We examine the role of financial analysts in forming institutional investors' investment decisions. In our model, a fund manager invests in a stock based on the optimal weighting of reports created by a biased sell-side analyst and an unbiased buy-side analyst. The manager puts a higher weight on the buy-side analyst's report when the quality of the buyside analyst's information relative to that of the sell-side analyst increases, or when the sell-side analyst's degree of bias or uncertainty about the bias increases. Utilizing a unique dataset of U.S. equity funds, we find evidence supporting our model predictions on how fund managers weigh buy-side research relative to sell-side and independent research.

This paper introduces and analyzes a new form of contingent convertible: a call option enhanced reverse convertible (COERC). If an issuing bank’s market value of capital breaches a trigger, COERCs convert to many new equity shares that would heavily dilute existing shareholders, except that shareholders have the option to purchase these shares at the bond’s par value. COERCs have low risk: They are almost always fully repaid in cash. Yet, they reduce government bailouts by replenishing a bank’s capital. COERCs’ design also avoids problems with market-value triggers, such as manipulation or panic, while reducing moral hazard and debt overhang.

Overconfident CEOs/senior executives tend to have excessively positive views of their own skills and their company’s future performance. We hypothesize that overconfident managers are more likely to engage in reckless or intentional actions/disclosures that give rise to securities class actions (SCAs). Empirical evidence is supportive: Overconfident CEOs/senior executives increase SCA likelihood, though litigation risk is ameliorated through improved governance, such as following the Sarbanes–Oxley Act of 2002. Post-SCA, companies are less likely to hire an overconfident CEO. Following an SCA, overconfident CEOs appear to moderate behavior and to reduce their litigation risk.

The literature documents heterogeneity in the delay of stock price reaction to systematic shocks, implying that asset risk depends on investment horizon. We study the pricing of risk factors across investment horizons. Value (liquidity) risk is priced over intermediate (short) horizons. Conditioning horizon-factor exposures on firm characteristics indicates that characteristics, with the exception of momentum, are not priced beyond their contribution to systematic risk. Long-horizon institutional investors overweight assets with high intermediate-horizon exposures to value risk and high short-horizon exposures to liquidity risk. The results highlight the importance of investment horizon in determining risk premia.

This paper examines the adverse selection problem that arises from the repeated trades of informed traders. We develop a model of trading that incorporates the interaction of expectations, prices, and volume. We then examine how trading volume affects the speed of price adjustment to information, and demonstrate how this price effect differs across markets. Our results suggest that the efficiency of price adjustment to new information may differ dramatically depending on security market structure, even when there is endogenous entry of informed traders. We illustrate these price adjustment properties by developing a simulation of our theoretical model.

We classify a unique and comprehensive data set of corporate press releases into topics and study the market reaction to various types of news. While confirming prior findings regarding strong stock price responses to financial news, we also document significant reactions to news about corporate strategy, customers and partners, products and services, management changes, and legal developments. Consistent with regulators' expectations, the level of informational asymmetry in the market declines following most types of press releases. At the same time, return volatility frequently increases in the post-announcement period, which we show can be attributed to higher levels of valuation uncertainty.

This study tests the popular claim that the DJIA's movements around key reference points affect “investor sentiment” and thus price behavior. It is found that the DJIA's rise and fall is indeed restrained by “support” and “resistance” levels at multiples of 100 (e.g., 2800, 2900, 3000, etc.) but that, having broken through a 100-level, the DJIA then moves by more than otherwise warranted. A Monte Carlo study and comparisons with other indices confirm the significance of these findings. This suggests that some agents may trade on the basis of the DJIA but does not necessarily suggest that the market is inefficient.

Variation in idiosyncratic return volatility from 1978 to 2009 is attributable to discretionary accrual volatility and the correlation between premanaged earnings and discretionary accruals reflective of information quality across firms. These results are robust to controls for firm operating uncertainty, growth options, business-cycle variations, and firm age and industry effects, and they highlight the importance of managerial discretion in determining idiosyncratic volatility.

This paper provides a detailed analysis of the impact of daily mutual fund flow volatility on fund performance. I document a significant negative relationship between the volatility of daily fund flows and cross-sectional differences in risk-adjusted performance. This relationship is driven by domestic equity funds, as well as small funds, well-performing funds, and funds that experience inflows over the sample period. My results are consistent with performance differences arising from the transaction costs of nondiscretionary trading driven by daily fund flows, but not with performance differences arising from the suboptimal cash holdings that arise from fund flows.

The Markowitz analysis of efficient portfolio selection, which can be interpreted as solving the quadratic-programming problem of minimizing the variance of a normal variate subject to each prescribed mean value, easily can be generalized (in the special case of independently distributed investments) to the concave-programming problem of minimizing the “dispersion” of a stable Pareto-Lévy variate subject to each prescribed mean value. Some further generalizations involving interdependent distributions will also be presented here.

