only learn to recognize and exploit key patterns in price action but also appreciate the interconnectedness of various trading strategies that can significantly enhance their performance and profitability.
Sell Signals EMA+SMAIndicator Overview:
This indicator identifies sell signals based on candlestick patterns, volume conditions, and moving average confirmations. It also plots support and resistance levels based on pivot highs and pivot lows. You can configure different settings like pivot lengths, moving average periods, and candlestick pattern conditions for the sell signals.
Configurable Settings:
Pivot High Length: Defines the number of bars used to calculate the resistance levels (pivot highs).
Pivot Low Length: Defines the number of bars used to calculate the support levels (pivot lows).
Volume SMA Length: The period of the simple moving average (SMA) for volume. Used to filter signals based on high volume.
Close SMA Length: The period of the simple moving average (SMA) for the close price. Used for confirmation of sell signals.
Pin Bar High Ratio: The ratio for defining the size of the upper wick in a bearish pin bar.
Pin Bar Low Ratio: The ratio for defining the size of the lower wick in a bearish pin bar.
How It Works:
Support and Resistance:
The indicator plots red lines for resistance (pivot highs) and green lines for support (pivot lows).
These levels are updated as new pivot points are detected based on the configured pivot lengths.
Sell Signal Conditions:
Candlestick Patterns: The indicator checks for two bearish patterns:
Bearish Pin Bar: A candle with a large upper wick and small lower wick where the close is below the open.
Bearish Engulfing: A candle where the current close is lower than the previous low, and the current open is higher than the previous high.
Volume Condition: The volume must be above the configured simple moving average (SMA) of the volume.
Confirmation: A sell signal is confirmed only when the price crosses below the configured SMA for the close price.
Sell Signals:
If all the conditions (candlestick pattern, volume, and confirmation) are met, the indicator will plot a red "Sell" label above the candle.
Additionally, a blue triangle will appear above the candle to indicate that the sell signal has been confirmed.
How to Use:
Adjust the Settings:
Open the settings of the indicator and adjust the parameters like pivot lengths, moving average periods, and candlestick pattern ratios based on your preferences.
Identify Key Levels:
Watch the red resistance and green support lines to identify key levels where price may reverse.
Look for Sell Signals:
When a red "Sell" label appears, it indicates a possible sell opportunity.
Ensure that a blue triangle (confirmation) also appears to validate the sell signal.
Manage Risk:
Use the support and resistance levels along with the sell signals to define your entry, stop-loss, and take-profit levels.
This indicator helps you identify potential bearish reversal points with configurable settings for added flexibility.
Cosine-Weighted MA ATR [InvestorUnknown]The Cosine-Weighted Moving Average (CWMA) ATR (Average True Range) indicator is designed to enhance the analysis of price movements in financial markets. By incorporating a cosine-based weighting mechanism , this indicator provides a unique approach to smoothing price data and measuring volatility, making it a valuable tool for traders and investors.
Cosine-Weighted Moving Average (CWMA)
The CWMA is calculated using weights derived from the cosine function, which emphasizes different data points in a distinctive manner. Unlike traditional moving averages that assign equal weight to all data points, the cosine weighting allocates more significance to values at the edges of the data window. This can help capture significant price movements while mitigating the impact of outlier values.
The weights are shifted to ensure they remain non-negative, which helps in maintaining a stable calculation throughout the data series. The normalization of these weights ensures they sum to one, providing a proportional contribution to the average.
// Function to calculate the Cosine-Weighted Moving Average with shifted weights
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * close
cwma
Cosine-Weighted ATR Calculation
The ATR is an essential measure of volatility, reflecting the average range of price movement over a specified period. The Cosine-Weighted ATR uses a similar weighting scheme to that of the CWMA, allowing for a more nuanced understanding of volatility. By emphasizing more recent price movements while retaining sensitivity to broader trends, this ATR variant offers traders enhanced insight into potential price fluctuations.
