Kalman Filtered ROC & Stochastic with MA SmoothingThe "Smooth ROC & Stochastic with Kalman Filter" indicator is a trend following tool designed to identify trends in the price movement. It combines the Rate of Change (ROC) and Stochastic indicators into a single oscillator, the combination of ROC and Stochastic indicators aims to offer complementary information: ROC measures the speed of price change, while Stochastic identifies overbought and oversold conditions, allowing for a more robust assessment of market trends and potential reversals. The indicator plots green "B" labels to indicate buy signals and blue "S" labels to represent sell signals. Additionally, it displays a white line that reflects the overall trend for buy signals and a blue line for sell signals. The aim of the indicator is to incorporate Kalman and Moving Average (MA) smoothing techniques to reduce noise and enhance the clarity of the signals.
Rationale for using Kalman Filter:
The Kalman Filter is chosen as a smoothing tool in the indicator because it effectively reduces noise and fluctuations. The Kalman Filter is a mathematical algorithm used for estimating and predicting the state of a system based on noisy and incomplete measurements. It combines information from previous states and current measurements to generate an optimal estimate of the true state, while simultaneously minimizing the effects of noise and uncertainty. In the context of the indicator, the Kalman Filter is applied to smooth the input data, which is the source for the Rate of Change (ROC) calculation. By considering the previous smoothed state and the difference between the current measurement and the predicted value, the Kalman Filter dynamically adjusts its estimation to reduce the impact of outliers.
Calculation:
The indicator utilizes a combination of the ROC and the Stochastic indicator. The ROC is smoothed using a Kalman Filter (credit to © Loxx: ), which helps eliminate unwanted fluctuations and improve the signal quality. The Stochastic indicator is calculated with customizable parameters for %K length, %K smoothing, and %D smoothing. The smoothed ROC and Stochastic values are then averaged using the formula ((roc + d) / 2) to create the blended oscillator. MA smoothing is applied to the combined oscillator aiming to further reduce fluctuations and enhance trend visibility. Traders are free to choose their own preferred MA type from 'EMA', 'DEMA', 'TEMA', 'WMA', 'VWMA', 'SMA', 'SMMA', 'HMA', 'LSMA', and 'PEMA' (credit to: © traderharikrishna for this code: ).
Application:
The indicator's buy signals (represented by green "B" labels) indicate potential entry points for buying assets, suggesting a bullish trend. The white line visually represents the trend, helping traders identify and follow the upward momentum. Conversely, the sell signals (blue "S" labels) highlight possible exit points or opportunities for short selling, indicating a bearish trend. The blue line illustrates the bearish movement, aiding in the identification of downward momentum.
The "Smoothed ROC & Stochastic" indicator offers traders a comprehensive view of market trends by combining two powerful oscillators. By incorporating the ROC and Stochastic indicators into a single oscillator, it provides a more holistic perspective on the market's momentum. The use of a Kalman Filter for smoothing helps reduce noise and enhance the accuracy of the signals. Additionally, the indicator allows customization of the smoothing technique through various moving average types. Traders can also utilize the overbought and oversold zones for additional analysis, providing insights into potential market reversals or extreme price conditions. Please note that future performance of any trading strategy is fundamentally unknowable, and past results do not guarantee future performance.
Stochastic RSI (STOCH RSI)
RSI with J-Line ***For ease of use, I recommend changing the J Histogram to a line indicator, then it works like the KDJ Stochastic indicator. Full disclosure, I created this script with the help of GPT. This script was inspired by the KDJ Stochastic indicator by Dreadblitz***
The "RSI with J-Line" script is essentially a modified Relative Strength Index (RSI) indicator with an added histogram component. Here's how to use the different components of the script:
RSI Line (Blue): The RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between zero and 100, and is typically used to identify overbought and oversold conditions in a market. Traditionally, readings over 70 are considered overbought, and readings under 30 are considered oversold. However, these are not strict rules and can vary depending on the market and the overall trend.
RSI Smooth Line (Orange): This is the simple moving average of the RSI. It helps to smooth out the RSI and to identify the overall trend of the momentum. When the RSI line crosses above the RSI Smooth line, it might indicate that the momentum is moving upwards. When the RSI line crosses below the RSI Smooth line, it might indicate that the momentum is moving downwards.
RSI J-Line (Red Histogram): The J-Line is an additional line that's calculated as 3*rsiSmooth - 2*rsi. It's similar to the %J line in the Stochastic indicator and is designed to provide quicker signals than the RSI or RSI Smooth line. When the histogram is above the 0 line, it might indicate bullish momentum. When it's below the 0 line, it might indicate bearish momentum.
Please note that these interpretations are standard for these types of indicators, but actual market behavior can be complex and is influenced by many factors. Indicators should be used as part of a comprehensive trading strategy, not in isolation. Always take into account other market information and indicators before making trading decisions.
Stochastic [Tcs] | OSCThis script is an implementation of the stochastic relative strength index (STOCH RSI) indicator
The script takes inputs from the length of the RSI, the source of the data, and parameters for the smoothing of the STOCH RSI.
The STOCH RSI is calculated by first calculating the RSI of the chosen source data, then smoothing it with an exponential moving average. The stochastic oscillator is then applied to the smoothed RSI, and smoothed again to create the final STOCH RSI.
The script also calculates a trigger value using a combination of the STOCH RSI and a volume-weighted moving average. It then plots the STOCH RSI, trigger value, and overbought/oversold levels, and fills the background of the plot based on the relationship between the trigger and STOCH RSI values.
Finally, the script plots buy and sell signals based on crossovers and crossunders of the STOCH RSI and its smoothed version.
The cross signal is stronger than the dots, in both direction and usually the best entries happen when two crosses signal on the level 0(long) or 100(short) appear after a dot signal.
Please note that this indicator is for educational purposes only and should not be used for trading without further testing and analysis.
Market Cycle IndicatorThe Market Cycle Indicator is a tool that integrates the elements of RSI, Stochastic RSI, and Donchian Channels. It is designed to detect market cycles, enabling traders to enter and exit the market at the most opportune times.
This indicator provides a unique perspective on the market, combining multiple strategies into one unified and weighted approach. By factoring in the inputs from each of these popular technical analysis methods, it offers a more holistic view of the market trends and cycles.
Parameter Details:
Donchian Channels (DCO):
- donchianPeriod: Sets the period for the Donchian Channel calculation. Default is set to 14.
- donchianSmoothing: Sets the smoothing factor for the Donchian Channel calculation. Default is set to 3.
- donchianPrice: Selects the price type to be used in the Donchian Channel calculation. Default is set to the closing price.
Relative Strength Index (RSI):
- rsiPeriod: Sets the period for the RSI calculation. Default is set to 14.
- rsiSmoothing: Sets the smoothing factor for the RSI calculation. Default is set to 3.
- rsiPrice: Selects the price type to be used in the RSI calculation. Default is set to the closing price.
Stochastic RSI (StochRSI):
- srsiPeriod: Sets the period for the Stochastic RSI calculation. Default is set to 20.
- srsiSmoothing: Sets the smoothing factor for the Stochastic RSI calculation. Default is set to 3.
- srsiK: Sets the period for the %K line in the Stochastic RSI calculation. Default is set to 5.
- srsiD: Sets the period for the %D line in the Stochastic RSI calculation. Default is set to 5.
- srsiPrice: Selects the price type to be used in the Stochastic RSI calculation. Default is set to the closing price.
Weights:
- rsiWeight: Sets the weight for the RSI in the final aggregate calculation. Default is set to 1.
- srsiWeight: Sets the weight for the Stochastic RSI in the final aggregate calculation. Default is set to 1.
- dcoWeight: Sets the weight for the Donchian Channel in the final aggregate calculation. Default is set to 1.
Limits:
- limitHigh: Sets the upper limit for the indicator. Default is set to 80.
- limitLow: Sets the lower limit for the indicator. Default is set to 20.
By customizing these parameters, users can tweak the indicator to align with their own trading strategies and risk tolerance levels. Whether you're a novice or an experienced trader, the Comprehensive Market Cycle Indicator provides valuable insights into the market's behavior.
Uses library HelperTA
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
True Trend Oscillator [wbburgin]The True Trend oscillator identifies trending or ranging markets with a stochastic ATR and RSI. Here are some examples for how it can be used.
Uptrends
If the candlesticks are lime green, this signals an uptrend. On the oscillator, you can identify an uptrend if the bull strength (the green line) is above the bear strength (the red line). The strength of the uptrend and the downtrend can be found by looking at the slope of these lines.
Downtrends
If the candlesticks are red, this signals a downtrend. On the oscillator, notice how the bear strength line is above the bull strength line.
Ranging Markets and Pullbacks
The True Trend oscillator can also be used to identify ranging markets or pullbacks. Let's look at the previous example again:
If you notice that the bull and bear lines are bouncing above the red weak-trend zone (as in the example above), this signals an extended trend. On the contrary, when the bull and bear lines fall into the weak-trend zone, this may indicate a larger pullback or a range to look to enter a trade again, as in this example, where the ranging candles in gray demonstrate temporary pullbacks in a larger bullish trend:
Ranges can also occur before trend reversals, so a range may also indicate a smart time to secure profits.
You can customize the ranging threshold in the settings. It can be set from 0-100 because the indicator is a stochastic.
Hope you all find this indicator useful!
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!
Stochastic RSI Strategy (with SMA and VWAP Filters)The strategy is designed to trade on the Stochastic RSI indicator crossover signals.
Below are all of the trading conditions:
-When the Stochastic RSI crosses above 30, a long position is entered.
-When the Stochastic RSI crosses below 70, a short position is entered.
-The strategy also includes two additional conditions for entry:
-Long entries must have a positive spread value between the 9 period simple moving average and the 21 period simple moving average.
-Short entries must have a negative spread value between the 9 period simple moving average and the 21 period simple moving average.
-Long entries must also be below the volume-weighted average price.
-Short entries must also be above the volume-weighted average price.
-The strategy includes stop loss and take profit orders for risk management:
-A stop loss of 20 ticks is placed for both long and short trades.
-A take profit of 25 ticks is placed for both long and short trades.
S & R RSi stratIn this updated version, a trend filter is applied using the Simple Moving Average (SMA) on the 4-hour timeframe. The trend is considered up when the 50-period SMA is below the 200-period SMA (ta.sma(trendFilterSource, 50) < ta.sma(trendFilterSource, 200)).
The buy condition (buyCondition) is triggered when the RSI crosses above the oversold threshold (ta.crossover(rsi, oversoldThreshold)), the trend filter confirms an uptrend (isUptrend is true), and the close price is greater than or equal to the support level (close >= supportLevel).
The sell condition (sellCondition) is triggered when the RSI crosses below the overbought threshold (ta.crossunder(rsi, overboughtThreshold)), the trend filter confirms a downtrend (isUptrend is false), and the close price is less than or equal to the resistance level (close <= resistanceLevel).
With this implementation, the signals will only be generated in the direction of the trend on the 4-hour timeframe.
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
JS-TechTrading: VWAP Momentum_Pullback StrategyGeneral Description and Unique Features of this Script
Introducing the VWAP Momentum-Pullback Strategy (long-only) that offers several unique features:
1. Our script/strategy utilizes Mark Minervini's Trend-Template as a qualifier for identifying stocks and other financial securities in confirmed uptrends.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available on TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
2. Our strategy is based on the supply/demand balance in the market, making it timeless and effective across all timeframes. Whether you are day trading using 1- or 5-min charts or swing-trading using daily charts, this strategy can be applied and works very well.
3. We have also integrated technical indicators such as the RSI and the MA / VWAP crossover into this strategy to identify low-risk pullback entries in the context of confirmed uptrends. By doing so, the risk profile of this strategy and drawdowns are being reduced to an absolute minimum.
