Hi, I am not able to extract variance and covariance
As mentioned, there are 5 stocks and changed the code [ http://www.forecastingfinancialrisk.com/3.html] as follows: > S<-cov(returns) > S V1 V2 V3 V4 V5 V1 0.0004951526 0.0001256519 0.0001651016 0.0003024310 0.0003516796 V2 0.0001256519 0.0008076471 0.0001251208 0.0002005305 0.0002347568 V3 0.0001651016 0.0001251208 0.0010000707 0.0003158028 0.0003682633 V4 0.0003024310 0.0002005305 0.0003158028 0.0011405561 0.0008442661 V5 0.0003516796 0.0002347568 0.0003682633 0.0008442661 0.0018536153 > EWMA[1,]<-c(S)[c(1,10,5)] > a=t(as.numeric(returns$i)) %*% as.numeric(returns$i) ---*Here we need to change dataframe to numeric, that too only columns.* > str(a) num [1, 1] 0 > dim(a) [1] 1 1 > dim(lambda*S) [1] 5 5 ---------*As the dimensions are not same we can not do %*%* > dim((1-lambda)*a) [1] 1 1 for(i in 2:T) { S<- lambda*S+ (1-lambda)*t(returns$i) %*% returns$i EWMA[i,]=c(S)[c(1,4,2)] } *Original code as per* http://www.forecastingfinancialrisk.com/3.html is EWMA = *matrix*(*nrow*=T,*ncol*=3) *# create a matrix to hold the covariance matrix for each t* lambda = 0.94 S = *cov*(y) *# initial (t=1) covariance matrix* EWMA[1,] = *c*(S)[*c*(1,4,2)] *# extract the variances and covariance* *for* (i *in* 2:T){ *# loop though the sample* S = lambda * S + (1-lambda) * *t*(y[i]) %*% y[i] [[alternative HTML version deleted]]
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