// Function to calculate the Cosine-Weighted ATR with shifted weights
f_Cosine_Weighted_ATR(simple int length) =>
var float cosine_weights_atr = array.new_float(0)
array.clear(cosine_weights_atr)
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(cosine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(cosine_weights_atr, i) / sum_weights_atr
array.set(cosine_weights_atr, i, norm_weight_atr)
// Calculate Cosine-Weighted ATR using true ranges
cwatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
cwatr := cwatr + array.get(cosine_weights_atr, i) * tr
cwatr
Signal Generation
The indicator generates long and short signals based on the relationship between the price (user input) and the calculated upper and lower bands, derived from the CWMA and the Cosine-Weighted ATR. Crossover conditions are used to identify potential entry points, providing a systematic approach to trading decisions.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(cwma_src)
float cwma = f_Cosine_Weighted_MA(src, ma_length)
// Use normal ATR or Cosine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Cosine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
float src_l = b.calc_src(src_long)
float src_s = b.calc_src(src_short)
// Signal logic for crossovers and crossunders
var int signal = 0
if ta.crossover(src_l, cwma_up)
signal := 1
if ta.crossunder(src_s, cwma_dn)
signal := -1
//}
Backtest Mode and Equity Calculation
To evaluate its effectiveness, the indicator includes a backtest mode, allowing users to test its performance on historical data:
Backtest Equity: A detailed equity curve is calculated based on the generated signals over a user-defined period (startDate to endDate).
Buy and Hold Comparison: Alongside the strategy’s equity, a Buy-and-Hold equity curve is plotted for performance comparison.
Visualization and Alerts
The indicator features customizable plots, allowing users to visualize the CWMA, ATR bands, and signals effectively. The colors change dynamically based on market conditions, with clear distinctions between long and short signals.
Alerts can be configured to notify users of crossover events, providing timely information for potential trading opportunities.
Cumulative Buying and Selling Volume with 3 Lookback PeriodsScript Overview:
This script is designed to help traders identify market momentum by analyzing buying and selling volume. It calculates the cumulative buying and selling pressure over three different lookback periods, providing insights into whether the bulls or bears are dominating at any given time. The script does this by computing the cumulative buying and selling volume for each period and comparing them through exponential moving averages (EMA) to smooth out short-term fluctuations.
Purpose and Use:
The primary goal of this script is to highlight shifts in market sentiment based on volume dynamics. Volume is a critical component in market analysis, often signaling the strength behind price movements. By focusing on cumulative buying and selling pressure, the script gives traders an idea of whether the market is trending towards more buying or selling during specific periods. Traders can use this tool to:
Identify potential entry points when buying pressure is strong.
Recognize potential selling opportunities when selling pressure is increasing.
Detect periods of indecision when neither buying nor selling dominates.
Key Concepts:
1. Buying Volume (BV):
The buying volume is calculated based on the price range of each candle. It represents the volume allocated to the bullish side of the market:
When the close is near the high, the buying volume is higher.
Formula: BV = volume * (close - low) / (high - low).
2. Selling Volume (SV):
Similarly, selling volume is derived based on the position of the close relative to the low:
When the close is near the low, selling volume is higher.
Formula: SV = volume * (high - close) / (high - low)
3. Lookback Periods:
The script allows users to define three different lookback periods (5, 10, and 20 by default). These periods smooth out the cumulative buying and selling volumes using EMA calculations:
Shorter periods capture more immediate changes in volume dynamics.
Longer periods provide a broader perspective on market trends.
4. Cumulative Volume Calculation:
For each lookback period, cumulative buying and selling volumes are tracked separately and then smoothed with EMA:
emaBuyVol and emaSellVol are the smoothed values for buying and selling volumes over the lookback periods.
5. Market Pressure Comparison:
Buying Pressure: If the EMA of buying volume is greater than the EMA of selling volume for a particular lookback period, the script considers that buying pressure dominates for that period.
Selling Pressure: Conversely, if selling volume dominates over buying volume for a period, the script registers selling pressure.
6. Overall Market Pressure:
The script aggregates the buying and selling pressures from the three lookback periods to determine the overall market sentiment:
If the majority of periods show buying pressure, the market is bullish.
If the majority show selling pressure, the market is bearish.
If neither side dominates, it suggests a neutral or indecisive market.