Minervini’s Trend-Template and the ‘Stage-Analysis’ of the Markets
This strategy is a so-called 'long-only' strategy. This means that we only take long positions, short positions are not considered.
The best market environment for such strategies are periods of stable upward trends in the so-called stage 2 - uptrend.
In stable upward trends, we increase our market exposure and risk.
In sideways markets and downward trends or bear markets, we reduce our exposure very quickly or go 100% to cash and wait for the markets to recover and improve. This allows us to avoid major losses and drawdowns.
This simple rule gives us a significant advantage over most undisciplined traders and amateurs!
'The Trend is your Friend'. This is a very old but true quote.
What's behind it???
• 98% of stocks made their biggest gains in a Phase 2 upward trend.
• If a stock is in a stable uptrend, this is evidence that larger institutions are buying the stock sustainably.
• By focusing on stocks that are in a stable uptrend, the chances of profit are significantly increased.
• In a stable uptrend, investors know exactly what to expect from further price developments. This makes it possible to locate low-risk entry points.
The goal is not to buy at the lowest price – the goal is to buy at the right price!
Each stock goes through the same maturity cycle – it starts at stage 1 and ends at stage 4
Stage 1 – Neglect Phase – Consolidation
Stage 2 – Progressive Phase – Accumulation
Stage 3 – Topping Phase – Distribution
Stage 4 – Downtrend – Capitulation
This strategy focuses on identifying stocks in confirmed stage 2 uptrends. This in itself gives us an advantage over long-term investors and less professional traders.
By focusing on stocks in a stage 2 uptrend, we avoid losses in downtrends (stage 4) or less profitable consolidation phases (stages 1 and 3). We are fully invested and put our money to work for us, and we are fully invested when stocks are in their stage 2 uptrends.
But how can we use technical chart analysis to find stocks that are in a stable stage 2 uptrend?
Mark Minervini has developed the so-called 'trend template' for this purpose. This is an essential part of our JS-TechTrading pullback strategy. For our watchlists, only those individual values that meet the tough requirements of Minervini's trend template are eligible.
The Trend Template
• 200d MA increasing over a period of at least 1 month, better 4-5 months or longer
• 150d MA above 200d MA
• 50d MA above 150d MA and 200d MA
• Course above 50d MA, 150d MA and 200d MA
• Ideally, the 50d MA is increasing over at least 1 month
• Price at least 25% above the 52w low
• Price within 25% of 52w high
• High relative strength according to IBD.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available in TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
This strategy can be applied to all timeframes from 5 min to daily.
The VWAP Momentum-Pullback Strateg y
For the JS-TechTrading VWAP Momentum-Pullback Strategy, only stocks and other financial instruments that meet the selected criteria of Mark Minervini's trend template are recommended for algorithmic trading with this startegy.
A further prerequisite for generating a buy signals is that the individual value is in a short-term oversold state (RSI).
When the selling pressure is over and the continuation of the uptrend can be confirmed by the MA / VWAP crossover after reaching a price low, a buy signal is issued by this strategy.
Stop-loss limits and profit targets can be set variably.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a technical indicator developed by Welles Wilder in 1978. The RSI is used to perform a market value analysis and identify the strength of a trend as well as overbought and oversold conditions. The indicator is calculated on a scale from 0 to 100 and shows how much an asset has risen or fallen relative to its own price in recent periods.
The RSI is calculated as the ratio of average profits to average losses over a certain period of time. A high value of the RSI indicates an overbought situation, while a low value indicates an oversold situation. Typically, a value > 70 is considered an overbought threshold and a value < 30 is considered an oversold threshold. A value above 70 signals that a single value may be overvalued and a decrease in price is likely , while a value below 30 signals that a single value may be undervalued and an increase in price is likely.
For example, let's say you're watching a stock XYZ. After a prolonged falling movement, the RSI value of this stock has fallen to 26. This means that the stock is oversold and that it is time for a potential recovery. Therefore, a trader might decide to buy this stock in the hope that it will rise again soon.
The MA / VWAP Crossover Trading Strategy
This strategy combines two popular technical indicators: the Moving Average (MA) and the Volume Weighted Average Price (VWAP). The MA VWAP crossover strategy is used to identify potential trend reversals and entry/exit points in the market.
The VWAP is calculated by taking the average price of an asset for a given period, weighted by the volume traded at each price level. The MA, on the other hand, is calculated by taking the average price of an asset over a specified number of periods. When the MA crosses above the VWAP, it suggests that buying pressure is increasing, and it may be a good time to enter a long position. When the MA crosses below the VWAP, it suggests that selling pressure is increasing, and it may be a good time to exit a long position or enter a short position.
Traders typically use the MA VWAP crossover strategy in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions. As with any trading strategy, it is important to carefully consider the risks and potential rewards before making any trades.
This strategy is applicable to all timeframes and the relevant parameters for the underlying indicators (RSI and MA/VWAP) can be adjusted and optimized as needed.
Backtesting
Backtesting gives outstanding results on all timeframes and drawdowns can be reduced to a minimum level. In this example, the hourly chart for MCFT has been used.
Settings for backtesting are:
- Period from April 2020 until April 2021 (1 yr)
- Starting capital 100k USD
- Position size = 25% of equity
- 0.01% commission = USD 2.50.- per Trade
- Slippage = 2 ticks
Other comments
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The RSI qualifier is highly selective and filters out the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• As a result, traders need to apply this strategy for a full watchlist rather than just one financial security.
"The Stocashi" - Stochastic RSI + Heikin-AshiWhat up guys and welcome to the coffee shop. I have a special little tool for you today to throw in your toolbox. This one is a freebie.
This is the Stochastic RS-Heiken-Ashi "The Stocashi"
This is the stochastic RSI built to look like Heikin-Ashi candles.
a lot of people have trouble using the stochastic indicator because of its ability to look very choppy at its edges instead of having nice curves or arcs to its form when you use it on scalping time frames it ends up being very pointed and you can't really tell when the bands turn over if you're using a stochastic Ribbon or you can't tell when it's actually moving in a particular direction if you're just using the K and the D line.
