EWMAvol function

Exponentially Weighted Moving-Average Volatility

Use exponentially weighted moving-average method to compute the volatility matrix

EWMAvol(rtn, lambda = 0.96)

Arguments

• rtn: A T-by-k data matrix of k-dimensional asset returns, assuming the mean is zero
• lambda: Smoothing parameter. The default is 0.96. If lambda is negative, then the multivariate Gaussian likelihood is used to estimate the smoothing parameter.

Returns

• Sigma.t: The volatility matrix with each row representing a volatility matrix

• return: The data

• lambda: The smoothing parameter lambda used

References

Tsay (2014, Chapter 7). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

Author(s)

Ruey S. Tsay

Examples

data("mts-examples",package="MTS")
rtn=log(ibmspko[,2:4]+1)
m1=EWMAvol(rtn)