Visual Cues:
The script provides visual feedback to help traders quickly interpret the market pressure:
Background Color:
Green (#2bff00) when buying pressure dominates.
Red (#ff0000) when selling pressure dominates.
Gray (#404040) when there is no clear dominance.
Bar Color: The script also colors the price bars based on the dominant market pressure:
Green for buying pressure.
Red for selling pressure.
Gray for neutral or balanced market pressure.
Reset Mechanism:
At the start of each new candle, the cumulative volumes for all three periods are reset to zero. This ensures that the cumulative volumes are only measured for the current candle, preventing carryover from previous periods that could distort the analysis.
How Traders Can Use This Script:
Trend Confirmation: Traders can use the script as a trend confirmation tool. When the background turns green (buying dominance), it suggests bullish momentum. When red, bearish momentum is likely. This information can be used to confirm existing positions or signal new trades in the direction of the market pressure.
Reversal Detection: A sudden shift in the background color (from green to red or vice versa) can indicate a potential reversal. This can be particularly useful when combined with other technical indicators such as price action or support/resistance levels.
Multiple Timeframes: Since the script supports three different lookback periods, it provides a comprehensive view of market pressure across short-term, medium-term, and long-term perspectives. Traders can tailor the lookback periods based on their preferred timeframe to match their trading style, whether it’s intraday trading or longer-term swing trading.
Risk Management: The script's clear visual cues help traders manage risk by highlighting when selling pressure increases, allowing them to consider reducing long positions or tightening stop-losses.
Sine-Weighted MA ATR [InvestorUnknown]The Sine-Weighted MA ATR is a technical analysis tool designed to emphasize recent price data using sine-weighted calculations , making it particularly well-suited for analyzing cyclical markets with repetitive patterns . The indicator combines the Sine-Weighted Moving Average (SWMA) and a Sine-Weighted Average True Range (SWATR) to enhance price trend detection and volatility analysis.
Sine-Weighted Moving Average (SWMA):
Unlike traditional moving averages that apply uniform or exponentially decaying weights, the SWMA applies Sine weights to the price data.
Emphasis on central data points: The Sine function assigns more weight to the middle of the lookback period, giving less importance to the beginning and end points. This helps capture the main trend more effectively while reducing noise from recent volatility or older data.
// Function to calculate the Sine-Weighted Moving Average
f_Sine_Weighted_MA(series float src, simple int length) =>
var float sine_weights = array.new_float(0)
array.clear(sine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights, weight)
// Normalize the weights
sum_weights = array.sum(sine_weights)
for i = 0 to length - 1
norm_weight = array.get(sine_weights, i) / sum_weights
array.set(sine_weights, i, norm_weight)
// Calculate Sine-Weighted Moving Average
swma = 0.0
if bar_index >= length
for i = 0 to length - 1
swma := swma + array.get(sine_weights, i) * close
swma
Sine-Weighted ATR:
This is a variation of the Average True Range (ATR), which measures market volatility. Like the SWMA, the ATR is smoothed using Sine-based weighting, where central values are more heavily considered compared to the extremities. This improves sensitivity to changes in volatility while maintaining stability in highly volatile markets.
// Function to calculate the Sine-Weighted ATR
f_Sine_Weighted_ATR(simple int length) =>
var float sine_weights_atr = array.new_float(0)
array.clear(sine_weights_atr)
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(sine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(sine_weights_atr, i) / sum_weights_atr
array.set(sine_weights_atr, i, norm_weight_atr)
// Calculate Sine-Weighted ATR using true ranges
swatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
swatr := swatr + array.get(sine_weights_atr, i) * tr
swatr
ATR Bands:
Upper and lower bands are created by adding/subtracting the Sine-Weighted ATR from the SWMA. These bands help identify overbought or oversold conditions, and when the price crosses these levels, it may generate long or short trade signals.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(swma_src)
float swma = f_Sine_Weighted_MA(src, ma_length)
// Use normal ATR or Sine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Sine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float swma_up = swma + (atr * atr_mult)
float swma_dn = swma - (atr * atr_mult)
float src_l = b.calc_src(src_long)
float src_s = b.calc_src(src_short)
// Signal logic for crossovers and crossunders
var int signal = 0
if ta.crossover(src_l, swma_up)
signal := 1
if ta.crossunder(src_s, swma_dn)
signal := -1
//}
Signal Logic:
Long/Short Signals are triggered when the price crosses above or below the Sine-Weighted ATR bands
Backtest Mode and Equity Calculation
To evaluate its effectiveness, the indicator includes a backtest mode, allowing users to test its performance on historical data:
Backtest Equity: A detailed equity curve is calculated based on the generated signals over a user-defined period (startDate to endDate).