This new format of Presentation seeks to get you to have a better visual representation of what the stochastic is actually doing.
It's long been noted that Heikin-Ashi do a very good job of representing momentum in a price so using it on something that is erratic as the stochastic indicator seems like a plausible idea.
The strategy is simple because you use it exactly the same way you've always used the stochastic indicator except now you can look for the full color of the candle.
this one uses a gradient color setup for the candle so when the candle is fully red then you have a confirmed downtrend and when the candle is fully green you have a confirmed up trend of the stochastic however if, you a combination of the two colors inside of one candle then you do not have a confirmed direction of the stochastic.
the strategy is simple for the stochastic and that you need to know your overall trend. if you are in an uptrend you are waiting for the stochastic to reach bottom and start curving up.
if you are in a downtrend you are waiting for the stochastic to reach its top or its peak and curve down.
In an uptrend you want to make sure that the stochastic is making consistently higher lows just like price should be. if at any moment it makes a lower low then you know you have a problem with your Trend and you should consider exiting.
The opposite is true for a downtrend. In a downtrend you want to make sure you have lower highs. if at any given moment you end up with a higher high than you know you have a problem with your Trend and it's probably ending so you should consider exiting.
The stochastic indicator done as he can actually candles also does a very good job of telling you when there is a change of character. In that moment when the change of character shows up you simply wait until your trend and your price start to match up.
You can also use the stochastic indicator in this format to find divergences the same way you would on the relative strength index against your price highs and price lows so Divergence trading is visually a little bit easier with this tool.
The settings for the K percent D percent RSI length and stochastic length can be adjusted at will so be sure to study the history of the stochastic and find the good settings for your trading 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.
[@btc_charlie] Trader XO Macro Trend ScannerWhat is this script?
This script has two main functions focusing on EMAs (Exponential Moving Average) and Stochastic RSI.
EMAs
EMAs are typically used to give a view of bullish / bearish momentum. When the shorter EMA (calculated off more recent price action) crosses, or is above, the slower moving EMA (calculated off a longer period of price action), it suggests that the market is in an uptrend. This can be an indication to either go long on said asset, or that it is more preferable to take long setups over short setups. Invalidation on long setups is usually found via price action (e.g. previous lows) or simply waiting for an EMA cross in the opposite direction (i.e. shorter EMA crosses under longer term EMA).
This is not a perfect system for trade entry or exit, but it does give a good indication of market trends. The settings for the EMAs can be changed based on user inputs, and by default the candles are coloured based on the crosses to make it more visual. The default settings are based on “Trader XO’s” settings who is an exceptional swing trader.
RSI
Stochastic RSI is a separate indicator that has been added to this script. RSI measures Relative Strength (RSI = Relative Strength Index). When RSI is <20 it is considered oversold, and when >80 it is overbought. These conditions suggests that momentum is very strong in the direction of the trend.
If there is a divergence between the price (e.g. price is creating higher highs, and stoch RSI is creating lower highs) it suggests the strength of the trend is weakening. Whilst this script does not highlight divergences, what it does highlight is when the shorter term RSI (K) crosses over D (the average of last 3 periods). This can give an indication that the trend is losing strength.
Combination
The EMAs indicate when trend shifts (bullish or bearish).
The RSI indicates when the trend is losing momentum.
The combination of the two can be used to suggest when to prefer a directional bias, and subsequently shift in anticipation of a trend reversal.
Note that no signal is 100% accurate and an interpretation of market conditions and price action will need to be overlayed to
Why is it different to others?
I have not found other scripts that are available in this way visually including alerts when Stoch RSI crosses over/under the extremes; or the mid points.
Whilst these indicators are default, the combination of them and how they are presented is not and makes use of the TradingView colouring functionalities.
What are the features?
Customise the variables (averages) used in the script.
Display as one EMA or two EMAs (the crossing ones).
Alerts on EMA crosses.
Alerts on Stoch RSI crosses - slow/fast, upper, lower areas.
- Currently set on the chart to show alerts when Stoch RSI is above 80, then falls below 80 (and colours it red).
Customisable colours.
What are the best conditions for this?
It is designed for high timeframe charts and analysis in crypto, since crypto tends to trend.
It can however be used for lower timeframes.
Disclaimer/Notes:
I have noticed several videos appearing suggesting that this is a "100% win rate indicator" .
NO indicator has 100% win rate.
An indicator is an *indicator* that is all.
Please use responsibly and let me know if there are any mods or updates you would like to see.
Any Oscillator Underlay [TTF]We are proud to release a new indicator that has been a while in the making - the Any Oscillator Underlay (AOU) !
Note: There is a lot to discuss regarding this indicator, including its intent and some of how it operates, so please be sure to read this entire description before using this indicator to help ensure you understand both the intent and some limitations with this tool.
Our intent for building this indicator was to accomplish the following:
Combine all of the oscillators that we like to use into a single indicator
Take up a bit less screen space for the underlay indicators for strategies that utilize multiple oscillators
Provide a tool for newer traders to be able to leverage multiple oscillators in a single indicator
Features:
Includes 8 separate, fully-functional indicators combined into one
Ability to easily enable/disable and configure each included indicator independently
Clearly named plots to support user customization of color and styling, as well as manual creation of alerts
Ability to customize sub-indicator title position and color
Ability to customize sub-indicator divider lines style and color
Indicators that are included in this initial release:
TSI
2x RSIs (dubbed the Twin RSI )
Stochastic RSI
Stochastic
Ultimate Oscillator
Awesome Oscillator
MACD
Outback RSI (Color-coding only)
Quick note on OB/OS:
Before we get into covering each included indicator, we first need to cover a core concept for how we're defining OB and OS levels. To help illustrate this, we will use the TSI as an example.
