TTP OI + LS signal filterThis oscillator helps filtering specific conditions in the market based on open interest (OI) and the ratio of longs and shorts (LS) for crypto assets.
Currently it works with BINANCE:BTCUSDT.P but soon I'll be adding support for more assets.
It flags areas of interest like:
- Too many longs, too many shorts in the market
- Open interest too high or too low
It accepts an external signal as a source in which case filters can be applied to the original signal. For example the external signal might trigger and plot a 1 when RSI break below 70. By connecting such signal with this oscillator you'll be able to only pass-through the ones that occur when any of the areas of interest mentioned above are also valid.
If both filter are applied it acts as an OR. For example, if too many longs and too many shorts are active, it will pass through the signal in either condition.
The results of the original signal filtered is printed to be able to later use it in any external backtester strategy that accepts external sources too.
If external source signal is disabled it will trigger any time the combined filters are returning true.
Open interest and the ratio of longs/shorts is considered too high whenever the stochastic RSI calculation of the OI or ratio LS reaches a level above 80 and too low when below 20
The ratio of long/shorts is calculated by dividing the ratio of longs vs shorts from BITFINEX:BTCUSDLONGS and BITFINEX:BTCUSDSHORTS
Cerca negli script per "股价在8元左右净利润为正市值小于80亿的热门股票有哪些"
RSI, SRSI, MACD and DMI cross - Open source codeHello,
I'm a passionate trader who has spent years studying technical analysis and exploring different trading strategies. Through my research, I've come to realize that certain indicators are essential tools for conducting accurate market analysis and identifying profitable trading opportunities. In particular, I've found that the RSI, SRSI, MACD cross, and Di cross indicators are crucial for my trading success.
Detailed explanation:
The RSI is a momentum indicator that measures the strength of price movements. It is calculated by comparing the average of gains and losses over a certain period of time. In this indicator, the RSI is calculated based on the close price with a length of 14 periods.
The Stochastic RSI is a combination of the Stochastic Oscillator and the RSI. It is used to identify overbought and oversold conditions of the market. In this indicator, the Stochastic RSI is calculated based on the RSI with a length of 14 periods.
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of prices. It consists of two lines, the MACD line and the signal line, which are used to generate buy and sell signals. In this indicator, the MACD is calculated based on the close price with fast and slow lengths of 12 and 26 periods, respectively, and a signal length of 9 periods.
The DMI is a trend-following indicator that measures the strength of directional movement in the market. It consists of three lines, the Positive Directional Indicator (+DI), the Negative Directional Indicator (-DI), and the Average Directional Index (ADX), which are used to generate buy and sell signals. In this indicator, the DMI is calculated with a length of 14 periods and an ADX smoothing of 14 periods.
The indicator generates buy signals when certain conditions are met for each of these indicators.
1) For the RSI, a buy signal is generated when the RSI is below or equal to 35 and the Stochastic RSI %K is below or equal to 15, or when the RSI is below or equal to 28 the Stochastic RSI %K is below or equal to 15 or when the RSI is below or equal to 25 and the Stochastic RSI %K is below or equal to 10 or when the RSI is below or equal to 28.
2) For the MACD, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than 0.
3) For the DMI, a buy signal is generated when the Positive Directional Indicator (+DI) crosses above the Negative Directional Indicator (-DI), and the -DI is less than the +DI.
The indicator generates sell signals when certain conditions are met for each of these indicators:
1) For the RSI, a sell signal is generated when the RSI is above or equal to 75 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 80 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 85 and the Stochastic RSI %K is above or equal to 90 or when the RSI is above or equal to 82.
2)For the MACD, a sell signal is generated when the MACD line is above 0, there is a change in the histogram from positive to negative, the MACD line and histogram are positive in the previous period, and the current histogram value is less than the previous histogram value. On the other hand, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than the previous histogram value.
3)For the DMI a bearish signal is generated when plusDI crosses above minusDI, indicating that bulls are losing strength and bears are taking control.
The indicator uses a combination of these four indicators to generate potential buy and sell signals. The buy signals are generated when RSI and SRSI values are in oversold conditions, while sell signals are generated when RSI and SRSI values are in overbought conditions. The indicator also uses MACD crossovers and DMI crossovers to generate additional buy and sell signals.
When a signal is strong?
The use of multiple signals within a specific timeframe can increase the accuracy and reliability of the signals generated by this indicator. It is recommended to look for at least two signals within a range of 5-8 candles in order to increase the probability of a successful trade.
Why it's original?
1) There is no indicator in the library that combine all of these indicators and give you a 360 view
2)The combination of the RSI, Stochastic RSI, MACD, and DMI indicators in a single script it's unique and not available in the libray.
3)The specific parameters and conditions used to calculate the signals may be unique and not found in other scripts or libraries.
4)The use of plotshape() to plot the signals as shapes on the chart may be unique compared to other scripts that simply plot lines or bars to indicate signals.
5)The use of alertcondition() to trigger alerts based on the signals may be unique compared to other scripts that do not have custom alert functionality.
Keep attention!
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
Support me:)
If you find this new indicator helpful in your trading analysis, I would greatly appreciate your support! Please consider giving it a like, leaving feedback, or sharing it with your trading network. Your engagement will not only help me improve this tool but will also help other traders discover it and benefit from its features. Thank you for your support!
hidden & regular rsi divergenceThis is a divergence indicator that draws regular and hidden divergences based on the Zigzag indicator and RSI indicator. There are two degrees of Zigzag. So, in each Zigzag degree, there are two types of regular divergences and one type of hidden divergence.
👉(The logic is written in case of a bearish regular divergence. The opposite will apply for a bullish one.)
Type 1 of regular divergence (Logic 1):
Zigzag has to form a higher high. The highest RSI within both Zigzag legs must form lower highs, but the RSI values which are exactly at the Zigzag highs should not form lower highs.
Type 2 of regular divergence (Logic 2):
Zigzag has to form a higher high. The highest RSI within both Zigzag legs must form lower highs, and the RSI values which are exactly at the Zigzag highs should form lower highs.
👉(The logic is written in case of a bearish hidden divergence. The opposite will apply for a bullish one.)
Zigzag has to form a lower high. The highest RSI within both Zigzag legs must form higher highs.
👉There is also a filter that will be applied to all the divergences. It only shows the divergences whose corresponding RSI value was above/below a level (overbought level/oversold level).
Logic for regular divergences:
Bearish regular divergence's first high's (leftmost) RSI value should be greater than or equal to 70.
Bullish regular divergence's first low's (leftmost) RSI value should be less than or equal to 30.
Logic for hidden divergences:
Bearish hidden divergence's second high's (rightmost) RSI value should be greater than or equal to 70.
Bullish hidden divergence's second low's (rightmost) RSI value should be less than or equal to 30.
👉There is another feature also. This indicator colors the background based on whether the RSI is in a bullish or bearish range.
If it's within 80-60, the background will be colored green (this means that RSI is in a bullish range).
If it's within 40-20, the background will be colored red (this means that RSI is in a bearish range).
Stochastic Chebyshev Smoothed With Zero Lag SmoothingFast and Smooth Stochastic Oscillator with Zero Lag
Introduction
In this post, we will discuss a custom implementation of a Stochastic Oscillator that not only smooths the signal but also does so without introducing any noticeable lag. This is a remarkable achievement, as it allows for a fast Stochastic Oscillator that is less prone to false signals without being slow and sluggish.
We will go through the code step by step, explaining the various functions and the overall structure of the code.
