Gtrades Forex RSI & Volume SignalThe "Forex RSI & Volume Signal" indicator combines Relative Strength Index (RSI) and volume analysis to identify potential buy signals in forex trading. It calculates RSI to gauge overbought or oversold conditions, while comparing current volume to a moving average to determine bullish volume momentum. When RSI indicates oversold conditions and volume suggests bullish momentum, a buy signal is generated. This indicator aims to identify favorable entry points during short-term uptrends in the forex market, leveraging both momentum and volume analysis to inform trading decisions. It provides traders with a comprehensive tool to identify potential buying opportunities based on multiple technical factors.
在腳本中搜尋"Relative Strength Index (RSI) "
Megabar Breakout (Range & Volume & RSI)Hey there,
This strategy is based on the idea that certain events lead to what are called Megabars. Megabars are bars that have a very large range and volume. I wanted to verify whether these bars indicate the start of a trend and whether one should follow the trend.
Summary of the Code:
The code is based on three indicators: the range of the bar, the volume of the bar, and the RSI. When certain values of these indicators are met, a Megabar is identified. The direction of the Megabar indicates the direction in which we should trade.
Why do I combine these indicators?
I want to identify special bars that have the potential to mark the beginning of a breakout. Therefore, a bar needs to exhibit high volume, have a large range (huge price movement), and we also use the Relative Strength Index (RSI) to assess potential momentum. Only if all three criteria are met within one candle, do we use this as an identifier for a megabar.
Explanation of Drawings on the Chart:
As you can see, there is a green background on my chart. The green background symbolizes the time when I'm entering a trade. Only if a Megabar happens during that time, I'm ready to enter a trade. The time is between 6 AM and 4 PM CET. It's just because I prefer that time. Also, the strategy draws an error every time a Megabar happens based on VOL and Range only (not on the RSI). That makes it pretty easy to go through your chart and check the biggest bars manually. You can activate or deactivate these settings via the input data of the strategy.
When Do We Enter a Trade?
We wait for a Megabar to happen during our trading session. If the Megabar is bullish, we open a LONG trade at the opening price of the next candle. If the Megabar is bearish, we open a SHORT trade at the opening price of the next candle.
Where Do We Put Our Take Profit & Stop Loss?
The default setting is TP = 40 Pips and SL = 30 Pips. In that case, we are always trading with a risk-reward ratio of 1.33 by default. You can easily change these settings via the input data of the strategy.
Strategy Results
The criteria for Megabars were chosen by me in a way that makes Megabars something special. They are not intended to occur too frequently, as the fundamental idea of this strategy would otherwise not hold. This results in only 37 closed trades within the last 12 months. If you change the criterias for a megabar to a milder one, you will create more Megabars and therefore more trades. It's up to you. I have adapted this strategy to the 30-minute chart of the EURUSD. In the evaluation, we consider a period of 12 months, which I believe is sufficient.
My default settings for the indicators look like this:
Avg Length Vol 20
Avg Multiplier Vol 3
Avg Length Range 20
Avg Multiplier Range 4
Value SMA RSI for Long Trades 50
Value SMA RSI for Short Trades 70
IMPORTANT: The current performance overview does not display the results of these settings. Please change the settings to my default ones so that you can see how I use this strategy.
I do not recommend trading this strategy without further testing. The script is meant to reflect a basic idea and be used as a tool to identify Megabars. I have made this strategy completely public so that it can be further developed. One can take this framework and test it on different timeframes and different markets.
SMA/EMA/RSImagic 36.963 by IgorPlahutaTwo Elements in this script:
Alerts: These are notifications that draw your attention to specific market conditions. There are two types:
RSI Higher Lows or Lower Highs: This alert triggers when the Relative Strength Index (RSI) forms higher lows or lower highs.
RSI Exiting 30 (Up) or RSI Exiting 70 (Down): These alerts activate when the RSI crosses the 30 threshold upwards or the 70 threshold downwards.
ALL BUY/SELL: to catch both of them with one setting
To Set Up an Alert: To configure an alert, select the one relevant to your trading strategy, choose the "Greater than" option, and input a value of "0" (this essentially activates the alert). Adjust other settings as per your requirements.
Please note that these alerts should be used in conjunction with a system you trust for confirmation.
Moving Averages: This involves monitoring several moving averages:
SMA12, SMA20, EMA12, EMA20: These moving averages are highlighted with background colors to help you quickly identify changes or crossovers. They are superimposed on each other for easy comparison.
SMA 50, SMA200: These moving averages are also highlighted with background colors to spot crossovers, and their lines change color depending on their direction (falling in red or rising in green).
Enjoy using these tools in your trading endeavors!
W and M Pattern Indicator- SwaGThis is a TradingView indicator script that identifies potential buy and sell signals based on ‘W’ and ‘M’ patterns in the Relative Strength Index (RSI). It provides visual alerts and draws horizontal lines to indicate potential trade entry points.
User Manual:
Inputs: The script takes two inputs - an upper limit and a lower limit. The default values are 70 and 40, respectively.
RSI Calculation: The script calculates the RSI based on the closing prices of the last 14 periods.
Pattern Identification: It identifies ‘W’ patterns when the RSI makes a higher low within the lower limit, and ‘M’ patterns when the RSI makes a lower high within the upper limit.
Visual Alerts: The script plots these patterns on the chart. ‘W’ patterns are marked with small green triangles below the bars, and ‘M’ patterns are marked with small red triangles above the bars.
Trade Entry Points: A horizontal line is drawn at the high or low of the candle to represent potential trade entry points. The line starts from one bar to the left and extends 10 bars to the right.
Trading Strategy:
For investing, use a weekly timeframe.
For swing trading, use a daily timeframe.
For intraday trading, use a 5 or 15-minute timeframe. Only consider sell-side signals for intraday trading.
Take a buy position if the high breaks above the green line or sell if the low breaks below the red line.
Use recent signals only and avoid signals that are too old.
Swing highs or lows will be your stop-loss level.
Always think about your stop-loss before entering a trade, not your target.
Avoid trades with a large stop-loss.
Remember, this script is a tool to aid in your trading decisions. Always test your strategies thoroughly before live trading. Happy trading! 😊
Philpose's Binary Turbo 1.2Hello there,
I'm thrilled to introduce my very first TradingView indicator - "Philpose's Binary Turbo 1.0." This indicator isn't just another tool; it's my unique take on binary options trading, powered by the Relative Strength Index (RSI).
Differences from Other Indicators:
This indicator is designed for traders who prefer short-term trading, as it uses a 1-minute timeframe.
It assumes that RSI crossovers of overbought and oversold levels can be used to generate binary options signals.
Users should backtest and evaluate the indicator's performance in different market conditions and consider risk management strategies.
Custom Logic: This indicator implements a custom trading logic based on RSI crossovers of overbought and oversold levels. Many indicators on TradingView use standard indicators, but this script incorporates unique logic.
Signal Tracking: It tracks and displays the last buy and sell signals on the chart. This visual representation can be helpful for traders to see when signals were generated.
Streak Tracking: The script keeps track of winning and losing streaks, which can provide traders with insights into their trading performance over time.
Table Summary: It creates a table summarizing various statistics related to the signals generated, such as total signals, wins, losses, and streaks. This tabular representation can be useful for traders to assess the indicator's performance.
How to Use:
To use this indicator effectively, follow these steps:
Add the Indicator: Copy and paste the script into TradingView's Pine Script editor. Then, apply the indicator to the chart.
Customize Parameters: Adjust the RSI parameters (period, overbought, and oversold levels) and the minimum bars between signals according to your trading strategy and preferences.
Interpret Signals: Buy signals are generated when the RSI crosses above the oversold level, and sell signals occur when it crosses below the overbought level.
Analyze Streaks: Keep an eye on the win and loss streaks to assess the indicator's performance and your trading strategy.
Review Table: The table at the top-right corner of the chart provides a summary of important statistics related to signals, wins, losses, and streaks.
Markets and Conditions:
The script can be used in various financial markets, including stocks, forex, commodities, and indices. However, it's important to note that binary options trading has a distinct risk profile and is available on certain platforms. Therefore, you should ensure that your chosen binary options platform supports TradingView indicators and that you understand the specific conditions of binary options trading.
Conditions for Use:
This indicator is designed for traders who prefer short-term trading, as it uses a 1-minute timeframe.
It assumes that RSI crossovers of overbought and oversold levels can be used to generate binary options signals.
Users should backtest and evaluate the indicator's performance in different market conditions and consider risk management strategies.
