Volume 17, No. 3, Third Quarter 2019

Does Trading by ETF and Mutual Fund Investors Hurt Performance? Evidence from Time- and Dollar-Weighted Returns

by: Ananth Madhavan and Aleksander Sobczyk

This paper analyzes the “return gap” between internal rate of returns that account for intermediate investor flows (“dollar-weighted returns”) and more familiar buy-and-hold returns that funds typically must report. Our sample constitutes all US-domiciled open- end mutual funds and exchange-traded funds (ETFs), and covers both fixed income and equity funds, as well as active and index styles of management. We find that return chasing behavior explains the cross-sectional pattern of the return gap. We conclude that high turnover of liquid ETFs does not lead to sub-par returns for investors in these funds.

How to Beat the Machines Before They Beat You

by: Vineer Bhansali

The use of “big” data, algorithms and machine learning is disrupting investment management. By carefully selecting domains where data is sparse and there is possibility of regime changes, a human investor can not only survive, but also thrive in a world of investment machines.

Embedded Betas and Better Bets: Factor Investing in Emerging Market Bonds

by: Johnny Kang, Kevin So and Thomas Tziortziotis

We document novel empirical insights driving the prices of sovereign external emerging market bonds. In the time series, we examine the market portfolio’s time-varying exposures to a broad set of macro factors (rates, credit, currency, and equity) and identify these embedded betas as key drivers of its excess returns. In the cross-section, we construct complementary value and momentum style factors and demonstrate their ability to explain country expected returns. Building off these insights, we introduce a simple risk-on versus risk-off framework to characterize the correlation structure spanning our macro and style factors. Lastly, we show how our style factors can be incorporated into an optimized long-only portfolio to generate outperformance relative to a value-weighted benchmark portfolio.

Return Predictability and Market-Timing: A One-Month Model

by: Blair Hull, Xiao Qiao and Petra Bakosova

We use weighted least squares to combine 15 diverse variables to build a predictive model for the one- month-ahead market excess returns.We transform our forecasts into investable positions to form a market-timing strategy. From 2003 to 2017, our strategy had 16.6% annual returns with 0.92 Sharpe ratio and 20.3% maximum drawdown. In comparison, the S&P 500 had annual returns of 10%, 0.46 Sharpe ratio, and maximum drawdown of 55.2%.We also combine our one-month model with the six-month model of Hull and Qiao (2017). The combined model had 15% annual returns, Sharpe ratio of 1.12, and maximum drawdown of 14%

Bill Gross’Alpha: The King Versus the Oracle

by: Aaron Brown and Richard Dewey

We set out to investigate whether “Bond King” Bill Gross demonstrated alpha (excess average return after adjusting for market exposures) over his career, in the spirit of earlier papers asking the same question of “Oracle of Omaha,” Warren Buffett. The journey turned out to be more interesting than the destination. We do find, contrary to previous research, that Gross demonstrated alpha at conventional levels of statistical significance. But we also find that result depends less on the historical record than on whether we take the perspective of academics interested in market efficiency, investors picking a fund or someone (say a potential employer) asking whether a manager has skill or is throwing darts to pick positions. These are often thought to be overlapping or even identical questions. That is not completely unreasonable in equity markets, but in fixed income these are distinct. We also find quantitative differences, mainly that fixed-income securities have much higher correlations with each other than equities, make alpha 4.5 times as hard to measure for Gross than Buffett.We do not think our results will have much practical effect on attitudes toward Gross as an investor, but we hope they will advance understanding of what alpha means and appropriate ways to estimate it.

Practitioner’s Digest • Vol. 17, No. 3

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.

Do You Know the Provenance of Your Alternative Data

by: 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.

The Son also Rises: Surnames and the History of Social Mobility

by: Gregory Clark • reviewed by: Savannah Smith

“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.

The F-Utility of Wealth: It’s All Relative

by: Arun Muralidhar

Finance theory is based on a very simple, yet critical assumption that “individuals maximize the expected utility of wealth”. However, there are three crucial elements of this simple six-word phrase that does not really stand the test of what investors actually do and one could argue that the incorrect use of Modern Portfolio Theory (MPT) has led to the looming global retirement crisis. First, investors care about relative wealth (i.e., wealth relative to a goal) rather than absolute wealth, popularly called “Goals-Based Investing”. Second, individuals (or principals) are not always the ultimate decision-makers—rather, many investment decisions are delegated to agents, which distorts behavior. Third, and most crucially, most investors do not appear to focus on utility functions, but rather seek to maximize risk-adjusted return. Instead, finance theory should start with the assumption that “investors delegate to maximize relative risk-adjusted returns.” This paper seeks to show how incorporating these three simple and completely realistic changes impacts asset pricing, asset allocation, and the correct use of risk-adjusted performance measures. While the initial step requires a rethink of finance theory and models, the more urgent goal is to ensure retirement security as this new approach leads to financial innovation, better regulation, investments and retirement outcomes