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Just a link to a book that compares this: https://eitsupi.github.io/querying-with-prql/timeseries#sec-moving-ave
Very cool!
I also used an SMA like that in my presentations, as well as an EWMA which you can find in this Google Colab if you want to include that as well? https://colab.research.google.com/drive/1asOWKjQbv6VWW9WjWR2Mer7PLmm0S0dT?usp=sharing
Originally posted by @snth in PRQL/prql#3618 (comment)
The text was updated successfully, but these errors were encountered:
@snth Thanks for sharing that! That looks awesome!
I don't see myself adding it anytime soon, but it would be great to have it shared.
let calc_ewma = alpha:null span:1 rel -> ( from rel filter t==1 select {t, x, ewma=x} loop ( join rel (that.t==this.t+1) select {t, x, ewma = (alpha ?? 2/(span+1))*x + (1-(alpha ?? 2/(span+1)))*ewma} ) ) let data = ( from tris_with_sma sort Date derive {t=row_number this, x=google_tri} ) from data #calc_ewma alpha:2/(10+1) calc_ewma span:10 derive google_ewma10 = ewma select {Date=t, google_tri=x, google_ewma10=ewma}
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Very cool!
I also used an SMA like that in my presentations, as well as an EWMA which you can find in this Google Colab if you want to include that as well?
https://colab.research.google.com/drive/1asOWKjQbv6VWW9WjWR2Mer7PLmm0S0dT?usp=sharing
Originally posted by @snth in PRQL/prql#3618 (comment)
The text was updated successfully, but these errors were encountered: