Question

你知道在哪个包中，我可以找到http://faculty.washington.edu/ezivot/econ589/econ589multivariateGarch.r中用于R的cov.EWMA和/或covEWMA功能吗？

谢谢。

Answer 1

在网上搜索我在R-Forge上找到了这个代码。

covEWMA <- function(factors, lambda=0.96, return.cor=FALSE) {
## Inputs:
## factors    N x K numerical factors data.  data is class data.frame
##            N is the time length and K is the number of the factors.  
## lambda     scalar. exponetial decay factor between 0 and 1. 
## return.cor Logical, if TRUE then return EWMA correlation matrices
## Output:  
## cov.f.ewma  array. dimension is N x K x K.
## comments:
## 1. add optional argument cov.start to specify initial covariance matrix
## 2. allow data input to be data class to be any rectangular data object


if (is.data.frame(factors)){
  factor.names  = colnames(factors)
  t.factor      = nrow(factors)
  k.factor      = ncol(factors)
  factors       = as.matrix(factors)
  t.names       = rownames(factors)
} else {
  stop("factor data should be saved in data.frame class.") 
}
if (lambda>=1 || lambda <= 0){
  stop("exponential decay value lambda should be between 0 and 1.")
} else {
  cov.f.ewma = array(,c(t.factor,k.factor,k.factor))
  cov.f = var(factors)  # unconditional variance as EWMA at time = 0 
  FF = (factors[1,]- mean(factors)) %*% t(factors[1,]- mean(factors))
  cov.f.ewma[1,,] = (1-lambda)*FF  + lambda*cov.f
  for (i in 2:t.factor) {
    FF = (factors[i,]- mean(factors)) %*% t(factors[i,]- mean(factors))
    cov.f.ewma[i,,] = (1-lambda)*FF  + lambda*cov.f.ewma[(i-1),,]
  }

}
  # 9/15/11: add dimnames to array
  dimnames(cov.f.ewma) = list(t.names, factor.names, factor.names)

  if(return.cor) {
   cor.f.ewma = cov.f.ewma
   for (i in 1:dim(cor.f.ewma)[1]) {
    cor.f.ewma[i, , ] = cov2cor(cov.f.ewma[i, ,])
   }
   return(cor.f.ewma)
  } else{
      return(cov.f.ewma)  
  }
}

计算R中的EWMA协方差和相关性

1 个答案: