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Re: st: RE: RE: Methodology question
P Ram <firstname.lastname@example.org>
Re: st: RE: RE: Methodology question
Sun, 20 Jun 2010 15:37:44 +0400
Thanks so much for your helpful comments. Apologies for not replying
earlier...my net conn was down. I fully agree with your thoughts.
Thanks so much for taking the time to share them with us.
On Thu, Jun 17, 2010 at 1:40 AM, Nick Cox <email@example.com> wrote:
> The implied reference is
> Harrell, F. 2001. Regression modeling strategies. New York: Springer.
> I also have a more general comment. Postings of the forms
> "I have this plan. What comments do you have?"
> "What should I do be doing in my project?"
> "I am doing this. Is this correct?"
> are unlikely to get much response. That is a statement of probability
> and in no sense implies a ban or rules out your good fortune that
> someone may have something interesting or useful to say. In practice, it
> is difficult to say what does and does not make sense for anybody else
> to do. We do not know the context, or the data, or at what level the
> person is operating. Also, it is tricky often: Something may look like
> someone's project for a course or degree. Shouldn't the students be
> working that out themselves, not pleading support on the net?
> The most successful threads on this list, at least in my experience,
> grow out of Stata-specific questions, which sometimes morph into
> interesting questions of statistical principles or practice. The other
> way round doesn't work so well. Again, I deal in probabilities here, not
> certainties. What else would you expect on a statistical list?
> Lachenbruch, Peter
> This procedure is essentially a stepwise regression and has all the
> headaches associated with this procedure. The book by Frank Harrell in
> Springer series (about 2002) discusses this. You might also investigate
> the lars command, but you need to read up on variable selection methods
> a bit.
> Prasad Ramani
> I am new here and my question is quite different from what is normally
> asked here. I have a few questions more from an application point of
> The Project
> I am analyzing a multi asset class portfolio whose composition has
> changed over the years from mainly equities to a mix of equities,
> fixed income, hedge funds & private equity. The objective of the
> analysis is to find which risk factors the portfolio is exposed to and
> how to hedge them. The data is a monthly series of returns of this
> portfolio for the past 7-8 years.
> My Proposed Methodology
> 1. Get monthly returns for a list of indices that represent the major
> asset classes: For equities: SP500, MSCI World etc., for Fixed Income:
> BarCap US Aggregate Bond fund, JP Morgan Emerging Market Bond index,
> for Commodities: Gold, Oil, for Interest rates: 3 month LIBOR etc. I
> end up with about 15 such factors...Factor 1 to Factor 15.
> 2. I come up with a correlation structure for these 15 factors based
> on weekly/monthly returns going back to about 3 years.
> 3. I regress the returns of my portfolio against these 15
> factors...and based on the t-stats of the factors and the overall adj
> r-squared, I eliminate those factors that are insignificant at 5%
> 4. I expect the ones with low t-stats to be highly correlated to some
> other factors...and this can be verified from the above Var-Covar
> matrix (point 2)
> Finally I end up with those factors that have significant t-stats,
> F-stat and adj r-squared.
> I would really appreciate if you can give me your views on this.
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