(Early Test) Weekly Seasonality with Dynamic Kelly Criterion# Enhancing Trading Strategies with the Weekly Seasonality Dynamic Kelly Criterion Indicator
Amidst this pursuit to chase price, a common pitfall emerges: an overemphasis on price movements without adequate attention to risk management, probabilistic analysis, and strategic position sizing. To address these challenges, I developed the **Weekly Seasonality with Dynamic Kelly Criterion Indicator**. It is designed to refocus traders on essential aspects of trading, such as risk management and probabilistic returns, thereby catering to both short-term swing traders and long-term investors aiming for tax-efficient positions.
## The Motivation Behind the Indicator
### Overemphasis on Price: A Common Trading Pitfall
Many traders concentrate heavily on price charts and technical indicators, often neglecting the underlying principles of risk management and probabilistic analysis. This overemphasis on price can lead to:
- **Overtrading:** Making frequent trades based solely on price movements without considering the associated risks.
- **Poor Risk Management:** Failing to set appropriate stop-loss levels or position sizes, increasing the potential for significant losses.
- **Emotional Trading:** Letting emotions drive trading decisions rather than objective analysis, which can result in impulsive and irrational trades.
### The Need for Balanced Focus
To achieve sustained trading success, it is crucial to balance price analysis with robust risk management and probabilistic strategies. Key areas of focus include:
1. **Risk Management:** Implementing strategies to protect capital, such as setting stop-loss orders and determining appropriate position sizes based on risk tolerance.
2. **Probabilistic Analysis:** Assessing the likelihood of various market outcomes to make informed trading decisions.
3. **Swing Trading Percent Returns:** Capitalizing on short- to medium-term price movements by buying assets below their average return and selling them above.
## Introducing the Weekly Seasonality with Dynamic Kelly Criterion Indicator
The **Weekly Seasonality with Dynamic Kelly Criterion Indicator** is designed to integrate these essential elements into a comprehensive tool that aids traders in making informed, risk-aware decisions. Below, we explore the key components and functionalities of this indicator.
### Key Components of the Indicator
1. **Average Return (%)**
- **Definition:** The mean percentage return for each week across multiple years.
- **Purpose:** Serves as a benchmark to identify weeks with above or below-average performance, guiding buy and sell decisions.
2. **Positive Percentage (%)**
- **Definition:** The proportion of weeks that yielded positive returns.
- **Purpose:** Indicates the consistency of positive returns, helping traders gauge the reliability of certain weeks for trading.
3. **Volatility (%)**
- **Definition:** The standard deviation of weekly returns.
- **Purpose:** Measures the variability of returns, providing insights into the risk associated with trading during specific weeks.
4. **Kelly Ratio**
- **Definition:** A mathematical formula used to determine the optimal size of a series of bets to maximize the logarithmic growth of capital.
- **Purpose:** Balances potential returns against risks, guiding traders on the appropriate position size to take.
5. **Adjusted Kelly Fraction**
- **Definition:** The Kelly Ratio adjusted based on user-defined risk tolerance and external factors like Federal Reserve (Fed) stance.
- **Purpose:** Personalizes the Kelly Criterion to align with individual risk preferences and market conditions, enhancing risk management.
6. **Position Size ($)**
- **Definition:** The calculated amount to invest based on the Adjusted Kelly Fraction.
- **Purpose:** Ensures that position sizes are aligned with risk management strategies, preventing overexposure to any single trade.
7. **Max Drawdown (%)**
- **Definition:** The maximum observed loss from a peak to a trough of a portfolio, before a new peak is attained.
- **Purpose:** Assesses the worst-case scenario for losses, crucial for understanding potential capital erosion.
### Functionality and Benefits
- **Weekly Data Aggregation:** Aggregates weekly returns across multiple years to provide a robust statistical foundation for decision-making.
- **Quarterly Filtering:** Allows users to filter weeks based on quarters, enabling seasonality analysis and tailored strategies aligned with specific timeframes.
- **Dynamic Risk Adjustment:** Incorporates the Dynamic Kelly Criterion to adjust position sizes in real-time based on changing risk profiles and market conditions.
- **User-Friendly Visualization:** Presents all essential metrics in an organized Summary Table, facilitating quick and informed decision-making.
## The Origin of the Kelly Criterion and Addressing Its Limitations
### Understanding the Kelly Criterion
The Kelly Criterion, developed by John L. Kelly Jr. in 1956, is a formula used to determine the optimal size of a series of bets to maximize the long-term growth of capital. The formula considers both the probability of winning and the payout ratio, balancing potential returns against the risk of loss.
**Kelly Formula:**
\
Where:
- \( b \) = the net odds received on the wager ("b to 1")
- \( p \) = probability of winning
- \( q \) = probability of losing ( \( q = 1 - p \) )
### The Risk of Ruin
While the Kelly Criterion is effective in optimizing growth, it carries inherent risks:
- **Overbetting:** If the input probabilities or payout ratios are misestimated, the Kelly Criterion can suggest overly aggressive position sizes, leading to significant losses.
- **Assumption of Constant Probabilities:** The criterion assumes that probabilities remain constant, which is rarely the case in dynamic markets.
- **Ignoring External Factors:** Traditional Kelly implementations do not account for external factors such as Federal Reserve rates, margin requirements, or market volatility, which can impact risk and returns.
### Addressing Traditional Limitations
Recognizing these limitations, the **Weekly Seasonality with Dynamic Kelly Criterion Indicator** introduces enhancements to the traditional Kelly approach:
- **Incorporation of Fed Stance:** Adjusts the Kelly Fraction based on the current stance of the Federal Reserve (neutral, dovish, or hawkish), reflecting broader economic conditions that influence market behavior.
- **Margin and Leverage Considerations:** Accounts for margin rates and leverage, ensuring that position sizes remain within manageable risk parameters.
- **Dynamic Adjustments:** Continuously updates position sizes based on real-time risk assessments and probabilistic analyses, mitigating the risk of ruin associated with static Kelly implementations.
## How the Indicator Aids Traders
### For Short-Term Swing Traders
Short-term swing traders thrive on capitalizing over weekly price movements. The indicator aids them by:
- **Identifying Favorable Weeks:** Highlights weeks with above-average returns and favorable volatility, guiding entry and exit points.
- **Optimal Position Sizing:** Utilizes the Adjusted Kelly Fraction to determine the optimal amount to invest, balancing potential returns with risk exposure.
- **Probabilistic Insights:** Provides metrics like Positive Percentage (%) and Kelly Ratio to assess the likelihood of favorable outcomes, enhancing decision-making.
### For Long-Term Tax-Free Investors
This is effectively a drop-in replacement for DCA which uses fixed position size that doesn't change based on market conditions, as a result, it's like catching multiple falling knifes by the blade and smiling with blood on your hand... I don't know about you, but I'd rather juggle by the hilt and look like an actual professional...
Long-term investors, especially those seeking tax-free positions (e.g., through retirement accounts), benefit from:
- **Consistent Risk Management:** Ensures that position sizes are aligned with long-term capital preservation strategies.
- **Seasonality Analysis:** Allows for strategic positioning based on historical performance trends across different weeks and quarters.
- **Dynamic Adjustments:** Adapts to changing market conditions, maintaining optimal risk profiles over extended investment horizons.
### Developers
Please double check the logic and functionality because I think there are a few issue and I need to crowd source solutions and be responsible about the code I publish. If you have corrections, please DM me or leave a respectful comment.
I want to publish this by the end of the year and include other things like highlighting triple witching weeks, adding columns for volume % stats, VaR and CVaR, alpha, beta (to see the seasonal alpha and beta based off a benchmark ticker and risk free rate ticker and other little goodies.
