Factor momentum and the momentum factor

with Sina Ehsani
2021, Journal of Finance, forthcoming

Momentum in individual stock returns emanates from momentum in factor returns. Most factors are positively autocorrelated: the average factor earns a monthly return of 6 basis points following a year of losses and 51 basis points following a positive year. We find that factor momentum concentrates in factors that explain more of the cross section of returns and that it is not incidental to individual stock momentum: momentum-neutral factors display more momentum and momentum in firm-specific residuals appears to capture momentum in omitted factors. Our key result is that momentum is not a distinct risk factor; it times other factors.

Media: Featured in Wall Street Journal ("A New Way to Think About Momentum Investing”, May 5, 2019)

Award: Q-Group’s Jack Treynor 2019 Prize Winner

Long-term discount rates do not vary across firms

with Matti Keloharju and Peter Nyberg
2020, Journal of Financial Economics, forthcoming

Long-term expected returns do not appear to vary in the cross section of stocks. We show that even negligible persistent differences in expected returns, if they existed, would be easy to detect. Markers of such differences, however, are absent from actual stock returns. Our results are consistent with behavioral models and production-based asset pricing models in which firms’ risks change over time. Consistent with the lack of long-term differences in expected returns, persistent differences in firm characteristics do not predict the cross section of stock returns. Our results imply stock market anomalies have only a limited effect on firm valuations.

Asset managers: Institutional performance and factor exposures

with Joseph Gerakos and Adair Morse
2020, Journal of Finance, forthcoming

Using data on $18 trillion of assets under management, we show that actively managed institutional accounts outperformed strategy benchmarks by 88 (44) basis points on a gross (net) basis during the period 2000–2012. Estimates from a Sharpe (1992) model imply that asset managers’ outperformance came from factor exposures. If institutions had instead implemented mean-variance efficient portfolios using index and institutional mutual funds available during the sample period, they would not have earned higher Sharpe ratios. Our results are consistent with the average asset manager having skill, managers competing for institutional capital, and institutions engaging in costly search to identify skilled managers.

Are return seasonalities due to risk or mispricing? Evidence from seasonal reversals

with Matti Keloharju and Peter Nyberg
2019, Journal of Financial Economics, forthcoming

Stocks tend to earn high or low returns relative to other stocks every year in the same month (Heston and Sadka 2008). We show these seasonalities are balanced out by seasonal reversals: a stock that has a high expected return relative to other stocks in one month has a low expected return relative to other stocks in the other months. The seasonalities and seasonal reversals add up to zero over the calendar year, which is consistent with seasonalities being driven by temporary mispricing. Seasonal reversals are economically large, statistically highly significant, and they resemble, but are distinct from, long-term reversals.

The misguided beliefs of financial advisors

with Brian Melzer and Alessandro Previtero
2018, Journal of Finance, forthcoming

A common view of retail finance is that conflicts of interest contribute to the high cost of advice. Within a large sample of Canadian financial advisors and their clients, however, we show that advisors typically invest personally just as they advise their clients. Advisors trade frequently, chase returns, prefer expensive, actively managed funds, and underdiversify. Advisors' net returns of -3% per year are similar to their clients' net returns. Advisors do not strategically hold expensive portfolios only to convince clients to do the same; they continue to do so after they leave the industry.

Media: Featured in MarketWatch ("Here’s why your investment adviser isn’t making you enough money”, February 26, 2018), MoneySense ("Advisors believe their own misguided advice”, April 22, 2018), and Tuck Research & Insights ("When It Comes to Household Finances, Are You Making the Right Decisions?”, April 29, 2019)

Earnings, retained earnings, and book-to-market in the cross section of expected returns

with Ray Ball, Joseph Gerakos, and Valeri Nikolaev
2018, Journal of Financial Economics 135(1), 231-254

Retained earnings-to-market subsumes book-to-market's power to predict the cross section of stock returns in pre- and post-Compustat U.S. data as well as in international data. Retained earnings-to-market's predictive power stems entirely from accumulated earnings. Our thesis is that retained earnings-to-market---and, by extension, book-to-market---predicts returns because it is a good proxy for earnings yield (Ball,1978; Berk, 1995).

