Volume 22, No. 1, First Quarter 2024

Practitioner’s Digest • Vol. 22, No. 1

The “Practitioners Digest” emphasizes the practical significance of manuscripts featured in the “Insights” and “Articles” sections of the journal. Readers who are interested in extracting the practical value of an article, or who are simply looking for a summary, may look to this section.

Limiting Investment Opportunity Sets, Asset Pricing, and the Roll Critique

by: Bob Korkie and H. J. Turtle

We consider the impact of low volatility assets on the investment opportunity set (IOS) and resultant asset pricing. The limiting IOS and its finite investable proxy imply an asset pricing model that differs from standard asset pricing models. The Sharpe (1964)–Lintner (1965) CAPM with a unique market portfolio is not descriptive of asset pricing and the zero-beta rate of the Black model, converges to the exogenous riskless rate. Spanning tests show that the limiting IOS, with estimated slope and upper bound Sharpe ratio of 0.18, is given by the linear limiting IOS asymptotes, implying multiple efficient portfolios of risky assets. We find no evidence of any efficient portfolio with only positive weights, implying that the market portfolio is not mean–variance efficient.

Accelerating the Capital Solution to Climate Change

by: Yu (Ben) Meng, Anne Simpson, Anna Snider and Christina Yi

The missing “I’s” of information and incentives have restrained the potential of the capital markets in previous decades to respond to the growing demand for climate solutions. Progress on both fronts in recent years, however, is moving us rapidly beyond an inflection point in climate investing to its turning point. In this article, the authors build upon previous work to examine this progress as well as analyse the potential for an enhanced return—a “greenium”—from investments in the transition to a low-carbon economy.

Biotech Asset Valuation Methods: A Practitioner’s Guide

by: Amitabh Chandra and Sumon Mazumdar

Biotech innovations lead to the development of life-saving drugs and vaccines. However, bringing a new drug to market is an expensive,risky, and time-consuming process. According to one survey, the probability that a drug that has completed pre-clinical trials, would successfully pass all three stages of clinical trials (the primary source of regulatory risk) and receive the FDA’s approval to be commercialized was less than 12%, is expected to take nearly 10 years on average, and costs $1.4 billion (in 2013 dollars, including the cost of compounds abandoned during testing). Biotech startups, which undertake such drug development efforts, typically have no existing revenue streams, and rely heavily on venture capitalists (VCs) for funding. This requires the VC and the startup’s founders to agree on the value of the drug in development (or equivalently, the startup’s value as the drug in development may be the startup’s only asset).

Unrealistic Expectations: The Futility of Precisely Estimating a Stock’s Expected Return

by: Sanjiv R. Das and Daniel Ostrov

...dedicated to the memory of Mark S. Joshi, who worked to make results like these better known

We reprise the result that even underthe best circumstances, it is impossible to use observed return data for a stock to determine its expected return with any useful precision in a reasonable time frame. This is because the sample mean of returns, which is the best estimator for the expected return, has a large standard error. More specifically, the formula for this standard error is σ/√T, where σ is the stock’s annual volatility and T is the number of years over which the returns are sampled. We note in particular that this standard error formula is not reduced by increasing the frequency of sampling the returns within the given time frame T.

Managing Market Downturns with NAV Loans

by: Ivan Asensio and Seoyoung Kim

“Case Studies” presents a case pertinent to contemporary issues and events in investment management. Insightful and provocative questions are posed at the end of each case to challenge the reader. Each case is an invitation to the critical thinking and pragmatic problem solving that are so fundamental to the practice of investment management.

Scary Smart: The Future of Artificial Intelligence and How You Can Save Our World

by: Mo Gawdat • reviewed by: Jana Minn, Senior Quantitative Researcher, State Street Associates

“Book Reviews” identifies important, and often popular, new books from a wide range of investment topics. Beyond providing a summary and review of the content and style of the books, “Book Reviews” seeks to contribute to a conscious, critical, and informed approach to investment literature.