ابحث في النصوص البرمجية عن "etf开盘时间"
Trend Following Moron TFM 10% System
Trend Following Moron TFM 10% System
The TFM 10% Market Timing System
The Trend Following Moron TFM 10% System is a powerful trading tool designed using Pine Script™, following the principles outlined by Dave S. Landry. This script helps traders identify optimal entry and exit points based on moving averages and market trends.
What the Script Does:
Visual representation of trend strength.
As long as it is trending in green band, trend is very strong and price is contained within 5% of the high.
As price drops to yellow band, strength is weakening and caution is advised. Price is between 5% to 10% away from52 week high.
As price drops in red band, it is to be avoided as trend is rolling over. Price is more than 10% way from 52 week high.
Moving Averages Calculation:
Users can choose between Simple Moving Average (SMA) and Exponential Moving Average (EMA) for daily, weekly, and monthly periods. The script calculates the moving averages to provide trend direction.
Trend Color Coding:
Moving averages are displayed in different colors based on market conditions: green indicates an uptrend, red for a downtrend, and gray for neutral conditions.
Highs Calculation:
The script calculates the 52-week and 12-month closing highs, which are crucial for identifying potential breakout points.
Level Definition:
Traders can set levels based on either Average True Range (ATR) or percentage changes from these highs, allowing for flexible risk management strategies.
Buy and Sell Conditions:
The script defines specific buy conditions: when the price is within 10% of the highest close and trading above the moving averages, and sell conditions: when the price falls below these thresholds.
Visual Indicators:
Buy and sell signals are visually represented on the chart with arrows, making it easy for traders to see potential trading opportunities at a glance.
Performance Labels:
The script includes performance labels that track the number of bars above or below the moving averages and the percentage change from the moving average, providing users with key metrics to evaluate their trades.
Interactive Table:
A table summarizing the buy and sell rules is displayed on the chart, ensuring that traders have quick access to the system’s trading logic.
Benefits of Using the TFM 10% System:
Streamlined Decision Making:
The script simplifies the trading process by clearly outlining buy and sell signals, making it accessible even for novice traders.
Customizable Parameters:
Users can tailor the script to their preferences by adjusting moving average types and lengths, ATR levels, and percentage thresholds. Bands are interchange able for ATR and Percent below 52 week high for volatility looks. But buy and sell are fixed in 10% threshold.
Risk Management:
By utilizing ATR and percentage levels, traders can effectively manage their risk, making the trading process more systematic.
Comprehensive Market Analysis:
The combination of multiple time frames (daily, weekly, monthly) allows for a well-rounded analysis of market trends, enhancing trading accuracy.
VR1 DEMA - Liquidity IdentifierThis custom Pine Script indicator, titled "VR1 DEMA - Liquidity Identifier", is designed to help traders identify periods of significant resistance to price movement, often indicating high liquidity areas where the market may encounter difficulty moving in one direction. The indicator analyzes the relationship between volume and price range, combined with bar volume conditions, to provide enhanced signals of potential liquidity buildup.
Key Features:
Customizable EMA Lengths:
Users can define the lengths of both the fast and slow Exponential Moving Averages (EMAs), with default values of 5 for the fast EMA and 13 for the slow EMA. These EMAs are calculated from the ratio of volume to price range, smoothing the data to detect trends in liquidity.
Dynamic Fast EMA Color:
The fast EMA changes color based on its relationship to the slow EMA:
Red when the fast EMA is above the slow EMA, signaling stronger resistance or greater liquidity.
White when the fast EMA is below the slow EMA, indicating potentially weaker resistance.
Liquidity Signal with Multiplier Condition:
The background of the chart changes to white when the volume-to-price ratio exceeds 1.5 times the fast EMA. This highlights potential areas of liquidity buildup where price movement may encounter stronger resistance. The 1.5 multiplier is adjustable, allowing for sensitivity customization.
Volume Condition for Enhanced Signals:
A new condition is added that requires the actual bar volume to exceed 1.2 times the 5-period EMA of average bar volume. This ensures that the background color only changes when there is not only increased liquidity but also significantly higher trading volume. The 1.2 multiplier is user-adjustable for further refinement.
Combined Liquidity and Volume Filtering:
Both conditions (volume-to-price ratio and actual volume) must be met for the background color to change. This double-filtering helps traders spot moments of unusual market activity more accurately.
Optional Volume/Price Range Visualization:
An optional plot of the volume-to-price ratio is included, providing a visual representation of how volume interacts with price movement in real-time. This can be enabled or disabled based on user preference.
User-Friendly Customization:
The script includes inputs for adjusting the fast and slow EMA lengths, as well as the multipliers for the volume-to-price ratio and actual volume conditions. These customizable parameters allow traders to tailor the indicator to their specific market strategies.
Use Case:
This indicator is particularly useful for identifying periods of high liquidity and resistance in the market, where price movement may stall or reverse. By combining volume-to-price ratio analysis with actual volume conditions, the indicator provides more reliable signals for detecting potential breakouts, reversals, or consolidation periods. The color-coded fast EMA and background shading make it easy to spot key moments of increased market activity and liquidity.
Auto Anchored Swing VWAP'sThe Auto Anchored Swing VWAP's indicator automatically anchors Volume-Weighted Average Price (VWAP) lines to recent swing highs and swing lows. VWAPs often act as key support or resistance levels because they represent the average price at which the majority of trading volume has occurred over a given time.
What is VWAP? VWAP is an essential tool in trading, representing the average price of a security over a specific period, weighted by volume. It helps traders identify the average price at which most trades have been executed, providing a balanced view of price action over time.
Anchored VWAPs: Unlike traditional VWAPs, which start from the beginning of the day, anchored VWAPs allow traders to "anchor" the calculation to a specific point in time or a pivot on the chart, in this case a swing high and swing low. This version of VWAP follows the price action from a selected point forward.
When the price is above the VWAP, it indicates that the majority of traders have paid less for the asset, creating a potential support zone as buyers may step in at or near this level. On the other hand, when the price is below the VWAP, it suggests that most traders have paid a higher price, which can lead to a resistance level where sellers may appear to defend their positions.
Anchored VWAPs, in particular, provide more precise support and resistance levels by starting from a specific swing high, swing low, or other significant point on the chart. This allows traders to track how price interacts with these levels after a certain bar.
The selectable pivot lookback length in this indicator defines the number of bars to the left and right of a potential swing high or swing low that must be lower (for a swing high) or higher (for a swing low) in order to confirm the pivot. In other words, it controls how many surrounding bars need to validate a local price extreme before it is considered a true swing point.
For example, if the lookback length is set to 9, a swing high is identified when there are 9 bars to the left and 9 bars to the right that all have lower highs than the current bar. The same logic applies for swing lows, where the price must be lower than the highs of the bars to the left and right for it to be considered a swing low.
This parameter allows traders to control the sensitivity of the swing points used to anchor VWAPs. A smaller lookback value will identify more frequent and short-term swing highs and lows, making the VWAPs more responsive to recent price action. Conversely, a larger lookback value will result in fewer but more significant swing points.
Pine Script
Utilization of Pine Script’s Enum Feature: This indicator leverages Pine Script's new enum feature for the selection of the VWAP lines (solid, dashed, or dotted) style.
Day & Swing Trading EMA Clouds with Adaptive LevelsDay & Swing Trading EMA Clouds with Adaptive Levels is a tool designed for traders who need a flexible indicator that adapts to both short-term (day trading) and long-term (swing trading) strategies. The indicator blends EMA clouds and adaptive support/resistance levels, making it suitable for analyzing trend strength and key price zones.
How It Works:
EMA Clouds for Trend Detection:
This indicator uses three EMAs (Fast, Intermediate, Slow) to create two clouds:
Fast Cloud: The area between the fast and Intermediate EMAs.
