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

 From "Eva Poen" To Statalist Subject Re: Re: st: RE: RE: Bootstrap and Technical analysis Date Tue, 19 Aug 2008 17:13:34 +0100

```Mahmoud,

I haven't followed all of the conversation. Just a few notes:

2008/8/19 Mahmoud Abd-El-Aal <ma7205@bristol.ac.uk>:
> bootstrap (location: mean=r(mean)), rep(1000): sum var2,detail
> then i want to save all the bootstrap samples, the 1000 samples in order
> to compare each individual mean to var1 single mean

Firstly, you don't need the detail option in your bootstrap command.
You can save the bootstrap results by using the -saving- option, see
-help bootstrap-. That would be

set seed 123
bootstrap (location: mean=r(mean)), rep(1000) saving(bootstrapsample,
replace): sum var2

You could then open the file bootstrapsample.dta and investigate the
1000 replications.

> Also when running the above command , the P value  what does it represent?

statistics text on the bootstrap technique. This will tell you about
the different confidence intervals that you can calculate after
-bootstrap- (normal based, percentile based, bias corrected). Type
-estat bootstrap, all- after running the bootstrap to see all
confidence intervals.

The P value refers to a test that the original sample mean is equal to
zero, very much like a coefficient test after -regress-. It uses the
estimated standard error from the bootstrap instead of the sample
standard error. A low p-value rejects the hypothesis that the original
sample mean is equal to zero. However, this is based on the normal
approximation. You might find one of the other methods more

> The basic point that i am trying to reach is how many samples from the
> bootstraped ones has a bigger mean than the value of 0.0001218, any
> suggestions?

I showed you how to do this (save the bootstrap replications in a .dta
file), but I am unsure how you would sensibly interpret such a
finding.

Hope this helps,
Eva
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