your comment is utter nonsense. quant funds are defined by the reliance on (i suppose, good) algorithms, not computers - literally everybody trades with computers. the number of trades you make doesn't determine alpha, which is a measure of relative performance given a particular risk level (beta). there is no statistical fact to any of that, and certainly no sense to 'alpha becoming beta.' there is no a priori reason that their strategies must or will become public (the fear of replication risk is a common bogeyman but is already priced in). everyone needs to keep innovating in their strategies, but mostly because markets change.
the only half-true statement you made was about scalability. like, theoretically every strategy has a limit to its effectiveness and i guess you can argue that algo-based trading funds should be limited in size and scope. but compare that to seriously unscalable fields such as venture capital, where the constraints are in lack of investment targets, need for GP's to consult/manage, domain expertise more important for companies w/o sec-standard accounting, covenants blocking investments in previously funded companies - in essence, high human capital costs. implementing an extra algo strategy is much less human-intensive, which might suggest easier scaling (though nowhere near mutual funds, etc)
Quant funds don't trade with computers - in fact, computers trade instead of humans.
> the number of trades you make doesn't determine alpha
No, but it does determine how statistically significant your alpha is. If I make 1 good trade, it might be alpha or it might be a lucky guess. If I make 10000 good trades, it's unlikely to be just a lucky guess.
> certainly no sense to 'alpha becoming beta.'
Trend following used to be "alpha", but now it's considered "beta" - in the sense that everybody can replicate it, and there is no specific "alpha"-based fee warranted for a fund executing trend-following strategies.
> there is no a priori reason that their strategies must or will become public
the more people know about it, the easier the math behind it, and the more broadly it applies, the more chance there is that it becomes "public" knowledge (public in the sense that many industry practitioners working for different funds know about it)
> but compare that to seriously unscalable fields such as venture capital
Well, given that quite a few venture funds are bigger than $10bn [1], I wouldn't call that "seriously unscalable". But in any case, my comparision was to trend following (Winton has about $30bn), global macro (Bridgewater's Pure Alpha has about $50bn), and passive index investing (SPDR S&P 500 ETF is > $100bn).
I think you misunderstood much of what tomp said, and willfully misinterpreted some of the rest.
The number of trades does not determine alpha, but it means that you can be much more certain about whether someone has alpha or not. For example, John Paulson made billions on (essentially) a single trade in 2007 and early 2008. Does he have alpha? It's hard to say, because all of those profits were from one trade, and he could have been lucky. Virtu Financial generates millions of dollars each year, by making tens of millions of trades. Do they have alpha? Absolutely - you can be certain of it, because it would be statistically impossible to get lucky tens of millions of times.
The idea "alpha becoming beta" is an extremely relevant one for many hedge funds today. As strategies become well known, they become commodified, and are often offered at a lower fee, both by hedge funds, ETFs and investment bank products. Frequently, they are offered for little or no performance fee, so they cannot be called "alpha" and are often referred to as "smart beta". For example, AQR Capital Management offers many low-fee funds giving exposure to value investing, momentum investing, managed futures, the FX carry trade and others. It sounds like you are using a very narrow definition of beta (exposure to the stock market) whereas the usage in the industry is much broader.
Pointing out that quant funds use "algorithms" to trade rather than "computers" is pointlessly picking holes. It's clear what he means.
the only half-true statement you made was about scalability. like, theoretically every strategy has a limit to its effectiveness and i guess you can argue that algo-based trading funds should be limited in size and scope. but compare that to seriously unscalable fields such as venture capital, where the constraints are in lack of investment targets, need for GP's to consult/manage, domain expertise more important for companies w/o sec-standard accounting, covenants blocking investments in previously funded companies - in essence, high human capital costs. implementing an extra algo strategy is much less human-intensive, which might suggest easier scaling (though nowhere near mutual funds, etc)