Knowledge that Transforms

Journal Article Competing Theories of Financial Anomalies Get access Alon Brav, Alon Brav Duke University Address correspondence to Alon Brav, Fuqua School of Business, Duke University, Box 90120, Durham, NC 27708-0120, or e-mail: [email protected]. Search for other works by this author on: Oxford Academic Google Scholar J.B. Heaton J.B. Heaton Bartlit Beck Herman Palenchar & Scott and Duke University Search for other works by this author on: Oxford Academic Google Scholar The Review of Financial Studies, Volume 15, Issue 2, 2 January 2002, Pages 575–606, https://doi.org/10.1093/rfs/15.2.575 Published: 16 June 2015

This article theoretically explores the characteristics underpinning quadratic term structure models (QTSMs), which designate the yield on a bond as a quadratic function of underlying state variables. We develop a comprehensive QTSM, which is maximally flexible and thus encompasses the features of several diverse models including the double square-root model of Longstaff (1989), the univariate quadratic model of Beaglehole and Tenney (1992), and the squared-autoregressive-independent-variable nominal term structure (SAINTS) model of Constantinides (1992). We document a complete classification of admissibility and empirical identification for the QTSM, and demonstrate that the QTSM can overcome limitations inherent in affine term structure models (ATSMs). Using the efficient method of moments of Gallant and Tauchen (1996), we test the empirical performance of the model in determining bond prices and compare the performance to the ATSMs. The results of the goodness-of-fit tests suggest that the QTSMs outperform the ATSMs in explaining historical bond price behavior in the United States.

This article studies momentum in stock returns, focusing on the role of industry, size, and book-to-market (B/M) factors. Size and B/M portfolios exhibit momentum as strong as that in individual stocks and industries. The size and B/M portfolios are well diversified, so momentum cannot be attributed to firm- or industry-specific returns. Further, industry, size, and B/M portfolios are negatively autocorrelated and cross-serially correlated over intermediate horizons. The evidence suggests that stocks covary “too strongly” with each other. I argue that excess covariance, not underreaction, explains momentum in the portfolios.

This article uses a new dataset of credit card accounts to analyze credit card delinquency, personal bankruptcy, and the stability of credit risk models. We estimate duration models for default and assess the relative importance of different variables in predicting default. We investigate how the propensity to default has changed over time, disentangling the two leading explanations for the recent increase in default rates—a deterioration in the risk composition of borrowers versus an increase in borrowers’ willingness to default due to declines in default costs. Even after controlling for risk composition and economic fundamentals, the propensity to default significantly increased between 1995 and 1997. Standard default models missed an important time-varying default factor, consistent with a decline in default costs.

Under the standard real options approach to investment under uncertainty, agents formulate optimal exercise strategies in isolation and ignore competitive interactions. However, in many real-world asset markets, exercise strategies cannot be determined separately, but must be formed as part of a strategic equilibrium. This article provides a tractable approach for deriving equilibrium investment strategies in a continuous-time Cournot–Nash framework. The impact of competition on exercise strategies is dramatic. For example, while standard real options models emphasize that a valuable “option to wait ” leads firms to invest only at large positive net present values, the impact of competition drastically erodes the value of the option to wait and leads to investment at very near the zero net present value threshold. The real options approach to analyzing investment under uncertainty has become part of the mainstream literature of financial economics. The real options approach to investment now typically comprises an entire chapter in corporate finance textbooks [see, e.g., Brealey and Myers (2000) and Van Horne (1998)]. Essentially the real options approach posits that the oppor-tunity to invest in a project is analogous to an American call option on the investment opportunity. Once that analogy is made, the vast and rigorous machinery of financial options theory is at the disposal of real investment analysis. The real options approach is well summarized in Dixit and Pindyck (1994) and Trigeorgis (1996).1 A feature that the vast majority of real options articles have in common is the lack of strategic interaction across option holders. Investment (exercise) strategies are formulated in isolation, without regard to the potential impact of other firms ’ exercise strategies. The standard starting point for such models is an exogenous process for underlying asset values (e.g., the stock price in

This article examines whether country-specific or global versions of Fama and French's three-factor model better explain time-series variation in international stock returns. Regressions for portfolios and individual stocks indicate that domestic factor models explain much more time-series variation in returns and generally have lower pricing errors than the world factor model. In addition, decomposing the world factors into domestic and foreign components demonstrates that the addition of foreign factors to domestic models leads to less accurate in-sample and out-of-sample pricing. Practical applications of the three-factor model, such as cost of capital calculations and performance evaluations, are best performed on a country-specific basis. Copyright 2002, Oxford University Press.

We examine the dynamic relation between return and volume of individual stocks. Using a simple model in which investors trade to share risk or speculate on private information, we show that returns generated by risk-sharing trades tend to reverse themselves, while returns generated by speculative trades tend to continue themselves. We test this theoretical prediction by analyzing the relation between daily volume and first-order return autocorrelation for individual stocks listed on the NYSE and AMEX. We find that the cross-sectional variation in the relation between volume and return autocorrelation is related to the extent of informed trading in a manner consistent with the theoretical prediction.

We analyze 1,607 investors who switched from phone-based to online trading during the 1990s. Those who switch to online trading perform well prior to going online, beating the market by more than 2% annually. After going online, they trade more actively, more speculatively, and less profitably than before—lagging the market by more than 3% annually. Reductions in market frictions (lower trading costs, improved execution speed, and greater ease of access) do not explain these findings. Overconfidence—augmented by self-attribution bias and the illusions of knowledge and control—can explain the increase in trading and reduction in performance of online investors.

Stock market returns are significantly correlated with inflation and money growth. The impact of real macroeconomic variables on aggregate equity returns has been difficult to establish, perhaps because their effects are neither linear nor time invariant. We estimate a GARCH model of daily equity returns, where realized returns and their conditional volatility depend on 17 macro series' announcements. We find six candidates for priced factors: three nominal (CPI, PPI, and a Monetary Aggregate) and three real (Balance of Trade, Employment Report, and Housing Starts). Popular measures of overall economic activity, such as Industrial Production or GNP are not represented.

One of the puzzles regarding initial public offerings (IPOs) is that issuers rarely get upset about leaving substantial amounts of money on the table, defined as the number of shares sold times the difference between the first-day closing market price and the offer price. The average IPO leaves $9.1 million on the table. This number is approximately twice as large as the fees paid to investment bankers and represents a substantial indirect cost to the issuing firm. We present a prospect theory model that focuses on the covariance of the money left on the table and wealth changes. Our reasoning also provides an explanation for a second puzzling pattern: much more money is left on the table following recent market rises than after market falls. This results in an explanation of hot issue markets. We also offer a new explanation for why IPOs are underpriced.