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Top authors: Least Squares Moving Average (LSMA)

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Impulse responses can fully describe their associated systems, for example a linearly weighted moving average (WMA) has a linearly decaying impulse response, therefore we can deduce that lag is reduced since recent values are the ones with the most weights, the Blackman moving average (or Blackman filter) has a bell shaped impulse response, that is mid term values...

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Introduction At the start of 2019 i published my first post "Approximating A Least Square Moving Average In Pine", who aimed to provide alternatives calculation of the least squares moving average (LSMA), a moving average who aim to estimate the underlying trend in the price without excessive lag. The LSMA has the form of a linear regression ax + b where x is a...

137

This is an experimental study which calculates a linear regression channel over a specified period or interval using custom moving average types for its calculations. Linear regression is a linear approach to modeling the relationship between a dependent variable and one or more independent variables. In linear regression, the relationships are modeled using...

562

Because it's not always easy to see your lovely MA crossovers points.. Details/usage: 3 seperate MA's which are fully customisable - types, sources, lengths, offsets. Types of MA available: SMA, EMA, WMA, VWMA, SMMA, DEMA, TEMA, HullMA, LSMA Custom time resolution available for the Short and Long "Minor" MA's together. Separate custom time resolution available...

1606

The "AC-P" version of Jaggedsoft's RSX Divergence and Everget's RSX script is my personal customized version of RSX with the following additions and modifications: LSMA-D line that averages in three LSMA components to form a composite, the LSMA-D line. Offset for the LSMA-D line is set to -2 to offset latency from averaging togther the LSMA components to form a...

443

Introduction Forecasting is a blurry science that deal with lot of uncertainty. Most of the time forecasting is made with the assumption that past values can be used to forecast a time series, the accuracy of the forecast depend on the type of time series, the pre-processing applied to it, the forecast model and the parameters of the model. In tradingview we...

332

This is revision 2 of "Multi Time Frame MA Duplicates" Honorable Mentions: @RicardoSantos - helped me fix my brain. Narf. Description: One stop shop for multiple MA duplicates over different resolutions. A veritable banquet of MA's to choose from. Set up your MA variables, and then plot up to 4 duplicates all using different time frames. r2 Changes: Simple...

601

Introduction The trend step indicator family has produced much interest in the community, those indicators showed in certain cases robustness and reactivity. Their ease of use/interpretation is also a major advantage. Although those indicators have a relatively good fit with the input price, they can still be improved by introducing least-squares fitting on their...

320

This script has been based on ProwdClown's instructions of usage. GM settings 9, 6, 3 should be used, LSMA 25, 0 has been implemented. Original author for main script: LazyBear, xSilas and Ni6HTH4wK, modified By sco77m4r7in and oh92, later modified By...

413

This is an experimental study designed using data from Bollinger Bands to determine price squeeze ranges and active levels of support and resistance. First, a set of Bollinger Bands using a Coefficient of Variation weighted moving average as the basis is calculated. Then, the relative percentage of current bandwidth to maximum bandwidth over the specified sampling...

343

Honorable Mention: @glaz for jumping on the "on price" suggestion and throwing the code at me - which spurred me to add shapes in too, because why not eh? Description: Multitude of MA choices. MA's can both be set to different resolutions. Crossover/Crossunder, drawn at an averaged position. r2 Changes: On-MA cross marker now only drawn at averaged...

362

Introduction Technical analysis make often uses of classical statistical procedures, one of them being regression analysis, and since fitting polynomial functions that minimize the sum of squares can be achieved with the use of the mean, variance, covariance...etc, technical analyst only needed to replace the mean in all those calculations with a moving average,...

144

Introduction I already estimated the least-squares moving average numerous times, one of the most elegant ways was by rescaling a linear function to the price by using the z-score, today i will propose a new smoother (FLSMA) based on the line rescaling approach and the inverse fisher transform of a scaled moving average error with the goal to provide an...

96

Introduction The last indicators i posted where about estimating the least squares moving average, the task of estimating a filter is a funny one because its always a challenge and it require to be really creative. After the last publication of the 1LC-LSMA, who estimate the lsma with 1 line of code and only 3 functions i felt like i could maybe make something...

54

Similar to Bollinger Bands but adjusted for momentum. Instead of having the centerline be a simply moving average and the bands showing the rolling variance, this does a linear regression, and shows the LSMA at the center, while the band width is the average deviation from the regression line instead of from the SMA. This means that unlike for normal Bollinger...

31

Quick script made by reusing some functions written for other projects. This is a variation on the least squares moving average, but with custom weights on the linear regression. This gives higher weights to recent values and values with high volume. Behaves very similarly to my volume weighted Hull moving average, especially with the hull smoothing option turned on.

43

Introduction It is possible to use a wide variety of filters for the estimation of a least squares moving average, one of the them being the Kaufman adaptive moving average (KAMA) which adapt to the market trend strength, by using KAMA in an lsma we therefore allow for an adaptive low lag filter which might provide a smarter way to remove noise while preserving...

73

Introduction The estimation of a least squares moving average of any degree isn't an interesting goal, this is due to the fact that lsma of high degrees would highly overshoot as well as overfit the closing price, which wouldn't really appear smooth. However i proposed an estimate of an lsma of any degree using convolution and a new sine wave series, all the...

88

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