Please exercise caution when using any trading indicator or strategy, especially in binary options trading, as it involves a high level of risk, and you may lose your entire investment. It's advisable to thoroughly test any strategy on a demo account before trading with real funds and to seek the advice of a qualified financial advisor if you are unsure about your trading decisions.
Multiple Ticker Stochastic RSIThe Stochastic RSI is a technical indicator ranging between 0 and 100, based on applying the Stochastic oscillator formula to a set of relative strength index (RSI). Unlike the original Stochastic RSI indicator, this allows you to define up to two additional tickers for which all three will be averaged and outputted visually looking like a standard Stochastic RSI indicator. Potential buy and sell visuals are included, as well as alerts. Please note that this indicator is not meant to be used by itself.
12&50 RSI + %R2/50 RSI+ %R is a PineScript indicator that combines two popular technical indicators, the Relative Strength Index (RSI) and the Williams %R. The indicator plots two lines, K and D, which represent the smoothed moving averages of the RSI. It also plots the RSI with a 60-period length and the Williams %R with a 21-period length. The indicator can be used to identify overbought and oversold conditions, as well as potential reversals.
Here are some of the key features of the script:
It uses two different RSI lengths to provide a more comprehensive view of the market.
It plots the Williams %R, which can be used to identify overbought and oversold conditions.
It includes overbought and oversold levels to help traders identify potential entry and exit points.
Jdawg Sentiment Momentum Oscillator EnhancedThe Jdawg Sentiment Momentum Oscillator Enhanced (JSMO_E) is a versatile technical analysis indicator designed to provide traders with insights into potential trend changes and overbought or oversold market conditions. JSMO_E combines the principles of the Relative Strength Index (RSI), the Simple Moving Average (SMA), and the Rate of Change (ROC) to create a comprehensive tool for assessing market sentiment and momentum.
The uniqueness of JSMO_E lies in its ability to integrate the RSI, SMA of RSI, and ROC of RSI, while also allowing users to customize the weight of the ROC component. This combination of features is not commonly found in other indicators, which increases its distinctiveness.
To effectively use JSMO_E, follow these steps:
Apply the JSMO_E indicator to the price chart of the asset you are analyzing.
Observe the plotted JSMO_E line in relation to the zero line, overbought, and oversold levels.
When the JSMO_E line crosses above the zero line, it may signal the beginning of an uptrend or bullish momentum. Conversely, when the JSMO_E line crosses below the zero line, it may indicate the start of a downtrend or bearish momentum.
Overbought and oversold levels, marked by the red and green dashed lines, respectively, can serve as a warning that a trend reversal may be imminent. When the JSMO_E line reaches or surpasses the overbought level, it might indicate that the asset is overvalued and could experience a price decline. Conversely, when the JSMO_E line reaches or goes below the oversold level, it can signal that the asset is undervalued and may experience a price increase.
Adjust the input parameters (RSI Period, SMA Period, ROC Period, and ROC Weight) as needed to optimize the indicator for the specific market and time frame you are analyzing.
The JSMO_E indicator is suitable for various markets, including stocks, forex, commodities, and cryptocurrencies. However, its effectiveness may vary depending on the market conditions and time frames used. It is recommended to use JSMO_E in conjunction with other technical analysis tools and methods to confirm potential trade setups and improve overall trading performance. Always conduct thorough backtesting and forward-testing before employing any indicator in a live trading environment.
TASC 2023.03 Every Little Bit Helps█ OVERVIEW
TASC's February 2023 edition of Traders' Tips includes an article titled "Every Little Bit Helps: Averaging The Open And Close To Reduce Noise" by John Ehlers. This code implements the numerical example from this article.
█ CONCEPTS
Using theories from digital signal processing as a starting point, John Ehlers argues that using the average of the open and close as the source time series of an indicator instead of using only the closing price can often lead to noise reduction in the output. This effect especially applies when there is no gap between the current bar's opening and the previous bar's closing prices. This trick can reduce noise in many common indicators such as the RSI, MACD, and Stochastic.
█ CALCULATIONS
Following the example presented in the original publication, this script illustrates the proposed strategy using the Relative Strength Index (RSI) as a test indicator. It plots two series:
RSI calculated using only closing prices as its source.
RSI of the same length as the first, but calculated using the average of open and close prices as its source, i.e. (open+close)/2 .
