[R-SIG-Finance] EMM: how to make forecast using EMM methods?

[Guy Yollin]

Michael,

If I understand correctly, you've used some EMM algorithms to estimate
the parameters of a stochastic volatility model.

If this is the case you should now be able to use Monte Carlo methods to
generate forecasts from your model.

That is, you will generate random variables (according to the
specifications of your model), feed them into your model and hence
simulate your stochastic volatility process.

Note sure what references you have been using but perhaps these would be
helpful:

Gallant, Hsieh and Tauchen (1997). "Estimation of stochastic volatility
models with diagnostics", Journal of Econometrics, 81, 159-192. 

Andersen, T.G. H.-J. Chung, and B.E. Sorensen (1999). "Efficient Method
of Moments Estimation of a Stochastic Volatility Model: A Monte Carlo
Study," Journal of Econometrics, 91, 61-87.

Best,

-- G



-----Original Message-----
From: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of Michael
Sent: Thursday, February 28, 2008 12:56 PM
To: r-sig-finance at stat.math.ethz.ch; r-help
Subject: [R-SIG-Finance] EMM: how to make forecast using EMM methods?

Hi all,

We followed some books and sample codes and did some EMM estimation,
only to find it won't be able to generate forecast.

This is because in the stochastic volatility models we are estimating,
the volatilities are latent variables, and we want to forecast 1-step
ahead or h-step ahead volatilities.

So it is nice to have the system estimated, but we couldn't get it to
forecast at all.

There is a "Reprojection" Method described in the original EMM paper,
but let's say we reproject to a GARCH(1,1) model, then only the
GARCH(1, 1) parameters are significant, which basically means we
degrade the SV model into a GARCH model. There is no way to do the
forecast...

Could anybody give some pointers?

Thanks!

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