The "Smooth ROC & Stochastic with Kalman Filter" indicator is a trend following tool designed to identify trends in the price movement. It combines the Rate of Change (ROC) and Stochastic indicators into a single oscillator, the combination of ROC and Stochastic indicators aims to offer complementary information: ROC measures the speed of price change, while...

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This is a simplified version of Kalman RSI by onegreencandle. Simplifications: It shows the indicator for a single configurable length with a default of 14. It does not color by region. It allows selecting the source, with a default of close . The version by onegreencandle uses ohlc4 instead. Note that both versions also use high and low . It...

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Introduction Heyo guys, I made a new (repainting) indicator called Local Model Kalman Market Mode. I created it, because I wanted a reliable market mode filter for a potential mean-reversion strategy (e. g. BB Scalping). On the screenshot you can see an example of how to use it in a BB strategy. E.g. you would enter long when you have bullish divergence, price...

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A simple form of recursive filtering using an adjustable gain and a memory length. The filter predicts the next sample based on the previous values and the calculated error.

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This is an upgrade to the HMA-Kahlman Trend & Trendlines script (). This version gives more flexibility because you can play around with 2 parameters to Kalman function (Sharpness and K (aka. step size)).

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Frequently asked question is to explain how Gain parameter works in kalman funtion. This script serves as a visual representation of Gain parameter of Kalman function used in HMA-Kalman & Trendlines script. (The function creator's name was misspeled in that script as Kahlman) To see better results set your Chart's timeframe to Daily.

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STD/Clutter Filtered, One-Sided, N-Sinc-Kernel, EFIR Filt is a normalized Cardinal Sine Filter Kernel Weighted Fir Filter that uses Ehler's FIR filter calculation instead of the general FIR filter calculation. This indicator has Kalman Velocity lag reduction, a standard deviation filter, a clutter filter, and a kernel noise filter. When calculating the Kernels,...

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Pips-Stepped, R-squared Adaptive T3 is a a T3 moving average with optional adaptivity, trend following, and pip-stepping. This indicator also uses optional flat coloring to determine chops zones. This indicator is R-squared adaptive. This is also an experimental indicator. What is the T3 moving average? Better Moving Averages Tim Tillson November 1,...

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Kalman filter is a recursive algorithm that has been invented in the 1960s to track a moving target, remove any noisy measurements of its position and predict its future position. In finance, KF has been used by the asset management industry for various purposes. KF is an optimal choice in many cases and do at least better than a moving average smoothing. A port...

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This strategy is an advanced version of the Loft Strategy V1, I shared earlier. (Loft Strategy V1 consists of a kalman filter (by alexgrover ) and a "stop and reverse" line which is following and the kalman filter. If the price goes in the same direction as the position side, the "stop and reverse" line approaches the kalman filter as set on the "Approach...

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This strategy consists of a kalman filter (by alexgrover ) and a "stop and reverse" line which is following the kalman filter. If the price goes in the same direction as the position side, the "stop and reverse" line approaches the kalman filter as set on the "Approach Decrease Step" parameter.

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This indicator plot 3 Kalman filter zero lag EMA lines. It has less lag and is also smoother than the original EMA. It also has an option to show the crossover of two EMAs.

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Price smoothed by a Kalman filter to cutout noisy price.

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Kalman filter on multiple RSI periods. Usefull on higher timeframes to confirm a change of trend.

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This script is a simplified version of John Ehlers's adaption of Dr. Kalman's optimum estimator as applied to price action (More can be found on this here: www.dimensionetrading.com). Here I have adapted two of these optimum estimators to work together to provide crossover signals. The user can choose the input of this filter in the 'input source'. The 'Ratio of...

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Introduction Inspired from the Kalman filter this indicator aim to provide a good result in term of smoothness and reactivity while letting the user the option to increase/decrease smoothing. Optimality And Dynamical Adjustment This indicator is constructed in the same manner as many adaptive moving averages by using exponential averaging with a smoothing...

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Introduction There are tons of filters, way to many, and some of them are redundant in the sense they produce the same results as others. The task to find an optimal filter is still a big challenge among technical analysis and engineering, a good filter is the Kalman filter who is one of the more precise filters out there. The optimal filter theorem state that :...

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Introduction Based on the exponential averaging method with lag reduction, this filter allow for smoother results thanks to a multi-poles approach. Translated and modified from the Non-Linear Kalman Filter from Mladen Rakic 01/07/19 www.mql5.com The Indicator length control the amount of smoothing, the poles can be from 1 to 3, higher values create smoother...

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