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Regressions

Weighted Least Squares Moving AverageLinearly Weighted Ordinary Least Squares Moving Regression aka Weighted Least Squares Moving Average -> WLSMA ^^ called it this way just to for... damn, forgot the word Totally pwns LSMA for some purposes here's why (just look up): - 'realistically' the same smoothness; - less lag; - less overshoot; - more or less same computationally intensive. "Pretty cool, huh?", Bucky Roberts©, thenewboston Now, would you please (just look down) and see the comparison of impulse & step responses: Impulse responses Step responses Ain't it beautiful? "Motivation behind the concept & rationale", by gorx1 Many been trippin' applying stats methods that require normally distributed data to time series, hence all these B*ll**** Bands and stuff don't really work as it should, while people blame themselves and buy snake oil seminars bout trading psychology, instead of using proper tools. Price... Neither population nor the samples are neither normally nor log-normally distributed. So we can't use all the stuff if we wanna get better results. I'm not talking bout passing each rolling window to a stat test in order to get the proper descriptor, that's the whole different story. Instead we can leverage the fact that our data is time-series hence we can apply linear weighting, basically we extract another info component from the data and use it to get better results. Volume, range weighting don't make much sense (saying that based on both common sense and test results). Tick count per bar, that would be nice tho... this is the way to measure "intensity". But we don't have it on TV unfortunately. Anyways, I'm both unhappy that no1 dropped it before me during all these years so I gotta do it myself, and happy that I can give smth cool to every1 Here is it, for you. P.S.: the script contains standalone functions to calculate linearly weighted variance, linearly weighted standard deviation, linearly weighted covariance and linearly weighted correlation. Good hunting
Chỉ báo Pine Script™
bởi gorx1
8
Linear Regression Channel Breakout StrategyThis strategy is based on LonesomeTheBlue's Linear Regression Channel Indicator. First of all, I would like to thank LonesomeTheBlue. Breaking the Linear Regression Channel to close the candle triggers a Long or Short signal. If the slope of the Linear Regression Channel is positive, it is Short when it breaks out the lower line, and when the slope is negative, it is Long when it breaks out the upper line. The default is optimized for 8-hour candles, and for other hour candles, find the optimal value yourself. Below is a description of LonesomeTheBlue's Linear Regression Channel. 이 전략은 LonesomeTheBlue의 Linear Regression Channel Indicator를 기반으로 만들어졌습니다. 우선 LonesomeTheBlue님께 감사의 말씀을 드립니다. Linear Regression Channel을 돌파하여 봉 마감하면 Long 또는 Short 신호를 트리거합니다. Linear Regression Channel의 기울기가 양인 경우 하단 라인을 돌파하면 Short이고 그 기울기가 음인 경우 상단 라인을 돌파하면 Long입니다. 기본값은 8시간봉에 최적화 되어 있으며, 다른 시간봉은 직접 최적값을 찾아보십시오. 아래는 LonesomeTheBlue의 Linear Regression Channel에 대한 설명을 퍼왔습니다. ________________________________________________ There are several nice Linear Regression Channel scripts in the Public Library. and I tried to make one with some extra features too. This one can check if the Price breaks the channel and it shows where is was broken. Also it checks the momentum of the channel and shows it's increasing/decreasing/equal in a label, shape of the label also changes. The line colors change according to direction. using the options, you can; - Set the Source (Close, HL2 etc) - Set the Channel length - Set Deviation - Change Up/Down Line colors - Show/hide broken channels - Change line width meaning of arrows: ⇑ : Uptrend and moment incresing ⇗ : Uptrend and moment decreasing ⇓ : Downtrend and moment incresing ⇘ : Downtrend and moment decreasing ⇒ : No trend
Chiến lược Pine Script™
bởi chanu_lev10k
14