Python: How to winsorize the Mean and Standard Deviation?

Question

I have a code that I use for multiple different metrics (e.g. Value at Risk, Omega, Sortino, etc.). The formula I use for the average is:

Mean (average):

e = numpy.mean(r)

return numpy.mean(diff) / vol(diff)

Standard deviation:

return numpy.std(returns)

I would like to winsorize the means (and standard deviations) that are used in my calculations. Can anyone advise how to do it? I have found this part but am not really sure how to implement it (if this is it of course):

https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.mstats.winsorize.html

Thanks

Asked By: Wheeliam

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Source

Answer 1

For a precise answer, an MCVE is needed.

Presuming ‘e’ is an nparray

import numpy as np
import scipy as sp
from scipy.stats.mstats import winsorize

e = np.random.rand(1,100)
print("{}".format(e))
winsorize(e, limits=(0.25,0.25), inplace=True)
print("{}".format(e))

Answered By: Rich Andrews

Answer 2

Try this one:

import os
import numpy as np

from scipy.stats.mstats import winsorize

file_location = input("path to file: ")
dirname = os.path.dirname(file_location)
filename = os.path.basename(file_location)

with open(file_location, 'r') as readfile, 
        open(os.path.join(dirname, 'win_' + filename), 'w') as writefile1, 
        open(os.path.join(dirname, 'mod_' + filename), 'w') as writefile2:
    writefile1.write('adj_mean,adj_stdn')
    for idx, line in enumerate(readfile):
        print("Reading line# {}...".format(idx))
        series = np.array([float(x) for x in line.split(',')])
        print("Read {} values...".format(len(series)))
        winsorized_series = winsorize(series, limits=[0.10, 0.10])
        print("Writing modified series to file...")
        writefile2.write(','.join(map(str, winsorized_series)) + 'n')
        adj_mean = np.mean(winsorized_series)
        adj_std = np.std(winsorized_series)
        print("adj mean and std dev...")
        writefile1.write("{},{}n".format(adj_mean, adj_std))

Answered By: West

Answer 3

import numpy as np
from scipy.stats.mstats import winsorize

def winsorized_mean(x, ql, qr):
    return np.mean(winsorize(x, limits=(ql, qr))

def winsorized_std(x, ql, qr):
    return np.std(winsorize(x, limits=(ql, qr))

Answered By: Roger Vadim

Python: How to winsorize the Mean and Standard Deviation?

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