First, let's start with a brief overview of the Stochastic Oscillator and the problem it addresses.
Background
The Stochastic Oscillator is a momentum indicator used in technical analysis to determine potential overbought or oversold conditions in an asset's price. It compares the closing price of an asset to its price range over a specified period. However, the Stochastic Oscillator is susceptible to false signals due to its sensitivity to price movements. This is where our custom implementation comes in, offering a smoother signal without noticeable lag, thus reducing the number of false signals.
Despite its popularity and widespread use in technical analysis, the Stochastic Oscillator has its share of drawbacks. While it is a price scaler that allows for easier comparisons across different assets and timeframes, it is also known for generating false signals, which can lead to poor trading decisions. In this section, we will delve deeper into the limitations of the Stochastic Oscillator and discuss the challenges associated with smoothing to mitigate its drawbacks.
Limitations of the Stochastic Oscillator
False Signals: The primary issue with the Stochastic Oscillator is its tendency to produce false signals. Since it is a momentum indicator, it reacts to short-term price movements, which can lead to frequent overbought and oversold signals that do not necessarily indicate a trend reversal. This can result in traders entering or exiting positions prematurely, incurring losses or missing out on potential gains.
Sensitivity to Market Noise: The Stochastic Oscillator is highly sensitive to market noise, which can create erratic signals in volatile markets. This sensitivity can make it difficult for traders to discern between genuine trend reversals and temporary fluctuations.
Lack of Predictive Power: Although the Stochastic Oscillator can help identify potential overbought and oversold conditions, it does not provide any information about the future direction or strength of a trend. As a result, it is often used in conjunction with other technical analysis tools to improve its predictive power.
Challenges of Smoothing the Stochastic Oscillator
To address the limitations of the Stochastic Oscillator, many traders attempt to smooth the indicator by applying various techniques. However, these approaches are not without their own set of challenges:
Trade-off between Smoothing and Responsiveness: The process of smoothing the Stochastic Oscillator inherently involves reducing its sensitivity to price movements. While this can help eliminate false signals, it can also result in a less responsive indicator, which may not react quickly enough to genuine trend reversals. This trade-off can make it challenging to find the optimal balance between smoothing and responsiveness.
Increased Complexity: Smoothing techniques often involve the use of additional mathematical functions and algorithms, which can increase the complexity of the indicator. This can make it more difficult for traders to understand and interpret the signals generated by the smoothed Stochastic Oscillator.
Lagging Signals: Some smoothing methods, such as moving averages, can introduce a time lag into the Stochastic Oscillator's signals. This can result in late entry or exit points, potentially reducing the profitability of a trading strategy based on the smoothed indicator.
Overfitting: In an attempt to eliminate false signals, traders may over-optimize their smoothing parameters, resulting in a Stochastic Oscillator that is overfitted to historical data. This can lead to poor performance in real-time trading, as the overfitted indicator may not accurately reflect the dynamics of the current market.
In our custom implementation of the Stochastic Oscillator, we used a combination of Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters to address the indicator's limitations while preserving its responsiveness. In this section, we will discuss the reasons behind selecting these specific filters and the advantages of using the Chebyshev filter for our purpose.
Filter Selection
Chebyshev Type I Moving Average: The Chebyshev filter was chosen for its ability to provide a smoother signal without sacrificing much responsiveness. This filter is designed to minimize the maximum error between the original and the filtered signal within a specific frequency range, effectively reducing noise while preserving the overall shape of the signal. The Chebyshev Type I Moving Average achieves this by allowing a specified amount of ripple in the passband, resulting in a more aggressive filter roll-off and better noise reduction compared to other filters, such as the Butterworth filter.
Zero-lag Gaussian-weighted Moving Average: To further improve the Stochastic Oscillator's performance without introducing noticeable lag, we used the zero-lag Gaussian-weighted moving average (GWMA) filter. This filter combines the benefits of a Gaussian-weighted moving average, which prioritizes recent data points by assigning them higher weights, with a zero-lag approach that minimizes the time delay in the filtered signal. The result is a smoother signal that is less prone to false signals and is more responsive than traditional moving average filters.
Advantages of the Chebyshev Filter
Effective Noise Reduction: The primary advantage of the Chebyshev filter is its ability to effectively reduce noise in the Stochastic Oscillator signal. By minimizing the maximum error within a specified frequency range, the Chebyshev filter suppresses short-term fluctuations that can lead to false signals while preserving the overall trend.
Customizable Ripple Factor: The Chebyshev Type I Moving Average allows for a customizable ripple factor, enabling traders to fine-tune the filter's aggressiveness in reducing noise. This flexibility allows for better adaptability to different market conditions and trading styles.
Responsiveness: Despite its effective noise reduction, the Chebyshev filter remains relatively responsive compared to other smoothing filters. This responsiveness allows for more accurate detection of genuine trend reversals, making it a suitable choice for our custom Stochastic Oscillator implementation.
Compatibility with Zero-lag Techniques: The Chebyshev filter can be effectively combined with zero-lag techniques, such as the Gaussian-weighted moving average filter used in our custom implementation. This combination results in a Stochastic Oscillator that is both smooth and responsive, with minimal lag.
Code Overview
The code begins with defining custom mathematical functions for hyperbolic sine, cosine, and their inverse functions. These functions will be used later in the code for smoothing purposes.
Next, the gaussian_weight function is defined, which calculates the Gaussian weight for a given 'k' and 'smooth_per'. The zero_lag_gwma function calculates the zero-lag moving average with Gaussian weights. This function is used to create a Gaussian-weighted moving average with minimal lag.
The chebyshevI function is an implementation of the Chebyshev Type I Moving Average, which is used for smoothing the Stochastic Oscillator. This function takes the source value (src), length of the moving average (len), and the ripple factor (ripple) as input parameters.
The main part of the code starts by defining input parameters for K and D smoothing and ripple values. The Stochastic Oscillator is calculated using the ta.stoch function with Chebyshev smoothed inputs for close, high, and low. The result is further smoothed using the zero-lag Gaussian-weighted moving average function (zero_lag_gwma).
Finally, the lag variable is calculated using the Chebyshev Type I Moving Average for the Stochastic Oscillator. The Stochastic Oscillator and the lag variable are plotted on the chart, along with upper and lower bands at 80 and 20 levels, respectively. A fill is added between the upper and lower bands for better visualization.
Conclusion
The custom Stochastic Oscillator presented in this blog post combines the Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters to provide a smooth and responsive signal without introducing noticeable lag. This innovative implementation results in a fast Stochastic Oscillator that is less prone to false signals, making it a valuable tool for technical analysts and traders alike.
However, it is crucial to recognize that the Stochastic Oscillator, despite being a price scaler, has its limitations, primarily due to its propensity for generating false signals. While smoothing techniques, like the ones used in our custom implementation, can help mitigate these issues, they often introduce new challenges, such as reduced responsiveness, increased complexity, lagging signals, and the risk of overfitting.
The selection of the Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters was driven by their combined ability to provide a smooth and responsive signal while minimizing false signals. The advantages of the Chebyshev filter, such as effective noise reduction, customizable ripple factor, and responsiveness, make it an excellent fit for addressing the limitations of the Stochastic Oscillator.
When using the Stochastic Oscillator, traders should be aware of these limitations and challenges, and consider incorporating other technical analysis tools and techniques to supplement the indicator's signals. This can help improve the overall accuracy and effectiveness of their trading strategies, reducing the risk of losses due to false signals and other limitations associated with the Stochastic Oscillator.