Slow Cloud: The area between the Intermediate and slow EMAs.
The cloud colors change based on trend direction:
Positive (uptrend): When the fast EMA is above the Intermediate EMA (turquoise) or the Intermediate EMA is above the slow EMA (teal).
Negative (downtrend): When the fast EMA is below the Intermediate EMA (pink) or the Intermediate EMA is below the slow EMA (magenta).
Traders can use these clouds to visually gauge market momentum and trend reversals.
Adaptive EMA Settings Based on Trading Mode:
The EMA lengths adjust automatically depending on whether you're in Day Trading or Swing Trading mode:
Day Trading Mode uses shorter periods to capture quick price movements:
Fast EMA: 5-period
Mid EMA: 13-period
Slow EMA: 21-period
Swing Trading Mode uses longer periods to capture broader trends:
Fast EMA: 12-period
Mid EMA: 26-period
Slow EMA: 50-period
This dynamic adjustment allows you to switch between trading styles seamlessly, with the EMAs reflecting the most relevant timeframes for each strategy.
Adaptive Support and Resistance Levels:
Depending on the selected trading mode, the indicator dynamically plots key levels:
Day Trading Mode: Previous day’s high, low, and midpoint, as well as 2-day levels.
Swing Trading Mode: Previous month’s high, low, and midpoint, as well as 2-month levels.
These levels act as dynamic support and resistance zones, giving traders critical areas to monitor for potential reversals or breakouts.
Buy & Sell Signals:
Visual buy/sell signals are generated when the fast EMA crosses above or below the slow EMA. These signals can help traders identify potential trend reversals.
Customization:
You can fully adjust the transparency and colors of the clouds to fit your personal preferences and trading style.
Why This Combination?
Combining EMA clouds with adaptive levels provides traders with a complete picture. The clouds highlight the underlying market momentum and trend strength, while the adaptive levels offer potential entry/exit points based on historical price action. This unique mashup allows traders to follow trends and plan trades around key support and resistance zones.
3-Bar (Outside Bar) Scanner with Table Display# 3-Bar (Outside Bar) Scanner with Table Display
## Overview
The **3-Bar (Outside Bar) Scanner with Table Display** is a custom TradingView indicator designed for traders who utilize **The Strat** methodology. This indicator scans for **3-bar (Outside Bar)** patterns across multiple symbols and displays the results in a convenient table format directly on your chart.
## Purpose
- **Efficient Multi-Symbol Scanning**: Monitor up to four symbols simultaneously for 3-bar patterns without the need to switch between charts.
- **Real-Time Updates**: The table dynamically updates with new price data, providing immediate insights into potential trading opportunities.
- **Visual Clarity**: Displays whether a 3-bar is bullish ("3 Up") or bearish ("3 Down"), helping you quickly interpret market sentiment.
## How It Works
- **Data Retrieval**: The indicator uses `request.security()` to fetch high, low, open, and close prices for the specified symbols and timeframe.
- **3-Bar Detection**:
- **Outside Bar Criteria**: Checks if the current candle's high is higher than the previous candle's high and the current low is lower than the previous low.
- **Direction Determination**:
- **"3 Up"**: If the candle closes higher than it opens (bullish candle).
- **"3 Down"**: If the candle closes lower than it opens (bearish candle).
- **Table Display**:
- The table shows the **Symbol**, **Timeframe**, and **State** ("3 Up", "3 Down", or blank if no pattern detected).
- Customizable colors and positioning to fit your chart's aesthetics.
## Best Use Cases
- **Rapid Market Analysis**: Ideal for traders needing a quick overview of multiple assets for potential 3-bar setups.
- **Strategic Decision-Making**: Helps identify key reversal or continuation patterns in alignment with **The Strat** principles.
- **Scalable Monitoring**: By utilizing TradingView's multi-chart layouts, you can expand monitoring beyond four symbols.
## Instructions for Use
### Adding the Indicator to Your Chart
1. **Copy the Code**: Use the provided Pine Script code for the indicator.
2. **Create a New Indicator**:
- In TradingView, click on **Pine Editor** at the bottom of the platform.
- Paste the code into the editor.
3. **Save and Add to Chart**:
- Click **Save** and give your indicator a name.
- Click **Add to Chart** to apply it.
### Customizing the Inputs
- **Symbols**:
- **Symbol 1**: Leave blank to use the current chart's symbol or enter a specific symbol (e.g., `AAPL`).
- **Symbol 2 to Symbol 4**: Enter additional symbols or leave them blank.
- **Timeframe**: Select your desired timeframe (e.g., `D` for Daily, `60` for 60-minute).
- **Table Colors**:
- Customize header and data colors for better visibility against your chart background.
### Interpreting the Table
- **Symbol**: Displays the symbol without the exchange prefix for clarity.
- **Timeframe**: Shows the timeframe applied to the analysis.
- **State**:
- **"3 Up"**: A bullish outside bar where the candle closed higher than it opened.
- **"3 Down"**: A bearish outside bar where the candle closed lower than it opened.
- **Blank**: No 3-bar pattern detected on the latest candle.
### Monitoring More Than Four Symbols
- **Multi-Chart Layout**:
- Use TradingView's multi-chart feature to display multiple charts within a single workspace.
- Apply the indicator to each chart. For example:
- **Four-Chart Grid**: Monitor up to 16 symbols by setting up four charts, each with the indicator tracking four symbols.
- **Steps**:
1. Arrange your workspace into a multi-chart layout.
2. Add the indicator to each chart.
3. Input different symbols into the indicator on each chart.
## Example Usage
Suppose you want to monitor the following symbols on a Daily timeframe:
- **Symbol 1**: *(Leave blank to use the current chart's symbol, e.g., `SPY`)*
- **Symbol 2**: `AAPL`
- **Symbol 3**: `TSLA`
- **Symbol 4**: `AMZN`
After adding the indicator and entering these symbols:
- **SPY**: The table shows "3 Up" in the State column, indicating a bullish outside bar.
- **AAPL**: No 3-bar pattern detected; the State column is blank.
- **TSLA**: The table shows "3 Down," indicating a bearish outside bar.
- **AMZN**: The table shows "3 Up," indicating another bullish outside bar.
This setup allows you to quickly assess which symbols are exhibiting significant patterns that may warrant further analysis or action.
## Notes
- **Customization**: Feel free to adjust the table's position and colors to suit your preferences.
- **Limitations**:
- Be aware of TradingView's limitations on `request.security()` calls, which may vary based on your subscription plan.
- The indicator is designed to monitor up to four symbols per instance due to these limitations.
- **Scalability**:
- By using multi-chart layouts, you can effectively monitor more symbols without overloading a single chart.
- This approach allows you to scale up your monitoring capabilities to fit your trading strategy.
## Conclusion
The **3-Bar (Outside Bar) Scanner with Table Display** is a valuable tool for traders who utilize **The Strat** methodology. It streamlines the process of identifying key 3-bar patterns across multiple symbols and timeframes, enhancing your ability to make informed trading decisions quickly.
By integrating this indicator into your trading routine, you can:
- Stay alert to significant market movements.
- Reduce the time spent manually scanning charts.
- Increase efficiency in executing your trading strategy.
---
Feel free to share this indicator with the Strat community. Feedback and suggestions are welcome to further enhance its functionality. Happy trading!
Flexible Moving Average StrategyThis strategy offers flexibility to choose between SMA and EMA, and allows users to set the review frequency to Daily, Weekly, or Monthly. It adapts to different market conditions by providing full control over the length and timeframe of the Moving Average.
### Key Features:
- **Moving Average Method**: Select between SMA and EMA.