Media: Featured in Chicago Booth Review ("Why this value-investing ‘buy’ signal is out of date”, April 25, 2017) and Wall Street Journal ("Why the Traditional Way of Measuring ‘Value’ Stocks May Be History”, September 9, 2018)

The history of the cross section of stock returns

with Michael Roberts
2018, Review of Financial Studies 31(7), 2606-2649

Using data spanning the 20th century, we show that the majority of accounting-based return anomalies, including investment, are most likely an artifact of data snooping. When examined out-of-sample by moving either backward or forward in time, most anomalies' average returns and Sharpe ratios decrease, while their volatilities and correlations with other anomalies increase. The data-snooping problem is so severe that even the true asset pricing model is expected to be rejected when tested using in-sample data. The few anomalies that do persist out-of-sample correlate with the shift from investment in physical capital to intangible capital, and the increasing reliance on debt financing observed over the 20th century. Our results emphasize the importance of validating asset pricing models out-of-sample, question the extent to which investors learn of mispricing from academic research, and highlight the linkages between anomalies and economic fundamentals.

Award: Marshall E. Blume Prize, First Prize for Best Paper Published by the Rodney L White Center, 2017 (announcement)

Decomposing value

with Joseph Gerakos
2018, Review of Financial Studies 31(5), 1825-1854

Firms move between growth and value because of either changes in size or the book value of equity. We show that the value premium is specific to the variation in book-to-market ratios that emanates from changes in firm size. A factor based on this variation earns the entire value premium; one based on the remaining variation earns no premium. Hence, not all high book-to-market firms earn value premium, and some low book-to-market firms earn value-like returns. This disconnect between book-to-market and the value premium provides testable restrictions for theories of the value premium. Many models price portfolios sorted by size and book-to-market. None distinguish firms that earn the value premium from those that have a high book-to-market but do not earn the premium.

Award: Second prize in the academic competition at the Chicago Quantitative Alliance (CQA) Fall 2012 Conference.

Accruals, cash flows, and operating profitability in the cross section of stock returns

with Ray Ball, Joseph Gerakos, and Valeri Nikolaev
2016, Journal of Financial Economics 121(1), 28–45

A cash-based operating profitability measure (that excludes accruals) outperforms other measures of profitability and subsumes accruals in predicting the cross section of average returns. Firms with high accruals earn low average returns because they are less profitable on a cash basis.

Note: Fama and French (2015) compare our cash-based operating profitability factor against two alternative profitability factors, and find that the cash factor improves the description of average returns for many left hand side sorts.

Award: First prize in the academic competition at the Chicago Quantitative Alliance (CQA) Fall 2015 Conference.

Retail financial advice: Does one size fit all?

with Stephen Foerster, Brian Melzer, and Alessandro Previtero
2017, Journal of Finance 72(4), 1441-1482

Advisor fixed effects explain considerably more variation in portfolio risk and home bias than a broad set of investor attributes that includes risk tolerance, stage in the lifecycle and financial sophistication. An advisor's own asset allocation strongly predicts the allocations chosen on clients' behalf.

Awards: 2015 CFA Society & Hillsdale Canadian Investment Research Award (announcement), 2018 Amundi Smith Breeden Prize (list of prize winners)

Media: Featured in Wall Street Journal ("Client Portfolios May Match Advisers’ Own Asset Allocation", December 12, 2014), Globe and Mail ("Make portfolio-building a priority to justify investment adviser fees," December 5, 2014; "Putting a number on the value of financial advice: 3%," June 14, 2015), Fiscal Times ("Expensive, one-size-fits-all advice," December 10, 2014), Booth Capital Ideas ("Why financial advice isn't worth the fees," February 25, 2015), and Kellogg Insight ("What Good is a Financial Advisor?," November 2, 2016)

Reading the tea leaves: Model uncertainty, robust forecasts, and the autocorrelation of analysts' forecast errors

with Walter Torous and James Yae
2016, Journal of Financial Economics 122(1), 42–64

Analysts optimally underreact to new information if they try to provide forecasts that are robust to model misspecification. We estimate that analysts' concerns for model misspecification explain approximately 60% of the autocorrelation in analysts' forecast errors. Our model of robust forecasting applies not only to analysts' forecasts but to all model-based forecasts.

Return seasonalities

with Matti Keloharju and Peter Nyberg
2016, Journal of Finance 71(4), 1557–1590

We document return seasonalities in individual stock returns, portfolio returns, anomalies, commodities, international stock market indices, and at the daily frequency. These return seasonalities overwhelm unconditional differences in expected returns.

Note: To replicate the results on seasonalities in daily returns, you need to account for market closures due to U.S. holidays. As the lag k grows, the likelihood that the days go out of sync increases; a regression at lag k=200, for example, is very unlikely a Monday-on-Monday (or Tuesday-on-Tuesday, and so forth) regression. You should "pad" the data with missing values so that there is an observation for every stock-day even when the market is closed.