The TSI by default has a mid-point of 0 and a range of -100 to 100. As a result, a common practice is to place lines on the -30 and +30 levels to represent OS and OB zones, respectively. Most people tend to view these levels as distance from the edges/outer bounds or as absolute levels, but we feel a more way to frame the OB/OS concept is to instead define it as distance ("offset") from the mid-line. In keeping with the -30 and +30 levels in our example, the offset in this case would be "30".
Taking this a step further, let's say we decided we wanted an offset of 25. Since the mid-point is 0, we'd then calculate the OB level as 0 + 25 (+25), and the OS level as 0 - 25 (-25).
Now that we've covered the concept of how we approach defining OB and OS levels (based on offset/distance from the mid-line), and since we did apply some transformations, rescaling, and/or repositioning to all of the indicators noted above, we are going to discuss each component indicator to detail both how it was modified from the original to fit the stacked-indicator model, as well as the various major components that the indicator contains.
TSI:
This indicator contains the following major elements:
TSI and TSI Signal Line
Color-coded fill for the TSI/TSI Signal lines
Moving Average for the TSI
TSI Histogram
Mid-line and OB/OS lines
Default TSI fill color coding:
Green : TSI is above the signal line
Red : TSI is below the signal line
Note: The TSI traditionally has a range of -100 to +100 with a mid-point of 0 (range of 200). To fit into our stacking model, we first shrunk the range to 100 (-50 to +50 - cut it in half), then repositioned it to have a mid-point of 50. Since this is the "bottom" of our indicator-stack, no additional repositioning is necessary.
Twin RSI:
This indicator contains the following major elements:
Fast RSI (useful if you want to leverage 2x RSIs as it makes it easier to see the overlaps and crosses - can be disabled if desired)
Slow RSI (primary RSI)
Color-coded fill for the Fast/Slow RSI lines (if Fast RSI is enabled and configured)
Moving Average for the Slow RSI
Mid-line and OB/OS lines
Default Twin RSI fill color coding:
Dark Red : Fast RSI below Slow RSI and Slow RSI below Slow RSI MA
Light Red : Fast RSI below Slow RSI and Slow RSI above Slow RSI MA
Dark Green : Fast RSI above Slow RSI and Slow RSI below Slow RSI MA
Light Green : Fast RSI above Slow RSI and Slow RSI above Slow RSI MA
Note: The RSI naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Stochastic and Stochastic RSI:
These indicators contain the following major elements:
Configurable lengths for the RSI (for the Stochastic RSI only), K, and D values
Configurable base price source
Mid-line and OB/OS lines
Note: The Stochastic and Stochastic RSI both have a normal range of 0 to 100 with a mid-point of 50, so no rescaling or transformations are done on either of these indicators. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Ultimate Oscillator (UO):
This indicator contains the following major elements:
Configurable lengths for the Fast, Middle, and Slow BP/TR components
Mid-line and OB/OS lines
Moving Average for the UO
Color-coded fill for the UO/UO MA lines (if UO MA is enabled and configured)
Default UO fill color coding:
Green : UO is above the moving average line
Red : UO is below the moving average line
Note: The UO naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Awesome Oscillator (AO):
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the AO calculation
Configurable price source for the moving averages used in the AO calculation
Mid-line
Option to display the AO as a line or pseudo-histogram
Moving Average for the AO
Color-coded fill for the AO/AO MA lines (if AO MA is enabled and configured)
Default AO fill color coding (Note: Fill was disabled in the image above to improve clarity):
Green : AO is above the moving average line
Red : AO is below the moving average line
Note: The AO is technically has an infinite (unbound) range - -∞ to ∞ - and the effective range is bound to the underlying security price (e.g. BTC will have a wider range than SP500, and SP500 will have a wider range than EUR/USD). We employed some special techniques to rescale this indicator into our desired range of 100 (-50 to 50), and then repositioned it to have a midpoint of 50 (range of 0 to 100) to meet the constraints of our stacking model. We then do one final repositioning to place it in the correct position the indicator-stack based on which other indicators are also enabled. For more details on how we accomplished this, read our section "Binding Infinity" below.
MACD:
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the MACD calculation
Configurable price source for the moving averages used in the MACD calculation
Configurable length and calculation method for the MACD Signal Line calculation
Mid-line
Note: Like the AO, the MACD also technically has an infinite (unbound) range. We employed the same principles here as we did with the AO to rescale and reposition this indicator as well. For more details on how we accomplished this, read our section "Binding Infinity" below.
Outback RSI (ORSI):
This is a stripped-down version of the Outback RSI indicator (linked above) that only includes the color-coding background (suffice it to say that it was not technically feasible to attempt to rescale the other components in a way that could consistently be clearly seen on-chart). As this component is a bit of a niche/special-purpose sub-indicator, it is disabled by default, and we suggest it remain disabled unless you have some pre-defined strategy that leverages the color-coding element of the Outback RSI that you wish to use.
Binding Infinity - How We Incorporated the AO and MACD (Warning - Math Talk Ahead!)
Note: This applies only to the AO and MACD at time of original publication. If any other indicators are added in the future that also fall into the category of "binding an infinite-range oscillator", we will make that clear in the release notes when that new addition is published.
To help set the stage for this discussion, it's important to note that the broader challenge of "equalizing inputs" is nothing new. In fact, it's a key element in many of the most popular fields of data science, such as AI and Machine Learning. They need to take a diverse set of inputs with a wide variety of ranges and seemingly-random inputs (referred to as "features"), and build a mathematical or computational model in order to work. But, when the raw inputs can vary significantly from one another, there is an inherent need to do some pre-processing to those inputs so that one doesn't overwhelm another simply due to the difference in raw values between them. This is where feature scaling comes into play.
With this in mind, we implemented 2 of the most common methods of Feature Scaling - Min-Max Normalization (which we call "Normalization" in our settings), and Z-Score Normalization (which we call "Standardization" in our settings). Let's take a look at each of those methods as they have been implemented in this script.