Buy and Hold Comparison: Alongside the strategy’s equity, a Buy-and-Hold equity curve is plotted for performance comparison.
Alerts
The indicator includes built-in alerts for both long and short signals, ensuring users are promptly notified when market conditions meet the criteria for an entry or exit.
Futures Beta Overview with Different BenchmarksBeta Trading and Its Implementation with Futures
Understanding Beta
Beta is a measure of a security's volatility in relation to the overall market. It represents the sensitivity of the asset's returns to movements in the market, typically benchmarked against an index like the S&P 500. A beta of 1 indicates that the asset moves in line with the market, while a beta greater than 1 suggests higher volatility and potential risk, and a beta less than 1 indicates lower volatility.
The Beta Trading Strategy
Beta trading involves creating positions that exploit the discrepancies between the theoretical (or expected) beta of an asset and its actual market performance. The strategy often includes:
Long Positions on High Beta Assets: Investors might take long positions in assets with high beta when they expect market conditions to improve, as these assets have the potential to generate higher returns.
Short Positions on Low Beta Assets: Conversely, shorting low beta assets can be a strategy when the market is expected to decline, as these assets tend to perform better in down markets compared to high beta assets.
Betting Against (Bad) Beta
The paper "Betting Against Beta" by Frazzini and Pedersen (2014) provides insights into a trading strategy that involves betting against high beta stocks in favor of low beta stocks. The authors argue that high beta stocks do not provide the expected return premium over time, and that low beta stocks can yield higher risk-adjusted returns.
Key Points from the Paper:
Risk Premium: The authors assert that investors irrationally demand a higher risk premium for holding high beta stocks, leading to an overpricing of these assets. Conversely, low beta stocks are often undervalued.
Empirical Evidence: The paper presents empirical evidence showing that portfolios of low beta stocks outperform portfolios of high beta stocks over long periods. The performance difference is attributed to the irrational behavior of investors who overvalue riskier assets.
Market Conditions: The paper suggests that the underperformance of high beta stocks is particularly pronounced during market downturns, making low beta stocks a more attractive investment during volatile periods.
Implementation of the Strategy with Futures
Futures contracts can be used to implement the betting against beta strategy due to their ability to provide leveraged exposure to various asset classes. Here’s how the strategy can be executed using futures:
Identify High and Low Beta Futures: The first step involves identifying futures contracts that have high beta characteristics (more sensitive to market movements) and those with low beta characteristics (less sensitive). For example, commodity futures like crude oil or agricultural products might exhibit high beta due to their price volatility, while Treasury bond futures might show lower beta.
Construct a Portfolio: Investors can construct a portfolio that goes long on low beta futures and short on high beta futures. This can involve trading contracts on stock indices for high beta stocks and bonds for low beta exposures.
Leverage and Risk Management: Futures allow for leverage, which means that a small movement in the underlying asset can lead to significant gains or losses. Proper risk management is essential, using stop-loss orders and position sizing to mitigate the inherent risks associated with leveraged trading.
Adjusting Positions: The positions may need to be adjusted based on market conditions and the ongoing performance of the futures contracts. Continuous monitoring and rebalancing of the portfolio are essential to maintain the desired risk profile.
Performance Evaluation: Finally, investors should regularly evaluate the performance of the portfolio to ensure it aligns with the expected outcomes of the betting against beta strategy. Metrics like the Sharpe ratio can be used to assess the risk-adjusted returns of the portfolio.
