I draw your attention to the following article in the Scientific American which you may or may not have read. In any event your readers may find it interesting. The gist being:

“The strategy the economists used was as simple as it was absurd—they substituted economic variables for physical ones. Utility (a measure of economic well-being) took the place of energy; the sum of utility and expenditure replaced potential and kinetic energy. A number of well-known mathematicians and physicists told the economists that there was absolutely no basis for making these substitutions. But the economists ignored such criticisms and proceeded to claim that they had transformed their field of study into a rigorously mathematical scientific discipline.”

The full article is here:
http://www.sciam.com/article.cfm?id=the-economist-has-no-clothes&SID=mail&sc=emailfriend

I leave you with a fitting reminder from my hero:

‘Science as it exits today is agreeable through the power which it gives us of manipulating our environment and to a small but important minority because it affords intellectual satisfaction. It is disagreeable because, however we may seek to disguise the fact, it assumes a determinism which involves, theoretically, the power of predicting human actions. In this respect it seems to lessen human power.’

Byrne, sadly I am stuck trying to work out the potential of “hip new technologies” (interestingly I saw a company that has new technology to make hips not so long ago). I am susceptible to manias, but don’t worry overly about the US’ indistrial base.

Sadly for the Quants however, they are susceptible to “style manias” and humble or not will bet billions in capital on algorithms, rather than individual stocks — in that sense they are not so different from me, but they may not be as diversified. . .

I share your suspicions on the potential dangers of a “7-minute abs” approach to specu-trage. I amusingly recall Louis Navellier in one of his more charlatanical moments (after getting hammered in the tech wreck) saying something like “I’m not a growth investor or a value investor but a do-what-works investor”. Shit! Why didn’t I think of that??!?! Undoubtedly, what has (more recently) worked are mimetic strategies, which themselves are caught up in a lovely recursive positive feedback loop that has attracted yet more capital to them at the expense of the mean-reverting Gaussians (now resembling Lamarckians if P&L is any measure?) , such that front-running, order-sniffing, and trend-following oriented pursuits garner a greater relative percentage of turnover.

Now, basking in their victory, such feedback traders, armed with more capital while market-makers and block-traders longer facilitate, and with mean-reverting Gaussians in the penalty box, or retraining for a mid-life career move, things will begin to get really interesting as the feedback traders duke it amongst themselves in an algorithmic fight to death…(or at least a pyrrhic duel to zero-alpha).

“In 1958, Simons and Mayer had celebrated their graduation by buying Lambretta motor scooters and driving to Bogota from Boston. In 1964, the three cobbled together money with Simons’s father to start a Colombian vinyl-floor-tile factory.” (http://www.bloomberg.com/apps/news?pid=newsarchive&sid=ayjImYcoCiH8).

D. E. Shaw tries to find people with those weird resumes — they have lots of published authors, former poker champions, and the like.

I don’t mean to imply that they set out to be humble — it’s quite arrogant to have an opinion on thousands of investment products when it’s so hard to predict the performance of even one. I just meant that quants ignore the evidence that other people overweight, they accidentally earn superior returns. Unless their models happen to mimic mania, they are less likely to be taken in by hip new technologies or awesome biotech stories, and are similarly unlikely to except that America’s industrial base will disappear any time soon. By getting rid of qualitative concerns, they get rid of the natural tendency to extrapolate heavily from qualitative data, and to overweight the value of judgments about which drugs will take off, which chips will sell well, etc.

When they can predict how I’m going to spend my time at 12:57 pm next Saturday they may be worth watching. Otherwise the best technology for predicting human behavior remains another human mind. Data and its manipulation into cognitively meaningful form is important to calibrate and inform those predictions but without incorporating human input the clock is ticking on the next blowup.

Applying techniques from physical science is complete folly. Hit a rock with a hammer ten times and it will behave very similarly each time; try to hit a human with a hammer and your results will vary (along with your lifespan).

By default then it will become a strategy that scales up, unless the machine has a built in “all right that’ s enough mate, I’m bored let’s think of something else” function.

Byrne, I hear and concur with your thoughts on fresh MBAs. I was partly alluding to them with my dismissive remarks on the “white teeth brigade”. More lapsed jesuits please.

But the problem with the mean reverting strategies is that pace Taleb, while mean reversion holds true most of the time, the times when it doesn’t, when as you put it “the detractors are vindicated”, tend to be so awfully dynamic that all at once you can lose more money than you made over the period when the means were still reverting. You have an asymmetric payoff, which will make you much more likely over a long period to blow up and lose all your money, especially if you play with leverage. That is the problem the quants faced in August. Humility was nothing to do with it.

This is a non-finance-specific kind of machine learning algorithm

“David Shaw, who came from Morgan Stanley, where he worked under renowned trader Nunzio Tartaglia. A onetime Jesuit with a Ph.D. in astrophysics”

I can almost guarantee that returns in any financial specialty peak when companies are being run by folks with really strange resumes. Once the ex-Jesuit PhDs get replaced by fresh MBAs, it all gets hopelessly conventional; 11% returns, plus or minus the occasional disaster.