Min-Max Normalization (Normalization)
This is one of the most common - and most basic - methods of feature scaling. The basic formula is: y = (x - min)/(max - min) - where x is the current data sample, min is the lowest value in the dataset, and max is the highest value in the dataset. In this transformation, the max would evaluate to 1, and the min would evaluate to 0, and any value in between the min and the max would evaluate somewhere between 0 and 1.
The key benefits of this method are:
It can be used to transform datasets of any range into a new dataset with a consistent and known range (0 to 1).
It has no dependency on the "shape" of the raw input dataset (i.e. does not assume the input dataset can be approximated to a normal distribution).
But there are a couple of "gotchas" with this technique...
First, it assumes the input dataset is complete, or an accurate representation of the population via random sampling. While in most situations this is a valid assumption, in trading indicators we don't really have that luxury as we're often limited in what sample data we can access (i.e. number of historical bars available).
Second, this method is highly sensitive to outliers. Since the crux of this transformation is based on the max-min to define the initial range, a single significant outlier can result in skewing the post-transformation dataset (i.e. major price movement as a reaction to a significant news event).
You can potentially mitigate those 2 "gotchas" by using a mechanism or technique to find and discard outliers (e.g. calculate the mean and standard deviation of the input dataset and discard any raw values more than 5 standard deviations from the mean), but if your most recent datapoint is an "outlier" as defined by that algorithm, processing it using the "scrubbed" dataset would result in that new datapoint being outside the intended range of 0 to 1 (e.g. if the new datapoint is greater than the "scrubbed" max, it's post-transformation value would be greater than 1). Even though this is a bit of an edge-case scenario, it is still sure to happen in live markets processing live data, so it's not an ideal solution in our opinion (which is why we chose not to attempt to discard outliers in this manner).
Z-Score Normalization (Standardization)
This method of rescaling is a bit more complex than the Min-Max Normalization method noted above, but it is also a widely used process. The basic formula is: y = (x – μ) / σ - where x is the current data sample, μ is the mean (average) of the input dataset, and σ is the standard deviation of the input dataset. While this transformation still results in a technically-infinite possible range, the output of this transformation has a 2 very significant properties - the mean (average) of the output dataset has a mean (μ) of 0 and a standard deviation (σ) of 1.
The key benefits of this method are:
As it's based on normalizing the mean and standard deviation of the input dataset instead of a linear range conversion, it is far less susceptible to outliers significantly affecting the result (and in fact has the effect of "squishing" outliers).
It can be used to accurately transform disparate sets of data into a similar range regardless of the original dataset's raw/actual range.
But there are a couple of "gotchas" with this technique as well...
First, it still technically does not do any form of range-binding, so it is still technically unbounded (range -∞ to ∞ with a mid-point of 0).
Second, it implicitly assumes that the raw input dataset to be transformed is normally distributed, which won't always be the case in financial markets.
The first "gotcha" is a bit of an annoyance, but isn't a huge issue as we can apply principles of normal distribution to conceptually limit the range by defining a fixed number of standard deviations from the mean. While this doesn't totally solve the "infinite range" problem (a strong enough sudden move can still break out of our "conceptual range" boundaries), the amount of movement needed to achieve that kind of impact will generally be pretty rare.
The bigger challenge is how to deal with the assumption of the input dataset being normally distributed. While most financial markets (and indicators) do tend towards a normal distribution, they are almost never going to match that distribution exactly. So let's dig a bit deeper into distributions are defined and how things like trending markets can affect them.
Skew (skewness): This is a measure of asymmetry of the bell curve, or put another way, how and in what way the bell curve is disfigured when comparing the 2 halves. The easiest way to visualize this is to draw an imaginary vertical line through the apex of the bell curve, then fold the curve in half along that line. If both halves are exactly the same, the skew is 0 (no skew/perfectly symmetrical) - which is what a normal distribution has (skew = 0). Most financial markets tend to have short, medium, and long-term trends, and these trends will cause the distribution curve to skew in one direction or another. Bullish markets tend to skew to the right (positive), and bearish markets to the left (negative).
Kurtosis: This is a measure of the "tail size" of the bell curve. Another way to state this could be how "flat" or "steep" the bell-shape is. If the bell is steep with a strong drop from the apex (like a steep cliff), it has low kurtosis. If the bell has a shallow, more sweeping drop from the apex (like a tall hill), is has high kurtosis. Translating this to financial markets, kurtosis is generally a metric of volatility as the bell shape is largely defined by the strength and frequency of outliers. This is effectively a measure of volatility - volatile markets tend to have a high level of kurtosis (>3), and stable/consolidating markets tend to have a low level of kurtosis (<3). A normal distribution (our reference), has a kurtosis value of 3.
So to try and bring all that back together, here's a quick recap of the Standardization rescaling method:
The Standardization method has an assumption of a normal distribution of input data by using the mean (average) and standard deviation to handle the transformation
Most financial markets do NOT have a normal distribution (as discussed above), and will have varying degrees of skew and kurtosis
Q: Why are we still favoring the Standardization method over the Normalization method, and how are we accounting for the innate skew and/or kurtosis inherent in most financial markets?
A: Well, since we're only trying to rescale oscillators that by-definition have a midpoint of 0, kurtosis isn't a major concern beyond the affect it has on the post-transformation scaling (specifically, the number of standard deviations from the mean we need to include in our "artificially-bound" range definition).
Q: So that answers the question about kurtosis, but what about skew?
A: So - for skew, the answer is in the formula - specifically the mean (average) element. The standard mean calculation assumes a complete dataset and therefore uses a standard (i.e. simple) average, but we're limited by the data history available to us. So we adapted the transformation formula to leverage a moving average that included a weighting element to it so that it favored recent datapoints more heavily than older ones. By making the average component more adaptive, we gained the effect of reducing the skew element by having the average itself be more responsive to recent movements, which significantly reduces the effect historical outliers have on the dataset as a whole. While this is certainly not a perfect solution, we've found that it serves the purpose of rescaling the MACD and AO to a far more well-defined range while still preserving the oscillator behavior and mid-line exceptionally well.
The most difficult parts to compensate for are periods where markets have low volatility for an extended period of time - to the point where the oscillators are hovering around the 0/midline (in the case of the AO), or when the oscillator and signal lines converge and remain close to each other (in the case of the MACD). It's during these periods where even our best attempt at ensuring accurate mirrored-behavior when compared to the original can still occasionally lead or lag by a candle.
Note: If this is a make-or-break situation for you or your strategy, then we recommend you do not use any of the included indicators that leverage this kind of bounding technique (the AO and MACD at time of publication) and instead use the Trandingview built-in versions!
We know this is a lot to read and digest, so please take your time and feel free to ask questions - we will do our best to answer! And as always, constructive feedback is always welcome!
Multi Timeframe Stochastic RSI ScreenerThis script is also a Stochastic RSI Screener, but it allows users to choose one specific symbol and three timeframes of that symbol to monitor at once.
Stochastic RSI ScreenerStochastic RSI Screener is built as an indicator and can be applied to any chart.
It gives users the ability to choose 5 specific symbols to watch and then specify the required options to change the RSI and Stochastic settings in a way that fits their needs.
This screener shows the values of (CURRENT PRICE, RSI, K-VALUE, D-VALUE) for each one of the specified symbols. It will do the calculations based on the currently opened timeframe for all symbols.
TradePro's 2 EMA + Stoch RSI + ATR StrategySaw TradePro's "NEW BEST HIGHEST PROFITING STRATEGY WITH CRAZY RESULTS - 2 EMA+ Stochastic RSI+ ATR", and was curious on the back testing results. This strategy is an attempt to recreate it.
This strategy uses 50 / 200 EMAs, Stochastic RSI and ATR.
Long Entry Criteria:
- 50 EMA > 200 EMA
- Price closes below 50 EMA
- Stochastic RSI has gone into oversold < 20
- Stochastic RSI crosses up while making higher low from previous cross up
Short Entry Criteria:
- 50 EMA < 200 EMA
- Price closes above 50 EMA
- Stochastic RSI has gone into overbought > 80
- Stochastic RSI crosses down while making lower high from previous cross down
Stop-loss is set to ATR stop-loss
Take Profit is 2x the risk
All parameters are configurable.
Enjoy~~
AII - Average indicator of indicatorsThis Pine Script for TradingView is a technical analysis tool that visualizes the average of several popular indicators in the trading world. The indicators included are the RSI (Relative Strength Index), RVI (Relative Vigor Index), Stochastic RSI, Williams %R, relative MACD (ranging from 0 to 100), and Bollinger Bands price distance from 0 to 100. The script uses the "input" function to customize the length of the indicators and the "plot" function to display the results on the chart. In addition, options are included to turn off certain indicators and change the line colors if the user desires. All indicators can also be activated independently, allowing the user to see only the indicators they want. It is also mentioned that the script will be improved in the future to offer a better user experience. The calculated values are calculated with the default EMA of 14. Overall, this script is an excellent option for those looking for a combined view of several important indicators for making trading decisions.
RSI Overbought/Oversold + Divergence IndicatorDESCRIPTION:
This script combines the Relative Strength Index ( RSI ), Moving Average and Divergence indicator to make a better decision when to enter or exit a trade.
- The Moving Average line (MA) has been made hidden by default but enhanced with an RSIMA cloud.
- When the RSI is above the selected MA it turns into green and when the RSI is below the select MA it turns into red.
- When the RSI is moving into the Overbought or Oversold area, some highlighted areas will appear.
- When some divergences or hidden divergences are detected an extra indication will be highlighted.
- When the divergence appear in the Overbought or Oversold area the more weight it give to make a decision.
- The same color pallet has been used as the default candlestick colors so it looks familiar.
HOW TO USE:
The prerequisite is that we have some knowledge about the Elliot Wave Theory, the Fibonacci Retracement and the Fibonacci Extension tools.
Wave 1
(1) When we receive some buy signals we wait until we receive some extra indications.
(2) On the RSI Overbought/Oversold + Divergence Indicator we can see a Bullish Divergence and our RSI is changing from red to green ( RSI is higher then the MA).
(3) If we are getting here into the trade then we need to use a stop loss. We put our stop loss 1 a 2 pips just below the lowest wick. We also invest maximum 50% of the total amount we want to invest.
Wave 2
(4) Now we wait until we see a clear reversal and here we starting to use the Fibonacci Retracement tool. We draw a line from the lowest point of wave(1) till the highest point of wave (1). When we are retraced till the 0.618 fib also called the golden ratio we check again the RSI Overbought/Oversold + Divergence Indicator. When we see a reversal we do our second buy. We set again a stop loss just below the lowest wick (this is the yellow line on the chart). We also move the stop loss we have set in step (3) to this level.
Wave 3
(5) To identify how far the uptrend can go we need to use the Fibonacci Extension tool. We draw a line from the lowest point of wave(1) till the highest point of wave (1) and draw it back to the lowest point of wave (2). Wave (3) is most of the time the longest wave and can go till it has reached the 1.618 or 2.618 fib. On the 1.618 we can take some profit. If we don't want to sell we move our stop loss to the 1 fib line (yellow line on the chart).
(6) We wait until we see a clear reversal on the Overbought/Oversold + Divergence Indicator and sell 33% to 50% of our investment.
Wave 4
(7) Now we wait again until we see a clear reversal and here we starting to use the Fibonacci Retracement tool. We draw a line from the lowest point of wave(2) till the highest point of wave (3). When we are retraced till the 0.618 fib also called the golden ratio we check again the RSI Overbought/Oversold + Divergence Indicator. When we see a reversal we buy again. We set again a stop loss just below the lowest wick (this is the yellow line on the chart).
(8) If we bought at the first reversal ours stop los was triggered (9) and we got out of the trade.
(9) If we did not bought at step (7) because our candle did not hit the 0.618 fib or we got stopped out of the trade we buy again at the reversal.