Feel free to use, modify, or improve upon this custom Stochastic Oscillator code in your trading strategies. We hope this detailed walkthrough of the custom Stochastic Oscillator, its limitations, challenges, and filter selection has provided you with valuable insights and a better understanding of how it works. Happy trading!
Spider VisionSpider Vision is an indicator that I created for trading view, which consists of a spider chart with 7 indicators built into it. This chart provides a visual representation of how these indicators are behaving, allowing traders to quickly assess the current market conditions.
The chart displays the following indicators:
RSI (Relative Strength Index): This is a momentum indicator that measures the strength of a security's price action. When the RSI is above 70, it is considered overbought, and when it is below 30, it is considered oversold.
Stochastic: This is another momentum indicator that compares the closing price of a security to its price range over a given time period. When the stochastic is above 80, it is considered overbought, and when it is below 20, it is considered oversold.
Momentum: This is a simple indicator that measures the change in a security's price over a given time period. When the momentum is positive, it indicates that the price is increasing, and when it is negative, it indicates that the price is decreasing.
BBW (Bollinger Bands Width): This indicator measures the width of the Bollinger Bands, which are a popular technical analysis tool used to identify potential trends and reversals. When the BBW is high, it suggests that the market is volatile, and when it is low, it suggests that the market is quiet.
DTO (Detrended Price Oscillator): This indicator measures the difference between the price of a security and its moving average. When the DTO is positive, it indicates that the price is above its moving average, and when it is negative, it indicates that the price is below its moving average.
Chop Zone: This indicator measures the choppiness of the market by comparing the average true range (ATR) to the difference between the high and low prices over a given time period. When the chop zone is high, it suggests that the market is choppy, and when it is low, it suggests that the market is trending.
Chaikin Oscillator: This is an oscillator that measures the accumulation/distribution of a security. When the Chaikin Oscillator is positive, it indicates that there is buying pressure in the market, and when it is negative, it indicates that there is selling pressure.
To use this indicator, traders can simply add it to their TradingView chart and adjust the input parameters to suit their trading style. The scale parameter can be used to adjust the size of the spider chart, while the color parameters can be used to customize the appearance of the chart. Traders can also adjust the length of each indicator to suit their preference.
Overall, the Spider Vision indicator provides a convenient way for traders to quickly assess the current market conditions and make more informed trading decisions.
SPY 4 Hour Swing TraderThe purpose of this script is to spot 4 hour pivots that indicate ~30 trading day swings. As VIX starts to drop options trading will get more boring and as we get back on the bull and can benefit from swing trading strategy. Swing trading doesn't make a whole lot of sense when VIX is above 28. Seems to get best results on 4 hour chart for this one. This indicator spots a go long opportunity when the 5 ema crosses the 13 ema on the 4 hour along with the RSI > 50 and the ADX > 20 and Stoichastic values (smoothed line < 80 or line < 90) and close > last candle close and the True Range < 6. It also spots uses a couple different means to determine when to exit the trade. Sell condition is primarily when the 13 ema crosses the 5 ema and the MACD line crosses below the signal line and the smoothed Stoichastic appears oversold (greater than 60) and slop of RSI < -.2. Stop Losses and Take Profits are configurable in Inputs along with ability to include short trades plus other MACD and Stoichastic settings. If a stop loss is encountered the trade will close. Also once twice the expected move is encountered partial profits will taken and stop losses and take profits will be re-established based on most recent close. Also a VIX above 28 will trigger any open positions to close. If trying to use this for something other than SPXL it is best to update stop losses and take profit percentages and check backtest results to ensure proper levels have been selected and the script gives satisfactory results.
Stochastic RSI of Smoothed Price [Loxx]What is Stochastic RSI of Smoothed Price?
This indicator is just as it's title suggests. There are six different signal types, various price smoothing types, and seven types of RSI.
This indicator contains 7 different types of RSI:
RSX
Regular
Slow
Rapid
Harris
Cuttler
Ehlers Smoothed
What is RSI?
RSI stands for Relative Strength Index . It is a technical indicator used to measure the strength or weakness of a financial instrument's price action.
The RSI is calculated based on the price movement of an asset over a specified period of time, typically 14 days, and is expressed on a scale of 0 to 100. The RSI is considered overbought when it is above 70 and oversold when it is below 30.
Traders and investors use the RSI to identify potential buy and sell signals. When the RSI indicates that an asset is oversold, it may be considered a buying opportunity, while an overbought RSI may signal that it is time to sell or take profits.
It's important to note that the RSI should not be used in isolation and should be used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is RSX?
Jurik RSX is a technical analysis indicator that is a variation of the Relative Strength Index Smoothed ( RSX ) indicator. It was developed by Mark Jurik and is designed to help traders identify trends and momentum in the market.
The Jurik RSX uses a combination of the RSX indicator and an adaptive moving average (AMA) to smooth out the price data and reduce the number of false signals. The adaptive moving average is designed to adjust the smoothing period based on the current market conditions, which makes the indicator more responsive to changes in price.
The Jurik RSX can be used to identify potential trend reversals and momentum shifts in the market. It oscillates between 0 and 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend . Traders can use these levels to make trading decisions, such as buying when the indicator crosses above 50 and selling when it crosses below 50.
The Jurik RSX is a more advanced version of the RSX indicator, and while it can be useful in identifying potential trade opportunities, it should not be used in isolation. It is best used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is Slow RSI?
Slow RSI is a variation of the traditional Relative Strength Index ( RSI ) indicator. It is a more smoothed version of the RSI and is designed to filter out some of the noise and short-term price fluctuations that can occur with the standard RSI .
The Slow RSI uses a longer period of time than the traditional RSI , typically 21 periods instead of 14. This longer period helps to smooth out the price data and makes the indicator less reactive to short-term price fluctuations.
Like the traditional RSI , the Slow RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Slow RSI is a more conservative version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also be slower to respond to changes in price, which may result in missed trading opportunities. Traders may choose to use a combination of both the Slow RSI and the traditional RSI to make informed trading decisions.
What is Rapid RSI?
Same as regular RSI but with a faster calculation method
What is Harris RSI?
Harris RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Larry Harris and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Harris RSI uses a different calculation formula compared to the traditional RSI . It takes into account both the opening and closing prices of a financial instrument, as well as the high and low prices. The Harris RSI is also normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Harris RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Harris RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Harris RSI and the traditional RSI to make informed trading decisions.
What is Cuttler RSI?
Cuttler RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Curt Cuttler and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Cuttler RSI uses a different calculation formula compared to the traditional RSI . It takes into account the difference between the closing price of a financial instrument and the average of the high and low prices over a specified period of time. This difference is then normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Cuttler RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Cuttler RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Cuttler RSI and the traditional RSI to make informed trading decisions.
What is Ehlers Smoothed RSI?
Ehlers smoothed RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by John Ehlers and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Ehlers smoothed RSI uses a different calculation formula compared to the traditional RSI . It uses a smoothing algorithm that is designed to reduce the noise and random fluctuations that can occur with the standard RSI . The smoothing algorithm is based on a concept called "digital signal processing" and is intended to improve the accuracy of the indicator.
Like the traditional RSI , the Ehlers smoothed RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Ehlers smoothed RSI can be useful in identifying longer-term trends and momentum shifts in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Ehlers smoothed RSI and the traditional RSI to make informed trading decisions.
What is Stochastic RSI?
