On-Chart QQE of RSI on Variety MA [Loxx]On-Chart QQE of RSI on Variety MA (Quantitative Qualitative Estimation) is usually calculated using RSI. This version is uses an RSI of a Moving Average instead. The results are completely different than the original QQE. Also, this version is drawn directly on chart. There are four types of signals.
What is QQE?
Quantitative Qualitative Estimation (QQE) is a technical analysis indicator used to identify trends and trading opportunities in financial markets. It is based on a combination of two popular technical analysis indicators - the Relative Strength Index (RSI) and Moving Averages (MA).
The QQE indicator uses a smoothed RSI to determine the trend direction, and a moving average of the smoothed RSI to identify potential trend changes. The indicator then plots a series of bands above and below the moving average to indicate overbought and oversold conditions in the market.
The QQE indicator is designed to provide traders with a reliable signal that confirms the strength of a trend or indicates a possible trend reversal. It is particularly useful for traders who are looking to trade in markets that are trending strongly, but also want to identify when a trend is losing momentum or reversing.
Traders can use QQE in a number of different ways, including as a confirmation tool for other indicators or as a standalone indicator. For example, when used in conjunction with other technical analysis tools like support and resistance levels, the QQE indicator can help traders identify key entry and exit points for their trades.
One of the main advantages of the QQE indicator is that it is designed to be more reliable than other indicators that can generate false signals. By smoothing out the price action, the QQE indicator can provide traders with more accurate and reliable signals, which can help them make more profitable trading decisions.
In conclusion, QQE is a popular technical analysis indicator that traders use to identify trends and trading opportunities in financial markets. It combines the RSI and moving average indicators and is designed to provide traders with reliable signals that confirm the strength of a trend or indicate a possible trend reversal.
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.
This indicator makes use of the following libraries:
Loxx's Moving Averages
Loxx's Expanded Source Types
Extras
Alerts
Signals
Signal Types
Change on Levels
Change on Slope
Change on Zero
Change on Original
Moving Averages
Hull PressureThis amazing oscillator displays the difference between the hull average calculated on the close of the candles and the one calculated between the average of the highs and lows.
This allows the user to identify the pressure of the closing price over the average, useful to identify trends, divergences, and reversals.
This indicator also has two dynamic overbought and oversold areas, calculated over the past extreme highs and lows of the oscillator.
Nadaraya-Watson OscillatorThis indicator is based on the work of @jdehorty and his amazing Nadaraya-Watson Kernel Envelope, which you can see here:
General Description
The Nadaraya-Watson Oscillator (NWO) will give the same information as the Nadaraya-Watson Envelope, but as an oscillator off the main chart, by plotting the relationship between price and the Kernel and its bands. This also means that we can now detect divergences between price and the NWO.
You can see the relationship between the two here:
You can think of this indicator as the kernel envelope version of a Bollinger Band %B. In ranging markets the bands are perfect for mean reversion trades, but in certain situations the break of one of the bands can signal the beggining of a strong trend and price will remain close to the bands for a long period and will only give small pullbacks. As with any indicator, confluence with price and other tools must be taken into account.
Main Features
As with @jdehorty 's Envelope, you can change the following settings:
Lookback Window.
Relative Weighting.
The initial bar for the regression.
ATR period for the bands.
Inner and Outer Multiples for the bands.
I also added the following:
A middle band around the Kernel to filter out false crossovers.
A Hull Moving Average to smoothen out the movements of the oscillator and give extra confirmation of turnover points.
Colors
Some special things to note regarding the coloring:
The zero line features a gradient that changes color every time the Kernel slope changes direction.
The Oscillator plot has a gradient coloring that gets stronger the closer it gets to each of the bands.
Every time the oscillator crosses over/under the outer bands the background will be highlighted.
Happy trading!
Historical AverageThis indicator calculates the sum of all past candles for each new candle.
For the second candle of the chart, the indicator shows the average of the first two candles. For the 10th candle, it's the average of the last ten candles.
Simple Moving Averages (SMAa) calculate the average of a specific timeframe (e.g. SMA200 for the last 200 candles). The historical moving average is an SMA 2 at the second candle, an SMA3 for the third candle, an SMA10 for the tenth, an SMA200 for the 200th candle etc.
Settings:
You can set the multiplier to move the Historical Moving Average along the price axis.
You can show two Historical Moving Averages with different multipliers.
You can add fibonacci multipliers to the Historical Moving Average.
This indicator works best on charts with a lot of historical data.
Recommended charts:
INDEX:BTCUSD
BLX
But you can use it e.g. on DJI or any other chart as well.
God's Little FingerThe "God's Little Finger" indicator uses several technical analysis tools to provide information about the direction of the market and generate buy/sell signals. These tools include a 200-period exponential moving average (EMA), Moving Average Convergence Divergence (MACD), Bollinger Bands, and the Relative Strength Index (RSI).
EMA is used to determine if prices are trending. MACD measures the speed and momentum of the trend. Bollinger Bands are used to determine if prices are staying within a range and to measure the strength of the trend. RSI shows overbought/oversold levels and can be used to determine if the trend will continue.
The indicator generates buy/sell signals based on market conditions. A buy signal is generated when the MACD line is below zero, the price is below the lower boundary of the Bollinger Bands, the price is above the 200-period EMA, and the RSI is in oversold levels (usually below 40). A sell signal is generated when the MACD line is above zero, the price is above the upper boundary of the Bollinger Bands, the price is below the 200-period EMA, and the RSI is in overbought levels (usually above 60).
