To open this issue, Elimelakh, Gillman, and Warren show how active share can be decomposed into segment and stock-specific exposures to create an “active share risk profile.” The method is demonstrated for global equity portfolios by attributing active share into contributions from country, sector, stock-specific, and non-equity positions within portfolios. Podkaminer, Tollette, and Siegel review the history and causes of real interest rate fluctuations using a nonmathematical “Very Simple Macro Model,” then assess the risks to each major asset class (and also to liabilities) from likely changes in the real rate. The objective is to help investors defend their portfolios against this important risk.
Next, Richey uses an EGARCH model to investigate whether a portfolio of sin stocks is less resistant to downside risk or losses during market downturns than is the S&P 500. He illustrates the defensive nature of sin stocks and helps reinforce the notion that sin stocks have some immunity from downside risk due to cyclical fluctuations and economic downturns. Tanner, Chittenden, and Payne evaluate style drift among value and growth funds and find that mutual fund managers frequently hold stocks outside their identified style; this effect is larger for Value Fund managers holding Growth stocks. They find that on average, Growth fund managers earn higher returns than their Index on these “crossover” stock holdings.
As we continue, Lamponi presents a comparison of the trend following (or time series) and cross-sectional momentum methodologies based on statistical factors. By creating models in four asset classes (Equity, Forex, Interest Rate, and Commodity) results show that the categorization is of minor importance, as returns are driven by exposure to factors, which can be modified in multiple ways, for example, by changes in the portfolio construction methodology. Gidwani evaluates how ESG ratings behave over time. Findings suggest that investors and company managers should both realize that ESG ratings are likely to change toward the mean and that this pattern does not necessarily mean that a good company is getting worse or a bad one is getting better. Morais and Morey discuss the “file drawer problem,” a publication bias where journal editors are much more likely to accept empirical papers with statistically significant results than those with statistically non-significant results. They examine the empirical papers presented at the annual Financial Management Association (FMA) conference from 2014–2018 and find that there is also a significant file drawer problem at finance conferences.
To conclude the issue, Frankfurter presents a commentary on the phenomenon of “bubbles.”
As always, we welcome your submissions. We value your comments and suggestions, so please email us at journals{at}investmentresearch.org.
Brian Bruce
Editor-in-Chief
- © 2020 Pageant Media Ltd