Question

Define and test a function to generate the covariance matrix for an input vector. For example, if the input is v=[1, 2, 5], then the matrix is v*vT = 1 2 5 2 4 10 5 10 25 (write the code in python

Answer 1

import numpy as np
	import math
	stdv = {"ABC":0.3,"XYZ":0.2}
	tickersCorr = ["ABC","XYZ"]
	# Assuming a 0.5 correlation here is the correlation matrix
	c = [[1,0.5],[0.5,1]]
	def varCovarMatrix(stocksInPortfolio):
	cm = np.array(c)
	vcv = []
	for eachStock in stocksInPortfolio:
	row = []
	for ticker in stocksInPortfolio:
	if eachStock == ticker:
	variance = math.pow(stdv[ticker],2)
	row.append(variance)
	else:
	cov = stdv[ticker]*stdv[eachStock]* cm[tickersCorr.index(ticker)][tickersCorr.index(eachStock)]
	row.append(cov)
	vcv.append(row)
	vcvmat = np.mat(vcv)
	return vcvmat
	print(varCovarMatrix(["ABC","XYZ"]))