Brian G. Peterson
brian at braverock.com
Thu Sep 18 12:47:13 CEST 2008
On Thu, 2008-09-18 at 11:00 +0100, Patrick Burns wrote:
> I disagree with Ajay about the value of Winsorization.
> Yes, it is ad hoc but it is simple to understand and
> often results in reasonable answers.
> It certainly depends on the context but if we are talking
> about financial returns, then I haven't had positive
> experience with traditional statistical robustness.
> (Given that my thesis was on robustness, I don't say
> this lightly.) Robustness often gives inferior answers
> in finance (in my experience) even when it is obvious
> that it "should" be the proper thing to do. This is
> a phenomenon that I don't understand.
I have to agree with Patrick. We proposed an extension above and beyond
classic Winsorization that would only reduce the outliers that occured
beyond a certain confidence level (e.g. 95% or 99%). Traditional robust
methods have a tendency to ignore outliers rather than simply reduce
their influence. In measuring risk, this is clearly quite dangerous.
We found that by only cleaning outliers beyond a certain confidence, we
got much more stable and accurate out of sample predictions on a variety
of risk measures (as well as predictions that compared well to kernel
estimation and Monte Carlo methods with lower computational burden).
Like I said in my previous email, code and documentation available upon
request or in the next version of PerformanceAnalytics.
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