The fourth quarter issue opens with the last in in the series reviewing 75 years of investment practice in the Financial Analysts Journal: “Environmental, Social and Governance Issues and the Financial Analysts Journal,” by Laura Starks, looks back over the Journal’s work since 1945 to show how long academics and investment practitioners have been grappling with environmental, social and governance issues; well before the ESG or SRI terminology became commonplace. In fact, our Journal was first! Over the years we’ve been at the forefront of this knowledge development with articles on the social responsibility of business and its investors, the performance of investments following ESG or SRI principals, the effects of divestment, climate risk, impact investing and the need for more ESG disclosure. This article will take you through the essential ESG arguments then and now and demonstrate how the insights from many decades ago remain relevant today for investor decision making. If you missed the earlier pieces in this series celebrating 75 years of the Financial Analysts Journal, see Andrew Lo’s piece, “The Financial System Red in Tooth and Claw: 75 Years of Co-Evolving Markets and Technology;” the endowment study “Seventy-Five Years of Investing for Future Generations;” Will Goetzmann’s “The Financial Analysts Journal and Investment Management;” and from Stephen Brown, “The Efficient Market Hypothesis, the Financial Analysts Journal, and the Professional Status of Investment Management.”

This issue's first research article treats the implementation of the Shanghai–Hong Kong Stock Connect in 2014 as an experiment and observes the effects on corporate investment efficiency that resulted. “Capital Market Liberalization and Investment Efficiency: Evidence from China” tells us about markets as a whole as a result of observations in China. The authors demonstrate that corporate investment efficiency is improved through market liberalization, chiefly through improved information disclosure and corporate governance. Governance and emerging market scholars can cite this study as proof that the gradual liberalization of a stock market and the introduction of foreign investors improves corporate governance, strengthens investor protection, and ultimately promotes the sustainable development of the capital market. Readers who are uninitiated in Chinese markets will find an excellent cheat sheet in the early part of this article, which provides a brief history of the liberalization of Chinese markets from 2002 as a context for the study.

In 2004, the Financial Analysts Journal published the seminal hedge fund replication work by Fung and Hsieh. Since then, the bank risk premia market has emerged and the second research article in this issue, “Hedge Funds vs Alternative Risk Premia,” provides the first analysis of these bank risk premia products in comparison to corresponding hedge fund performances. Author Phillipe Jorion finds several risk premia within equities, rates, and credit that provide significantly positive returns. In fact, their explanatory power improves on the well used Fung–Hsieh 7 factor model. In the quantitative hedge fund space particularly, this article provides evidence of improved hedge fund index replication.

Next, the simply titled “Index + Factors + Alpha” addresses the question of how best to allocate among the three return sources: market index, factors or smart beta, and alpha-generating funds. The authors derive and demonstrate their proposed method of using a Bayesian framework where the investor sets priors on Sharpe ratios or information ratios in excess of the index and factor strategies. Don't miss their step-by-step demonstration of how to implement this intuitively appealing model in your investment process.

In “Boosting the Equity Momentum Factor in Credit,” authors Kaufmann, Messow, and Vogt show how machine learning techniques can be used to improve the quality of equity momentum signals used in fixed-income investing. This is a cross-asset strategy using information from equities to predict returns in their corresponding credit listings but the real contribution is to show how alpha can be doubled using boosted regression trees. If you need to catch up on machine learning in general, the 2019 article “Machine Learning for Stock Selection” makes very good pre-reading.

In the next article, “ESG Rating Disagreement and Stock Returns,” three Swiss authors focus in on the dispersion among ESG ratings. There are other papers covering why ESG ratings differ but this one is about how much the ratings differ and which aspects are most dispersed. They extend the analysis to the relationship between these rating dispersions and cost of capital and, by extension, equity performance. This article makes use of a particularly comprehensive set of rating providers — seven of them — so if you use ESG ratings at all, you will find the authors’ data and rating comparisons worth a look. 

Finally, in the last article of this issue, authors from Vanguard demonstrate that tax-loss harvesting is not one-size-fits-all. In fact, it’s not worth the cost for everyone. “Tax-loss Harvesting: An Individual Investor’s Perspective” uses investor archetypes to represent the spectrum of clients who may be in the market for tax managed investments and demonstrates that there is substantial dispersion in the outcomes. Some of that dispersion is environmental but most of the dispersion in benefits from tax-loss harvesting are a result of the investor’s own characteristics (their own tax rates, and how much offsetting income they have). Private wealth practitioners can track the development of tax management through a number of recently published tax-related articles, including “An Empirical Evaluation of Tax-Loss Harvesting Alpha;” “Tax-Managed Factor Strategies;” and “The Tax Benefits of Separating Alpha From Beta."