FICO Xpress Optimization Examples Repository: Portfolio optimization using pandas to calculate covariance

FICO Xpress Optimization Examples Repository

Portfolio optimization using pandas to calculate covariance

Description

Modeling a small QP problem to perform portfolio optimization using pandas Python library to calculate covariance matrix.

Further explanation of this example: see Chapter 'Python' in the 'Mosel Language Reference Manual'

folioqp_pandas.zip

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Source Files

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folioqp_pandas.mos

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Data Files

folioqp.dat	[download]
folioqphist.dat	[download]
folioqp_pandas.py	[download]

folioqp_pandas.py

# *********************************************************
#   Mosel Example Problems
#   ======================
#
#   file folioqp_py.py
#   ``````````````````
#   Python function definitions for Mosel parent model
#   folioqp_py.mos.
#
#   (c) 2019 Fair Isaac Corporation
#       author: J. Müller
# *********************************************************
import platform
import numpy as np
import pandas as pd


def covariance_of_series(series):
    """ Compute covariance matrix of two-dimensional series. """

    covariance_data_frame = series.unstack(level = 0).cov()
    print(covariance_data_frame)

    return covariance_data_frame.stack()


if __name__ == "__main__":
    print("Python library version: ", platform.python_version())
    print("NumPy library version:  ", np.__version__)
    print("pandas library version: ", pd.__version__)