OPEN-SOURCE SCRIPT

Autoregressive Covariance Oscillator by Tenozen

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Well to be honest I don't know what to name this indicator lol. But anyway, here is my another original work! Gonna give some background of why I create this indicator, it's all pretty much a coincidence when I'm learning about time series analysis.
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Well, the formula of Auto-covariance is:
E{(X(t)-(t) * (X(t-s)-(t-s))}= Y_s

But I don't multiply both values but rather subtract them:
E{(X(t)-(t) - (X(t-s)-(t-s))}= Y_s?
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For arm_vald, the equation is as follows:
arm_vald = val_mu + mu_plus_lsm + et

val_mu --> mean of time series
mu_plus_lsm --> val_mu + LSM
et --> error term

As you can see, val_mu^2. I did this so the oscillator is much smoother.
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After I get the value, I normalize them:
aco = Y_s? / arm_vald
So by this calculation, I get something like an oscillator!

(more details in the code)
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So how to use this indicator? It's so easy! If the value is above 0, we gonna expect a bullish response, if the value is below 0, we gonna expect a bearish response; that simple. Be aware that you should wait for the price to be closed before executing a trade.

Well, try it out! So far this is the most powerful indicator that I've created, hope it's useful. Ciao.

(more updates for the indicator if needed)
Nota Keluaran
Fixed:
- line plots NaN/Incomplete line.
- Some timeframes plot NaN.

Usage reminder:
- If the resolution is lower than 10 Minutes, it won't plot anything. Please use a resolution equal to or above 10 Minutes.
Nota Keluaran
Updating the Indicator Preview
Nota Keluaran
Added src input
Nota Keluaran
Added PVMA
Nota Keluaran
Added invert value option
Nota Keluaran
Added custom symbol option and an option to multiply the value by price
autoregressivecovarianceforecastforecastinglinear-regressionLinear RegressionOscillatorsquantitativetimeseriesanalysistrendfollowing

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