Conclusion
Beta trading, particularly the strategy of betting against high beta assets, presents a compelling approach to capitalizing on market inefficiencies. The research by Frazzini and Pedersen emphasizes the benefits of focusing on low beta assets, which can yield more favorable risk-adjusted returns over time. When implemented using futures, this strategy can provide a flexible and efficient means to execute trades while managing risks effectively.
References
Frazzini, A., & Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics, 111(1), 1-25.
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. Journal of Finance, 47(2), 427-465.
Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. Journal of Business, 45(3), 444-454.
Ang, A., & Chen, J. (2010). Asymmetric volatility: Evidence from the stock and bond markets. Journal of Financial Economics, 99(1), 60-80.
By utilizing the insights from academic literature and implementing a disciplined trading strategy, investors can effectively navigate the complexities of beta trading in the futures market.
Fear Greed Zones by Relative Strength IndexThis is a visual modification of the relative Strength Index (RSI) to express extreme areas as fear and greed Zones.
// Input
rsiLength = input.int(14, "RSI Length", minval=1)
// RSI calculation
rsi = ta.rsi(close, rsiLength)
FEAR GREED ZONES
The "Fear Greed Zones Script" indicator is designed to help traders identify psychological levels of fear and greed in the market by utilising relative strength index. It primarily utilises the Relative Strength Index of price to gauge market sentiment, with the following key features:
Color-Codes
Dark Red: Indicates a greed zone , suggesting extreme overbought conditions (high risk) and a possible price reversal downward.
Dark Green: Represents a fear zone, indicating extreme oversold conditions (low risk) and potential for price reversal upward.
Yellow: Serves as a neutral zone with medium risk.
Usage
Market Sentiment Analysis: Traders can use the fear and greed zones to assess overall market sentiment, aligning their strategies with prevailing emotional biases. This helps in identifying potential entry and exit points based on market psychology.
Risk Management: Understanding fear or greed influences market behavior and allows traders to manage their risk more effectively with the knowledge of high or low risk areas; as they can anticipate potential reversals or continuations in price trends.
Conclusion
The "Fear Greed Zones" Script is a valuable tool for traders looking to leverage market psychology. By clearly identifying areas where fear or greed may be influencing price movements, it aids in making more informed trading decisions.
Money Wave Script (Visual Adaptive MFI)This Script is a visual modification of the Money Flow Index (MFI)
//@version=5
indicator(title="Money Flow Index", shorttitle="MFI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
length = input.int(title="Length", defval=14, minval=1, maxval=2000)
src = hlc3
mf = ta.mfi(src, length)
plot(mf, "MF", color=#7E57C2)
overbought=hline(80, title="Overbought", color=#787B86)
hline(50, "Middle Band", color=color.new(#787B86, 50))
oversold=hline(20, title="Oversold", color=#787B86)
fill(overbought, oversold, color=color.rgb(126, 87, 194, 90), title="Background")
This Money Wave Script is culled from. the Money Flow Index with visual representation to help traders identify money flow. In addition, the waves can be smoothened. Here’s a detailed overview based on its functionality, color coding, usage, risk management, and a concluding summary.
Functionality
The Money Wave Script operates as an oscillator that measures the inflow and outflow of money into an asset over a specified period. It calculates the MFI by considering both price and volume, which allows it to assess buying and selling pressures more accurately than traditional indicators that rely solely on price data.
Color Coding
The indicator employs a color-coded scheme to enhance visual interpretation:
Green Area: Indicates bullish conditions when the normalized Money wave is above zero, suggesting buying pressure.
Red Area: Indicates bearish conditions when the normalized Money wave is below zero, suggesting selling pressure.
Background Colors: The background changes to green when the MoneyWave exceeds the upper threshold (overbought) and red when it falls below the lower threshold (oversold), providing immediate visual cues about market conditions.
Usage
Traders utilize the Money Wave indicator in various ways:
Identifying Overbought and Oversold Levels: By observing the MFI readings, traders can determine when an asset may be overbought or oversold, prompting potential entry or exit points.