Award: AQR Insight Award Finalist 2015 [Announcement]

Deflating profitability

with Ray Ball, Joseph Gerakos, and Valeri Nikolaev
2015, Journal of Financial Economics 117(2), 225–248 (lead article)

An alternative measure of firm profits, operating profits, exhibits a far stronger link with expected returns than either net income or gross profit.

Note: The XSGA variable in Compustat adds to the SG&A reported by the company other items such as R&D expenses. This issue is discussed on p. 254 of Volume 5 of Compustat Manuals. You can recover the reported SG&A by subtracting XRD from XSGA.

Media: Featured in Forbes ("The Profitability Factor Redux: Super-Duel in Space," June 2, 2014)

Market reactions to tangible and intangible information revisited

with Joseph Gerakos
2016, Critical Finance Review 5, 135–163

A decomposition of book-to-market ratio into stock and book returns creates a book return polluted by past book-to-market ratios, stock returns, net issuances, and dividends. Our results cast doubt on the argument that book-to-market forecasts returns because it is a good proxy for the intangible return.

Reverse survivorship bias

2013, Journal of Finance 68(3), 789–813 (lead article)

The distribution of estimated alphas is biased downwards if funds tend to disappear following poor performance. This paper estimates a structural model to correct for this "reverse survivorship bias."

Media: Mutual fund research featured in Time magazine ("The Triumph of Index Funds," September 18, 2014) and "The Big Question: Are successful active managers lucky or skilled?" (Capital Ideas, August 2014).

Do investors buy what they know? Product market choices and investment decisions

with Matti Keloharju and Samuli Knüpfer
2012, Review of Financial Studies 25(10), 2921–2958 (lead article)

Individuals’ product market choices influence their investment decisions.

Lack of anonymity and the inference from order flow

with Gideon Saar
2012, Review of Financial Studies 25(5), 1414–1456

We demonstrate that broker identity is a powerful signal about the identity of investors who initiate trades, and that the broker ID signal is important enough to affect prices.

IQ, trading behavior, and performance

with Mark Grinblatt and Matti Keloharju
2012, Journal of Financial Economics 104(2), 339–362 

Reprinted in Household Finance, M. Haliassos (ed.), The International Library of Critical Writings in Economics series, Edward Elgar Publishing (2015)

High-IQ investors are less subject to the disposition effect and more aggressive about tax-loss trading, and they exhibit superior market timing, stock-picking skill, and trade execution.

Award: Runner-up for Goldman Sachs International - Best Conference Paper Award at the 2010 European Finance Association Conference.

IQ and stock market participation

with Mark Grinblatt and Matti Keloharju
2011, Journal of Finance 66(6), 2121–2164

Reprinted in Household Finance, M. Haliassos (ed.), The International Library of Critical Writings in Economics series, Edward Elgar Publishing (2015)

Stock market participation is monotonically related to IQ, controlling for wealth, income, age, and other demographic and occupational information.

Media: Featured in Bloomberg Businessweek ("Smart Money Owns More Equities Says IQ Study of Who Buys Stocks," January 19, 2012) and New York Times ("What High-I.Q. Investors Do Differently," February 26, 2012)

Why do (some) households trade so much?

2011, Review of Financial Studies 24(5), 1630–1666

When agents can learn about their abilities as active investors, they rationally "trade to learn" even if they expect to lose from active investing. This learning-about-type mechanism may explain why some households begin experimenting with day trading, lose money, and then quit. 

Jensen's inequality, parameter uncertainty, and multi-period investment

with Mark Grinblatt
2011, Review of Asset Pricing Studies 1(1), 1–34 (lead article)

The proper application of Jensen’s inequality to the multi-period investment decision turns finance intuition on its head: multi-period investments with negative risk premia can be profitable, risk-averse investors can have infinite demand for risky securities, settings exist in which risk-averse investors should not diversify, and demand for mutual funds with negative alphas may be rational.

Do limit orders alter inferences about investor performance and behavior?

2010, Journal of Finance 65(4), 1473–1506

Use of limit orders drives a wedge between investors' intentions and realized trades. Limit orders are contrarian; they are more likely to execute when there are news or asymmetric information; and they lose money when new information arrives to the market. When we try to infer investors' information sets or intentions from their realized trades, our inferences are biased. I call this bias the "limit order effect."

Media: Featured in the Chicago Booth Capital Ideas (October 2007) and the Economist Intelligence Unit.