However, it should be noted that indicators can be used to predict market conditions, but they do not guarantee results and any changes or unexpected events in the market can affect predictions. Therefore, they should always be used in conjunction with other analysis methods and risk management strategies.
Momentum Ratio Oscillator [Loxx]What is Momentum Ratio Oscillator?
The theory behind this indicator involves utilizing a sequence of exponential moving average (EMA) calculations to achieve a smoother value of momentum ratio, which compares the current value to the previous one. Although this results in an outcome similar to that of some pre-existing indicators (such as volume zone or price zone oscillators), the use of EMA for smoothing is what sets it apart. EMA produces a smooth step-like output when values undergo sudden changes, whereas the mathematics used for those other indicators are completely distinct. This is a concept by the beloved Mladen of FX forums.
To utilize this version of the indicator, you have the option of using either levels, middle, or signal crosses for signals. The indicator is range bound from 0 to 1.
What is an EMA?
EMA stands for Exponential Moving Average, which is a type of moving average that is commonly used in technical analysis to smooth out price data and identify trends.
In a simple moving average (SMA), each data point is given equal weight when calculating the average. For example, if you are calculating the 10-day SMA, you would add up the prices for the past 10 days and divide by 10 to get the average. In contrast, in an EMA, more weight is given to recent prices, while older prices are given less weight.
The formula for calculating an EMA involves using a smoothing factor that is multiplied by the difference between the current price and the previous EMA value, and then adding this to the previous EMA value. The smoothing factor is typically calculated based on the length of the EMA being used. For example, a 10-day EMA might use a smoothing factor of 2/(10+1) or 0.1818.
The result of using an EMA is that the line produced is more responsive to recent price changes than a simple moving average. This makes it useful for identifying short-term trends and potential trend reversals. However, it can also be more volatile and prone to whipsaws, so it is often used in combination with other indicators to confirm signals.
Overall, the EMA is a widely used and versatile tool in technical analysis, and its effectiveness depends on the specific context in which it is applied.
What is Momentum?
In technical analysis, momentum refers to the rate of change of an asset's price over a certain period of time. It is often used to identify trends and potential trend reversals in financial markets.
Momentum is calculated by subtracting the closing price of an asset X days ago from its current closing price, where X is the number of days being used for the calculation. The result is the momentum value for that particular day. A positive momentum value suggests that prices are increasing, while a negative value indicates that prices are decreasing.
Traders use momentum in a variety of ways. One common approach is to look for divergences between the momentum indicator and the price of the asset being traded. For example, if an asset's price is trending upwards but its momentum is trending downwards, this could be a sign of a potential trend reversal.
Another popular strategy is to use momentum to identify overbought and oversold conditions in the market. When an asset's price has been rising rapidly and its momentum is high, it may be considered overbought and due for a correction. Conversely, when an asset's price has been falling rapidly and its momentum is low, it may be considered oversold and due for a bounce back up.
Momentum is also often used in conjunction with other technical indicators, such as moving averages or Bollinger Bands, to confirm signals and improve the accuracy of trading decisions.
Overall, momentum is a useful tool for traders and investors to analyze price movements and identify potential trading opportunities. However, like all technical indicators, it should be used in conjunction with other forms of analysis and with consideration of the broader market context.
Extras
Alerts
Signals
Loxx's Expanded Source Types, see here for details
+ Bollinger Bands WidthHere is my rendition of Bollinger Bands Width. If you are unfamiliar, Bollinger Bands Width is a measure of the distance between the top and bottom bands of Bollinger Bands. Bollinger Bands themselves being a measure of market volatility, BB Width is a simpler, cleaner way of determining the amount of volatility in the market. Myself, I found the original, basic version of BB Width a bit too basic, and I thought that by adding to it it might make for an improvement for traders over the original.
Simple things that I've done are adding a signal line; adding a 'baseline' using Donchian Channels (such as that which is in my Average Candle Bodies Range indicator); adding bar and background coloring; and adding alerts for increasing volatility, and baseline and signal line crosses. It really ends up making for a much improved version of the basic indicator.
A note on how I created the baseline:
First, what do I mean by 'baseline?' I think of it as an area of the indicator where if the BB Width is below you will not want to enter into any trades, and if the BB Width is above then you are free to enter trades based on your system. It's basically a volatility measure of the volatility indicator. Waddah Attar Explosion is a popular indicator that implements something similar. The baseline is calculated thus: make a Donchian Channel of the BB Width, and then use the basis as the baseline while not plotting the actual highs and lows of the Donchian Channel. Now, the basis of a Donchian Channel is the average of the highs and the lows. If we did that here we would have a baseline much too high, however, by making the basis adjustable with a divisor input it no longer must be plotted in the center of the channel, but may be moved much lower (unless you set the divisor to 2, but you wouldn't do that). This divisor is essentially a sensitivity adjustment for the indicator. Of course you don't have to use the baseline. You could ignore it and only use the signal line, or just use the rising and falling of the BB Width by itself as your volatility measure.
I should make note: the main image above at default settings is an 8 period lookback (so, yes, that is quite fast), and the signal line is a Hull MA set to 13. The background and bar coloring are simply set to the rising and falling of the BB Width. Images below will show some different settings, but definitely play with it yourself to determine if it might be a good fit for your system.
Above, settings are background and bar coloring tuned to BB Width being above the baseline, and also requiring that the BB Width be rising. Background coloring only highlights increasing volatility or volatility above a certain threshold. Grey candles are because the BB Width is above the baseline but falling. We'll see an example without the requirement of BB Width rising, below.
Here, we see that background highlights and aqua candles are more prevalent because I've checked off the requirement that BB Width be rising. The idea is that BB Width is above the baseline therefor there is sufficient volatility to enter trades if our indicators give us the go-ahead.
This here is set to BB Width being above the signal line and also requiring a rising BB Width. Keep in mind the signal line is a Hull MA.
And this fourth and final image uses a volume-weighted MA as the signal line. Bar coloring is turned off, and instead the checkboxes for volatility advancing and declining are turned on under the signal line options. BB Width crosses up the signal line is advancing volatility, while falling below it is declining volatility. Background highlights are set to baseline and not requiring a rising BB Width. This way, with a quick glance you can see if the rising volatility is legitimate, i.e., is the cross up of the signal line coupled with it being above the baseline.
Please enjoy.
CPR with inside candle, Pivot Points and 4EMA The CPR trading strategy is a technical analysis approach that combines multiple indicators to determine potential price levels and trading opportunities. The strategy uses three main components: Inside Candles, Pivot Points, and the 4EMA.
Inside Candles: The Inside Candle pattern is a candlestick pattern where the current candle has a lower high and a higher low than the previous candle. This pattern can indicate a period of consolidation or indecision in the market and can signal a potential reversal or continuation of the trend.
Pivot Points: Pivot Points are technical indicators that use the previous day's price data to calculate key levels of support and resistance for the current trading day. These levels can act as potential areas of buying or selling pressure and can help traders identify potential entry and exit points.
4EMA: The 4EMA is a short-term Exponential Moving Average that tracks the average price of an asset over the previous four periods. This indicator is used to help identify short-term trends in the market and can signal potential buying or selling opportunities.
To apply the CPR strategy, traders first look for Inside Candles on their chart, indicating a period of consolidation or indecision in the market. Next, they identify the Pivot Points for the current trading day, which can act as potential areas of support or resistance. Finally, traders use the 4EMA to confirm the direction of the trend and potential entry or exit points.
For example, if an Inside Candle forms at a Pivot Point level and the 4EMA is indicating an uptrend, this could be a potential buying opportunity. Conversely, if an Inside Candle forms at a Pivot Point level and the 4EMA is indicating a downtrend, this could be a potential selling opportunity.
VWAP ROC Weighted AverageThe VWAP ROC Weighted Average indicator combines the concepts of Volume Weighted Average Price (VWAP) and Rate of Change (ROC) to create a unique and versatile tool for traders. The indicator calculates the average VWAP and average ROC over a specified period (default: 200 bars) and then creates a weighted average of these two values. This provides a single line that can help traders identify potential entry and exit points in a market.
How it can be used in trading:
Trend Confirmation: The VWAP_ROC_WA can be used to confirm the prevailing trend of an asset. If the weighted average line is moving upward, it indicates a bullish trend, while a downward-moving line suggests a bearish trend. Traders can use this information to enter trades in the direction of the trend to improve their odds of success.
Support and Resistance: The VWAP_ROC_WA line can act as dynamic support and resistance levels. When the price is above the weighted average line, it can act as a support level, and when the price is below the line, it can serve as a resistance level. Traders can use these levels to set stop-loss and take-profit orders or to identify potential entry and exit points.
Divergences: Traders can look for divergences between the price and the VWAP_ROC_WA line to identify potential reversals. For instance, if the price is making higher highs while the weighted average line is making lower highs, it may signal a bearish divergence, indicating a potential reversal to the downside. Conversely, if the price is making lower lows while the weighted average line is making higher lows, it may signal a bullish divergence, indicating a potential reversal to the upside.
Crossovers: Traders can monitor crossovers between the price and the VWAP_ROC_WA line. A bullish crossover occurs when the price crosses above the weighted average line, suggesting a potential long entry point. A bearish crossover occurs when the price crosses below the line, suggesting a potential short entry point.
CoffeeShopCrypto 3pl MAThe CoffeeShopCrypto 3pl MA indicator is a technical analysis tool that uses three different moving averages to identify trends in the price of an asset. The three moving averages have lengths of 12, 26, and 50. If these numbers sound familiar its because they are based off the standard of the MACD indicator, and can be either simple moving averages (SMA) or exponential moving averages (EMA), depending on user preference.
The following is plotted on the chart
The fast EMA/SMA (based on the 12-period length) in yellow.
The mid EMA/SMA (based on the 26-period length) in gray.
The slow EMA/SMA (based on the 50-period length) in either green or red, depending on whether the current close price is above or below the Overall Trend MA.
In addition to the moving averages, the indicator also calculates the MACD (Moving Average Convergence Divergence), and uses it to color the bars based on the momentum of the asset.
The MACD is calculated using two user-defined lengths (fast and slow), as well as a user-defined smoothing length for the signal line. The oscillator and signal line can be either SMA or EMA, and the colors of the MACD bars are based on whether the histogram is growing or falling, and whether it is above or below the zero line.
Overall, this indicator provides traders with a comprehensive tool for understanding the trend of an asset, as well as the momentum behind that trend. The moving averages provide a clear visual representation of the trend, while the MACD bars give insight into the strength of that trend and potential shifts in momentum.
