Speculative language in corporate disclosures can convey valuable information about firms’ fundamentals. We evaluate this idea by developing a measure for speculative statements based on sentences marked with the “weasel tag” on Wikipedia. In the 16-week test period after filing, greater use of speculative statements in 10-Ks predicts higher and nonreverting abnormal returns, more insider and informed buying, and higher news sentiment. These findings imply that managers’ usage of speculative language in 10-Ks reflects voluntary disclosure of their private information about the positive prospects of events when market implications of the events are uncertain and thus have room for (re)interpretation.

This study examines the relation between employee incentives and corporate innovation. We find that firms with a higher defined benefit (DB) pension value secure more patents and patent citations. We further show that pension freezes, which stop the accumulation of pension obligations, negatively affect innovation outcomes. The value of a DB plan enhances innovation by motivating employees to produce higher output and through loyalty. However, pension deficits impede innovation because of the nature of inside debt. Overall, our findings call for a fresh look at pensions by policy makers and practitioners, given the historic shift away from DB plans.

We examine the role private equity (PE) sponsors play in the resolution of financial distress of portfolio companies. PE-backed firms have higher leverage and default at higher rates than other companies borrowing in leveraged loan markets. But, PE-backed firms restructure more quickly, avoid bankruptcy court more often, and liquidate less often compared to other highly leveraged firms experiencing financial distress. PE owners are also more likely to retain control post-restructuring, often by infusing capital as firms approach distress. While default frequencies are higher among PE-backed firms, PE investors appear to manage financial distress at lower cost compared to other owners.

Standard Bayesians’ beliefs converge when they receive the same piece of new information. However, when agents initially disagree and have uncertainty about the precision of a signal, their disagreement might instead increase, despite receiving the same information. We demonstrate that this divergence of beliefs leads to a unimodal effect of the absolute surprise in the signal on trading volume. We show that this prediction is consistent with the empirical evidence using trading volume around earnings announcements of U.S. firms. We find evidence of elevated volume following moderate surprises and depressed volume following more extreme surprises, a pattern that is more pronounced when investors hold more distant prior beliefs and are more uncertain about earnings’ precision. The evidence is consistent with the model where investors disagree about stocks’ expected returns and do not know the precision of earnings as a signal about the firm’s value.

As argued by Jensen (1993), the primary tasks of a firm’s board of directors are to advise, hire, fire and determine the level and form of managerial compensation. Managerial pay can be structured as part cash and in part be tied to a performance index, such as corporate earnings or the firm’s stock price. The latter effectively aligns the interest of managers with those of stockholders, which in turn reduces agency problems related to free cash flow, managerial time horizons and effort levels. At the same time, stock-based compensation increases managerial exposure to non-diversifiable risk, which may cause risk-averse managers to underinvest in risky projects. The trade-off between the benefits of managerial incentive alignment and the cost of underinvestment is largely an empirical issue, and the widespread observation that managerial compensation is primarily paid in cash 1 suggests that managerial risk aversion weighs heavily or that boards generally resort to substitute monitoring mechanisms. The paper by Angbazo and Narayanan (1997) is part of a rapidly growing empirical literature attempting to identify important cross-sectional determinants

Boquist, Racette, and Schlarbaum [3] and Livingston [6] show that a security systematic risk may be expressed as a function of its duration. These results have led to research examining the role of duration in explaining systematic risk, but Lanstein and Sharpe [5] indicate that Livingston's expression relies on the implicit assumption that extra-market covariances between securities are insignificant. Lanstein and Sharpe argue that such an assumption is unwarranted. They find a significant negative relationship between extra-market covariances and differences in duration between paired samples of common stock. Their paper suggests that duration may be associated with unsystematic risk and that any relation between duration and systematic risk is more complex than implied in [3] and [6].

Predictability of future returns using ex ante information (e.g., analyst forecasts) violates market efficiency. We show that predictability can be due to non-random data deletion, especially in skewed distributions of long-horizon security returns. Passive deletion arises because some firms do not survive the post-event long horizon. Active deletion arises when extreme observations are truncated by the researcher. Simulations demonstrate that data deletion induces a negative relation between future returns and ex ante information variables. Analysis of actual data suggests a 30–50% bias in the estimated relations. We recommend specific robustness checks when testing return predictability using ex ante information.

Assessing the predictive ability of behavioral finance theories using out-of-sample data is important. Otherwise, the potentially boundless set of psychological biases underlying the behavioral explanations for security price behavior can lead to overfitting of theories to data. We test pricing effects attributed to two psychological biases, representativeness and conservatism, which underlie many behavioral finance theories. Using trends and consistency of accounting performance, we look for the pricing consequences of representativeness and conservatism. We find mixed evidence consistent with behavioral finance. Specifically, the theories based on representativeness are not supported, but we find some evidence of the pricing implications of conservatism.

This study examines the determinants and implications of the volume of tax-related numbers reported in the financial statements. I document that the volume of tax numbers increases with tax reporting requirements and decreases with the complexity of the tax rate, implying that firms with greater proprietary costs decrease their numeric disclosures once they meet mandatory reporting requirements. With respect to implications, I document that firms reporting more tax numbers improve the transparency of the information environment, reducing the errors and dispersion of analysts’ implied effective tax rate forecasts. In contrast, greater emphasis on narrative tax disclosure does not reduce information frictions, highlighting an important trade-off between numeric detail and strategic narratives. Further investigation suggests that this relationship is driven by more tax numbers in the financial statement footnotes rather than in the face financial statements. These findings suggest firms’ tax information environment improves with a greater volume of numeric tax-related disclosures.

This paper combines traditional fundamentals, such as earnings and cash flows, with measures tailored for growth firms, such as earnings stability, growth stability and intensity of R&D, capital expenditure and advertising, to create an index – GSCORE. A long–short strategy based on GSCORE earns significant excess returns, though most of the returns come from the short side. Results are robust in partitions of size, analyst following and liquidity and persist after controlling for momentum, book-to-market, accruals and size. High GSCORE firms have greater market reaction and analyst forecast surprises with respect to future earnings announcements. Further, the results are inconsistent with a risk-based explanation as returns are positive in most years, and firms with lower risk earn higher returns. Finally, a contextual approach towards fundamental analysis works best, with traditional analysis appropriate for high BM stocks and growth oriented fundamental analysis appropriate for low BM stocks.