William Eckhardt; infamous for his bet with Richard Dennis and the original Turtles.
Read more about him here, and the turtle story here. To see his performance, check his amazing equity curve here.
Here's a piece that he presented back in '96. Many of the ideas put forth, especially those applying to his methods and systems, are worth exploring.
EDIT:
Adding a link to another older thread about Eckhardt's discussion on randomness.
Read more about him here, and the turtle story here. To see his performance, check his amazing equity curve here.
Here's a piece that he presented back in '96. Many of the ideas put forth, especially those applying to his methods and systems, are worth exploring.
June 29, 1996
Ritz Carlton Hotel
Address by William Eckhardt
President, Eckhardt Trading Company
At Eckhardt Trading Company ("ETC") we try to take a scientific approach to trading. This is not an easy description to live up to. We try to earn it by paying a lot of attention to the foundations of the subject, to the soundness of our methodology, and to the correctness of our statistics.
In terms of the foundations of the subject, we rely heavily on Decision Theory and Utility Theory. To see the usefulness of this, first note that there are two respects in which profits and losses are not equivalent. One is objective and has to do with nonlinearity. For example, it requires a 100% profit to balance a 50% loss. The second is subjective and has to do with risk aversion, for many people even the prospect of a 150% profit does not compensate for the risk of a 50% loss. Through Utility Theory, such imbalances can be treated in a rigorous, quantitative manner and in this way uniform and unified procedures can be developed. Look at the question of risk management. Any trader who survives any length of time knows something about his subject, but in my experience, traders simply graft risk control on top of whatever else they are doing, often in an arbitrary way. For instance, many prospective clients have asked me whatâs the most Iâll lose on one trade. I can look up these statistics, but this is not something I would ordinarily pay any attention to. It doesnât matter how little you lose on an individual trade, but how much you might lose on your whole portfolio. Youâre not going to keep a ship afloat just by making sure the leaks are small. The important thing is to limit portfolio risk, the trades will take care of themselves.
We have devised a portfolio theory quite different from the classical theory that permits factors such as risk aversion, the nonlinear imbalances between profits and drawdowns, and long-term utility growth to be built in at the ground floor. They are all part of the formulas that define what it means for a system to be good. In this way, on even the most preliminary test run of a new idea we are forced to take into consideration the subtle and complex relations between drawdowns and long-term growth. At ETC we are dedicated utility maximizers and pay particular attention to the rate of expected utility growth.
It has been shown again and again, that without proper controls, even the most honest researcher will unconsciously bias research usually in a favorable direction. Trading systems research is especially rife with possibilities for this kind of wish fulfillment. During more than 20 years, we have seen an amazing variety of ways in which research can mislead or falsify. In response to this we have developed a veritable gauntlet of tests that any system must pass to be taken seriously. We test for post-dictiveness, for computer glitches, and for statistical artifacts. We test for overfitting, for maldistribution of returns, and the degree to which a system takes advantage of unusual and possibly nonrepeatable circumstances. Theses are just a few of the potential sources of trouble that we routinely monitor. This battery of tests can bring runaway enthusiasms back down to earth.
An important feature of our approach is that we work almost exclusively with price, past and current. One reason for this is that to make any progress in the early stages of quantitative investigation you usually have to reduce the relevant factors to one or two crucial variables. Price is definitely the variable traders live and die by, so it is the obvious candidate for investigation. The other reason is that in a system thatâs making good use of price information, it is very difficult to add other information without degradation. Pure price systems are close enough to the North Pole that any departure tends to bring you farther south.
Many systematic traders spend the majority of their time searching for good places to initiate. It just seems to be part of human nature to focus on the most hopeful point of the trading cycle. Our research indicated that liquidations are vastly more important than initiations. If you initiate purely randomly, you do surprisingly well with a good liquidation criterion. In contract, random liquidations will kill the best system. At ETC we expend a lot of our research effort on liquidations.
Most standard statistical techniques are inappropriate for analyzing trading. Statisticians have developed many delicate techniques that squeeze information from minimal data, but these give false results in this business. I tell traders that if the results donât sock you in the eye, theyâre probably not real. Accordingly, we use only the most robust and assumption free statistical tests, We have an aversion to summary statistics that obliterate important structural elements. For assessing systems, we use a technique called bootstrapping so that the complete distribution of past outcomes can make itself felt in decisions; the distribution is not simply viewed in terms of its mean and variance which can give a distorted picture.
Our aversion to summary statistics that obliterate structure extends to the trading systems themselves. For instance, we avoid moving averages of price in making trades. Such moving averages are popular mostly because theyâre mathematically tractable, but they smooth away all the structural information inherent in the price data.
Another popular tool, the price breakout, may be far better than the moving average, but it still eliminates most of the relevant structure. A breakout trader keeps two pieces of structural information, the high and the low for a given time period, but ignores all the price structure in between. For this and for other reasons we judiciously avoid breakout trading in all parts of all our systems.
Itâs a lot easier to look scientific than to be scientific. We try to avoid the kind of delicate fine tuning that gives on the feeling of being very accurate, but that is in fact mostly arbitrary. We have taken to heart the research that shows that simple yes-no schemes, either fully accept or fully reject something, are more useful and more robust tan delicate weighting schemes. For instance, we do not favor trades according to how good they are supposed to be, instead we use the following rule: if a trade is good enough to make, itâs good enough to make at full size; if a trade isnât good enough to make at full size, then donât make it at all. We adhere to this kind of reasoning all the way down the line. All five systems we currently use are given equal weight. We also try to give equal weight to each of the fifty or so markets we trade.
I would characterize our overall approach as "conservative". This does not mean that we avoid market risk, for market risk is the raw material from which profit is fashioned, but we are conservative about what we know and about what can be done. My experience with Decision Theory indicates that knowing what it is you are ignorant of is in fact a powerful position to be in. The task of the trader is to locate those few areas where ignorance is not complete and to convert this information into profitability in an efficient way. False knowledge can be very detrimental to this process, but acknowledged ignorance can be quite beneficial.
EDIT:
Adding a link to another older thread about Eckhardt's discussion on randomness.