---------------LONG ENTRY----------------
MA1 above MA2 and Overall trend = Green
IF RSI is above its midline you are confirmed for a long entry
-----------Short Entry--------------
MA1 below MA2 and Overall trend = Red
IF RSI is below its midline you are confirmed for a short entry
Custom Weighted Moving Average with SMA, EMA, and VWAPThe Custom Weighted Moving Average with SMA, EMA, and VWAP (CWMA-SMA-EMA-VWAP) is a versatile and comprehensive trading indicator that combines the strength of Simple Moving Averages (SMAs), Exponential Moving Averages (EMAs), and the Volume Weighted Average Price (VWAP) to create a custom weighted moving average. This indicator is designed to provide a more holistic view of the market and enhance trading decisions by considering multiple moving average types and their respective timeframes. The indicator also highlights intersections between the custom weighted moving average and the individual SMA, EMA, and VWAP lines by changing their color to yellow, which can be used as potential entry or exit signals.
How to Use:
The CWMA-SMA-EMA-VWAP indicator can be used in various ways to make informed trading decisions. Here are some possible strategies:
Trend Identification: The custom weighted moving average (CWMA) can act as a dynamic support and resistance level, smoothing out the price movements and revealing the underlying trend. When the price is above the CWMA, it may indicate an uptrend, and when it's below, a downtrend. Traders can use this information to align their trades with the prevailing market trend.
Crossovers: The intersections between the CWMA and individual SMA, EMA, and VWAP lines are highlighted in yellow, which can serve as potential entry or exit signals. For instance, when the price or one of the moving averages crosses above the CWMA, it may signal a bullish trend, and traders could consider entering a long position. Conversely, when the price or one of the moving averages crosses below the CWMA, it may signal a bearish trend, and traders could consider entering a short position.
Confirmation of Signals: The CWMA-SMA-EMA-VWAP indicator can be used in conjunction with other technical analysis tools to confirm or strengthen trading signals. For example, traders may use oscillators like the RSI or MACD to confirm overbought or oversold conditions and identify potential reversals in tandem with the CWMA-SMA-EMA-VWAP crossovers.
Stop Loss and Take Profit Levels: The CWMA, SMAs, EMAs, and VWAP lines can serve as dynamic support and resistance levels, helping traders set stop loss and take profit targets. For example, a trader might set a stop loss below the CWMA during an uptrend or above the CWMA during a downtrend. Similarly, they might set take profit targets near significant SMA or EMA levels, anticipating that the price may reverse or consolidate at these points.
It's important to note that the CWMA-SMA-EMA-VWAP indicator, like any other technical analysis tool, should not be used in isolation. Combining it with other technical analysis methods, proper risk management, and a well-defined trading plan will increase the chances of success in the market. Additionally, traders should backtest and validate any strategy using historical data before applying it to real-world trading.
Weighted Moving Average Indicator (WMAI) with Std DevThe updated Weighted Moving Average Indicator with Standard Deviation (WMAI_SD) now includes the central line, which is the weighted moving average, along with 3 lines above and 3 lines below the central line that represent different levels of standard deviation. This combination can be used to identify trends, potential entry and exit points, support and resistance levels, and to gauge the volatility of the asset. Here's how to use this updated indicator:
Identifying trends: The central line (Weighted Moving Average) can be used to identify trends. When the line is moving upwards, it signals a bullish trend, and when it's moving downwards, it signals a bearish trend. A flat central line suggests a sideways or consolidating market.
Potential entry and exit points: You can use the crossing of the price with the central line to identify potential entry and exit points for trades. When the price crosses above the central line, it might be considered a buy signal. Conversely, when the price crosses below the central line, it might be considered a sell signal. Keep in mind that the WMAI_SD is not foolproof and should be used in conjunction with other technical analysis tools and techniques to increase the chances of successful trades.
Support and resistance levels: The central line, along with the standard deviation lines, can act as dynamic support and resistance levels. When the price is above the central line, the line can act as support. Conversely, when the price is below the central line, it can act as resistance. The standard deviation lines can also serve as additional support and resistance levels, with the lines closer to the central line being less significant than the ones further away.
Gauging volatility: The distance between the standard deviation lines can give you an idea of the asset's volatility. When the distance between the lines is wide, it indicates higher volatility, while a narrower distance indicates lower volatility. An increase in volatility could signal a strong trend or a potential trend reversal, whereas low volatility might suggest a lack of conviction in the current trend.
Confirming signals from other indicators: You can use the WMAI_SD to confirm signals from other technical analysis tools. For instance, if you use a momentum oscillator like the Relative Strength Index (RSI) to identify overbought or oversold conditions, you can look for confluence with the WMAI_SD central line and standard deviation lines.
Weighted Moving Average Indicator (WMAI) 50/100/200 SMA + 21 EMAThe Weighted Moving Average Indicator (WMAI) is a custom technical analysis tool that combines the information from three Simple Moving Averages (SMA) and one Exponential Moving Average (EMA) to create a single line on the chart. This line can be used to identify trends, potential entry and exit points, and overall market direction. Here's how to use this indicator:
Identifying trends: When the WMAI line is moving upwards, it signals a bullish trend, meaning that the asset's price is generally increasing. Conversely, when the WMAI line is moving downwards, it signals a bearish trend, indicating that the asset's price is generally decreasing. A flat WMAI line suggests a sideways or consolidating market.
Potential entry and exit points: You can use the WMAI line in combination with the asset's price or other technical indicators to identify potential entry and exit points for trades. For example, when the price crosses above the WMAI line, it might be considered a buy signal, as it suggests a potential upward trend. Conversely, when the price crosses below the WMAI line, it might be considered a sell signal, indicating a potential downward trend. Keep in mind that, like any other indicator, WMAI is not foolproof and should be used in conjunction with other technical analysis tools and techniques to increase the chances of successful trades.
Support and resistance levels: The WMAI line can act as a dynamic support and resistance level. When the price is above the WMAI line, the line can act as a support level, making it less likely for the price to drop below the line. Conversely, when the price is below the WMAI line, it can act as a resistance level, making it harder for the price to rise above the line.
