Selected Others

The links below pertain, in one way or another, to the prospects for portfolio-management success via dynamic asset allocation.

  • In this interview the celebrated Edward O. Thorp, mathematician, gambler, author and hedge fund manager, explains that he discovered that “trend following” actually works, albeit in his experience only well when supplemented with fundamental data.
  • This is an account of an interview with the famous Professor Fama, who admits that there is some evidence that momentum investing works. The interviewer, who is quite a knowledgeable professional, goes over all of the tricky business of whether or not empirical evidence for the success of such investing can be trusted and discusses in particular “data mining”, which is dealt with forthrightly in the first two Retail Backtest articles on the right (albeit without explicit use of that phrase as it hardly connotes anything with clarity).
  • Here's another interview with another mathematician who got richer than any physicist with just mathematics, Jim Simmons. See also.
  • Tobias J. Moscowitz and others here investigate momentum and generally find that it does pay to use it. See also his numerous other publications on this list.
  • What's worse than just spreading your money around equally among a list of securities? Let Mssrs. DeMiguel, Garlappi and Uppal answer: Using the Nobel Prize-winning mean-variance models (also known as “modern portfolio theory” or MPT), that are still being foisted off on investors by some advisors and fund managers— that's what worse.

Note: Retail Backtest articles contain a number of other links to financial papers by academicians. And notwithstanding the several mentions in these pages of momentum or relative strength, the current not-yet-disclosed best scheme of Retail Backtest makes use of none of that. Stay tuned for announcements!

RB

Retail Backtest Originals

RB

The following articles are all by me. Do write in with comments, questions and corrections. The home page at www.mocpa.com profiles me and another page there is a microblog that chronicles the development of this site and business. —Mike O'Connor



  • “Does Anything Work? | Chance or Discovery? Part A”

    Hopefully readers won't be put off by the first paragraph, which freely admits that the subject matter is mainly about “hypothesis testing”. Not only is that dreary discipline put to intense use, but you'll want to know all about what investing in the market has to do with painting houses. You don't want to wind up like the painting contractor in the article who didn't get his logic straight, do you? Well then, read the article. This is your chance, in the span of only three pages, to learn what in Hell is meant by “refuting the null hypothesis”. And who in the world burdened us with that?

  • “Does Momentum Work? | Chance or Discovery? Part B”

    Both questions are answered in this article. The first is about a particular type of scheme for active portfolio management; the other is about the means whereby we could develop confidence in such a scheme... “how can we be sure?” After the basic principles are explained the text moves on to demonstrating how to use them to rescue a simple momentum/relative strength scheme that would otherwise be dangerous to use. A spirited effort was put into writing something that earnest beginners could comprehend in its entirety. But professionals should benefit from seeing how proper simulation via a conceptually-simple walkthrough method (followed by a Monte Carlo procedure to determine the odds that the good results were due to a well-exploited market inefficiency and not to mere chance) can be truly effective. The principles and methods are applied to three portfolios of ETFs of generally high liquidity, with very promising results. And the finalized scheme has features that you may never have seen in use. Nota bene: everything is disclosed!

  • Kelly Criterion | “Fortune's Formula” Revisited

    Kelly was working on information theory and discovered a simple mathematical procedure which, when applied to investments, determines that there is a fixed fraction of an investor's equity that should sequentially be put at risk, with the rest held as cash, if the most-likely rate of growth of the equity is to be maximized. And the big news— this is of practical interest— is that the fraction is often, in the circumstances of retail investors, considerably less than 1.0 . This is not consistent with the standard ideology of, say, the mutual fund industry whose managers are compelled to come as close to being 100% invested as possible. As articles go, this one is electrifying. Or, more modestly, electrified. That is, if you print it out you won't be able to make use of the article's JavaScript-powered widgets. They spin wheels of fortune for you— nay, they let you spin the wheels— which wheels are the very ones in the book “Fortune's Formula” by William Poundstone. And the associated graphs, which are also interactive, illustrate exactly how the choice of the fixed fraction determines both risk and return.

  • A Hidden Cost of Trading | Profitable Stop-Loss Trading

    Whipsaws are long two-man saws that were used to rip-saw logs lengthwise into timbers (still used in places). There would be one man on top of a log that was suspended horizontally about six feet above the ground, and another who stood under the log. So the one below pulled down on the saw, then the one on top subsequently pulled up, repetitively of course. They progressed sideways, horizontally. But not so with you if you get whipsawed in the markets— you're likely to go down, to start losing. Basically you get whipsawed with securities if you try to sell at the start of a decline and then try to buy back if the stock turns around and starts to go up in price past the price at which you sold. If you try that then on numerous occasions you'll get a fill on your sell order that is at a price that is less than the price at which you intended to get out, and on other numerous occasions you'll similarly come up short relative to buy-and-hold investors by having to buy back in at a price higher than the price at which you sold. But still, you clearly do get some downside protection from such a scheme, because if there were a market crash you'd be out of it. So how does it really work out? How big is the penalty that we pay for stop-loss trading? In this article it's explained that the work of Black and Scholes on their famous options pricing formula proves that there are innate costs of stop-loss trading (which they rather exactly quantified, for their particular circumstances). But the article also presents the results of implementing a “Poor Man's Option” which is a simple type of stop-loss scheme that some retail investors might be tempted to try (ill-advisedly). Naturally a full-featured interactive chart and table have been provided, which utilize only real S&P500, SPY, VIX and 13-week Treasury Bill data. Find out the truth about stop-loss trading. Find out if buying options is profitable in the long run!

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