Stochastic RSI (StochRSI) is a technical analysis indicator that combines the concepts of the Stochastic Oscillator and the Relative Strength Index (RSI). It is used to identify potential overbought and oversold conditions in financial markets, as well as to generate buy and sell signals based on the momentum of price movements.
To understand Stochastic RSI, let's first define the two individual indicators it is based on:
Stochastic Oscillator: A momentum indicator that compares a particular closing price of a security to a range of its prices over a certain period. It is used to identify potential trend reversals and generate buy and sell signals.
Relative Strength Index (RSI): A momentum oscillator that measures the speed and change of price movements. It ranges between 0 and 100 and is used to identify overbought or oversold conditions in the market.
Now, let's dive into the Stochastic RSI:
The Stochastic RSI applies the Stochastic Oscillator formula to the RSI values, essentially creating an indicator of an indicator. It helps to identify when the RSI is in overbought or oversold territory with more sensitivity, providing more frequent signals than the standalone RSI.
The formula for StochRSI is as follows:
StochRSI = (RSI - Lowest Low RSI) / (Highest High RSI - Lowest Low RSI)
Where:
RSI is the current RSI value.
Lowest Low RSI is the lowest RSI value over a specified period (e.g., 14 days).
Highest High RSI is the highest RSI value over the same specified period.
StochRSI ranges from 0 to 1, but it is usually multiplied by 100 for easier interpretation, making the range 0 to 100. Like the RSI, values close to 0 indicate oversold conditions, while values close to 100 indicate overbought conditions. However, since the StochRSI is more sensitive, traders typically use 20 as the oversold threshold and 80 as the overbought threshold.
Traders use the StochRSI to generate buy and sell signals by looking for crossovers with a signal line (a moving average of the StochRSI), similar to the way the Stochastic Oscillator is used. When the StochRSI crosses above the signal line, it is considered a bullish signal, and when it crosses below the signal line, it is considered a bearish signal.
It is essential to use the Stochastic RSI in conjunction with other technical analysis tools and indicators, as well as to consider the overall market context, to improve the accuracy and reliability of trading signals.
Signal types included are the following;
Fixed Levels
Floating Levels
Quantile Levels
Fixed Middle
Floating Middle
Quantile Middle
Extras
Alerts
Bar coloring
Loxx's Expanded Source Types
Smoothing R-Squared ComparisonIntroduction
Heyo guys, here I made a comparison between my favorised smoothing algorithms.
I chose the R-Squared value as rating factor to accomplish the comparison.
The indicator is non-repainting.
Description
In technical analysis, traders often use moving averages to smooth out the noise in price data and identify trends. While moving averages are a useful tool, they can also obscure important information about the underlying relationship between the price and the smoothed price.
One way to evaluate this relationship is by calculating the R-squared value, which represents the proportion of the variance in the price that can be explained by the smoothed price in a linear regression model.
This PineScript code implements a smoothing R-squared comparison indicator.
It provides a comparison of different smoothing techniques such as Kalman filter, T3, JMA, EMA, SMA, Super Smoother and some special combinations of them.
The Kalman filter is a mathematical algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement.
The input parameters for the Kalman filter include the process noise covariance and the measurement noise covariance, which help to adjust the sensitivity of the filter to changes in the input data.
The T3 smoothing technique is a popular method used in technical analysis to remove noise from a signal.
The input parameters for the T3 smoothing method include the length of the window used for smoothing, the type of smoothing used (Normal or New), and the smoothing factor used to adjust the sensitivity to changes in the input data.
The JMA smoothing technique is another popular method used in technical analysis to remove noise from a signal.
The input parameters for the JMA smoothing method include the length of the window used for smoothing, the phase used to shift the input data before applying the smoothing algorithm, and the power used to adjust the sensitivity of the JMA to changes in the input data.
The EMA and SMA techniques are also popular methods used in technical analysis to remove noise from a signal.
The input parameters for the EMA and SMA techniques include the length of the window used for smoothing.
The indicator displays a comparison of the R-squared values for each smoothing technique, which provides an indication of how well the technique is fitting the data.
Higher R-squared values indicate a better fit. By adjusting the input parameters for each smoothing technique, the user can compare the effectiveness of different techniques in removing noise from the input data.
Usage
You can use it to find the best fitting smoothing method for the timeframe you usually use.
Just apply it on your preferred timeframe and look for the highlighted table cell.
Conclusion
It seems like the T3 works best on timeframes under 4H.
There's where I am active, so I will use this one more in the future.
Thank you for checking this out. Enjoy your day and leave me a like or comment. 🧙♂️
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Credits to:
▪@loxx – T3
▪@balipour – Super Smoother
▪ChatGPT – Wrote 80 % of this article and helped with the research
WillyCycle Oscillator&DoubleMa/ErkOzi/version 2This oscillator can be customized by adjusting the length of the Willy period, the length of Willy's EMA, and the upper and lower bands. The upper and lower bands help traders identify overbought and oversold conditions.
The WillyCycle Oscillator is a technical analysis tool used to measure the momentum of an asset and identify overbought and oversold conditions based on the price range of a specific period and calculating the percentage of the closing price in that range. The WillyCycle Oscillator consists of two main components: Willy and Willy's EMA. The Willy component is the percentage calculation of the asset's price range, and Willy's EMA is the exponential moving average of the Willy component. Willy's EMA is used to smooth out the Willy component and make it easier to identify trends.
*** When the oscillator is above the 80 level, it indicates that the asset is overbought, and when it is below the 20 level, it indicates that the asset is oversold. Traders can use these levels as a guide for buying and selling signals.
***Traders can also use the WillyCycle Oscillator to identify trend reversals. When the oscillator rises above the 50 level, it signals a potential uptrend, and when it falls below the 50 level, it signals a potential downtrend.
***I have added a smoothed line option to the WillyCycle Oscillator, which allows traders to see a more smoothed version of the oscillator. This option can be enabled by setting the 'smoothed' input to true. The default value for the smoothed line is 15.
***We have also changed the value range of the WillyCycle Oscillator from -100 to 100 to 0 to 100. This change was made to make the oscillator more user-friendly and easier to read.
In conclusion, the WillyCycle Oscillator is a versatile tool that can help traders identify potential trading opportunities and trend reversals. Traders can customize the oscillator to fit their trading style and preferences. Adding a smoothed line and changing the value range can enhance the user experience and make the oscillator easier to use.
RSI with Keltner Channel (+EMA Ribbon)Note that the EMA Ribbon is not embedded into the custom RSI with KC. In the future I plan to embed it. The EMA Ribbon I use is the following:
This is my very first attempt at modifying an indicator. I basically attempted to add a Keltner Channel around RSI.
This was used as an alternative channel to the standard Bollinger Band. KC goes hand-in-hand with the EMA Ribbon. KC also helps to better pinpoint relative-overbought/oversold conditions.
In my belief, the 20-80 levels don't behave as overbought/oversold levels. An exponential chart would always be overbought. So a Keltner Channel could in theory (and in practice) give us greater understanding on chart analysis.
This custom indicator is a bodge . It has lots of extra calculations that can be removed. I post this rough indicator for the community to give feedback on how I can improve it, or perhaps give an idea to some of you. Please don't judge me, I wouldn't post it but lately some have asked me about it.
In the future I would like to embed an EMA ribbon in this RSI indicator, just like I did in the following idea.
During this period, I don't really have the time to fix this indicator to my standards. So I will leave it as is for the foreseeable future.
If you have the will and knowledge however, feel free to built upon this indicator and share it!
Tread lightly, for this is hallowed ground.
-Father Grigori
PS. In this indicator, I would replace all the moving averages with an EMA Ribbon "average".
Mean Reversion and TrendfollowingTitle: Mean Reversion and Trendfollowing
Introduction:
This script presents a hybrid trading strategy that combines mean reversion and trend following techniques. The strategy aims to capitalize on short-term price corrections during a downtrend (mean reversion) as well as ride the momentum of a trending market (trend following). It uses a 200-period Simple Moving Average (SMA) and a 2-period Relative Strength Index (RSI) to generate buy and sell signals.
Key Features:
Combines mean reversion and trend following techniques
Utilizes 200-period SMA and 2-period RSI
Customizable starting date
Allows for enabling/disabling mean reversion or trend following modes
Adjustable position sizing for trend following and mean reversion
Script Description:
The script implements a trading strategy that combines mean reversion and trend following techniques. Users can enable or disable either of these techniques through the input options. The strategy uses a 200-period Simple Moving Average (SMA) and a 2-period Relative Strength Index (RSI) to generate buy and sell signals.
The mean reversion mode is active when the price is below the SMA200, while the trend following mode is active when the price is above the SMA200. The script generates buy signals when the RSI is below 20 (oversold) in mean reversion mode or when the price is above the SMA200 in trend following mode. The script generates sell signals when the RSI is above 80 (overbought) in mean reversion mode or when the price falls below 95% of the SMA200 in trend following mode.
Users can adjust the position sizing for both trend following and mean reversion modes using the input options.
To use this script on TradingView, follow these steps:
Open TradingView and load your preferred chart.
Click on the 'Pine Editor' tab located at the bottom of the screen.
Paste the provided script into the Pine Editor.
Click 'Add to Chart' to apply the strategy to your chart.
Please note that the past performance of any trading system or methodology is not necessarily indicative of future results. Always use proper risk management and consult a financial advisor before making any investment decisions.
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The following is a summary of the underlying whitepaper (onlinelibrary.wiley.com) for this strategy:
This paper proposes a theory of securities market under- and overreactions based on two psychological biases: investor overconfidence about the precision of private information and biased self-attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. The authors show that overconfidence implies negative long-lag autocorrelations, excess volatility, and public-event-based return predictability. Biased self-attribution adds positive short-lag autocorrelations (momentum), short-run earnings "drift," and negative correlation between future returns and long-term past stock market and accounting performance.
The paper explains that there is empirical evidence challenging the traditional view that securities are rationally priced to reflect all publicly available information. Some of these anomalies include event-based return predictability, short-term momentum, long-term reversal, high volatility of asset prices relative to fundamentals, and short-run post-earnings announcement stock price "drift."
The authors argue that investor overconfidence can lead to stock prices overreacting to private information signals and underreacting to public signals. This overreaction-correction pattern is consistent with long-run negative autocorrelation in stock returns, excess volatility, and further implications for volatility conditional on the type of signal. The market's tendency to over- or underreact to different types of information allows the authors to address the pattern that average announcement date returns in virtually all event studies are of the same sign as the average post-event abnormal returns.
Biased self-attribution implies short-run momentum and long-term reversals in security prices. The dynamic analysis based on biased self-attribution can also lead to a lag-dependent response to corporate events. Cash flow or earnings surprises at first tend to reinforce confidence, causing a same-direction average stock price trend. Later reversal of overreaction can lead to an opposing stock price trend.
The paper concludes by summarizing the findings, relating the analysis to the literature on exogenous noise trading, and discussing issues related to the survival of overconfident traders in financial markets.
Orion:SagittaSagitta
Sagitta is an indicator the works to assist in the validation of potential long entries and to place stop-loss orders. Sagitta is not a "golden indicator" but more of a confirmation indicator of what prices might be suggesting.
The concept is that while stocks can turn in one bar, it usually takes two bars or more to signal a turn. So, using a measurement of two bars help determine the potential turning of prices.
Behind the scenes, Sagitta is nothing more than a 2 period stochastic which has had its values divided into five specific zones.
Dividing the range of the two bars in five sections, the High is equal to 100 and the Low is equal to 0.
The zones are:
20 = bearish (red) – This is when the close is the lower 20% of the two bars
40 = bearish (orange) – This is when the close is between the lower 20% and 40% of the two bars.
60 = neutral (yellow) – This is when the close is between the middle 40% - 60% of the two bars.
80 = bullish (blue) – This is when the close is between the upper 60% - 80% of the two bars.
100 = bullish (green) – This is when the close is above the upper 80% of the bar.
The general confirmation concept works as such:
When the following bar is of a higher value than the previous bar, there is potential for further upward price movement. Conversely when the following bar is lower than the previous bar, there is potential for further downward movement.
Going from a red bar to orange bar Might be an indication of a positive turn in direction of prices.
Going from a green bar to an orange bar would also be considered a negative directional turn of prices.
When the follow on bar decreases (ie, green to blue, blue to yellow, etc) placing a stop-loss would be prudent.
Maroon lines in the middle of a bar is an indication that prices are currently caught in consolidation.
Silver/Gray bars indicate that a high potential exists for a strong upward turn in prices exists.
Consolidation is calculated by determining if the close of one bar is between the high and low of another bar. This then establishes the range high and low. As long as closes continue with this range, the high and low of the range can expand. When the close is outside of the range, the consolidation is reset.
Signals in areas of consolidation (maroon center bar) should be looked upon as if the prices are going to challenge the high of the consolidation range and not necessarily break through.
The entry technique used is:
The greater of the following two calculations:
High of signal bar * 1.002 or High of signal bar + .03
The stop-loss technique used is:
The lesser of the following two calculations:
Low of signal bar * .998 or Low of signal bar - .03
IF an entry signal is generated and the price doesn’t reach the entry calculation. It is considered a failed entry and is not considered a negative or that you missed out on something. This has saved you from losing money since the prices are not ready to commit to the direction.
When placing a stop-loss, it is never suggested that you lower the value of a stop-loss. Always move your stop-losses higher in order to lock in profit in case of a negative turn.
DSS Bressert Stochastic MTFDouble Smoothed Stochastics – DSS Bressert is an oscillator introduced by William Blau and Walter Bressert shortly after each other in two slightly different versions. The calculation of DSS Bressert values is similar to the stochastic indicator. The difference is the use of double exponential smoothing. The advantages over the classic stochastic oscillators are the fast response to price changes in a still very smooth pattern. In addition, the extreme zones at the other end of the scale are reached quite frequently, even in strong trends, resulting in many trend conforming signals. Double Smoothed Stochastics – DSS The Bressert values are the same as the stochastics – values above 80 indicate an overbought condition of the market, values below 20 indicate an oversold condition of the market.
This is a full implementation of the original Stochastic Calulation with Multi-Time-Frame options. Other available scrips are lagging here and messing MTF up...
This Scrip will plot 2 lines for the double smoothed Stochastic based on the original exponential calculation from Blau/Bressert. Whilst the original stochastic is only simple moving average.
If you are a daytrader or scalper, the script is able to show a slow line and a fast line pair. Preferred Settings are embedded as screenshot.
Soheil PKO's 5 min Hitman Scalp - 3MA + Laguerre RSI + ADX [Pt]Someone sent me this strategy found on YouTube. It is Soheil PKO's "The Best and Most Profitable Scalping Strategy" Best way to find out is to code it =)
This strategy uses Moving Average Ribbon, Laguerre RSI, and ADX. This script only displays the MA ribbon, you will need to add Laguerre RSI and ADX separately.
