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  • How to find covariance Matrix?

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    I am very new to python, in fact this is my first code in python.

    I am attempting to find the covariance matrix for 4 rows of data with each element having a decreasing weight datewise

     

    I have performed the calculations on excel already, and a snapshot of how the data looks is like is below:

    Date Obs SPX DJI VIX VXD SPX DJI VIX VXD   Weights
    12-Feb-2016 1 1864.78 15,973.84 25.4 24.58 1.93% 1.98% -10.24% -10.82%   0.060000
    11-Feb-2016 2 1829.08 15,660.18 28.14 27.39 -1.24% -1.61% 6.80% 8.85%   0.056400
    10-Feb-2016 3 1851.86 15,914.74 26.29 25.07 -0.02% -0.62% -0.95% -0.56%   0.053016
    9-Feb-2016 4 1852.21 16,014.38 26.54 25.21 -0.07% -0.08% 2.06% 2.21%   0.049835
    8-Feb-2016 5 1853.44 16,027.05 26 24.66 -1.43% -1.10% 10.62% 10.82%   0.046845

     

    I need to calculate the covariance matrix in the following format:

      SPX DJI VIX VXD
    SPX 0.000174 0.000170 -0.000985 -0.000906
    DJI 0.000170 0.000175 -0.000944 -0.000887
    VIX -0.000985 -0.000944 0.006568 0.005917
    VXD -0.000906 -0.000887 0.005917 0.005573

    I have to use python where i have calculated the returns and the weights

    to find the covariance matrix.

    I would appreciate any help thank you


    import pandas as pd
    import numpy as np

    import math
    xl = pd.ExcelFile('path+file.xlsx')
    xl.sheet_names
    df = xl.parse('Sheet 1')
    df['spxr']=np.log(df.SPX/df.SPX.shift(-1))
    df['djir']=np.log(df.DJI/df.DJI.shift(-1))
    df['vixr']=np.log(df.VIX/df.VIX.shift(-1))
    df['vxdr']=np.log(df.VXD/df.VXD.shift(-1))
    df['weights']=(0.06)*(0.94**(df.Obs-1))
    df=df.fillna(0)

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