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Re: Re: st: RE: RE: Bootstrap and Technical analysis


From   Mahmoud Abd-El-Aal <ma7205@bristol.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: Re: st: RE: RE: Bootstrap and Technical analysis
Date   Wed, 20 Aug 2008 14:53:53 +0100 (BST)

Dear eva and Raj,
thanx for the comments, i have implemented your technique and it works
just fine. when i save the bootstrap samples i see how many of the samples
are greater than a specific mean using the count if command

on to another point, i am trying to do the same but with an AR(1) process,
therefore i was thinking about this command:
bs "reg var2 lag1" "e(rss)", reps(1000) saving (k:\bssample.dta)
since i want to bootstrap the residuals to generate new AR (1) processes
that could fit to the rest of the returns.
the AR(1) model is as follows:
rt= a+b r(t-1) +e
rt is returns on day t......

the question i have, is there a way after bootstraping the residuals to
fit the new models to the returns i have already to bootstrap the mean of
these returns after fitting them into the model ?? I know it is a little
bit of a complicated question, i do not know if i am asking it correctly,
but that is the way i understadn it.
Regards,
Mo

-- 
Mahmoud Abd El Aal
MSc. F&I
UOB


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