[R-SIG-Finance] Riskmetrics volatility and correlation estimation

[Brian G. Peterson]

Murali Menon wrote:
> Are there functions available to compute the Riskmetrics (1996) 
> volatilities and correlations for financial time-series? 
 > I refer to the exponentially weighted moving average vols
 > and exponentially smoothed correlations (with lambda = 0.94).
 > I looked in the VarModelling part of fPortfolio, but this
 > stuff doesn't seem to be there?

Not that I know of, but they shouldn't be too hard to construct.

So, if you want help constructing them from this group:

1> post the link to the RiskMetrics algorithms

2> do a little research on Google and the list archives

There have been several examples posted of exponentially weighted moving 
averages in R which should go a long way toward solving the volatility 
question above, for example.

R contains many different smoothing algorithms, as you can see with 
help.search("smooth") or help.search("smoothing")

3> suggest an approach, try an approach, post your failures

and I'm sure someone here can probably help you out.

Another interesting (to me anyway) question is "Why do you care?"  What 
in the literature leads you to want to try these techniques?  Are you 
just trying to replicate a set of RiskMetrics algorithms in R?  Have you 
looked at other research on smoothing and rolling windows?  I ask this 
trailing set of questions because often when I go looking in the 
literature, I find that there are several newer techniques which have 
been shown to work better than the older methods.  Sometimes these newer 
techniques are already implemented in R, other times I have to do it 
(but at least I'm then implementing a more modern approach).

Regards,

   - Brian