Wave 5
(10) To identify how far the uptrend can go we need to use the Fibonacci Extension tool. We draw a line from the lowest point of wave(2) till the highest point of wave (3) and draw it back to the lowest point of wave (4). Most of the time wave 5 goes up till it has reached the 1 fib. And that is the point where we got out of the trade with all of our investment. In this trade we got out of the trade a bit earlier. We received the sell signals and got a reversal on the Overbought/Oversold + Divergence Indicator.
We are hoping you learned something so you can make better decisions when to get into or out of a trade.
If you have any question just drop it into the comments below.
FEATURES:
• You can show/hide the RSI .
• You can show/hide the MA.
• You can show/hide the lRSIMA cloud.
• You can show/hide the Stoch RSI cloud.
• You can show/hide and adjust the Overbought and Oversold zones.
• You can show/hide and adjust the Overbought Extended and Oversold Extended zones.
• You can show/hide the Overbought and Oversold highlighted zones.
• Etc...
HOW TO GET ACCESS TO THE SCRIPT:
• Favorite the script and add it to your chart.
REMARKS:
• This advice is NOT financial advice.
• We do not provide personal investment advice and we are not a qualified licensed investment advisor.
• All information found here, including any ideas, opinions, views, predictions, forecasts, commentaries, suggestions, or stock picks, expressed or implied herein, are for informational, entertainment or educational purposes only and should not be construed as personal investment advice.
• We will not and cannot be held liable for any actions you take as a result of anything you read here.
• We only provide this information to help you make a better decision.
• While the information provided is believed to be accurate, it may include errors or inaccuracies.
Good Luck and have fun,
The CryptoSignalScanner Team
Bull Trend Filtered StochRSI (BTFS)Ride Bull Trends Via Stochastic with Special Rules for Heavy Bullish Bias
TLDR: Long Only Trend Indicator Where you are always entered Long if the stochastic is over the lower band line and the price is above the Donchian Chanel high. Exit when Stochastic RSI is below the lower band.
Indicators:
Filter = Trend/Bullish indicator is Donchian of ema(high) this is set as the highest ema(high, 6) in the last 30 candles. this can be adjusted to fit the market as desired.
**indicator prints green background when the filter condition is satisfied***
Entry Exit = enter when the Stoch RSI is above the given lower trend band. This value is set at 35 but can be adjusted according to risk tolerance and market conditions.
Logic:
this indicator allows a trader to be present during bullish/parabolic trends by only triggering if the close is > than the highest 6 candle average high over the last 30 candles. This filter requires the market to be in a generally bullish posture. If the market is in this condition the stochastic RSI indicator value offers a good gauge of price action and only goes significantly down if price trends below the average range of the rsi period. This filters out noise and keeps a trader from over trading on inconsequential corrections while responding fairly quickly to changes in general trend direction. the response is fast enough to produce an unprofitable amount of false signals if the bull market filter is not implemented. However when used in combination the signals return desirable results in bull trending markets.
Hope this Helps. Happy Trades.
-Snarky Puppy
Rich Robin Index, The Crypto Fear & Greed Index with RSI Trend The Relative Strength Index (RSI) is a technical indicator based on price movements that is used to determine whether a particular asset is overbought or oversold. It measures the ratio of rising to falling prices over a certain period of time.
The Fear & Greed Index, on the other hand, is a composite index that tracks the sentiment of the crypto market. It is based on seven indicators, each of which measures a different aspect of market behavior. These indicators are: Safe Haven Demand, Stock Price Breadth, Market Momentum, Stock Price Strength, Put and Call Options, Junk Bond Demand, and Market Volatility.
The combination of the RSI and the Fear & Greed Index can provide valuable insights for crypto traders. The RSI can help identify overbought and oversold conditions, while the Fear & Greed Index can give an overall sense of the sentiment in the market. Together, they can provide a more complete picture of the market conditions. For example, if the RSI is indicating that an asset is overbought, but the Fear & Greed Index is showing that the market is still in a state of fear, it may be a good time to sell. On the other hand, if the RSI is indicating that an asset is oversold, but the Fear & Greed Index is showing that the market is in a state of greed, it may be a good time to buy.
Overall, the combination of the RSI and the Fear & Greed Index can provide useful information for traders to make more informed decisions, by giving a sense of the market conditions, and providing a way to identify overbought and oversold conditions.
Stoch RSI 15 min - multi time frame tableABOUT THIS INDICATOR
This indicator calculates the Stochastic RSI for the time frames 15 min, 30 min, 1h, 4h, and 12h. However, the 15 min time frame should always be the default time frame for your chart.
IMPORTANT
* NOTE! It's extremely important that the chosen time frame for your chart is 15 min. Otherwise the Stochastic RSI for the longer time frames won’t be correctly calculated.
* Stochastic RSI will be calculated and displayed in a table for the time frames: 15 min, 30 min, 1h, 4h, 12h.
* All time frames are based on closed bars except the "15minR" that are realtime updated values calculated on a 15 min time frame.
ABOUT STOCHASTIC RSI
The Stochastic RSI (StochRSI) is a momentum indicator that ranges between 0 and 100. A Stochastic RSI value above 80 is considered overbought and below 20 is considered oversold.
By using different time frames you can get a better idea of what direction the trade could take in a "longer" perspective.
SETTINGS
1.) Length RSI = 14 (default period)
2.) Smoothing parameter of Stochastic RSI (Length Moving Average = 3) . Moving average of stochastic RSI
* By default the displayed Stochastic RSI values are smoothed values of the actual Stochastic RSI. The smoothnes is formed by a calculated moving average of with the length of 3 by default.
If you want Stochastic RSI with a sharper signal (higher risk for "false alarms" being more sensitive) change the Length Moving Average to = 1 (no smoothness at all)
You can see the selected "Length RSI" and "Length Moving Average" on top of the Stochastic RSI table.
Next version of this script will be updated with more a more flexible solution for different time frames.
* NOTE, Tradingview comes with a inbuilt Stochastic RSI. See the the chart below. The blue line in the Stochastic-RSI chart represents (K value = 3) the same value as the script calculate/display in the table.
