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Well, if you get 30 persons to flip a coin six time, there is good chance one of them will get all tails or all head. Now ask him his strategy for such amazing coin flipping skills! (example taken from the book "statistics done wrong"[1]).

I would be interested in seeing a total distribution of hedge funds return, not just outliers.

[1]:https://www.statisticsdonewrong.com/



I understand what you are saying, but the equivalent to the Medallion fund would be something more akin to winning that same coin flip 30 times in a row. They have been running approximately 30 years, beating market returns by a significant margin, year after year. The 40% average is net of fees, so the overall return of their strategy has actually been higher than that. The odds that they have accomplished these returns through luck alone are astronomically low.


The trick is this: the chances that a specific fund will do well that long via luck are very low, but the chances that there exists a fund among all that exist that has done well via luck are quite high.


I can tell you haven't actually done the calculation. There's only been about 20000 hedge funds in total over history. The odds of random chance producing Medallion's track record with that many draws are actually very low.


This is true, though I don't know how many edge funds operate. I guess some people really have working strategy!

The example I gave was more of a word of caution regarding past performances as indicator of expertise, but I guess I made it sound more generalizable than needed!


Jim Simons is certainly an outlier and the chance that the implemented strategies are not winning strategies is astronomical low.


But if you keep an eye on the lucky ones, they should also go back to being noise, if what you're saying is correct.

Is that what happened?


That would be the reversion to the mean[1]. This is a term I really dislike because it makes it sounds as if there is some sort of equalizing force making over-performers under-perform later. This is more the following: if you overestimates the expectation of a random process, you are going to be disappointed.

In our case, this does not makes the "hot streak" any less probable when you start looking, for a specific edge fund. It is true it would be interesting to select a group of over-perfomer and study their future return to know if past performances are a good predictor of future performance. I feel you would probably get mixed results!

Although as I said in the sibling comment, you are probably right, and no amount of statistics could explain performances seen in this particular edge fund.

[1]https://en.wikipedia.org/wiki/Regression_toward_the_mean




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