This script demonstrates that using the average of open and close as the calculation source results in a smoother indicator. To visually emphasize the advantage of this proposed trick, the script's color scheme is sensitive to both the RSI value and the difference between the two RSI data streams.
Juirk-Filtered QQE Histogram [Loxx]Juirk-Filtered QQE Histogram is a QQE indicator with 7 different RSI types, Jurik-Filtering with the option of double filtering. 2 types of signals, and Loxx's Expanded Source types. These additions are useful to filter out noise.
What is Qualitative Quantitative Estimation (QQE)?
The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index ( RSI ) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR).
There are many indicators for many purposes. Some of them are complex and some are comparatively easy to handle. The QQE indicator is a really useful analytical tool and one of the most accurate indicators. It offers numerous strategies for using the buy and sell signals. Essentially, it can help detect trend reversal and enter the trade at the most optimal positions.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
Included:
Loxx's Expanded Source Types
Alerts
Signals
Bar coloring
Included Libraries
Loxx's Variety RSI
Loxx's Jurik Tools
Loxx's Expanded Source Types
Related indicators:
Natural Market Mirror (NMM) and NMAs w/ Dynamic Zones
RSI/RSX QQE Histogram w/ Discontinued Signal Line
Jurik CFB Adaptive QQE
Adaptive Qualitative Quantitative Estimation (QQE)
Short Term RSI and SMA Percentage ChangeThis strategy utilises common indicators like RSI and moving averages in order to enter and exit trades. The Relative Strength Index (RSI) is a momentum indicator that has a value between 0 and 100, where a value greater than 70 is considered overbought and a value less than 30 is oversold. If the RSI value is above or below these values, then it can signal a possible trend reversal.
The second indicator used in this strategy is the Simple Moving Average (SMA). A SMA is an arithmetic moving average calculated by adding recent prices and then dividing that figure by the number of time periods in the calculation average. For example, one could add the closing price of a coin for a number of time periods and then divide this total by that same number of periods. Short-term averages respond quickly to changes in the price of the underlying coin, while long-term averages are slower to react.
Long/Exit orders are placed when three basic signals are triggered.
Long Position:
RSI is greater than 50
MA9 is greater than MA100
MA9 increases by 6%
Exit Position:
Price increases 5% trailing
Price decreases 5% trailing
The script is backtested from 1 May 2022 and provides good returns.
A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
This script also works well on AVAX 45m/1h, MATIC 15m/45m/1h and ETH 4h.
RSI Precision Trend Candles [Loxx]RSI Precision Trend Candles is a candle coloring indicator that uses an average range algorithm to determine trend direction. The precision trend algorithm can be used on any calculated output to tease out interesting trend information.
What is RSI?
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security.
The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The indicator was developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, New Concepts in Technical Trading Systems.
Included
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
APA Adaptive Fisher Transform [Loxx]APA Adaptive Fisher Transform is an adaptive cycle Fisher Transform using Ehlers Autocorrelation Periodogram Algorithm to calculate the dominant cycle period.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
Included:
Zero-line and signal cross options for bar coloring
Customizable overbought/oversold thresh-holds
Alerts
Signals
APA-Adaptive, Ehlers Early Onset Trend [Loxx]APA-Adaptive, Ehlers Early Onset Trend is Ehlers Early Onset Trend but with Autocorrelation Periodogram Algorithm dominant cycle period input.
What is Ehlers Early Onset Trend?
The Onset Trend Detector study is a trend analyzing technical indicator developed by John F. Ehlers , based on a non-linear quotient transform. Two of Mr. Ehlers' previous studies, the Super Smoother Filter and the Roofing Filter, were used and expanded to create this new complex technical indicator. Being a trend-following analysis technique, its main purpose is to address the problem of lag that is common among moving average type indicators.
The Onset Trend Detector first applies the EhlersRoofingFilter to the input data in order to eliminate cyclic components with periods longer than, for example, 100 bars (default value, customizable via input parameters) as those are considered spectral dilation. Filtered data is then subjected to re-filtering by the Super Smoother Filter so that the noise (cyclic components with low length) is reduced to minimum. The period of 10 bars is a default maximum value for a wave cycle to be considered noise; it can be customized via input parameters as well. Once the data is cleared of both noise and spectral dilation, the filter processes it with the automatic gain control algorithm which is widely used in digital signal processing. This algorithm registers the most recent peak value and normalizes it; the normalized value slowly decays until the next peak swing. The ratio of previously filtered value to the corresponding peak value is then quotiently transformed to provide the resulting oscillator. The quotient transform is controlled by the K coefficient: its allowed values are in the range from -1 to +1. K values close to 1 leave the ratio almost untouched, those close to -1 will translate it to around the additive inverse, and those close to zero will collapse small values of the ratio while keeping the higher values high.
Indicator values around 1 signify uptrend and those around -1, downtrend.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Adaptive, Jurik-Filtered, JMA/DWMA MACD [Loxx]Adaptive, Jurik-Filtered, JMA/DWMA MACD is MACD oscillator with a twist. The traditional calculation of MACD is the between two EMAs of price. This traditional approach yields a very noisy and lagged signal. To solve this problem, JMA/DWMA MACD uses the difference between adaptive Juirk-Filtered price and adaptive DWMA to yield a marked improvement over traditional MACD.
What is JMA / DWMA oscillator (MACD)?
Of all the different combinations of moving average filters to use for a MACD oscillator, we prefer using the JMA - DWMA combination.
JMA is ideal for the fast moving average line because it is quick to respond to reversals, is smooth and can be set to have no overshoot. DWMA (double weighted moving average) is ideal for the slower line as is tends to delay reversing direction until JMA crosses it.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- Toggle on/off bar coloring
Adaptive Jurik Filter MACD [Loxx]Adaptive Jurik Filter MACD uses Jurik Volty and Adaptive Double Jurik Filter Moving Average (AJFMA) to derive Jurik Filter smoothed volatility.
What is MACD?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence (MACD) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- Change colors of oscillators and bars
Adaptive Jurik Filter Volatility Oscillator [Loxx]Adaptive Jurik Filter Volatility Oscillator uses Jurik Volty and Adaptive Double Jurik Filter Moving Average (AJFMA) to derive Jurik Filter smoothed volatility.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- UI options to color bars
Adaptive Jurik Filter Volatility Bands [Loxx]Adaptive Jurik Filter Volatility Bands uses Jurik Volty and Adaptive, Double Jurik Filter Moving Average (AJFMA) to derive Jurik Filter smoothed volatility channels around an Adaptive Jurik Filter Moving Average. Bands are placed at 1, 2, and 3 deviations from the core basline.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- UI options to shut off colors and bands
Adaptive, Double Jurik Filter Moving Average (AJFMA) [Loxx]Adaptive, Double Jurik Filter Moving Average (AJFMA) is moving average like Jurik Moving Average but with the addition of double smoothing and adaptive length (Autocorrelation Periodogram Algorithm) and power/volatility {Juirk Volty) inputs to further reduce noise and identify trends.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- Double calculation of AJFMA for even smoother results
Adaptive, Jurik-Smoothed, Trend Continuation Factor [Loxx]Adaptive, Jurik-Smoothed, Trend Continuation Factor is a Trend Continuation Factor indicator with adaptive length and volatility inputs
What is the Trend Continuation Factor?
The Trend Continuation Factor (TCF) identifies the trend and its direction. TCF was introduced by M. H. Pee. Positive values of either the Positive Trend Continuation Factor (TCF+) and the Negative Trend Continuation Factor (TCF-) indicate the presence of a strong trend.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
-Your choice of length input calculation, either fixed or adaptive cycle
-Bar coloring to paint the trend
Happy trading!
Ehlers Autocorrelation Periodogram [Loxx]Ehlers Autocorrelation Periodogram contains two versions of Ehlers Autocorrelation Periodogram Algorithm. This indicator is meant to supplement adaptive cycle indicators that myself and others have published on Trading View, will continue to publish on Trading View. These are fast-loading, low-overhead, streamlined, exact replicas of Ehlers' work without any other adjustments or inputs.
Versions:
- 2013, Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers
- 2016, TASC September, "Measuring Market Cycles"
Description
The Ehlers Autocorrelation study is a technical indicator used in the calculation of John F. Ehlers’s Autocorrelation Periodogram. Its main purpose is to eliminate noise from the price data, reduce effects of the “spectral dilation” phenomenon, and reveal dominant cycle periods. The spectral dilation has been discussed in several studies by John F. Ehlers; for more information on this, refer to sources in the "Further Reading" section.
