Editor’s Letter

Welcome to the Spring issue of The Journal of Beta Investment Strategies.

We started covering exchange-traded funds (ETFs) over 20 years ago with our ETF Guides. Those guides became The Journal of Index Investing, which is now The Journal of Beta Investment Strategies. With this issue, we return to our original topic of ETFs. ETFs continue to see record inflows, massive product launches, and a sustained push by large-scale asset managers into the space. This issue will cover the latest changes in the field.

To begin the issue, we have a commentary from Madden looking at ETFs and liquidity. It provides some useful insight into liquidity and risks when trading ETFs.

Next, McMillan and Myers examine the risk–return profile of commodity ETFs. The article shows that using a multifactor momentum model applied to a single exchange-traded product can do a good job of providing investors with a superior exposure to commodities while also providing a useful benchmark for evaluating the true alpha associated with adjacent strategies such as commodity trading advisors.

Dolvin and Foltice study stop-loss orders trading in ETFs. They find that a stop-loss strategy can work to enhance systematic risk-adjusted returns and that implementing trailing stop-loss orders can help offset the disposition effect, a behavioral bias that leads investors to sell winning stocks too soon and hold losing stocks too long.

Our next ETF article is by Malhotra. This study compares the risk-adjusted performance of technology mutual funds and ETFs. The author shows that returns on technology mutual funds and ETFs were highly correlated with the DJIA US Technology, NASDAQ 100 Tech, NY ARCA TECH 100, and S&P 500 Information Technology benchmark indexes. The article suggests that technology mutual fund managers may have some market timing ability but no security selection skill.

Slen, Rankin, Lin, and Yiu examine option strategies that may provide meaningful benefits in terms of increasing potential returns, reducing risk, and generating income and are accessible via ETFs.

Next, Schmidt uses a news-based model to look at stock returns using macroeconomic, industry, and company-specific news. He examines relevant ETF returns and an optimized ARMA-GARCH model.

Finally, Hopf, Hudert, Schmitt, and von Thaden close this issue using state-of-the-art statistical tests to show that excess returns cannot be regarded as normally distributed for a considerable number of ETFs.

As always, we welcome your submissions on factor investing, ETFs, smart beta, indexes, passive investing, or related subjects. We value your comments and suggestions, so please email us at journals{at}investmentresearch.org.

Brian R. Bruce

Editor-in-Chief

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