This chart on creating shareholder value through ESG engagement is useful when evaluating if ESG practices boost valuations.
The following exhibit, which is useful to the subject of mitigating risks with factor strategies, provides the total return of the four benchmark portfolios and the five anomaly portfolios.
The illiquid nature of the asset class makes the demystifying of private equity returns difficult to achieve under any circumstances, but the framework presented in this article should move the reader closer to the goal.
How do you separate the signal from the noise? To have confidence that a factor premium, or strategy, isn’t just the result of data mining - a lucky/random outcome - we recommended that you should require evidence that the premium has been not only persistent over long periods of time and across economic regimes, but also pervasive across sectors, countries, geographic regions and even asset classes; robust to various definitions (for example, there has been both a value and a momentum premium using many different metrics); survives transactions costs; and has intuitive risk- or behavioral-based explanations for the premium to persist.
In this article about asset pricing theory, we examine the research on the impact of technological advances that displace human labor in favor of machine capital to asset pricing.
The past decade has seen a dramatic growth in sustainable investing—applying environmental, social and governance (ESG) criteria to investment strategies. Investments considered environmentally friendly are often referred to as “green,” while “brown” denotes the opposite. Important questions for investors are: What are the expected returns to green stocks? What does their past performance tell us about their future expected returns? We begin by looking at what economic theory tells us our expectations should be.
Although geopolitical risk has traditionally been approached from a qualitative aspect, what makes it a novel risk is the application of innovative techniques to measure it.
To determine if a multi-factor approach has provided diversification benefits in terms of exposure to economic cycle risks, the research team at Counterpoint evaluated returns to multifactor long-short strategies, stocks, and 1-month T-bills in a variety of economic conditions (recession or no recession, high or no high inflation, and stagflation) over the period July 1963-August 2022.
Pastor, Stambaugh, and Taylor (2015) and Zhu (2018) provide significant evidence of decreasing returns to scale (DRS) at both the fund and industry levels. The authors examine the robustness of their inferences after Adams, Hayunga, and Mansi (2021) critique the above two studies.
The paper documents that return forecasts from machine learning methods lead to superior out-of-sample returns in emerging markets.
Given that tightening monetary policy increases economic risks, Simpson and Grossman provided compelling evidence of a risk explanation for the size factor. For those investors who engage in tactical asset allocation strategies (market timing), their evidence suggests that it might be possible to exploit the information. Before jumping to that conclusion, I would caution that because markets are forward-looking, they should anticipate periods of Fed tightening and the heightened risks of small stocks.
In this article, we examine the research on investing during inflationary regimes such as deflation, inflation, and stagflation. Factors perform relatively well in all regimes on a real basis.
Since it is likely that both the Relative Sentiment and Trend Following strategies will underperform at some points in the future, “a 50-50 combination of TF and RS might reduce the emotional volatility an investor may experience from holding only the underperforming strategy.”
We examine trend-following rules when the stock returns follow a two-state process that randomly switches between bull and bear markets.