clear all;
close all;
clc;
% R_bar
c = [1.1 1.2]
%Var-Cov matrix V
% Find Covariance From Corr And Varaince
cov = 0.25*0.1*-1
var_Ra = 0.1^2
var_Rb = 0.25^2
V = [var_Ra cov;cov var_Rb]
V_inv = inv(V)

% Variance-Covariance Matrix and Inverse
H = [var_Ra cov;cov var_Rb]
H_inv = inv(H)

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