Confirming signals from other indicators: You can use the WMAI line to confirm signals from other technical analysis tools. For instance, if you use a momentum oscillator like the Relative Strength Index (RSI) to identify overbought or oversold conditions, you can look for confluence with the WMAI line. If the WMAI line is also pointing in the same direction as the RSI signal, it can add confidence to the trade.
Variety MA Cluster Filter Crosses [Loxx]What is a Cluster Filter?
One of the approaches to determining a useful signal (trend) in stream data. Small filtering (smoothing) tests applied to market quotes demonstrate the potential for creating non-lagging digital filters (indicators) that are not redrawn on the last bars.
Standard Approach
This approach is based on classical time series smoothing methods. There are lots of articles devoted to this subject both on this and other websites. The results are also classical:
1. The changes in trends are displayed with latency;
2. Better indicator (digital filter) response achieved at the expense of smoothing quality decrease;
3. Attempts to implement non-lagging indicators lead to redrawing on the last samples (bars).
And whereas traders have learned to cope with these things using persistence of economic processes and other tricks, this would be unacceptable in evaluating real-time experimental data, e.g. when testing aerostructures.
The Main Problem
It is a known fact that the majority of trading systems stop performing with the course of time, and that the indicators are only indicative over certain intervals. This can easily be explained: market quotes are not stationary. The definition of a stationary process is available in Wikipedia:
A stationary process is a stochastic process whose joint probability distribution does not change when shifted in time.
Judging by this definition, methods of analysis of stationary time series are not applicable in technical analysis. And this is understandable. A skillful market-maker entering the market will mess up all the calculations we may have made prior to that with regard to parameters of a known series of market quotes.
Even though this seems obvious, a lot of indicators are based on the theory of stationary time series analysis. Examples of such indicators are moving averages and their modifications. However, there are some attempts to create adaptive indicators. They are supposed to take into account non-stationarity of market quotes to some extent, yet they do not seem to work wonders. The attempts to "punish" the market-maker using the currently known methods of analysis of non-stationary series (wavelets, empirical modes and others) are not successful either. It looks like a certain key factor is constantly being ignored or unidentified.
The main reason for this is that the methods used are not designed for working with stream data. All (or almost all) of them were developed for analysis of the already known or, speaking in terms of technical analysis, historical data. These methods are convenient, e.g., in geophysics: you feel the earthquake, get a seismogram and then analyze it for few months. In other words, these methods are appropriate where uncertainties arising at the ends of a time series in the course of filtering affect the end result.
When analyzing experimental stream data or market quotes, we are focused on the most recent data received, rather than history. These are data that cannot be dealt with using classical algorithms.
Cluster Filter
Cluster filter is a set of digital filters approximating the initial sequence. Cluster filters should not be confused with cluster indicators.
Cluster filters are convenient when analyzing non-stationary time series in real time, in other words, stream data. It means that these filters are of principal interest not for smoothing the already known time series values, but for getting the most probable smoothed values of the new data received in real time.
Unlike various decomposition methods or simply filters of desired frequency, cluster filters create a composition or a fan of probable values of initial series which are further analyzed for approximation of the initial sequence. The input sequence acts more as a reference than the target of the analysis. The main analysis concerns values calculated by a set of filters after processing the data received.
In the general case, every filter included in the cluster has its own individual characteristics and is not related to others in any way. These filters are sometimes customized for the analysis of a stationary time series of their own which describes individual properties of the initial non-stationary time series. In the simplest case, if the initial non-stationary series changes its parameters, the filters "switch" over. Thus, a cluster filter tracks real time changes in characteristics.
Cluster Filter Design Procedure
Any cluster filter can be designed in three steps:
1. The first step is usually the most difficult one but this is where probabilistic models of stream data received are formed. The number of these models can be arbitrary large. They are not always related to physical processes that affect the approximable data. The more precisely models describe the approximable sequence, the higher the probability to get a non-lagging cluster filter.
2. At the second step, one or more digital filters are created for each model. The most general condition for joining filters together in a cluster is that they belong to the models describing the approximable sequence.
3. So, we can have one or more filters in a cluster. Consequently, with each new sample we have the sample value and one or more filter values. Thus, with each sample we have a vector or artificial noise made up of several (minimum two) values. All we need to do now is to select the most appropriate value.
An Example of a Simple Cluster Filter
For illustration, we will implement a simple cluster filter corresponding to the above diagram, using market quotes as input sequence. You can simply use closing prices of any time frame.
1. Model description. We will proceed on the assumption that:
The aproximate sequence is non-stationary, i.e. its characteristics tend to change with the course of time.
The closing price of a bar is not the actual bar price. In other words, the registered closing price of a bar is one of the noise movements, like other price movements on that bar.
The actual price or the actual value of the approximable sequence is between the closing price of the current bar and the closing price of the previous bar.
The approximable sequence tends to maintain its direction. That is, if it was growing on the previous bar, it will tend to keep on growing on the current bar.
2. Selecting digital filters. For the sake of simplicity, we take two filters:
The first filter will be a variety filter calculated based on the last closing prices using the slow period. I believe this fits well in the third assumption we specified for our model.
Since we have a non-stationary filter, we will try to also use an additional filter that will hopefully facilitate to identify changes in characteristics of the time series. I've chosen a variety filter using the fast period.
3. Selecting the appropriate value for the cluster filter.
So, with each new sample we will have the sample value (closing price), as well as the value of MA and fast filter. The closing price will be ignored according to the second assumption specified for our model. Further, we select the МА or ЕМА value based on the last assumption, i.e. maintaining trend direction:
For an uptrend, i.e. CF(i-1)>CF(i-2), we select one of the following four variants:
if CF(i-1)fastfilter(i), then CF(i)=slowfilter(i);
if CF(i-1)>slowfilter(i) and CF(i-1)slowfilter(i) and CF(i-1)>fastfilter(i), then CF(i)=MAX(slowfilter(i),fastfilter(i)).
For a downtrend, i.e. CF(i-1)slowfilter(i) and CF(i-1)>fastfilter(i), then CF(i)=MAX(slowfilter(i),fastfilter(i));
if CF(i-1)>slowfilter(i) and CF(i-1)fastfilter(i), then CF(i)=fastfilter(i);
if CF(i-1)<slowfilter(i) and CF(i-1)<fastfilter(i), then CF(i)=MIN(slowfilter(i),fastfilter(i)).
Where:
CF(i) – value of the cluster filter on the current bar;
CF(i-1) and CF(i-2) – values of the cluster filter on the previous bars;
slowfilter(i) – value of the slow filter
fastfilter(i) – value of the fast filter
MIN – the minimum value;
MAX – the maximum value;
What is Variety MA Cluster Filter Crosses?
For this indicator we calculate a fast and slow filter of the same filter and then we run a cluster filter between the fast and slow filter outputs to detect areas of chop/noise. The output is the uptrend is denoted by green color, downtrend by red color, and chop/noise/no-trade zone by white color. As a trader, you'll likely want to avoid trading during areas of chop/noise so you'll want to avoid trading when the color turns white.
Extras
Bar coloring
Alerts
Loxx's Expanded Source Types, see here:
Loxx's Moving Averages, see here:
An example of filtered chop, see the yellow circles. The cluster filter identifies chop zones so you don't get stuck in a sideways market.
Moving Average Resting Point [theEccentricTrader]█ OVERVIEW
This indicator uses peak and trough prices to calculate the moving average resting point and plots it as a line on the chart. The lookback length is variable and the indicator can plot up to three lines with different lookback lengths and colors.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. As can be seen in the example above, the first swing high or swing low will set the course for the sequence of wave cycles that follow; a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Wave Length
Wave length is here measured in terms of bar distance between the start and end of a wave cycle. For example, if the current wave cycle ends on a swing low the wave length will be the difference in bars between the current swing low and current swing high. In such a case, if the current swing low completes on candle 100 and the current swing high completed on candle 95, we would simply subtract 95 from 100 to give us a wave length of 5 bars.
Average wave length is here measured in terms of total bars as a proportion as total waves. The average wavelength is calculated by dividing the total candles by the total wave cycles.
Wave Height
Wave height is here measured in terms of current range. For example, if the current peak price is 100 and the current trough price is 80, the wave height will be 20.
Amplitude
Amplitude is here measured in terms of current range divided by two. For example if the current peak price is 100 and the current trough price is 80, the amplitude would be calculated by subtracting 80 from 100 and dividing the answer by 2 to give us an amplitude of 10.
Resting Point
The resting point is here calculated by subtracting the current trough price from the current peak price and adding the difference to the current trough price to output the price in the middle of the two prices. Essentially it is the current trough price plus the amplitude. For example, if the current peak price is 100 and the current trough price is 80, the resting point 90.
The moving average resting point is here calculated by subtracting the moving average trough price from the moving average peak price, dividing the answer by two and adding the difference to the moving average trough price.
Frequency
Frequency is here measured in terms of wave cycles per second (Hertz). For example, if the total wave cycle count is 10 and the amount of time it has taken to complete these 10 cycles is 1-year (31,536,000 seconds), the frequency would be calculated by dividing 10 by 31,536,000 to give us a frequency of 0.00000032 Hz.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
█ FEATURES
Inputs
Show MARP 1
Show MARP 2
Show MARP 3
MARP 1 Length
MARP 2 Length
MARP 3 Length
MARP 1 Color
MARP 2 Color
MARP 3 Color
█ HOW TO USE
This indicator can be used like any other moving average indicator to analyse trend direction and momentum, identify potential support and resistance levels, or for filtering trading strategies and developing new ones.
Know Sure Thing + RibbonFrom now on this will be the main indicator I will be using.
The mathematical foundation of KST is elegant and trustworthy. I took the time to share this beautiful (in my opinion) indicator, because you will probably be seeing it in my future ideas.
I am not a trader, this indicator was made to analyze mainly long-term charts, and trend-continuation/change analysis.
The purpose of this indicator is not to give entry/exit points. However, the 9-period EMA (tightest EMA) can serve as an alternative to the classic "9-period MA signal line".
Tread lightly, for this is hallowed ground.
-Father Grigori
ADD 2This is a modification to the original ADD script by Tom1trader
I added the option to choose the timeframe, moving average type and length.
Note from the original script:
"This is the NYSE Advancers - decliners which the SPX pretty much follows. You can chart it like any index (ADD -NYSE $ADV MINUS $DECL) but I find it more useful in a separate panel with colors for direction.
The level gives an idea of days move (example: plus or minus 500 is not much movement through the session) but I follow the direction as when more stocks advance (green) or decline (red) the index tends to track it pretty closely.
On SPX , SPY and correlates - very useful for intra-day trading (Scalping or 0DTE option trades) but not for higher time frames at all. If you chart the ADD in a chart and compare 5 minute to daily you will see what I mean."
