numpy - Slow Stochastic Implementation in Python Pandas -


i new pandas , need function calculating slow stochastic. think should possible without difficulty not familiar advanced apis in pandas.

my data frame contains, 'open', 'high', 'low' , 'close' prices , indexed on dates. information should enough calculate slow stochastic.

following formula calculating slow stochastic: %k = 100[(c - l14)/(h14 - l14)]   c = recent closing price  l14 = low of 14 previous trading sessions  h14 = highest price traded during same 14-day period.  %d = 3-period moving average of %k

you can rolling_* family of functions.

e.g., 100[(c - l14)/(h14 - l14)] can found by:

import pandas pd  l, h = pd.rolling_min(c, 4), pd.rolling_max(c, 4) k = 100 * (c - l) / (h - l)

and rolling mean can found by:

pd.rolling_mean(k, 3)

moreover, if you're stuff, can check out pandas & econometrics.


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