[R-SIG-Finance] Simulate the stock market for back testing strategy ---R bootstrap function

[Frederick Novomestky]

To all:

The best reference that I am aware of on boostrap methods, in general, and 
block resampling iw the Davison and Hinkley book, Bootstrap Methods and 
their Applications.  I have used block resampling on vectors of asset class 
returns and it works quite well.

Sincerest regards,

Fred Novomestky
(also Industry Professor Finance and Risk Engineering, Polytechnic 
Unversity, Brooklyn, NY 11201 )

At 10:49 AM 2/9/2008, Brian G. Peterson wrote:
>Dirk Eddelbuettel wrote:
> > On 9 February 2008 at 07:05, elton wang wrote:
> > | Thanks for Brian's reply.
> > | to make this  more relevant to this list, what
> > | functions in R can do bootstrap resampling while
> > | keeping the autocorrelation in the original data? (I
> > | only know function of sample()). Would this resmapled
> > | data do any good on back testing?
> >
> > No.
> >
> > But any decent book on bootstrapping mentions the problem, and many theses
> > and papers were (are ?) written on the issue. I haven't looked in a while,
> > but 'block bootstrap' once was a popular idea for this. And an ad-hoc 
> method
> > I used five or six years ago for low-frequency (monthly) data was to sample
> > in two stages
> >       first sample an integer (say between 1 and 6) to determine how 
> 'large'
> >               a chunk I would fetch
> >       then sample an integer between 1 and N to determine where I pick the
> >               chunk from
> > and re-constitute resample series this way.  As I said, 
> 'ad-hoc'.  There are
> > many other ways.   But don't do just sample() as it is guaranteed to break
> > any possible structure in the correlation your data.
>
>A block bootstrap for time series is implemented in a slightly more
>robust manner than that described by Dirk above in the function
>tsbootstrap(tseries)
>
>There are a number of other bootstrap methods available in package
>"boot" and corresponding function "boot", but I haven't examined these
>in detail for their tuning or applicability in time series.
>
>I think I laid out some basic steps of building a trading model on
>actual historical data in my prior email.  Simulated data (via
>resampling or any other method) after the point where you have a target
>model is only a validator of the model, not the starting point, or
>you're almost certain to get worthless results.
>
>Regards,
>
>    - Brian
>
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Frederick Novomestky, Ph.D.
Novomestky Associates LLC
41 Eastover Drive
East Northport, NY 11731-4330
Vox: 1.631.368.0701
Fax: 1.631.368.1696
URL: http://www.novoassoc.com

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