Long Entry Criteria:
- 16 EMA > 48 EMA > 200 SMA
- Laguerre RSI > 80
- ADX > 20
Long Exit Criterion:
- 16 EMA < 48 EMA
Short Entry Criteria:
- 16 EMA < 48 EMA < 200 SMA
- Laguerre RSI < 20
- ADX > 20
Short Exit Criterion:
- 16 EMA > 48 EMA
As mentioned in the video, risk management is very important, especially for scalping strategies. Therefore, I've added option for setting Stop Loss and Price Target in the options for you guys to play with.
All parameters are configurable.
Enjoy~~
Trend Indicator with RSI and Fibbonacci Band 0.702 crossingsToday we have a new Indicator set, which I created using inspiration from the Trend Magic Indicator from KivancOzbilgic and adding several new aspects to it and a slightly modified calculation of the trend indicator itself.
You can change the inputs by changing the pre set values in the settings, but I found the current settings quite accurate. Feel free to experiment to fine tune the indicators.
Here are the details of the script:
Trend indicated within candles and as a line
- bullish and bearish trends are now also indicated within the candle based on the CCI calculation.
- Bullish is indicated by a green circle below the candle or as one may call it a "dot"
- bearish trend is indicated by a red circle above the candle
Entry Signal based on RSI crossing its EMA
- my motivation was to have a clearer entry signal besides highlighting a trend, which can not really be used to identify a good entry but to give confidence or when loosing trend to give an exit signal.
- after studiying the RSI and how it works together with its EMA it looks quite interesting as an entry or exit signal. But be cautios if the EMA and RSI values are moving in a narrow area we get a lot of crosses and therefore signals which should rather be ignored rather to be act on. So the the range where the cross happens is also quite important. But this aspect is not yet reflected as a rule/ logic.
But I am thinking of adding something.. or alternativly best to switch to another timeframe to get some better data
RSI overbought and oversold as Diamonds
- I also added key indications of oversold or overbought as Blue and Pink diamonds, can be considered as additional information to maybe identify a short term top or bottom.. but its not very accurate.
Entry signal based on crossing Fibbonachi Band 0.702
- So far the 0.702 seems to be quite an interesting retracement level which seems to be met a lot of times
- based on the assumption the price will evantually hit the 0.702 either direction I wanted to get a signal when this happens
- BUT! a big but, unfortunalty the Fibbonachi bands tend to bloat up in case of high volatility so it is not easy to find the crossing on higher timeframes
Here are the standard value which I found quite accurate for the assets I use this indicator set:
CCI Period = 5
ATR Multiplier = 1
ATR Period = 1
Source = High Low Close (hlc3 average value of the candle
Here the inputs used for the RSI Crossing signal (here you should play around a little to see which entry would have been best..)
RSI Length = 14
RSI Oversold = 25 (to be used for the "golden" entry signal based on the FBB crossing)
RSI Overbought = 80 (to be used for the "golden" entry signal based on the FBB crossing)
RSI Moving Average Length
In future versions I will add options to activate or deactive some of the plotting and espacially this golden dot when the fibbonachi band is being crossed needs some fine tuning..
And lets see if there is a way to fix the bloating of those bands..
Ehlers Stochastic Center Of Gravity [CC]The Stochastic Center Of Gravity Indicator was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pgs 79-80), and this is one of the many cycle scripts that I have created but not published yet because, to be honest, I don't use cycle indicators in my everyday trading. Many of you probably do, so I will start publishing my big backlog of cycle-based indicators. These indicators work best with a trend confirmation or some other confirmation indicator to pair with it. The current cycle is the length of the trend, and since most stocks generally change their underlying trend quite often, especially during the day, it makes sense to adjust the length of this indicator to match the stock you are using it on. As you can see, the indicator gives constant buy and sell signals during a trend which is why I recommend using a confirmation indicator.
I have color-coded it to use lighter colors for normal signals and darker colors for strong signals. Buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts you would like to see me publish!
Negative Correlation SignalsThank you to Hendrik Fuchs who coded this for me - I highly recommend you...
The AUDUSD/EURUSD has a negative correlation with the DXY as does the GBPJPY/USDJPY have with the JPYX. This indicator is very simple and uses opposite candle pinbars (pinbar/doji structure can be set by you) of the two instruments on the chart whilst the stochastic RSI should be above 80 for overbought on the one but below 20 on the other for oversold (or vice versa) to generate a signal.
This indicator works as follow:
1. Choose an instrument that has an opposing negatively correlated instrument (EURUSD & DXY, GBPJPY & JPYX, US100 & VIX, etc.)
2. Add indicator to the chart and open settings.
3. Open the settings and add the correct instruments (default is set to GBPJPY & JPYX).
4. Enter your desired Stochastic RSI & candle formation settings.
You will see buy and sell signals appear on the charts. Alerts are possible (Any alert() function call). Does not repaint after close of candle. Better on higher timeframes but can also be used for scalping. Best used as confluence or as part of a trend trading system.
There are obviously many many variations that I have not even thought off - please let us know in the comment section if you find settings/timeframes/instruments that work particularly well.
Sniper EntryThis source code is an implementation of a TradingView indicator called "Sniper Entry". The purpose of this indicator is to identify potential entry points for trades based on certain candlestick patterns and the Stochastic oscillator.
The indicator calculates the Stochastic oscillator based on the close, high, and low prices of the asset over a period of 14 bars. It then uses this oscillator to generate buy and sell signals.
For a buy signal to be generated, the Stochastic oscillator must cross above the oversold level of 20, and the current candle must either be a bullish pin bar or a bullish engulfing pattern. For a sell signal to be generated, the Stochastic oscillator must cross below the overbought level of 80, and the current candle must either be a bearish pin bar or a bearish engulfing pattern.
The indicator also calculates the stop loss and target levels for both buy and sell trades. The stop loss is calculated based on the low or high of the candle that generated the signal, depending on whether it's a buy or sell signal. The target is calculated based on the risk/reward ratio, which is set to 3 in this implementation. The lot size is also set to 0.01, and the starting capital is set to 100.
The indicator then plots the buy and sell signals, the stop loss and target levels, and the Stochastic oscillator on the chart.
It's important to note that this is just one example of a trading indicator, and its effectiveness may vary depending on market conditions and the asset being traded. It's also important to perform your own analysis and use proper risk management techniques when making trades based on any indicator or strategy.
BB Running Away CandleHello,
here is an indicator that can be helpful for your trading that is simple and easy to use.
Our culprit here is a candle that opens and closes below the lower band of Bollinger Band, Black and red lines are put on the high and low of that candle.
Green Arrows are happening when:
1- When candle closes above the black line and Stochastic RSI is in the oversold area >> "Confirmed B"
2- When candle closes above the black line >> "B"
Note that you can choose from the settings whether you want it confirmed or not.
Red Arrows are happening when:
1- Price reached the higher band of Bollinger Bands >> "BB High"
2- Stochastic crosses down from above 80 level >> "Stoch Crossdown"
3- RSI reached above 70 levle >> "RSI Oversold"
Note that you can choose to turn these on or off from the settings.
Settings of indicators are set to default.
NOTE: Alerts are put there however i didn't get the chance to test them, so would like to hear your feedback about them.
THE USE OF THIS INDICATOR IS YOUR OWN RESPONSIBILITY.
wishing you the best.
PitchforkTypesLibrary "PitchforkTypes"
User Defined Types to be used for Pitchfork and Drawing elements of Pitchfork. Depends on DrawingTypes for Point, Line, and LineProperties objects
PitchforkDrawingProperties
Pitchfork Drawing Properties object
Fields:
extend : If set to true, forks are extended towards right. Default is true
fill : Fill forklines with transparent color. Default is true
fillTransparency : Transparency at which fills are made. Only considered when fill is set. Default is 80
forceCommonColor : Force use of common color for forks and fills. Default is false
commonColor : common fill color. Used only if ratio specific fill colors are not available or if forceCommonColor is set to true.
PitchforkDrawing
Pitchfork drawing components
Fields:
medianLine : Median line of the pitchfork
baseLine : Base line of the pitchfork
forkLines : fork lines of the pitchfork
linefills : Linefills between forks
Fork
Fork object property
Fields:
ratio : Fork ratio
forkColor : color of fork. Default is blue
include : flag to include the fork in drawing. Default is true
PitchforkProperties
Pitchfork Properties
Fields:
forks : Array of Fork objects
type : Pitchfork type. Supported values are "regular", "schiff", "mschiff", Default is regular
inside : Flag to identify if to draw inside fork. If set to true, inside fork will be drawn
Pitchfork
Pitchfork object
Fields:
a : Pivot Point A of pitchfork
b : Pivot Point B of pitchfork
c : Pivot Point C of pitchfork
properties : PitchforkProperties object which determines type and composition of pitchfork
dProperties : Drawing properties for pitchfork
lProperties : Common line properties for Pitchfork lines
drawing : PitchforkDrawing object
DrawingMethodsLibrary "DrawingMethods"
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Point object to string representation
Parameters:
this : DrawingTypes/Point object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Point
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/LineProperties object to string representation
Parameters:
this : DrawingTypes/LineProperties object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/LineProperties
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Line object to string representation
Parameters:
this : DrawingTypes/Line object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Line
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/LabelProperties object to string representation
Parameters:
this : DrawingTypes/LabelProperties object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/LabelProperties
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Label object to string representation
Parameters:
this : DrawingTypes/Label object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Label
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Linefill object to string representation
Parameters:
this : DrawingTypes/Linefill object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Linefill
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/BoxProperties object to string representation
Parameters:
this : DrawingTypes/BoxProperties object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/BoxProperties
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/BoxText object to string representation
Parameters:
this : DrawingTypes/BoxText object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/BoxText
tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Box object to string representation
Parameters:
this : DrawingTypes/Box object
sortKeys : If set to true, string output is sorted by keys.
sortOrder : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Box
delete(this)
Deletes line from DrawingTypes/Line object
Parameters:
this : DrawingTypes/Line object
Returns: Line object deleted
delete(this)
Deletes label from DrawingTypes/Label object
Parameters:
this : DrawingTypes/Label object
Returns: Label object deleted
delete(this)
Deletes Linefill from DrawingTypes/Linefill object
Parameters:
this : DrawingTypes/Linefill object
Returns: Linefill object deleted
delete(this)
Deletes box from DrawingTypes/Box object
Parameters:
this : DrawingTypes/Box object
Returns: DrawingTypes/Box object deleted
delete(this)
Deletes lines from array of DrawingTypes/Line objects
Parameters:
this : Array of DrawingTypes/Line objects
Returns: Array of DrawingTypes/Line objects
delete(this)
Deletes labels from array of DrawingTypes/Label objects
Parameters:
this : Array of DrawingTypes/Label objects
Returns: Array of DrawingTypes/Label objects
delete(this)
Deletes linefill from array of DrawingTypes/Linefill objects
Parameters:
this : Array of DrawingTypes/Linefill objects
Returns: Array of DrawingTypes/Linefill objects
delete(this)
Deletes boxes from array of DrawingTypes/Box objects
Parameters:
this : Array of DrawingTypes/Box objects
Returns: Array of DrawingTypes/Box objects
clear(this)
clear items from array of DrawingTypes/Line while deleting underlying objects
Parameters:
this : array
Returns: void
clear(this)
clear items from array of DrawingTypes/Label while deleting underlying objects
Parameters:
this : array
Returns: void
clear(this)
clear items from array of DrawingTypes/Linefill while deleting underlying objects
Parameters:
this : array
Returns: void
clear(this)
clear items from array of DrawingTypes/Box while deleting underlying objects
Parameters:
this : array
Returns: void
draw(this)
Creates line from DrawingTypes/Line object
Parameters:
this : DrawingTypes/Line object
Returns: line created from DrawingTypes/Line object
draw(this)
Creates lines from array of DrawingTypes/Line objects
Parameters:
this : Array of DrawingTypes/Line objects
Returns: Array of DrawingTypes/Line objects
draw(this)
Creates label from DrawingTypes/Label object
Parameters:
this : DrawingTypes/Label object
Returns: label created from DrawingTypes/Label object
draw(this)
Creates labels from array of DrawingTypes/Label objects
Parameters:
this : Array of DrawingTypes/Label objects
Returns: Array of DrawingTypes/Label objects
draw(this)
Creates linefill object from DrawingTypes/Linefill
Parameters:
this : DrawingTypes/Linefill objects
Returns: linefill object created
draw(this)
Creates linefill objects from array of DrawingTypes/Linefill objects
Parameters:
this : Array of DrawingTypes/Linefill objects
Returns: Array of DrawingTypes/Linefill used for creating linefills
draw(this)
Creates box from DrawingTypes/Box object
Parameters:
this : DrawingTypes/Box object
Returns: box created from DrawingTypes/Box object
draw(this)
Creates labels from array of DrawingTypes/Label objects
Parameters:
this : Array of DrawingTypes/Label objects
Returns: Array of DrawingTypes/Label objects
createLabel(this, lblText, tooltip, properties)
Creates DrawingTypes/Label object from DrawingTypes/Point
Parameters:
this : DrawingTypes/Point object
lblText : Label text
tooltip : Tooltip text. Default is na
properties : DrawingTypes/LabelProperties object. Default is na - meaning default values are used.
Returns: DrawingTypes/Label object
createLine(this, other, properties)
Creates DrawingTypes/Line object from one DrawingTypes/Point to other
Parameters:
this : First DrawingTypes/Point object
other : Second DrawingTypes/Point object
properties : DrawingTypes/LineProperties object. Default set to na - meaning default values are used.
Returns: DrawingTypes/Line object
createLinefill(this, other, fillColor, transparency)
Creates DrawingTypes/Linefill object from DrawingTypes/Line object to other DrawingTypes/Line object
Parameters:
this : First DrawingTypes/Line object
other : Other DrawingTypes/Line object
fillColor : fill color of linefill. Default is color.blue
transparency : fill transparency for linefill. Default is 80
Returns: Array of DrawingTypes/Linefill object
createBox(this, other, properties, textProperties)
Creates DrawingTypes/Box object from one DrawingTypes/Point to other
Parameters:
this : First DrawingTypes/Point object
other : Second DrawingTypes/Point object
properties : DrawingTypes/BoxProperties object. Default set to na - meaning default values are used.
textProperties : DrawingTypes/BoxText object. Default is na - meaning no text will be drawn
Returns: DrawingTypes/Box object
createBox(this, properties, textProperties)
Creates DrawingTypes/Box object from DrawingTypes/Line as diagonal line
Parameters:
this : Diagonal DrawingTypes/PoLineint object
properties : DrawingTypes/BoxProperties object. Default set to na - meaning default values are used.
textProperties : DrawingTypes/BoxText object. Default is na - meaning no text will be drawn
Returns: DrawingTypes/Box object
Dynamo
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Overview
Dynamo is built to be the Swiss-knife for price-movement & strength detection, it aims to provide a holistic view of the current price across multiple dimensions. This is achieved by combining 3 very specific indicators(RSI, Stochastic & ADX) into a single view. Each of which serve a different purpose, and collectively provide a simple, yet powerful tool to gauge the true nature of price-action.
