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Dimitri A. Sogoloff, President & CEO of quant manager Horton Point LLC writes in a paper made available to Opalesque for further distribution:
"A few weeks after the unusually large drawdowns attracted everyone’s attention to the perils of
“quantitative” investing, the popular opinion of what may have happened, has been formed. The
answer, apparently, lies in the quantitative space becoming overcrowded, with most models
generating similar forecasts and thus similar portfolios. Losses began with the rapid unwind of a
large market-neutral equity portfolio and have generated ripples throughout the quant world.
Still un-answered is the more fundamental question: why have different quant groups, using
supposedly different investment tools, ended up with similar models?
The empirical evidence suggests that the majority of the equity market-neutral models are indeed
similar in their approach to forecasting price behavior. In fact, they use one form of statistical
analysis or the other (hence the commonly used term, “Statistical Arbitrage”). The first problem
with statistical analysis of financial data is that it assumes stable relationships between market
factors, which we know not to be the case. The other problem is that everyone is looking at the
same data sets (after all, every security generates only one time series of historical returns).
This paper suggest an alternative approach to development of quantitative investment...................... To view our full article Click here
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