Nested For loop in R -

this simple question taking time new in r.

i'm trying write code variance of portfolio.

for example, have following :-

weight=c(0.3,0.2,0.5) cov  = matrix( c(0.2, 0.4, 0.3, 0.4, 0.5, 0.3,0.3,0.3,0.4),nrow=3, ncol=3, byrow = true)  (i in 1:3){ (j in 1:3) { port = sum((weight[i]^2) * (cov[i,i]^2)) + sum(weight[i] *weight[j]* cov[i,j]) }} 

the answer if calculate manually should 0.336. r gave me port=0.12 wrong. mistake?

first calculate matrix product w %*% t(w):

tcrossprod(weight) #     [,1] [,2] [,3] #[1,] 0.09 0.06 0.15 #[2,] 0.06 0.04 0.10 #[3,] 0.15 0.10 0.25 

then multiply variance-covariance matrix , take sum of elements:

sum(tcrossprod(weight) * cov) #[1] 0.336 

or loop (inefficient):

port <- 0 (i in 1:3){   (j in 1:3) {     port  <- if (i == j) {       port + sum((weight[i]^2) * (cov[i,i]))     } else {       port + sum(weight[i] *weight[j]* cov[i,j])     }    } } port #[1] 0.336 

note variance-covariance matrix typically contains variances (sigma_i^2) on diagonal.