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

[Mark Leeds]

I can't say much about Garch/SV being better or worse but I know that's
there an approximate functional equivalence between exponential smoothing
and a regular moving average ( i.e: rolling window ). It's something like
lambda = 1/(2n +1) or something like that but I don't remember. It's in any
decent technical analysis book and it's true empirically because I've played
around with it in the past.



-----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 elton wang
Sent: Thursday, February 28, 2008 4:36 PM
To: r-sig-finance at stat.math.ethz.ch; r-help
Subject: Re: [R-SIG-Finance] EMM: how to make forecast using EMM methods?

I've heard opinions that GARCH/SV volatility models
are not better on forecasting than simple exponential
moving average volatilities or even rolling window
historical vol.
Any practitioners mind comment?

--- Michael <comtech.usa at gmail.com> wrote:

> 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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