- **Review Frequency**: Choose Daily, Weekly, or Monthly review periods.
- **Customizable**: Set the Moving Average length and timeframe.
- **Entry/Exit Rules**:
- **Enter Long**: When the close price is above the Moving Average at the end of the period.
- **Exit**: When the close price falls below the Moving Average.
### Parameters:
- **Review Frequency**: Daily, Weekly, Monthly
- **Moving Average Method**: SMA or EMA
- **Length & Timeframe**: Fully adjustable
This strategy suits traders who prefer a flexible, trend-following approach based on long-term price movements.
EMA CheatsheetEMA Clouds Indicator: A Comprehensive Guide for Traders
The Exponential Moving Average (EMA) Clouds indicator is a dynamic tool designed to provide traders with visual cues about the current trend and potential shifts in market momentum. The EMA is a type of moving average that gives more weight to recent price data, making it highly responsive to price changes compared to a Simple Moving Average (SMA). When used in the form of clouds, EMAs are layered on top of each other to form a visual representation of bullish and bearish trends.
Understanding EMA Clouds
EMA Clouds consist of two or more EMAs, typically a short-term EMA (e.g., 9-period) and a longer-term EMA (e.g., 21-period). When these two EMAs are plotted together, they create a "cloud" between them. The interaction between these EMAs gives traders critical insights into the market's trend:
Bullish Clouds: When the shorter-term EMA crosses above the longer-term EMA, the market is considered to be in a bullish trend. This creates a green (or lighter colored) cloud between the EMAs, signaling upward momentum. Bullish clouds suggest that buyers are in control, and the price is likely to continue higher.
Bearish Clouds: Conversely, when the shorter-term EMA crosses below the longer-term EMA, the market is considered to be in a bearish trend. This forms a red (or darker colored) cloud between the EMAs, indicating downward momentum. Bearish clouds imply that sellers are dominating the market, and the price is likely to decline.
Key Components of the EMA Clouds Indicator:
Short-Term EMA: This is the fast-moving average (e.g., 9-period EMA) and reacts quickly to recent price changes. It’s used to detect short-term shifts in momentum.
Long-Term EMA: This is the slower-moving average (e.g., 21-period EMA), which smooths out price data over a longer period and identifies the general trend direction.
Cloud: The area between the short-term and long-term EMAs. When this cloud is green (bullish), it indicates that the short-term trend is stronger than the long-term trend. When the cloud turns red (bearish), it suggests that the short-term trend is weaker than the long-term trend.
Cloud Thickness: The thickness of the cloud provides additional information about the strength of the trend. A thicker cloud suggests strong price divergence between short and long-term trends, which could indicate a robust trend. A thinner cloud, on the other hand, may signal trend weakness or consolidation.
Long Signal Consecutive Lower Shadows - Correct Bars ColoredThis script identifies and highlights consecutive lower shadows on candlesticks in TradingView. A lower shadow is the portion of the candlestick between the low price and the lower of the open or close prices, often indicating price rejection at lower levels.
Key Features:
Threshold Settings: The user can customize the minimum length of the lower shadow (lowerShadowThreshold) and the maximum allowable price difference between consecutive lows (priceDifferenceThreshold).
Bar Coloring: When two consecutive bars meet the lower shadow condition, both bars are colored (default green).
Alerts: An alert is triggered when consecutive lower shadows are detected, allowing users to be notified of potential market reversals or buy opportunities.
TASC 2024.10 Adaptive Oscillator Threshold█ OVERVIEW
This script introduces a more dynamic approach to generating trading signals using the RSI indicator and a threshold that adapts to price trends and dispersion. This methodology comes from Francesco Bufi's article "Overbought/Oversold Oscillators: Useless Or Just Misused" from the October 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
According to Francesco Bufi's observations, an oscillator-based buy signal should have a threshold that varies with the trend direction: higher during uptrends and lower during downtrends. Additionally, the level should decrease as the distance from the price to its mean increases to reduce signals in volatile conditions. Accordingly, Bufi proposes a formula for an adaptive buy level whose value is proportional to the trend (linear regression slope) and inversely proportional to the typical distance between price and its mean (standard deviation). Traders can apply this method to any oscillator to add adaptivity without modifying the oscillator's calculations, as it's simply an adaptive technique for interpreting the calculated values.
This script demonstrates the application of Bufi's Adaptive Threshold (BAT) in a simple RSI-based strategy and allows users to compare its performance to the traditional fixed-threshold approach. Bufi's observations suggest that using the BAT instead of a static threshold can help improve the backtest performance of oscillator-based systems.
█ DISCLAIMER
This strategy script educates users on the trading systems outlined by the TASC article. By default, it uses 10% of equity as the order size and a slippage amount of 5 ticks. Traders should adjust these settings and the commission amount when using this script.
Daily Moving Average for Intraday TimeframesThis indicator provides a dynamic tool for visualizing the Daily Moving Average (DMA) on intraday timeframes.
It allows you to analyze how the price behaves in relation to the daily moving average in timeframes from 1 minute up to 1 day.
KEY FEATURES
DMA on Intraday timeframes only : This indicator is designed to work exclusively on intraday charts with timeframes between 1 minute and 1 day. It will not function on tick, second-based, or daily-and-above charts.
Color-Coded Zones for Trend Identification :
Green Zone: The price is above a rising DMA, signaling a bullish momentum.
Red Zone: The price is below a falling DMA, signaling a bearish momentum.
Yellow Zone: Signaling uncertainty or mixed conditions, where either the price is above a falling DMA or below a rising/flat DMA.
Configurable DMA Period : You can adjust the number of days over which the DMA is calculated (default is 5 days). This can be customized based on your trading strategy or market preferences.
24/7 Market Option : For assets that trade continuously (e.g., cryptocurrencies), activate the "Is trading 24/7?" setting to ensure accurate calculations.
WHAT IS THE DMA AND WHY USE IT INTRADAY?
The Daily Moving Average is a Simple Moving Average indicator used to smooth out price fluctuations over a specified period (in days) and reveal the underlying trend.
Typically, a SMA takes price value for the current timeframe and reveal the trend for this timeframe. It gives you the average price for the last N candles for the given timeframe.
But what makes the Intraday DMA interesting is that it shows the underlying trend of the Daily timeframe on a chart set on a shorter timeframe . This helps to align intraday trades with broader market movements.
HOW IS THE DMA CALCULATED?
If we are to build a N-day Daily Moving Average using a Simple Moving Average, we need to take the amount of candles A needed in that timeframe to account for a period of a day and multiply it by the number of days N of the desired DMA.
So for instance, let say we want to compute the 5-Day DMA on the 10 minute timeframe :
In the 10 minute timeframe there are 39 candles in a day in the regular session.
We would take the 39 candles per day and then multiply that by 5 days. 39 x 5 = 195.
So a 5-day moving average is represented by a simple moving average with a period of 195 when looking at a 10 minute timeframe.
So for each period, to create a 5-day DMA, you would have to set the period of your simple moving average like so :
- 195 minutes = 10 period
- 130 minutes = 15 period
- 65 minutes = 30 period
- 30 minutes = 65 period
- 15 minutes = 130 period
- 10 minutes = 195 period
- 5 minutes = 390 period
and so on.
This indicator attempts to do this calculation for you on any intraday timeframe and whatever the period you want to use is for your DMA. You can create a 10-day moving average, a 30-day moving average, etc.
Magic Order Blocks [MW]Add a slim design, minimalist view of the most relevant higher and lower order blocks to your chart. Use our novel method of filtering that uses both the the number of consecutive bullish or bearish candles that follow the order block, and the number of ATRs that the asset’s price changed following the order block. View just the order blocks above and below the current price, or view the backgrounds for each and every one. And, if you're up to it, dig into a comprehensive view of the data for each order block candle.
Settings:
General Settings
Minimum # of Consecutive Bars Following Order Block
Show Bullish Order Blocks Below / Hide Last Bullish Block
Show Bearish Order Blocks Above / Hide Last Bearish Block
Use ATR Filter - Select # of ATRs Below
Closest Order Block is Followed by This Many ATRs
Preferences
Right Offset of Indicator Label
Show Mid-Line from Recent Order Block Indicator Label
Use ATRs Instead of Consecutive Candles in Label Indicator
Show Timestamp of Recent Order Block
Show Large Order Block Detail Labels
Show Small Order Block Labels
Background Settings
Show Background for Recent Order Block Indicator Label
# of Backgrounds to Show Before Now
Show All Bullish Order Block Backgrounds
Show All Bearish Order Block Backgrounds
Calculations
This indicator creates a matrix of each order block that is followed by the user-specified number of consecutive bullish or bearish candles. The data can be further filtered by the number of ATRs that the price moves after the order block - also user-defined. The most recent bearish order block above the current price takes arrays from the initial filtered matrix of arrays, filters once more by the “mid-price” of the order block (the average between the order block candle high and low) and selects the last element from this order block matrix. The same follows for the latest bearish order block above the current price.
How to Use
An order block refers to a price range or zone on a chart where large institutional orders have been placed, causing a significant shift in market direction. These zones are crucial because they often indicate areas of strong buying or selling interest, which can lead to future support or resistance levels. Traders use order blocks to identify potential points of market reversal or continuation.
The Magic Order Blocks default view shows the most recent overhead bearish order block above the current price, and the most recent bullish order block below. These can presumably act as support or resistance levels, because they reflect the last price where a significant price move occurred. “Significant” meaning that the order block candle was followed by many consecutive bullish or bearish candles. Based on the user-defined settings, it can also mean that price moved multiples of the asset's average true range (ATR). More consecutive candles means that the duration of the move lasted a long time. A higher ATR move indicates that the price moved impulsively in one direction.
The default view also shows a label to the right of the current price that provides the price level, the time stamp of the order block (optional), and a sequence of bars that show the significance of the level. By default, these bars represent the number of ATRs that price rose or fell following the order block, but they can be toggled to show the number of consecutive bullish or bearish candles that followed the order block.
Although the default view provides the zones that are most relevant to the current price, past order block candles can also be identified visually with labels as well with translucent backgrounds color-coded for bullish or bearish bias. Overlapping backgrounds can identify an area that has been repeatedly been an area of support or resistance.
A detailed view of each order block can also be viewed the includes the following data points:
Bar Index
Timestamp
Consecutive Accumulated Volume
Consecutive Bars
Price Change over Consecutive Bars
Price/Volume Ratio Over Consecutive Bars
Mid Price of Order Block
High Price of Order Block
Low Price of Order Block
ATRs over Consecutive Bars
- Other Usage Notes and Limitations:
The calculations used only provide an estimated relationship or a close approximation, and are not exact.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Things to keep in mind. Longer timeframes don’t necessarily have a as many consecutive candle drops or gains as with shorter timeframes, so be sure to adjust your settings when moving to 1 hour, 1 day, or 1 week timeframes from 1 minute, 5 minute, or 15 minute timeframes.
Bull Bear Power With EMA FilterDescription of Indicator:
This Pine Script indicator colors price bars based on the open price in relation to custom moving averages (EMA/SMA), Bull/Bear Power (BBPower), and an optional VWAP filter. The bar colors help identify bullish and bearish conditions with added visual cues for price positioning relative to VWAP.
Key Features:
Customizable Moving Averages (EMA/SMA):
The user can select between EMA or SMA for both short-term and long-term moving averages.
Default moving averages are set to 5 (short-term) and 9 (long-term) but can be adjusted by the user.
Bullish Condition (Blue or Purple Bars):
A bar is colored blue if the following conditions are met:
The open price is above both the short-term and long-term moving averages.
The short-term moving average (MA 1) is above the long-term moving average (MA 2).
BBPower (open price minus the 13-period EMA) is positive, indicating bullish strength.
If the VWAP filter is enabled and the price opens below VWAP, the bullish bars will turn purple.
Bearish Condition (Yellow or Orange Bars):
A bar is colored yellow if the following conditions are met:
The open price is below both the short-term and long-term moving averages.
The short-term moving average (MA 1) is below the long-term moving average (MA 2).
BBPower is negative or zero, indicating bearish market conditions.
If the VWAP filter is enabled and the price opens above VWAP, the bearish bars will turn orange.
VWAP Filter (Optional):
An optional filter allows the user to add VWAP (Volume-Weighted Average Price) to the bar coloring logic.
When the VWAP filter is enabled, it provides additional information about price positioning relative to VWAP, turning bullish bars purple and bearish bars orange depending on whether the price opens above or below VWAP.
Usage:
Bullish Trend: Look for blue or purple bars to identify potential bullish momentum.
Bearish Trend: Look for yellow or orange bars to spot bearish conditions in the market.
The indicator allows users to customize the length and type of moving averages (EMA or SMA), as well as decide whether to apply the VWAP filter.
This indicator provides traders with clear visual signals to quickly assess the strength of bullish or bearish conditions based on the price's position relative to custom moving averages, BBPower, and VWAP, helping with trend identification and potential trade setups.
Hull MA with Alerts and LabelsThis script is designed to help traders visually track market trends using various types of moving averages (MAs) and to receive alerts when certain conditions are met. Here’s a detailed breakdown of how the script works:
1. User Inputs and Customization:
MA Length: Traders can define the length of the moving average (default is 100).
Confirmation Candles: The trader can specify how many candles must confirm a trend before the script triggers a signal (default is 1).
MA Variation: The trader can choose between different moving average types: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), or Hull Moving Average (HMA).
Source: Traders select the price source for the moving average calculation (e.g., close price).
Ribbon Transparency: Allows control over the transparency level of the ribbon plotted between the moving averages.
Bullish/Bearish Ribbon Colors: The user can choose the colors for bullish and bearish trends.
2. Moving Average Calculations:
The script provides multiple options for calculating moving averages:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
For the Hull Moving Average (HMA), it uses a specific formula that smoothens the movement and reduces lag, which is helpful for more reactive trend detection.
3. Plotting Moving Averages and Trend Ribbon:
The script calculates two key moving averages:
MHULL: The main moving average, selected based on the user’s chosen MA variation and source.
SHULL: A shifted version of the MHULL to help compare trends (shifted by 2 bars).
These two moving averages are plotted on the chart for visualization. MHULL is plotted in green (or another color if changed), while SHULL is plotted in red. A ribbon is drawn between MHULL and SHULL to indicate trends visually. The ribbon changes color depending on whether the trend is bullish (MHULL > SHULL) or bearish (MHULL < SHULL). The ribbon’s transparency can be adjusted for visual clarity.
4. Trend Detection:
Bullish Trend: The script checks if the price has closed above MHULL for the defined number of confirmation candles. If confirmed, a bullish trend is detected.
Bearish Trend: Similarly, the script checks if the price has closed below SHULL for the confirmation period, indicating a bearish trend.
The script tracks whether the market is in a bullish or bearish trend and prevents repeated signals by remembering the current trend state.
5. Alerts and Labels:
Bullish Alerts and Labels: When a confirmed bullish trend is detected (i.e., price closes above MHULL for the entire confirmation period and MHULL > SHULL), the script triggers an alert notifying the trader of the bullish condition. A "BULLISH" label is placed on the chart near the low of the candle where the trend was confirmed.
Bearish Alerts and Labels: If a confirmed bearish trend is detected (i.e., price closes below SHULL for the confirmation period and MHULL < SHULL), the script triggers an alert for the bearish condition. A "BEARISH" label is placed on the chart near the high of the candle where the trend was confirmed.
These alerts and labels help traders act quickly on trend changes and align their trading strategy with market conditions.
6. Practical Use for Traders:
For traders, this script offers:
Customizability : It allows traders to define the length and type of moving averages, choose price sources, and control how signals are confirmed.
Visual Trend Representation : The plotted MA lines and colored ribbons help traders easily see market direction.
Early Warnings : With alerts and labels, the script gives traders early signals when trends are shifting, allowing them to adjust positions accordingly.
Trend Confirmation : The script waits for a user-defined number of confirmation candles before signaling a new trend, reducing false signals.
Overall, the script helps traders automate their strategy by tracking moving averages and alerting them when key trend conditions are met.
Dynamic ConfluenceThe Dynamic MA Confluence Indicator is a powerful tool designed to simplify your trading experience by automatically identifying the most influential moving average (MA) lengths on your chart. Whether you're using Simple Moving Averages (SMA) or Exponential Moving Averages (EMA), this indicator helps you pinpoint the MA length that holds the greatest confluence, allowing you to make informed trading decisions with ease.
How It Works:
This indicator analyzes a wide range of moving averages, from short-term to long-term, to determine which ones are closest to each other. By setting a "Proximity Percentage," you can control how close these MAs need to be to be considered as having confluence. The indicator then calculates the average of these close MAs to establish a dynamic support or resistance level on your chart.
Why Use This Indicator?
Automatic Optimization: Unsure of which MA length to apply? The indicator automatically highlights the MA length with the most confluence, giving you a clear edge in identifying significant market levels.
Adaptability: Choose between SMA and EMA to suit your trading strategy and market conditions.
Enhanced Decision-Making: By focusing on the MA length with the greatest influence, you can better anticipate market movements and adjust your strategies accordingly.
Customizable Sensitivity: Adjust the Proximity Percentage to fine-tune the indicator's sensitivity, ensuring it aligns with your trading preferences.
Key Feature:
Current Key Confluence MA Length: Displayed in an optional table, this feature shows the MA length that currently has the most impact on the confluence level, providing you with actionable insights at a glance.
Whether you're a seasoned trader or just starting, the Dynamic MA Confluence Indicator offers a streamlined approach to understanding market dynamics, helping you trade smarter and with more confidence. This presentation text is designed to clearly communicate the purpose, functionality, and benefits of the indicator, making it easy for users to understand its value and how it can enhance their trading strategies.
The Dynamic MA Confluence Indicator is a tool designed to assist traders in analyzing market trends. It should not be considered as financial advice or a guarantee of future performance. Trading involves significant risk, and it is possible to lose more than your initial investment. Users should conduct their own research and consider their financial situation before making trading decisions. Always consult with a financial advisor if you are unsure about any trading strategies or decisions. This disclaimer is intended to remind users of the inherent risks in trading and the importance of conducting their own due diligence.
Dynamic Jurik RSX w/ Fisher Transform█ Introduction
The Dynamic Jurik RSX with Fisher Transform is a powerful and adaptive momentum indicator designed for traders who seek a non-laggy view of price movements. This script is based on the classic Jurik RSX (Relative Strength Index). It also includes features such as the dynamic overbought and oversold limits, the Inverse Fisher Transform, trend display, slope calculations, and the ability to color extremes for better clarity.
█ Key Features:
• RSX: The Relative Strength Index (RSX) in this script is based on Jurik’s RSX, which is smoother than the traditional RSI and aims to reduce noise and lag. This script calculates the RSX using an exponential smoothing technique and adaptive adjustments.
• Inverse Fisher Transform: This script can optionally apply the Inverse Fisher Transform to the RSX, which helps to normalize the RSX values, compressing them between -1 and 1. The inverse transformation makes it easier to spot extreme values (overbought and oversold conditions) by enhancing the visual clarity of those extremes. It also smooths the curve over a user-defined period in hopes of providing a more consistent signal.
• Dynamic Limits: The dynamic overbought and oversold limits are calculated based on the RSX's recent high and low values. The limits adjust dynamically depending on market conditions, making them more relevant to current price action.
• Slope Display: The slope of the RSX is calculated as the rate of change between the current and previous RSX value. The slope is displayed as dots when the slope exceeds the threshold designated by the user, providing visual cues for momentum shifts.
• Trend Coloring: Optionally, the user can also enable a trend-based display. It is simply based on current value of RSX versus the previous one. If RSX is rising then the trend is bullish, if not, then the trend is bearish.
• Coloring Extremes: Users can configure the RSX to color the chart when prices enter extreme conditions, such as overbought or oversold zones, providing visual cues for market reversals.
█ Attached Chart Notes:
• Top Panel: Enabled dynamic limits, Trend display, standard Jurik RSX with 20 lookback period, and Slope display.
• Middle Panel: Enabled dynamic limits, Extremes display, and standard Jurik RSX with 20 lookback period.
• Bottom Panel: Enabled dynamic limits, Trend display, Inverse Fisher Transform with 14 lookback period and 9 smoothing period. and Slope display.
█ Credits:
Special thanks to Everget for providing the original script. The script was also slightly modified based on updates from outside sources.
█ Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research and consult a professional before making any trading decisions.
Sinc MAKaiser Windowed Sinc Moving Average Indicator
The Kaiser Windowed Sinc Moving Average is an advanced technical indicator that combines the sinc function with the Kaiser window to create a highly customizable finite impulse response (FIR) filter for financial time series analysis.
Sinc Function: The Ideal Low-Pass Filter
At the core of this indicator is the sinc function, which represents the impulse response of an ideal low-pass filter. In signal processing and technical analysis, the sinc function is crucial because it allows for the creation of filters with precise frequency cutoff characteristics. When applied to financial data, this means the ability to separate long-term trends from short-term fluctuations with remarkable accuracy.
The primary advantage of using a sinc-based filter is the independent control over two critical parameters: the cutoff frequency and the number of samples used. The cutoff frequency, analogous to the "length" in traditional moving averages, determines which price movements are considered significant (low frequency) and which are treated as noise (high frequency). By adjusting the cutoff, analysts can fine-tune the filter to respond to specific market cycles or timeframes of interest.
The number of samples used in the filter doesn't affect the cutoff frequency but instead influences the filter's accuracy and steepness. Increasing the sample size results in a better approximation of the ideal low-pass filter, leading to sharper transitions between passed and attenuated frequencies. This allows for more precise trend identification and noise reduction without changing the fundamental frequency response characteristics.
Kaiser Window: Optimizing the Sinc Filter
While the sinc function provides excellent frequency domain characteristics, it has infinite length in the time domain, which is impractical for real-world applications. This is where the Kaiser window comes into play. By applying the Kaiser window to the sinc function, we create a finite-length filter that approximates the ideal response while minimizing unwanted oscillations (known as the Gibbs phenomenon) in the frequency domain.
The Kaiser window introduces an additional parameter, alpha, which controls the trade-off between the main-lobe width and side-lobe levels in the frequency response. This parameter allows users to fine-tune the filter's behavior, balancing between sharp cutoffs and minimal ripple effects.
Customizable Parameters
The Kaiser Windowed Sinc Moving Average offers several key parameters for customization:
Cutoff: Controls the filter's cutoff frequency, determining the divide between trends and noise.
Length: Sets the number of samples used in the FIR filter calculation, affecting the filter's accuracy and computational complexity.
Alpha: Influences the shape of the Kaiser window, allowing for fine-tuning of the filter's frequency response characteristics.