As the first step, Autocorrelation uses Mr. Ehlers’s previous installment, Ehlers Roofing Filter, in order to enhance the signal-to-noise ratio and neutralize the spectral dilation. This filter is based on aerospace analog filters and when applied to market data, it attempts to only pass spectral components whose periods are between 10 and 48 bars.
Autocorrelation is then applied to the filtered data: as its name implies, this function correlates the data with itself a certain period back. As with other correlation techniques, the value of +1 would signify the perfect correlation and -1, the perfect anti-correlation.
Using values of Autocorrelation in Thermo Mode may help you reveal the cycle periods within which the data is best correlated (or anti-correlated) with itself. Those periods are displayed in the extreme colors (orange) while areas of intermediate colors mark periods of less useful cycles.
What is an adaptive cycle, and what is the Autocorrelation Periodogram Algorithm?
From his Ehlers' book mentioned above, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator.This look-back period is commonly a fixed value. However, since the measured cycle period is changing, as we have seen in previous chapters, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
How to use this indicator
The point of the Ehlers Autocorrelation Periodogram Algorithm is to dynamically set a period between a minimum and a maximum period length. While I leave the exact explanation of the mechanic to Dr. Ehlers’s book, for all practical intents and purposes, in my opinion, the punchline of this method is to attempt to remove a massive source of overfitting from trading system creation–namely specifying a look-back period. SMA of 50 days? 100 days? 200 days? Well, theoretically, this algorithm takes that possibility of overfitting out of your hands. Simply, specify an upper and lower bound for your look-back, and it does the rest. In addition, this indicator tells you when its best to use adaptive cycle inputs for your other indicators.
Usage Example 1
Let's say you're using "Adaptive Qualitative Quantitative Estimation (QQE) ". This indicator has the option of adaptive cycle inputs. When the "Ehlers Autocorrelation Periodogram " shows a period of high correlation that adaptive cycle inputs work best during that period.
Usage Example 2
Check where the dominant cycle line lines, grab that output number and inject it into your other standard indicators for the length input.
Haydens RSI CompanionPreface: I'm just the bartender serving today's freshly blended concoction; I'd like to send a massive THANK YOU to all the coders and PineWizards for the locally-sourced ingredients. I am simply a code editor, not a code author. The book that inspired this indicator is a free download, plus all of the pieces I used were free code from the community; my hope is that any additional useful development of The Complete RSI is also offered open-source to the community for collaboration.
Features: Fibonacci retracement plus targets. Advanced dual data ticker. Heiken Ashi or bar overlay. Hayden, BarefootJoey, Tradingview, or Custom watermark of choice. Trend lines for spotting wedges, triangles, pennants, etc. Divergences for spotting potential reversals and Momentum Discrepancy Reversal Point opportunities. Percent change and price pivot labels with advanced data & retracement targets upon hover.
‼ IMPORTANT: Hover over labels for advanced information, like targets. Google & read John Hayden's "The Complete RSI" pdf book for comprehensive instructions before attempting to trade with this indicator. Always keep an eye on higher/stronger timeframes. See the companion oscillator here:
⚠ DISCLAIMER: DYOR. Not financial advice. Not a trading system. I am not affiliated with TradingView or John Hayden; this is my own personally PineScripted presentation of a suitable RSI chart companion to use when trading according to Hayden's rules.
About the Editor: I am a former-FINRA Registered Representative, inventor/patent-holder, and self-taught PineScripter. I mostly code on a v3 Pinescript level so expect heavy scripts that could use some shortening with modern conventions.
MACD+RSI+Flag v2 by RMThis source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
There are a number of very clever people I have taken bits of code and ideas, thanks to you all :) © raul3429
www.investopedia.com
RSI: The relative strength index (RSI) is a momentum indicator measures recent price changes to evaluate overbought or oversold conditions.
MACD: Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is = 12EMA - 26EMA, The histogram represent this difference.
Notes:
This code has Flags for first candle change during oversold/overbought shown as triangles, also and MACD 12 and MACD 26 crossings as diamonds. These are sometimes indicators of trend change.
RSI has been scaled down by "scaleRSI" parameter to enable plotting alongside MACD
Depending on the security being evaluated the RSI scale may need to be adjusted as the MACD ranges vary between symbols.
Disclaimer:
This is not a Financial advisory tool. For education purposes only. Use at your own risk.