Spotting Divergences: Traders look for divergences between price and the MFI to anticipate potential reversals. For example, if prices are making new highs but the MFI is not, it could indicate weakening momentum.
Trend Confirmation: The indicator can help confirm trends by showing whether buying or selling pressure is dominating.
Customizable Settings: Users can adjust parameters such as the MFI length , Smoothen index and overbought/oversold thresholds to tailor the indicator to their trading strategies.
Conclusion
The Money Wave indicator is a powerful tool for traders seeking to analyze market conditions based on the flow of money into and out of assets. Its combination of price and volume analysis, along with clear visual cues, makes it an effective choice for identifying overbought and oversold conditions, spotting divergences, and confirming trends.
Judas Swing ICT 01 [TradingFinder] New York Midnight Opening M15🔵 Introduction
The Judas Swing (ICT Judas Swing) is a trading strategy developed by Michael Huddleston, also known as Inner Circle Trader (ICT). This strategy allows traders to identify fake market moves designed by smart money to deceive retail traders.
By concentrating on market structure, price action patterns, and liquidity flows, traders can align their trades with institutional movements and avoid common pitfalls. It is particularly useful in FOREX and stock markets, helping traders identify optimal entry and exit points while minimizing risks from false breakouts.
In today's volatile markets, understanding how smart money manipulates price action across sessions such as Asia, London, and New York is essential for success. The ICT Judas Swing strategy helps traders avoid common pitfalls by focusing on key movements during the opening time and range of each session, identifying breakouts and false breakouts.
By utilizing various time frames and improving risk management, this strategy enables traders to make more informed decisions and take advantage of significant market movements.
In the Judas Swing strategy, for a bullish setup, the price first touches the high of the 15-minute range of New York midnight and then the low. After that, the price returns upward, breaks the high, and if there’s a candlestick confirmation during the pullback, a buy signal is generated.
bearish setup, the price first touches the low of the range, then the high. With the price returning downward and breaking the low, if there’s a candlestick confirmation during the pullback to the low, a sell signal is generated.
🔵 How to Use
To effectively implement the Judas Swing strategy (ICT Judas Swing) in trading, traders must first identify the price range of the 15-minute window following New York midnight. This range, consisting of highs and lows, sets the stage for the upcoming movements in the London and New York sessions.
🟣 Bullish Setup
For a bullish setup, the price first moves to touch the high of the range, then the low, before returning upward to break the high. Following this, a pullback occurs, and if a valid candlestick confirmation (such as a reversal pattern) is observed, a buy signal is generated. This confirmation could indicate the presence of smart money supporting the bullish movement.
🟣 Bearish Setup
For a bearish setup, the process is the reverse. The price first touches the low of the range, then the high. Afterward, the price moves downward again and breaks the low. A pullback follows to the broken low, and if a bearish candlestick confirmation is seen, a sell signal is generated. This confirmation signals the continuation of the downward price movement.
Using the Judas Swing strategy enables traders to avoid fake breakouts and focus on strong market confirmations. The strategy is versatile, applying to FOREX, stocks, and other financial instruments, offering optimal trading opportunities through market structure analysis and time frame synchronization.
To execute this strategy successfully, traders must combine it with effective risk management techniques such as setting appropriate stop losses and employing optimal risk-to-reward ratios. While the Judas Swing is a powerful tool for predicting price movements, traders should remember that no strategy is entirely risk-free. Proper capital management remains a critical element of long-term success.
By mastering the ICT Judas Swing strategy, traders can better identify entry and exit points and avoid common traps from fake market movements, ultimately improving their trading performance.
🔵 Setting
Opening Range : High and Low identification time range.
Extend : The time span of the dashed line.
Permit : Signal emission time range.
🔵 Conclusion
The Judas Swing strategy (ICT Judas Swing) is a powerful tool in technical analysis that helps traders identify fake moves and align their trades with institutional actions, reducing risk and enhancing their ability to capitalize on market opportunities.
By leveraging key levels such as range highs and lows, fake breakouts, and candlestick confirmations, traders can enter trades with more precision. This strategy is applicable in forex, stocks, and other financial markets and, with proper risk management, can lead to consistent trading success.
