clc;
clear all;
close all;

%% Gross Return Vector

c = [1.1 1.2]
%% Find Covariance and Variance of R_a and R_b

cov_RaRb = -0.1*0.25
var_Ra = 0.1^2
var_Rb = 0.25^2
%% Variance-Covariance Matrix and Its Inverse

H = [var_Ra cov_RaRb;cov_RaRb var_Rb]
H_inv = inv(H)
%% Others

e = ones(size(c))
alpha = e*H_inv*transpose(c)
sigma = c*H_inv*transpose(c)
delta = e*H_inv*transpose(e)
%% Minimum Variance Portfolio

R_bar = alpha/delta
variance = 1/delta
std = sqrt(variance)
weight = (1/delta)*e*H_inv