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

From   Mahmoud Abd-El-Aal <>
Subject   Re:Re: st: RE: RE: Bootstrap and Technical analysis
Date   Mon, 18 Aug 2008 17:04:08 +0100 (BST)

It seems that my email explaining my actions did not appeal to some and
made sense to others. Just a comment about what clive said mentioned and
the reply he got from chris about it, i do definitely support a section
about guidelines/rules about using stata, then it would be much easier to
know what is considered appropriate behaviour and to be more honest i can
not believe that the only 2 words that was mentioned in my original post
(stuck & help) could be considered as emotional blackmail :)
Not to take anymore of the precious times of everyone i would like to
close the page and move on to more important topics such as stata and
again its optional if anybody wants to answer or not.

I am using stata version 9
in order to compare two variables means (how many of the means of the
bootstraped samples are larger than the original series sample) i had the
following commands in my mind:
gen mean diff= var2-var1
ttest diff==0

One-sample t test

Variable      Obs	Mean	Std. Err.   Std. Dev.	[95% Conf. Interval]

diff     3516	.0006044	.0000962    .0057026	.0004158    .0007929

mean = mean(diff)			t =   6.2842
Ho: mean = 0		degrees	of freedom =     3515

Ha: mean < 0		Ha: mean != 0	Ha: mean > 0
Pr(T < t) = 1.0000	Pr(T > t) = 0.0000	Pr(T > t) = 0.0000

as i am new stata just see if this interpretation is correct, so we reject
the null hypothesis of mean(diff) is 0 so its either bigger or smaller ,
but from what i see the mean fall with the 95% CI right? another thing
looking at the Ha: mean<0, does that mean that var2(mean)<var1(mean),
again this might be a very easy question to some, but a comment about the
interpretation is needed

To carry on to the bootstrap:
drop if diff==.
bs "ttest diff=0" "r(mu_1)", rep (1000)

my results are as follows
bs "ttest diff=0" "r(mu_1)", rep (1000)

command:      ttest diff=0
statistic:    _bs_1      = r(mu_1)

Warning:  Since ttest is not an estimation command or does not set
e(sample), bootstrap has no
way to determine which observations are used in calculating the statistics
and so
assumes that all observations are used.  This means no observations will
be excluded
from the resampling due to missing values or other reasons.

If the assumption is not true, press Break, save the data, and drop the
that are to be excluded.  Be sure that the dataset in memory contains only
relevant data.

Bootstrap statistics                              Number of obs    =     
Replications     =      1000

Variable       Reps  Observed      Bias  Std. Err. [95% Conf. Interval]

_bs_1   1000  .0006044  1.16e-06  .0000963   .0004155   .0007933   (N)
.0004207   .0008018   (P)
.0004239   .0008027  (BC)

so again here i can see that the mean falls within the 95%CI, so does that
mean after bootstrapping is not=0, so the question is, is it bigger or
smaller. I am trying to get around this problem in some way so maybe the
commands used a bit ridiculous or better yet can be implemented in another
way. I also want to compare the std.err. of the bootstraped var2 with the
original var1. so should i use the same idea and if so , what would be the

Sorry for the long email, i am des........(oops was going to do the same
old mistake again:)
thank you for reading

Mahmoud Abd El Aal
MSc. F&I

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