Centered and Non-Centered Modes
The indicator provides two operational modes:
Non-Centered (Real-time) Mode: Uses half of the windowed sinc function, suitable for real-time analysis and current market conditions.
Centered Mode: Utilizes the full windowed sinc function, resulting in a zero-phase filter. This mode introduces a delay but offers the most accurate trend identification for historical analysis.
Visualization Features
To enhance the analytical value of the indicator, several visualization options are included:
Gradient Coloring: Offers a range of color schemes to represent trend direction and strength.
Glow Effect: An optional visual enhancement for improved line visibility.
Background Fill: Highlights the area between the moving average and price, aiding in trend visualization.
Applications in Technical Analysis
The Kaiser Windowed Sinc Moving Average is particularly useful for precise trend identification, cycle analysis, and noise reduction in financial time series. Its ability to create custom low-pass filters with independent control over cutoff and filter accuracy makes it a powerful tool for analyzing various market conditions and timeframes.
Compared to traditional moving averages, this indicator offers superior frequency response characteristics and reduced lag in trend identification when properly tuned. It provides greater flexibility in filter design, allowing analysts to create moving averages tailored to specific trading strategies or market behaviors.
Conclusion
The Kaiser Windowed Sinc Moving Average represents an advanced approach to price smoothing and trend identification in technical analysis. By making the ideal low-pass filter characteristics of the sinc function practically applicable through Kaiser windowing, this indicator provides traders and analysts with a sophisticated tool for examining price trends and cycles.
Its implementation in Pine Script contributes to the TradingView community by making advanced signal processing techniques accessible for experimentation and further development in technical analysis. This indicator serves not only as a practical tool for market analysis but also as an educational resource for those interested in the intersection of signal processing and financial markets.
Related script:
Larry Connors 3 Day High/Low StrategyThe Larry Connors 3 Day High/Low Strategy is a short-term mean-reversion trading strategy that is designed to identify potential buying opportunities when a security is oversold. This strategy is based on the principles developed by Larry Connors, a well-known trading system developer and author.
Key Strategy Elements:
1. Trend Confirmation: The strategy first confirms that the security is in a long-term uptrend by ensuring that the closing price is above the 200-day moving average (condition1). This rule helps filter trades to align with the longer-term trend.
2. Short-Term Pullback: The strategy looks for a short-term pullback by ensuring that the closing price is below the 5-day moving average (condition2). This identifies potential entry points when the price temporarily moves against the longer-term trend.
3. Three Consecutive Lower Highs and Lows:
• The high and low two days ago are lower than those of the day before (condition3).
• The high and low yesterday are lower than those of two days ago (condition4).
• Today’s high and low are lower than yesterday’s (condition5).
These conditions are used to identify a sequence of declining highs and lows, signaling a short-term pullback or oversold condition in the context of an overall uptrend.
4. Entry and Exit Signals:
• Buy Signal: A buy order is triggered when all the above conditions are met (buyCondition).
• Sell Signal: A sell order is executed when the closing price is above the 5-day moving average (sellCondition), indicating that the pullback might be ending.
Risks of the Strategy
1. Mean Reversion Failure: This strategy relies on the assumption that prices will revert to the mean after a short-term pullback. In strong downtrends or during market crashes, prices may continue to decline, leading to significant losses.
2. Whipsaws and False Signals: The strategy may generate false signals, especially in choppy or sideways markets where the price does not follow a clear trend. This can lead to frequent small losses that can add up over time.
3. Dependence on Historical Patterns: The strategy is based on historical price patterns, which do not always predict future price movements accurately. Sudden market news or economic changes can disrupt the pattern.
4. Lack of Risk Management: The strategy as written does not include stop losses or position sizing rules, which can expose traders to larger-than-expected losses if conditions change rapidly.
About Larry Connors
Larry Connors is a renowned trader, author, and founder of Connors Research and TradingMarkets.com. He is widely recognized for his development of quantitative trading strategies, especially those focusing on short-term mean reversion techniques. Connors has authored several books on trading, including “Short-Term Trading Strategies That Work” and “Street Smarts,” co-authored with Linda Raschke. His strategies are known for their systematic, rules-based approach and have been widely used by traders and investment professionals.
Connors’ research often emphasizes the importance of trading with the trend, managing risk, and using statistically validated techniques to improve trading outcomes. His work has been influential in the field of quantitative trading, providing accessible strategies for traders at various skill levels.
References
1. Connors, L., & Raschke, L. (1995). Street Smarts: High Probability Short-Term Trading Strategies.
2. Connors, L. (2009). Short-Term Trading Strategies That Work.
3. Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
This strategy and its variations are popular among traders looking to capitalize on short-term price movements while aligning with longer-term trends. However, like all trading strategies, it requires rigorous backtesting and risk management to ensure its effectiveness under different market conditions.
Averaging Down Strategy1. Averaging Down:
Definition: "Averaging Down" is a strategy in which an investor buys more shares of a declining asset, thus lowering the average purchase price. The main idea is that, by averaging down, the investor can recover faster when the price eventually rebounds.
Risk Considerations: This strategy assumes that the asset will recover in value. If the price continues to decline, however, the investor may suffer larger losses. Academic research highlights the psychological bias of loss aversion that often leads investors to engage in averaging down, despite the increased risk (Barberis & Huang, 2001).
2. RSI (Relative Strength Index):
Definition: The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is commonly used to identify overbought or oversold conditions. A reading below 30 (or in this case, 35) typically indicates an oversold condition, which might suggest a potential buying opportunity (Wilder, 1978).
Risk Considerations: RSI-based strategies can produce many false signals in range-bound or choppy markets, where prices do not exhibit strong trends. This can lead to multiple losing trades and an overall negative performance (Gencay, 1998).
3. Combination of RSI and Price Movement:
Approach: The combination of RSI for entry signals and price movement (previous day's high) for exit signals aims to capture short-term market reversals. This hybrid approach attempts to balance momentum with price confirmation.
Risk Considerations: While this combination can work well in trending markets, it may struggle in volatile or sideways markets. Additionally, a significant risk of averaging down is that the trader may continue adding to a losing position, which can exacerbate losses if the price keeps falling.
Risk Warnings:
Increased Losses Through Averaging Down:
Averaging down involves buying more of a falling asset, which can increase exposure to downside risk. Studies have shown that this approach can lead to larger losses when markets continue to decline, especially during prolonged bear markets (Statman, 2004).
A key risk is that this strategy may lead to significant capital drawdowns if the price of the asset does not recover as expected. In the worst-case scenario, this can result in a total loss of the invested capital.
False Signals with RSI:
RSI-based strategies are prone to generating false signals, particularly in markets that do not exhibit strong trends. For example, Gencay (1998) found that while RSI can be effective in certain conditions, it often fails in choppy or range-bound markets, leading to frequent stop-outs and drawdowns.
Psychological Bias:
Behavioral finance research suggests that the "Averaging Down" strategy may be influenced by loss aversion, a bias where investors prefer to avoid losses rather than achieve gains (Kahneman & Tversky, 1979). This can lead to poor decision-making, as investors continue to add to losing positions in the hope of a recovery.
Empirical Studies:
Gencay (1998): The study "The Predictability of Security Returns with Simple Technical Trading Rules" found that technical indicators like RSI can provide predictive value in certain markets, particularly in volatile environments. However, they are less reliable in markets that lack clear trends.
Barberis & Huang (2001): Their research on behavioral biases, including loss aversion, explains why investors are often tempted to average down despite the risks, as they attempt to avoid realizing losses.
Statman (2004): In "The Diversification Puzzle," Statman discusses how strategies like averaging down can increase risk exposure without necessarily improving long-term returns, especially if the underlying asset continues to perform poorly.
Conclusion:
The "Averaging Down Strategy with RSI" combines elements of technical analysis with a psychologically-driven averaging down approach. While the strategy may offer opportunities in trending or oversold markets, it carries significant risks, particularly in volatile or declining markets. Traders should be cautious when using this strategy, ensuring they manage risk effectively and avoid overexposure to a losing position.
Support Resistance UltimateThe "Support Resistance ULTIMATE" indicator is a comprehensive tool for traders on the TradingView platform, designed to identify key support and resistance levels using two primary techniques: pivot points and volume data. This indicator provides flexibility and customization, allowing traders to adapt it to their specific trading strategies.
KEY FEATURES
Pivot-Based Levels:
This feature calculates support and resistance levels using pivot points, which are derived from the high, low, and close prices of previous trading periods. Pivot points are crucial for forecasting potential market turning points.
Users can customize the pivot calculation by selecting the source type (either 'Close' or 'High/Low') and adjusting the lookback periods for both the left and right sides of the pivot calculation. This flexibility allows traders to adapt the indicator to different market conditions and timeframes.
Volume-Based Levels:
This option focuses on identifying support and resistance levels based on volume data, specifically the Point of Control (POC). The POC represents the price level with the highest traded volume during a specific time period, reflecting a consensus value among market participants.
The indicator includes a rolling POC calculation, allowing traders to dynamically assess areas of significant trading interest that may serve as support or resistance zones.
ADVANTAGES
Customization and Flexibility:
Traders can choose between pivot-based and volume-based levels or use both simultaneously, depending on their analysis needs. This dual approach provides a comprehensive view of market dynamics, accommodating various trading styles.
The indicator offers customizable color settings for support and resistance lines, enhancing chart readability and allowing traders to personalize their visual analysis.
Enhanced Market Insights:
By utilizing pivot points, traders can identify potential reversal or consolidation points, aiding in the prediction of market trends and the establishment of strategic entry and exit points.
Volume-based levels provide insights into market sentiment and participation, highlighting areas of strong support or resistance based on trading volume. This can improve risk management and trade execution by identifying high-probability trading zones.
Importance Scoring:
The indicator calculates the importance of each level based on the number of touches and the duration it holds. This scoring system helps traders assess the strength of support and resistance levels, with thicker lines indicating more significant levels.
This indicator is intended for educational and informational purposes only and should not be considered financial advice. Trading involves significant risk, and you should consult with a financial advisor before making any trading decisions. The performance of this indicator is not guaranteed, and past results do not predict future performance. Use at your own risk.
Kaiser Window MAKaiser Window Moving Average Indicator
The Kaiser Window Moving Average is a technical indicator that implements the Kaiser window function in the context of a moving average. This indicator serves as an example of applying the Kaiser window and the modified Bessel function of the first kind in technical analysis, providing an open-source implementation of these functions in the TradingView Pine Script ecosystem.
Key Components
Kaiser Window Implementation
This indicator incorporates the Kaiser window, a parameterized window function with certain frequency response characteristics. By making this implementation available in Pine Script, it allows for exploration and experimentation with the Kaiser window in the context of financial time series analysis.
Modified Bessel Function of the First Kind
The indicator includes an implementation of the modified Bessel function of the first kind, which is integral to the Kaiser window calculation. This mathematical function is now accessible within TradingView, potentially useful for other custom indicators or studies.
Customizable Alpha Parameter
The indicator features an adjustable alpha parameter, which directly influences the shape of the Kaiser window. This parameter allows for experimentation with the indicator's behavior:
Lower alpha values: The indicator's behavior approaches that of a Simple Moving Average (SMA)
Moderate alpha values: The behavior becomes more similar to a Weighted Moving Average (WMA)
Higher alpha values: Increases the weight of more recent data points
In signal processing terms, the alpha parameter affects the trade-off between main-lobe width and side lobe level in the frequency domain.
Centered and Non-Centered Modes
The indicator offers two operational modes:
Non-Centered (Real-time) Mode: Uses half of the Kaiser window, starting from the peak. This mode operates similarly to traditional moving averages, suitable for real-time analysis.
Centered Mode: Utilizes the full Kaiser window, resulting in a phase-correct filter. This mode introduces a delay equal to half the window size, with the plot automatically offset to align with the correct time points.
Visualization Options
The indicator includes several visualization features to aid in analysis:
Gradient Coloring: Offers three gradient options:
• Three-color gradient: Includes a neutral color
• Two-color gradient: Traditional up/down color scheme
• Solid color: For a uniform appearance
Glow Effect: An optional visual enhancement for the moving average line.
Background Fill: An option to fill the area between the moving average and the price.
Use Cases
The Kaiser Window Moving Average can be applied similarly to other moving averages. Its primary value lies in providing an example implementation of the Kaiser window and modified Bessel function in TradingView. It serves as a starting point for traders and analysts interested in exploring these mathematical concepts in the context of technical analysis.
Conclusion
The Kaiser Window Moving Average indicator demonstrates the application of the Kaiser window function in a moving average calculation. By providing open-source implementations of the Kaiser window and the modified Bessel function of the first kind, this indicator contributes to the expansion of available mathematical tools in the TradingView Pine Script environment, potentially facilitating further experimentation and development in technical analysis.
Composite Momentum█ Introduction
The Composite Momentum Indicator is a tool we came across that we found to be useful at detecting implied tops and bottoms within quick market cycles. Its approach to analyzing momentum through a combination of moving averages and summation techniques makes it a useful addition to the range of available indicators on TradingView.
█ How It Works
This indicator operates by calculating the difference between two moving averages—one fast and one slow, which can be customized by the user. The difference between these two averages is then expressed as a percentage of the fast moving average, forming the core momentum value which is then smoothed with an Exponential Moving Average is applied. The smoothed momentum is then compared across periods to identify directional changes in direction
Furthermore, the script calculates the absolute differences between consecutive momentum values. These differences are used to determine periods of momentum acceleration or deceleration, aiming to establish potential reversals.
In addition to tracking momentum changes, the indicator sums positive and negative momentum changes separately over a user-defined period. This summation is intended to provide a clearer picture of the prevailing market bias—whether it’s leaning towards strength or weakness.
Finally, the summed-up values are normalized to a percentage scale. This normalization helps in identifying potential tops and bottoms by comparing the relative strength of the momentum within a given cycle.
█ Usage
This indicator is primarily useful for traders who focus on detecting quick cycle tops and bottoms. It provides a view of momentum shifts that can signal these extremes, though it’s important to use it in conjunction with other tools and market analysis techniques. Given its ability to highlight potential reversals, it may be of interest to those who seek to understand short-term market dynamics.
█ Disclaimer
This script was discovered without any information about its author or original intent but was nonetheless ported from its original format that is available publicly. It’s provided here for educational purposes and should not be considered a guaranteed method for market analysis. Users are encouraged to test and understand the indicator thoroughly before applying it in real trading scenarios.
Honey Badger and Dip and Rip Days**Definitions**
A Honey Badger Day is defined as a day where the market dips below a certain threshold but then closes above it. Specifically:
- The day's low is less than or equal to the lower of either the opening price or the previous day's closing price.
- The day's closing price is greater than or equal to this same lower threshold.
Dip and Rip Day:A Dip and Rip Day is characterized by a more pronounced dip followed by a stronger recovery. The criteria are:
- The day's low is below 0.11% of the lower of the day's opening price or the previous day's closing price.
- The day's closing price is at least 0.405% higher than its opening price.
- The day's closing price is at least 0.792% higher than its low.
- The day's closing price is at least 0.405% higher than the previous day's closing price.
Both patterns indicate a day where the market experiences a dip but then recovers, with the Dip and Rip pattern showing a more dramatic movement in both directions.
