Old School Academics on Moving Average Rules: Remarkable.

////Old School Academics on Moving Average Rules: Remarkable.

Old School Academics on Moving Average Rules: Remarkable.

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(Last Updated On: January 18, 2017)

Simple Technical Trading Rules and the Stochastic Properties of Stock Returns

Abstract:

This paper tests two of the simplest and most popular trading rules–moving average and trading range break-by utilizing the Dow Jones Index from 1897 to 1986. Standard statistical analysis is extended through the use of bootstrap techniques. Overall, our results provide strong support for the technical strategies. The returns obtained from these strategies are not consistent with four popular null models: the random walk, the AR(1), the GARCH-M, and the Exponential GARCH. Buy signals consistently generate higher returns than sell signals, and further, the returns following buy signals are less volatile than returns following sell signals, and further, the returns following buy signals are less volatile than returns following sell signals. Moreover, returns following sell signals are negative, which is not easily explained by any of the currently existing equilibrium models.

Alpha Highlight:

I’m always interested in anything Josef Lakonishok has written. Why? Well, the “L” in LSV stands for Lakonishok and they managed to create a wonderful business that manages around $100 billion. Not bad.

Lakonishok and his coauthors were academics well ahead of their time. Their paper on simple moving average trading rules was published in the Journal of Finance in 1992. What makes this feat even more amazing is that they were publishing papers in top academic journals on technical trading rules in an environment that was extremely hostile towards all things “chartist.”

A quote from Burt Malkiel’s 1981 Random Walk Down Wall Street says it all:

Obviously, I am biased against the “chartist.” This is not only a personal predilection, but a professional one as well. Technical analysis is anathema to the academic world. We love to pick on it. Our bullying tactics’ are prompted by two considerations: (1) the method is patently false; and (2) it’s easy to pick on. And while it may seem a bit unfair to pick on such a sorry target, just remember: His your money we are trying to save.

The results of the study are below.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

The authors find that moving average trading rules work pretty well. The best performing rule is actually the 50-day moving average. They also identify that a 1% trading band improves the trading rule across the board.

As a value-investor by nature, reading papers on technical analysis can be a bit gut-wrenching, however, as an evidence-based investor by faith, the results are interesting!

Old School Evidence on a New School Trading Theme


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About the Author:

After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes, ETF.com, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.