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

[elton wang]

But I doubt this is not a one-step forecast.
For one-step cast, you only need start from today's
value and simulate one step ahead. you need to use the
orignal innovations as of today instead of simulating
from day 1.

--- Guy Yollin <guy.yollin at rotellacapital.com> wrote:

> Hi Michael,
> 
> Yes, this is what I'm suggesting.  Bear in mind,
> your model estimation
> process should have also resulted in volatility
> estimates for t-1, t-2,
> etc.
> 
> Your simulation will require one or more of these
> terms as input (in
> addition to the random innovations) since your
> stochastic volatility
> model will have lagged volatility terms.
> 
> Good luck.
> 
> -- G
> 
> 
> -----Original Message-----
> From: Michael [mailto:comtech.usa at gmail.com] 
> Sent: Thursday, February 28, 2008 5:46 PM
> To: Guy Yollin; r-help;
> r-sig-finance at stat.math.ethz.ch
> Subject: Re: [R-SIG-Finance] EMM: how to make
> forecast using EMM
> methods?
> 
> Hi Guy,
> 
> Thanks for your help! Yes, we have the coefficient
> estimated using
> EMM. And we followed those papers.
> 
> Just want to check my understanding about your
> suggestion:
> 
> Do you mean that after we obtain the estimated
> coefficients,
> 
> we run one simulation to obtain the whole sequence
> of latent variable
> (the volatility time series, from time 0 to time
> t+1),
> 
> where time t is today, and t+1 is tomorrow(one step
> forecast);
> 
> And that's one simulation.
> 
> And we run such simulation for N times, let's say
> N=10000,
> 
> and obtain 10000 such volatility time series, each
> ending at time t+1,
> 
> and then we take average of the 10000 data points at
> t+1,
> 
> the average will be the mean-forecast of the
> volatility tomorrow(i.e.
> that's the one step forecast that we want)...
> 
> Am I right in doing these procedures?
> 
> Thanks
> 
> 
> 
> On Thu, Feb 28, 2008 at 4:30 PM, Guy Yollin
> <guy.yollin at rotellacapital.com> wrote:
> > 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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> > 
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