Triple RSI Indicator with ToggleThis script combines three relative strength index (RSI) indicators with different periods, and allows the user to toggle between them to generate overbought and oversold signals. The indicator is named "Triple RSI Indicator with Toggle" and has the short title "TRSI-T."
The input parameters for the RSI periods are set by the user and include a short RSI with a period of 5, a main RSI with a period of 14, and a long RSI with a period of 28. The overbought and oversold levels for each RSI can also be set by the user.
The script plots the three RSI lines on the chart and calculates a bar color based on the enabled RSI values. If all three RSI values are overbought, the bar color is set to fuchsia, if all three RSI values are oversold, the bar color is set to aqua, and if neither of these conditions is met, the bar color is set to not available.
The script also includes a fast RSI and an RSI exponential moving average (EMA) with adjustable periods. The RSI fast line is plotted along with the RSI EMA line, and a cloud fill is generated between the two lines. The fill color is based on whether the fast RSI line is above or below the RSI EMA line, with a blue color used for long signals and a pink color used for short signals.
This indicator can be used as part of a trading strategy in a number of ways. Here are a few examples:
Overbought and Oversold Signals: When the bar color of the indicator is fuchsia, it indicates that all three RSIs are overbought, and when the bar color is aqua, it indicates that all three RSIs are oversold. These signals can be used to enter a trade in the opposite direction, anticipating a reversal in price.
RSI Divergence: Traders can also look for divergences between the price and the RSI values. For example, if the price is making higher highs but the RSI values are making lower highs, it could indicate that the price trend is weakening and a reversal may be imminent. Conversely, if the price is making lower lows but the RSI values are making higher lows, it could indicate that the price trend is about to reverse.
RSI Cloud Signals: The cloud fill generated between the fast RSI and RSI EMA lines can be used to generate trading signals. When the fast RSI line is above the RSI EMA line and the fill color is blue, it can be a signal to go long. When the fast RSI line is below the RSI EMA line and the fill color is pink, it can be a signal to go short.
If anybody has some interesting thoughts on how to improve it, let me know!!
Oliver Velez IndicatorOliver Velez is a well-known trader and educator who has developed multiple trading strategies. One of them is the 20-200sma strategy, which is a basic moving average crossover strategy. The strategy involves using two simple moving averages (SMAs) - a short-term SMA with a period of 20 and a long-term SMA with a period of 200 - on a 2-minute timeframe chart.
When the short-term SMA crosses above the long-term SMA, it signals a potential bullish trend and traders may look for opportunities to enter a long position. Conversely, when the short-term SMA crosses below the long-term SMA, it signals a potential bearish trend and traders may look for opportunities to enter a short position.
Traders using this strategy may also look for additional confirmations, such as price action signals or other technical indicators, before entering or exiting a trade. It is important to note that no trading strategy can guarantee profits, and traders should always use risk management techniques to limit potential losses.
This script is an implementation of the 2 SMA's (can also choose other types of MA's), with Elephant Bar Indicator (EBI) and the Tail Bars Indicator in TradingView.
The Elephant Bar Indicator is a technical indicator used in trading to identify potential trend reversals in the market. It is named after the large size of the bullish or bearish candlestick that it represents. The Tail Bars Indicator is a pattern recognition technique that identifies candlestick patterns with long tails or wicks.
The script starts by defining the input parameters for both indicators. For the Elephant Bar Indicator, the user inputs the lookback period and the size multiplier. For the Tail Bars Indicator, the user inputs the tail ratio and opposite wick ratio.
Next, the script calculates the moving averages of the closing price over the defined short and long periods using the Moving Average function. The script then calculates the average candle size and volume over the lookback period.
The script then identifies the Elephant Bars and Tail Bars using the input parameters and additional conditions. For Elephant Bars, the script identifies bullish and bearish bars that meet certain criteria, such as a size greater than the average candle size and volume greater than the average volume.
For Tail Bars, the script identifies bullish and bearish bars that have long tails or wicks and meet certain criteria such as opposite wick size less than or equal to the tail size multiplied by the input opposite wick ratio.
Finally, the script plots the Elephant Bar and Tail Bar signals on the chart using different colors and shapes. The script also plots the moving averages and Keltner Channels to help traders identify potential trend reversals.
It is still under development, so please, if someone has ideas to add, more than welcome
Momentum Reversal [AngelAlgo]The Momentum Reversal Indicator is a technical analysis tool used to identify potential reversals and trends in financial markets. It does this by comparing the momentum of a market to its trend. The momentum is calculated by measuring the change in price over a specified time interval set by the "Period" input. The trend is then determined as the simple moving average of the momentum, with the length of the moving average determined by the "Trend length" input. When the momentum deviates significantly from the trend, it is considered a potential reversal signal. The user can choose to receive signals based on either "Contrarian" or "Trend" signals type, and also has the option to smooth the signals using the Hull Moving Average. The indicator is plotted as a histogram with trading signals indicated by triangle shapes (up for buys, down for sells). The histogram is also accompanied by a smoothed line representation of the indicator and dynamic threshold levels.
The color of the histogram bars is green if the momentum is positive, red if it's negative. The histogram can be smoothed using the Hull Moving Average (HMA) if the "Smoothed signals" input is set to true.
The indicator also plots the threshold levels, which are dynamically calculated as the simple moving average (SMA) of the absolute value of the histogram. The threshold levels are plotted as circles on the chart.
The signals are plotted as arrows on the chart, either triangle-up for buy signals, or triangle-down for sell signals. If "Contrarian" signals are selected, a triangle-up will appear when the histogram crosses below the lower threshold, and a triangle-down will appear when it crosses above the upper threshold. If "Trend" signals are selected, a triangle-up will appear when the histogram crosses above the upper threshold, and a triangle-down will appear when it crosses below the lower threshold. Trend signals work for trending markets, Contrarian signals are good for ranging markets.
