A mathematically elegant, native & modern way how to measure velocity/ strength/ momentum. As you can see it looks like MACD, but !suddenly! has N times shorter code (disregard the functions), and only 1 parameter instead of 3. OMG HOW DID HE DO IT?!?
MACD: "Let's take one filter (1 parameter), than another filter (2 parameters), then let's take dem difference, then let's place another filter over the difference (3rd parameter + introduction of a nested calculation), and let's write a whole book about it, make thousands of multi-hours YouTube videos about it, and let's never mention about the amount of uncertainty being introduced by multiple parameters & introduction of the nested calculation."
Strength: "let's get real, let's drop a weighted linear regression & usual linear regression over the data of the same length, take dem slopes, then make the difference over these slopes, all good. And then share it with people w/o putting an ® sign".
Fyi, regressions were introduced centuries ago, maybe decades idk, the point is long time ago, and computational power enough to calculate what I'm saying is slightly more than required for macd.
Rationale. Linearly weighted linear regression has steeper slope (W) than the usual linear regression slope (S) due to the fact that the recent datapoints got more weight. This alone is enough of a metric to measure velocity. But still I've recalled macd and decided to make smth like it cuz I knew it'll might make you happy. I realized that S can be used instead of smoothing the W, thus eliminating the nested calculation and keeping entropy & info loss in place. And see, what we get is natural, simple, makes sense and brings flex. I also wanna remind you that by applying regression we maximize the info gain by using all the data in the window, instead of taking difference between the first and the last datapoints.
This script is dedicated to my friend Fabien. Man, you were the light in the darkness in that company. You'll get your alien green Lambo if you'll really want it, no doubts on my side bout that.
Was very interesting to read the description, also thanks for great implemenation! Seems to be accurate
gorx1
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@crypteisfuture, Yeah, my pleasure. I'm trying to popularize these "info gain" and "info loss" terms I came up with lately. These 2 help, I believe, to think in the right direction.
OutsourcE
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Thx for that! Awesome 👍
peacefulLizard50262
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"let's get real, let's drop a weighted linear regression & usual linear regression over the data of the same length, take dem slopes, then make the difference over these slopes, all good." omg I was day dreaming about this! Excellent!
MoAtlas
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Genius work..thank you for sharing this with the community…
stinkbug
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I been back testing and checking against current trends and seem to find Stoch & RSI more telling of trend. This seems to be lagging a bit even with change in time period. I may be using it wrong, but the divergences on RSI are more telling of trend change. this seems to act like MACD and be way behind, any advice ? I really like the concept of being able to see acceleration/decelaration rate as a measure of strength. This is will full respect to your work, admire your willingness to share and help thanks.
gorx1
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@stinkbug, Hey mane, the idea was to create an alternative to MACD with only 1 variable to optimize instead of 3, no more / no less.
I advice not to use RSI and Stoch at all. In fact these are very outdated ways to analyze de-trended volatility. They don't show trends btw.
If you want a way measure de-trended fluctuations, apply high pass filter to WLSMA. Thats's the best we can do without calculating the appropriate EV
stinkbug
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Im trying to understand exactly, i been looking to measure rate of change or acceleration in RSI, for example a how fast a move in one direction vs a similar move which re-occurs. Essentially tying a # to RSI divergences or movements. Is this a method i can use on here. Sorry for being so dense
gorx1
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@stinkbug, I'd advise not to use divergences and whatsoever, otherwise you'd need to apply another set of metrics to the initial metric itself in order to quantify the dynamics. I think increasing the moving window size will give you the necessary info
stinkbug
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@gorx1, Thanks, do you think changing source to RSI makes sense? I still trying to understand exactly what the indicator is telling us but I do want to measure "excitement" in a move and compare it to other similar moves....i was thinking if i compared 2 similar moves acceleration they would show me excitement in the stock
Seems to be accurate