Ernie Chan claims that statistical arbitrage is better than momentum like trend

I wouldnt be so negative about Ernie... I personaly trade statarb and mean reverting strategies only and I havent seen anything better so far... Results are stable even in trending stock markets, because I keep portfolio beta neutral.

From my point of view it is better to think about markets in Ernies way rather than buy some "WCCI knowledge" from Woodie :D
 
Personally I believe arbitrage is more powerful and consistent than trend following kind of ways, and most of the FI uses arbitrage more than trend following.
 
volpunter said:
if Ernie Chan made a single dime trading his own money or institutional money then he would not have to write retarded books for retail trading wannabees and he would not waste all his time on his blog posts, or have you heard or seen a single blog written by any of the successful hedge fund managers? I have not, their lawyers would scream at them day and night to not expose anything in public domain that they may later be held liable in a law context. So, relax, Ernie is a failed quant (PhD or not PhD makes actually zero difference at Wall Street) and now peddles books and, guess what, trading courses, lol.
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Based on your logic every professor at any university is a loser and a failure because he could be cashing out real money somewhere instead of teaching all those "wannabees".

Genious...
 
Depends on your definition of both probably, but I think stat arb is going to generally show lower variance of returns than momentum strategies. If you can find a consistently stationary relationship to exploit then you will almost certainly be able to predict your duration of drawdown and expected loss with more accuracy than you could with momentum trading. This is just a generalization though for example just simple lower frequency single stock vs stock pairs trading is going to usually have unsuitably high variance of returns in my experience.
 
More or less you are correct, at least in most every case. How many of your college professors do you remember to be highly motivated, passionate, and engaged with students? I remember one single one. All others in business school came across as some frustrated individuals who frantically tried to make it to as many conferences and speaking engagement as possible in order to "belong". And most looked jealously at those who started a consultancy on the side. It still was all about money for them. They got paid their 200-400k per year instead of making 10x as much like their fellow alumni working at Wall Street or at law firms. And thats the same with the Krugmans and Roubinis of the world and all other academic "heavy lifters" who would not make a single dime if you asked them to trade short, medium, or long-term (and they are exposed in the exact same way in their investment accounts than your and my grandma). There is ALWAYS a reason someone is selling books and advice rather than just doing what one advises others to do....which leads me back to Ernie Chan ;-)

Arti said:
Based on your logic every professor at any university is a loser and a failure because he could be cashing out real money somewhere instead of teaching all those "wannabees".

Genious...
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You know that's a dangerous opinion about professors @volpunter , education is important and so is the research they do. It's not all about the money for some people either. I go to school in New York City and a substantial portion of the professors in the Operations Research & Financial Engineering, Math, and especially comp sci departments are former Wall Street employees, some of which even tell us they're trying to repent. In my experience as a student, this culture of complacent ivory tower academics people seem to believe in just doesn't exist. I wouldn't conflate "those who can't do" with "those who teach" so quickly, that said, I wouldn't recommend Ernie Chan's books to anyone but someone just starting out in quantitative trading. There are better resources available, some of which are even textbooks written by professors
 
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