Michael Covel

Kathryn Welling brings the great question forward:

“What struck me even at the time was that here were these supposedly very bright guys who insisted on applying a theory to the markets despite plentiful evidence that what the theory said couldn’t happen in fact doesoccur with staggering regularity in the markets. Big fat tails swat investors in the fanny with fair frequency. So-called ’six sigma events’ aren’t really terribly rare, no matter what the equations tell you.”
Kathryn M. Welling, Weeden & Co.

Woody Dorsey responds:

“Absolutely. What I wrote about in the book is that it is like the invisible hand comes along once in a while to spank the markets. The inference is that boy, you really should be on your guard because you know these events are going to happen. And when they do, those big fat tails provide the biggest and best opportunities to safely build capital; that’s when you take advantage of market opportunities. That’s the lesson. Yet [efficient market theorist and University of Chicago Professor] Eugene Fama himself says that the 1987 crash was an aberration–as was 1929. Insists they really didn’t matter. But they mattered to a lot of people.”
Woody Dorsey, Market Semiotics

“Most things in life are not like steam engines, but people treat them as if they were. Life in general, and markets in particular, involve large random factors, have complicated stochastic structures, and regularly spring nasty surprises. Their behaviour over short timespans may have so little significance as to be nothing but noise. Extrapolation is impossible or meaningless. Yet try as we might, we continue to see patterns where none exist, misunderstand the role of randomness, seek explanations for chance phenomena, and believe that we know more about the future than we do.”
Mark Wainwright
Plus Magazine

In a recent paper Nassim Nicholas Taleb outlined:

“In some strategies and life situations, it is said, one gambles dollars to win a succession of pennies. In others one risks a succession of pennies to win dollars. While one would think that the second category would be more appealing to investors and economic agents, we have an overwhelming evidence of the popularity of the first. A popular illustration of such asymmetry in returns is evident in the story of the Long Term Capital Management hedge fund. The fund derived steady returns over a dozen quarters then lost all of them in addition to almost all its capital in a single observation - only for the main principals to restart a new, albeit milder, version of the strategy. Is there a systematic bias in favor of such return profiles?”
Nassim Nicholas Taleb

The Economist: An eerie calm
Jul 22nd 2004

The fact that implied

James Simons, President of Renaissance Technologies, offered in a roundtable forum:

“I heard this story and I think it’s true. Anyway, it’s a pretty good story. It’s about how the Air Force trains pilots. When a trainee made a good landing, he would be praised. When a trainee made a bad landing, he would be ridiculed. Well, it was perfectly clear to the general that the first approach was lousy and the second approach was good. He had statistics demonstrating that when you praised a pilot who made a perfect landing, his next landing was not likely to be as good. Whereas, if you berated a pilot who made a bad landing, his next landing was likely to be much better. However, if you think about it, it doesn’t matter what you do, because landings are most likely to be average. If a pilot had an exceptional landing, his next landing was likely to be average. If he had a poor landing, his next landing was likely to be average, also. By slicing the data and only looking at what follows good landings and praise, you only see part of the picture. You must consider how data was selected before you can draw conclusions. This example is closer to home. We interview a lot of managers, because we do some asset allocations. Although I haven’t compiled careful statistics on this, it frequently seems that a manager with a marvelous record does not perform as well after I invest with him. Why is that? Well, do managers who lost 35% in the last three years show you their records? No, those guys aren’t showing anyone their records. You are seeing a sample of the best managers, a sample of “good landings.” Going forward, some people do better and some people do worse, but reversion to the mean is probably a persistent phenomenon in both managing money and landing airplanes.”

“The question that I don’t yet know the answer to, and I suppose what the partners of Long Term Capital, I can suppose what their answer would be, but I don’t yet know the balance between whether this was a random event or whether this was negligence on theirs and their creditors’ parts. If a random bolt of lightning hits you when you’re standing in the middle of the field, that feels like a random event. But if your business is to stand in random fields during lightning storms, then you should anticipate, perhaps a little more robustly, the risks you’re taking on.”
Trillion Dollar Bet (PBS Special)

Ponder the statement:

“Statistics alone can never prove causality, but it can show you where to look.”

True trend following traders, if trading similar markets, will typically have very similar winning months and very similar losing months. A good historical example is the summer of 1998 (when Long Term Capital Management went bust). During August and September 1998 most trend followers had winning months. Interestingly, July 1998 was a losing month for most trend followers. Comparing monthly performance numbers of trend followers is best done through correlation analysis. Correlation, however, does not prove causality. It tells us where to begin the investigation. So when looking at correlations among trend followers, especially very large monthly gains or losses, it makes sense to look for the other side of the trade to better understand “why”.

We have all heard the term “100-year flood” applied to the markets. The Long Term Capital Managements of the world predicated their trading on the flood happening only once every 100 years. Reality is quite different as Hunt Taylor reminds:

“I’m wondering when statisticians are going to figure out that the statistical probability of improbable losses are absolutely the worst predictors of the regularity with which they’ll occur. I mean, the single worst descriptor of negative events is the hundred-year flood. Am I wrong? How many hundred-year floods have we lived through in this room? Statistically maybe we should have lived through one and we lived through seven now at this point.”
Hunt Taylor
Director of Investments, Stern Investment Holdings

James Simons reminds us all that complication in trading can cause problems:

“Years ago, a colleague came up with an extremely complicated model. Initially, it worked well, but then it began to falter. I said, “Can we understand more about this model? It’s so complicated.” He said, “Oh no, you can’t understand it. I’ve added this and that and put it all together and I’ve maximized here and there and…who knows what it is?” I said, “That is not satisfactory. I know it

H.G. Wells outlined many moons ago the keys:

“If we want to have an educated citizenship in a modern technological society, we need to teach them three things: reading, writing, and statistical thinking.”

Statistical thinking is the ugly stepchild. To this day it is left out of basic equations of our day to day life. Good directions to explore.

Some professional short-term traders have raised some serious money in the last two years. Roy Niederhoffer (brother of Victor) trades short-term trading systems. However, should there be caution? What makes him different in the long run than Long Term Capital Management or Victor Niederhoffer? Are other short term traders also reliant on standard deviation as their measure of risk?

David Harding of trend follower Winton Capital argues for more than simple acceptance of the Sharpe ratio as the measure for assessing “risky investments”:

“…large positive returns increase the perception of risk as though they could as easily be negative, which for a dynamic investment strategy may not be the case. Large positive returns are penalised, and thus the removal of the highest returns from the distribution can increase the Sharpe ratio: a case of