Suggested Weekend Reading

Two recent articles from The Journal of Investing might be of interest.
Portfolio Rebalancing in Theory and Practice
Yesim Tokat; Nelson W. Wicas
A portfolio’s asset allocation determines the portfolio’s risk and return characteristics. To maintain its original risk and return characteristics over time, the portfolio must be rebalanced. This paper identifies the factors that influence a rebalancing strategy. We present a conceptual framework for developing rebalancing strategies that can accommodate changes in the financial market environment and in asset class characteristics, as well as account for an institution’s unique risk tolerance and time horizon. We conduct simulations to analyze how these different factors and different rebalancing guidelines affect a portfolio’s risk and return characteristics. We conclude with a review of practical rebalancing considerations.
Stupid Data Miner Tricks: Overfitting the S&P 500
David J. Leinweber
This article originated over ten years ago as a set of joke slides showing silly spurious correlations. These statistically appealing relationships between the stock market and diary products and third world livestock populations have been cited often, in Business Week, the Wall Street Journal, the book “A Mathematician Looks at the Stock Market,” and elsewhere. Students from Bill Sharpe’s classes at Stanford seem to be familiar with them. The slides were expanded to include some actual content about data mining, and reissued as an academic working paper in 2001. Occasional requests arrive from distant corners of the world, so I thank the editors of the Journal of Investing for publishing this article. Without taking a hatchet to the original, the advice offered remains valuable, perhaps even more so now that there is so much more data to mine. Monthly data arrives as a single data point, once a month. It’s hard to avoid data mining sins if you look twice. Ticks, quotes, and executions arrive in millions per minute, and many of the practices which fail the statistical sniff tests for low frequency data can now be used responsibly. Nevertheless, fooling yourself remains an occupational hazard in quantitative trading.
The first one is a reworked version of a paper recently published by Vanguard Institutional [DOWNLOAD PDF] while an earlier version of the second one can be downloaded [DOWNLOAD PDF] courtesy of the author at his blog, Nerds on Wall Street.