Background
Dynamo uses 3 technical analysis tools in conjunction to provide better insights into price movement, they are briefly explained below:
Relative Strength Index(RSI)
RSI is a popular indicator that is often used to measure the velocity of price change & the intensity of directional moves. RSI computes the relative strength of the current price by comparing the security’s bullish strength versus bearish strength for a given period, i.e. by comparing average gain to average loss.
It is a range bound(0-100) variable that generates a bullish reading if average gain is higher, and a bullish reading if average loss is higher. Values over 50 are generally considered bullish & values less than 50 indicate a bearish market. Values over 70 indicate an overbought condition, and values below 30 indicate oversold condition.
Stochastic
Stochastic is an indicator that aims to measure the momentum in the market, by comparing most recent closing price of the security to its price range for a given period. It is based on the assumption that price tends to close near the recent high in an up trend, and it closes near the recent low during a down trend.
It is also range bound(0-100), values over 80 indicate overbought condition and values below 20 indicate oversold condition.
Average Directional Index(ADX)
ADX is an indicator that can quantify trend strength, it is derived from two underlying indices, known as Directional Movement Index(DMI). +DMI represents strength of the up trend, and -DMI represents strength of the down trend, and ADX is the average of the two.
ADX is non-directional or trend-neutral, which means, it does not follow the direction of the price, instead ADX will rise only when there is a strong trend, it does not matter if it’s an up trend or a down trend. Typical ranges of ADX are 25-50 for a strong trend, anything below 25 is considered as no trend or weak trend. ADX can frequently shoot upto higher values, but it generally finds exhaustion levels around the 60-75 range.
About the script
All these indicators are very powerful tools, but just like any other indicator they have their limitations. Stochastic & ADX can generate false signals in volatile markets, meaning price wouldn’t always follow through with what’s being indicated. ADX may even fail to generate a signal in less volatile markets, simply because it is based on moving averages, it tends to react slower to price changes. RSI can also lose it’s effectiveness when markets are trending strong, as it can stay in the overbought or oversold ranges for an extended period of time.
Dynamo aims to provide the trader with a much broader perspective by bringing together these contrasting indicators into a single simplified view. When Stochastic becomes less reliable in highly volatile conditions, one can cross validate their deduction by looking at RSI patterns. When RSI gets stuck in overbought or oversold range, one can refer to ADX to get better picture about the current trend. Similarly, various combinations of rules & setups can be formulated to get a more deterministic view, when working with either of these indicators.
There many possible use cases for a tool like this, and it totally depends on how you want to use it. An obvious option is to use it to trigger signals only after it has been confirmed by two or more indicators, for example, RSI & Stochastic make a great combination for cross-over or cross-under strategies. Some of the other options include trend detection, strength detection, reversals or price rejection points, possible duration of a trend, and all of these can very easily be translated into effective entry and exit points for trades.
How to use it
Dynamo is an easy-to-use tool, just add it to your chart and you’re good to start with your market analysis. Output consists of three overlapping plots, each of which tackle price movement from a slightly different angle.
Stochastic: A momentum indicator that plots the current closing price in relation to the price-range over a given period of time.
Can be used to detect the direction of the price movement, potential reversals, or duration of an up/down move.
Plotted as grey coloured histograms in the background.
Relative Strength Index(RSI): RSI is also a momentum indicator that measures the velocity with which the price changes.
Can be used to detect the speed of the price movement, RSI divergences can be a nice way to detect directional changes.
Plotted as an aqua coloured line.
Average Directional Index(ADX): ADX is an indicator that is used to measure the strength of the current trend.
Can be used to measure how strong the price movement is, both up and down, or to establish long terms trends.
Plotted as an orange coloured line.
Features
Provides a well-rounded view of the market movement by amalgamating some of the best strength indicators, helping traders make better informed decisions with minimal effort.
Simplistic plots that aim to convey clean signals, as a result, reducing clutter on the chart, and hopefully in the trader's head too.
Combines different types of indicators into a single view, which leads to an optimised use of the precious screen real-estate.
Final Note
Dynamo is designed to be minimalistic in functionality and in appearance, as it is being built to be a general purpose tool that is not only beginner friendly, but can also be highly-configurable to meet the needs of pro traders.
Thresholds & default values for the indicators are only suggestions based on industry standards, they may not be an exact match for all markets & conditions. Hence, it is advisable for the user to test & adjust these values according their securities and trading styles.
The chart highlights one of many possible setups using this tool, and it can used to create various types of setups & strategies, but it is also worth noting that the usability & the effectiveness of this tool also depends on the user’s understanding & interpretation of the underlying indicators.
Lastly, this tool is only an indicator and should only be perceived that way. It does not guarantee anything, and the user should do their own research before committing to trades based on any indicator.
Dominant Cycle Detection OscillatorThis is a Dominant Cycle Detection Oscillator that searches multiple ranges of wavelengths within a spectrum. Choose one of 4 different dominant cycle detection methods (MESA MAMA cycle, Pearson Autocorrelation, Discreet Fourier Transform, and Phase Accumulation) to determine the most dominant cycles and see the historical results. Straight lines can indicate a steady dominant cycle; while Wavy lines might indicate a varying dominant cycle length. The steadier the cycle, the easier it may be to predict future events in that cycle (keep the log scale in mind when considering steadiness). The presence of evenly divisible (or harmonic) cycle lengths may also indicate stronger cycles; for example, 19, 38, and 76 dominant lengths for the 2x, 4x, and 8x cycles. Practically, a trader can use these cycle outputs as the default settings for other Hurst/cycle indicators. For example, if you see dominant cycle oscillator outputs of 38 & 76 for the 4x and 8x cycle respectively, you might want to test/use defaults of 38 & 76 for the 4x & 8x lengths in the bandpass, diamond/semi-circle notation, moving average & envelope, and FLD instead of the defaults 40 & 80 for a more fine-tuned analysis.
Muting the oscillator's historical lines and overlaying the indicator on the chart can visually cue a trader to the cycle lengths without taking up extra panes. The DFT Cycle lengths with muted historical lines have been overlayed on the chart in the photo.
The y-axis scale for this indicator's pane (just the oscillator pane, not the chart) most likely needs to be changed to logarithmic to look normal, but it depends on the search ranges in your settings. There are instructions in the settings. In the photo, the MESA MAMA scale is set to regular (not logarithmic) which demonstrates how difficult it can be to read if not changed.
In the Spectral Analysis chapter of Hurst's book Profit Magic, he recommended doing a Fourier analysis across a spectrum of frequencies. Hurst acknowledged there were many ways to do this analysis but recommended the method described by Lanczos. Currently in this indicator, the closest thing to the method described by Lanczos is the DFT Discreet Fourier Transform method.
Shoutout to @lastguru for the dominant cycle library referenced in this code. He mentioned that he may add more methods in the future.
