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From |
Mahmoud Abd-El-Aal <[email protected]> |

To |
[email protected] |

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 observations that are to be excluded. Be sure that the dataset in memory contains only the relevant data. Bootstrap statistics Number of obs = 6266 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 interpretation. Sorry for the long email, i am des........(oops was going to do the same old mistake again:) thank you for reading regards, Mahmoud -- Mahmoud Abd El Aal MSc. F&I UOB * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: Re: st: RE: RE: Bootstrap and Technical analysis***From:*"Nick Cox" <[email protected]>

**RE: Re: st: RE: RE: Bootstrap and Technical analysis***From:*"Lachenbruch, Peter" <[email protected]>

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