SETTINGS
Period: This input allows you to set the period for the momentum calculation. The default value is 14.
Trend length: This input allows you to set the length of the trend-following moving average. The default value is 50.
Signals type : This input allows you to choose the type of signals you want to receive. You can choose between "Contrarian" and "Trend" signals. The default value is "Contrarian".
Smoothed signals: This input allows you to choose between the raw or smoothed signals. If set to true, the signals will be based on the smoothed histogram line, otherwise, they will be based on the raw histogram. The default value is true.
MarketronShows you how the asset on the chart is trending versus the market. You can customise the market that it uses, and there are some common markets programmed in as options.
Displays moving averages and a simple red/green bias.
You could do this yourself by typing, e.g., ADAUSDT/TOTAL into the asset box in TradingView and adding some EMAs manually and then interpreting them by eye. There's no hidden technology in this indicator. It just makes it a lot easier.
You can choose various bias options.
I'm not sure if it will work at resolutions lower than one day, depending on the level of your TradingView plan.
These are all the user-configurable settings and what they do.
Market (Auto) – Choose from various preselected markets.
Market Ticker Manual Override – You can type in the ticker for your market if it's not in the list. If you do, it overrides the Auto list.
Show Classic EMAs – Show customisable Exponential Moving Averages.
Bias Mode – Derive the red/green bias from whether price is above/below the Classic EMAs, or from a custom EMA function, or both.
Show Bias Background – Colour the background, or not, with the directional bias.
EMA 1 Length (smallest) – The length for the smallest EMA.
EMA 2 Length – Length for the second EMA.
EMA 3 Length – Length for the third EMA.
RedK DIY ZLMA: Customizable Zero-Lag MA (Educational / Utility)This script is more of an educational / utility piece rather than a fully-fledged indicator - It provides an easy way to customize and produce a zero-lag Moving average that can then be used in various scenarios
What is DIY_ZLMA?
------------------------
The DIY ZLMA is for fans and enthusiasts of researching Moving Averages (like me) - the script enables the user to play around with one of the common approaches used to reduce lag in moving averages - which was explained in this old post below
Suggested uses of the DIY_ZLMA
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* The Zero-lag approach here applies 3 moving average passes to a source data series - I'll refer to these 3 passes as Base MA Pass , De-lagging Pass, and Smoothing Pass - these "passes" can be customized from the indicator settings in terms of MA Length and type. The first pass allows the choice of a "source", and the second pass allows additional fine tuning by playing around with the magnification factor. The 3rd pass (smoothing) is optional and can be skipped altogether when needed. (as noted in the script, HMA and TEMA, which are very common low-lag MA's use slightly different approach in the calculation than the one used here .. so we can't get an equivalent of either of these MA's with the customization of DIY_ZLMA parameters)
* After the user experiments with the various settings for the 3 passes, and finds a "preferred combination", the script not only plots the resulting My_ZLMA - it also produces the "1-line Pine script formula" that the user can then use in any other script, maybe to smoothen some data series, or to combine with other types of moving averages to create multi-MA cross-over trading signals... and so on.
* The DIY_ZLMA can also be added to another indicator as a signal line using the Indicator-on-Indicator feature of TradingView (review this post for step-by-step -->
)
* the script also showcases couple of recent (and very neat) Pine features: the use of User-defined Types (UDT) and User-defined Methods - which are awesome and a lot of fun to work with :)
Since this is more of a utility piece, I added as many comments as possible to the script to explain the way it works - so it's more valuable if someone finds it by searching the "Add Indicator" feature in TradingView charts
Please feel free to play around with this new toy :) and share comments and feedback below if you find this useful. I truly hope you do.
Spectral Gating (SG)The Spectral Gating (SG) Indicator is a technical analysis tool inspired by music production techniques. It aims to help traders reduce noise in their charts by focusing on the significant frequency components of the data, providing a clearer view of market trends.
By incorporating complex number operations and Fast Fourier Transform (FFT) algorithms, the SG Indicator efficiently processes market data. The indicator transforms input data into the frequency domain and applies a threshold to the power spectrum, filtering out noise and retaining only the frequency components that exceed the threshold.
Key aspects of the Spectral Gating Indicator include:
Adjustable Window Size: Customize the window size (ranging from 2 to 6) to control the amount of data considered during the analysis, giving you the flexibility to adapt the indicator to your trading strategy.
Complex Number Arithmetic: The indicator uses complex number addition, subtraction, and multiplication, as well as radius calculations for accurate data processing.
Iterative FFT and IFFT: The SG Indicator features iterative FFT and Inverse Fast Fourier Transform (IFFT) algorithms for rapid data analysis. The FFT algorithm converts input data into the frequency domain, while the IFFT algorithm restores the filtered data back to the time domain.
Spectral Gating: At the heart of the indicator, the spectral gating function applies a threshold to the power spectrum, suppressing frequency components below the threshold. This process helps to enhance the clarity of the data by reducing noise and focusing on the more significant frequency components.
Visualization: The indicator plots the filtered data on the chart with a simple blue line, providing a clean and easily interpretable representation of the results.
Although the Spectral Gating Indicator may not be a one-size-fits-all solution for all trading scenarios, it serves as a valuable tool for traders looking to reduce noise and concentrate on relevant market trends. By incorporating this indicator into your analysis toolkit, you can potentially make more informed trading decisions.
