Parabolic SAR of KAMA attempts to reduce noise and volatility from regular Parabolic SAR in order to derive more accurate trends. In addition, and to further reduce noise and enhance trend identification, PSAR of KAMA includes two calculations of efficiency ratio: 1) price change adjusted for the daily volatility; or, 2) Jurik Fractal Dimension Adaptive...
A trend indicator FiboBars Extended , the main purpose of which is to confirm the trend and cut off market noise. In his logic, he uses the Fibonacci sequence.
Two settings are used to account for noise suppression accuracy:
Period - number of calculation bars
Level - Fibonacci number selection
I've seen several youtubers using 2 RSI's on top of one another to filter trades for their strategies. I figured I would just code it up as an all-in-one indicator for people who have the basic package. This way they have an extra slot for another indicator if they need one and also for convenience.
Longs only when RSI 1 is above RSI 2 and shorts only when...
This indicator builds upon the previously posted Nadaraya-Watson Estimator. Here we have created an envelope indicator based on kernel smoothing with integrated alerts from crosses between the price and envelope extremities. Unlike the Nadaraya-Watson Estimator, this indicator follows a contrarian methodology.
For more information on the Nadaraya-Watson Estimator...
OVERVIEW
The Average True Range Moving Average (ATRMA) is a technical indicator that gauges the amount of volatility currently present in the market, relative to the historical average volatility that was present before. It adds a moving average to the Average True Range (ATR) indicator.
This indicator is extremely similar to the VOXI indicator, but instead of...
The following tool smooths the price data using the Nadaraya-Watson estimator, a simple Kernel regression method. We make use of the Gaussian kernel as a weighting function.
Kernel smoothing allows the estimating of underlying trends in the price and has found certain applications in stock prices pattern detection.
Note that results are subject to repainting,...
This study is an experiment utilizing the Ehlers Gaussian Filter technique combined with lag reduction techniques and true range to analyze trend activity.
Gaussian filters, as Ehlers explains it, are simply exponential moving averages applied multiple times.
First, beta and alpha are calculated based on the sampling period and number of poles specified. The...
Bollinger Bands Breakout Strategy is the strategy version of Bollinger Bands Filter study version, which can be found under my scripts page. The strategy goes long when price closes above the upper band and goes short signal when price closes below the lower band.
Bollinger Bands is a classic indicator that uses a simple moving average of 20 periods, along...
This is a potential solution to dealing with the inherent lag in most filters especially with instruments such as BTC and the effects of long periods of low volatility followed by massive volatility spikes as well as whipsaws/barts etc.
We can try and solve these issues in a number of ways, adaptive lengths, dynamic weighting etc. This filter uses a non linear...
This is an experimental study designed to filter out minor price action for a clearer view of trends.
Inspired by the QQE's volatility filter, this filter applies the process directly to price rather than to a smoothed RSI.
First, a smooth average price range is calculated for the basis of the filter and multiplied by a specified amount.
Next, the filter is...
This is a simple script designed to help filter out bad trades. LSMA is a trend king and by using the 21,200 and 1000 length lines traders can get a clear view of where price action is travelling. This indicator is the perfect companion to the LSMA Wave Rider indicator. Once a pullback is discovered (price action crosses under blue or white line) Traders can use...
Price curves consist of much noise and little signal. For separating the latter from the former, John Ehlers proposed in the Stocks&Commodities May 2021 issue an unusual approach: Treat the price curve like a radio wave. Apply AM and FM demodulating technology for separating trade signals from the underlying noise.
reference: financial-hacker.com
Check the settings to see how the filters work. I added alerts and a feature that shows the divergences that have been filtered, but as faded "ghost" divergences. Spooooky. This is useful for tuning the script to a particular market. All credit to RicardoSantos for the original.
The new array feature is extremely powerful, as it will allow pinescript users to do more complex things, or compute existing calculations more efficiently, it will also be possible to shine some light to some already existing functions, one of them being percentile_nearest_rank .
We have been working on this new feature with our pal alexgrover, and made this...
Introduction
There is a lot of indicators similar to this one, however i think this one don't share the same calculation method and this is why i share it. This indicator aim to forecast price direction using an exponential filter architecture using highest and lowest information for the estimation of a smoothing variable. This filter is similar to the average...
What's new?
v2 has added multi timeframe support.
Blatantly stole Chris Moody's code for multi timeframe, because why re-invent the wheel? Thanks Chris ;P
BUT -- modified the coloring to work correctly with higher timeframes, just another Lark hack, so it's a give and take :)
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The Laguerre Average (filter) was discovered by John...
- Hurst Exponent Signal Filter -
The Hurst Exponent Signal Filter is meant to be used with an external signal source, this can be any indicator with a signal plot output (-1 Sell / 1 Buy)
It filters out a lot of noisy signals and improves the performance of many indicators.
- Example: How to Use -
1. Add a trend Indicator like Trend Index MTF to your...
The Triangle Moving Average is the last of custom scripts converting Ehlers Window Indicators to Moving Averages. As you can see this is actually very similar to the Hamming Moving Average and the Hann Moving Average so I would recommend to test this one out with different settings and see what works best for you. As far as the formula calculation, it is a...
![EURUSD: Parabolic SAR of KAMA [Loxx]](https://s3.tradingview.com/s/sN2E9kBG_mid.png "Parabolic SAR of KAMA [Loxx]")
![TSLA: Nadaraya-Watson Envelope [LUX]](https://s3.tradingview.com/i/Iko0E2kL_mid.png "Nadaraya-Watson Envelope [LUX]")
![BTCUSD: Nadaraya-Watson Estimator [LUX]](https://s3.tradingview.com/a/amRCTgFw_mid.png "Nadaraya-Watson Estimator [LUX]")
![BTCUSD: Gaussian Channel [DW]](https://s3.tradingview.com/w/WpVY7GKW_mid.png "Gaussian Channel [DW]")
![EURUSD: Range Filter [DW]](https://s3.tradingview.com/l/lut7sBgG_mid.png "Range Filter [DW]")
![TSLA: Percentile Nearest Rank Using Arrays [LUX]](https://s3.tradingview.com/y/YDpNmgQV_mid.png "Percentile Nearest Rank Using Arrays [LUX]")
![DEFIPERP: [NLX-L2] Hurst Exponent Signal Filter](https://s3.tradingview.com/5/5WNVqqxJ_mid.png "[NLX-L2] Hurst Exponent Signal Filter")
![AAPL: Ehlers Triangle Moving Average [CC]](https://s3.tradingview.com/d/DG9SIozf_mid.png "Ehlers Triangle Moving Average [CC]")
