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Dec
6
awarded  Nice Answer
Oct
15
awarded  Scholar
Oct
15
accepted Any research on how natural language processing can be used to forecast stocks?
Oct
10
awarded  Nice Question
Oct
10
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Oct
6
awarded  Critic
Oct
6
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Oct
5
answered Switching from C++ to R - limitations/applications
Aug
24
awarded  Nice Question
Apr
20
revised Strategy of Renaissance Technologies Medallion fund: Holy Grail or next Madoff?
edited body; edited title
Apr
17
answered What is the effect of quant finance on global markets?
Apr
17
answered How do equivalent martingale measures arise in pricing?
Apr
16
comment Most successful investors using academic-based framework?
Don't know Hussman, but would say that the performance of AQR, although good overall, is not a sterling one. They lost 40% in the opening months of the fund in 1997-8, and then they lost a lot in 2008. All of which has not counterbalanced by outsize annual returns. Dalio's strategies span the gamut, where for "gamut" I mean "I don't really know what they do". But they seem to have the typically choppy performance of a fundamental fund, with lean years (2009) followed by fat years (2010). Not what you'd expect from a quant fund.
Apr
16
asked Most successful investors using academic-based framework?
Apr
10
awarded  Commentator
Apr
10
comment Are there ways to measure the risk aversion of a representative investor, based on publicly available market data?
Sell-side people talk about changes is risk aversion and risk appetite all the time. I should ask them but I am a bit shy.
Apr
4
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Apr
3
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Mar
17
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Feb
13
comment How do you correct Max Draw-Down for auto-correlation?
The reference paper is actually "The Statistics of the Sharpe Ratio" by A.Lo. Financial Analysts Journal, Vol. 58, No. 4, July/August 2002. And, as it is the statement in the question is incorrect: when returns are positively autocorrelated, the SR is too large. When they are negatively autocorrelated however, it is too small. Also, it is Calmar ratio, not Calamar ratio. And finally, it is not heavily used in practice because, being based on an extremal statistics, it has very high variance.