Analysts' earnings forecasts are influenced by their desire to win investment banking clients. We hypothesize that the equity bull market of the 1990s, along with the boom in investment banking business, exacerbated analysts' conflicts of interest and their incentives to strategically adjust forecasts to avoid earnings disappointments. We document shifts in the distribution of earnings surprises and related changes in the market's response to surprises and forecast revisions. The evidence for shifts is stronger for growth stocks, where conflicts of interest are more pronounced. However, shifts are less notable for analysts without ties to investment banking and in international markets.

This paper explores the effect of project interrelationships on investment decisions and project values in a real options framework. We examine in detail the mutually exclusive case where a firm may invest in the development stage of two projects and then may select only a single project to implement. The firm can develop the projects in parallel or in sequence. The choice of development policy depends on the relative values of the embedded options for each strategy. Sequential development is shown to be superior to parallel development when projects have highly correlated values, and when they require a large commitment of capital for development, are short term in nature, and have relatively low volatility. We also show that the optimal ordering of sequential projects does not always begin with the most profitable project.

We study a sample of Form 13F filings where fund advisors seek confidential treatment for some or all of their 13(f)-reportable positions. Consistent with the hypothesis that managers seek confidentiality to protect proprietary information, we find that confidential positions earn positive and significant abnormal returns over the post-filing confidential period. We also find that managers are more likely to seek confidential treatment of illiquid positions that are more susceptible to front-running. Overall, our analysis highlights important benefits of reduced disclosure that are relevant to the current policy debate on hedge fund transparency.

We examine the efficiency of using individual stocks or portfolios as base assets to test asset pricing models using cross-sectional data. The literature has argued that creating portfolios reduces idiosyncratic volatility and allows more precise estimates of factor loadings, and consequently risk premia. We show analytically and empirically that smaller standard errors of portfolio beta estimates do not lead to smaller standard errors of cross-sectional coefficient estimates. Factor risk premia standard errors are determined by the cross-sectional distributions of factor loadings and residual risk. Portfolios destroy information by shrinking the dispersion of betas, leading to larger standard errors.

Empirical studies of dual class shares indicate that superior voting shares (SVS) sell at a premium relative to their counterpart restricted shares (RVS). This paper uses Toronto Stock Exchange data to show that SVS price premium over RVS reflects the expected takeover premium paid to shareholders outside the control block. Thus, marginal shareholders pay a higher SVS price in anticipation of receiving a differential takeover bid as suggested by the extra merger hypothesis. Further analysis indicates that voting power increases the price premium while ownership, size, and the higher trading liquidity of RVS are inversely related to the premium.

This paper introduces a Monte Carlo simulation method for pricing multidimensional American options based on the computation of the optimal exercise frontier. We consider Bermudan options that can be exercised at a finite number of times and compute the optimal exercise frontier recursively. We show that for every date of possible exercise, any single point of the optimal exercise frontier is a fixed point of a simple algorithm. Once the frontier is computed, we use plain vanilla Monte Carlo simulation to price the option and obtain a low-biased estimator. We illustrate the method with applications to several types of options.

Innovating firms pay more bribes than noninnovators across 25,000 firms in 57 countries. The difference is larger in countries with more bureaucratic regulation and weaker governance. Innovators that pay bribes do not receive better services and do not have greater propensity to engage in other illegal activities such as tax evasion. Thus, innovators are more likely to be victims of corruption than perpetrators. Our findings point to the challenges facing entrepreneurs in developing countries and are consistent with the view that rent seeking by government officials unlike private criminal activity is more likely to target innovators.

Do happy people predict future risk and return differently from unhappy people, or do individuals rely only on economic facts? We survey investors on their subjective sentiment-creating factors, return and risk expectations, and investment plans. We find that noneconomic factors systematically affect return and risk expectations, where the return effect is more profound. Investment plans are also affected by noneconomic factors. Sports results and general feelings significantly affect predictions. Sufferers from seasonal affective disorder have lower return expectations in the autumn than in other seasons, supporting the winter blues hypothesis.

We document that a firm’s culture, specifically, its religiosity, affects its cost of debt. Firms in higher-religiosity counties have higher credit ratings and lower debt costs. The impact of religiosity is stronger for firms with greater information asymmetry and during recessions. Further, religiosity has additional explanatory power for the cost of bank loans (but not the cost of public bonds) beyond its impact through ratings. This supports the argument that banks have superior abilities in pricing soft information, such as corporate culture. Finally, the impact of religiosity is stronger when the lender is a small bank.

Many empirical studies find that the distribution of stock returns departs from normality. In such cases, it is desirable to employ a statistical estimation procedure that may be more efficient than ordinary least squares. This paper describes various robust methods, which have attracted increasing attention in the statistical literature, in the context of estimating beta risk. The empirical analysis documents the potential efficiency gains from using robust methods as an alternative to ordinary least squares, based on both simulated and actual returns data.