Knowledge that Transforms

Abstract This paper examines time-series forecast errors of expected returns from conditional and unconditional asset pricing models for portfolio and individual firm equity returns. A new result that increases predictive precision concerning model specification and forecasting is introduced. Conditional versions of the models generally produce higher mean squared errors than unconditional versions for step ahead prediction. This holds for individual firm data when the instruments are firm specific. Mean square forecast error decompositions indicate that the asset pricing models produce relatively unbiased predictions, but the variance is severe enough to ruin the step ahead predictive ability beyond that of a constant benchmark.

Abstract We show that if true returns are independently distributed and a manager fully reports gains but delays reporting losses, then reported returns will feature conditional serial correlation. We use conditional serial correlation as a measure of conditional return smoothing. We estimate conditional serial correlation in a large sample of hedge funds. We find that the probability of observing conditional serial correlation is related to the volatility and magnitude of investor cash flows, consistent with conditional return smoothing in response to the risk of capital flight. We also present evidence that conditional serial correlation is a leading indicator of fraud.

Abstract Theory indicates that frictions (e. g., information and transaction costs) could account for the lower than expected stock market participation rates. This paper examines the hypothesis that there has been a fundamental change in participation and links this change to the reduction of these frictions by the advent of the Internet. Using panel data on household participation rates over the past decade, the results show computer/Internet using households raised participation substantially more than non-computer using households. The increased probability of participation was equivalent to having over $27,000 in additional household income or over two more mean years of education.

Abstract Starting from the reward-risk model for portfolio selection introduced in De Giorgi (2005), we derive the reward-risk Capital Asset Pricing Model (CAPM) analogously to the classical mean-variance CAPM. In contrast to the mean-variance model, reward-risk portfolio selection arises from an axiomatic definition of reward and risk measures based on a few basic principles, including consistency with second-order stochastic dominance. With complete markets, we show that at any financial market equilibrium, reward-risk investors' optimal allocations are comonotonic and, therefore, our model reduces to a representative investor model. Moreover, the pricing kernel is an explicitly given, non-increasing function of the market portfolio return, reflecting the representative investor's risk attitude. Finally, an empirical application shows that the reward-risk CAPM captures the cross section of U.S. stock returns better than the mean-variance CAPM does.

Abstract This paper provides the first theoretical explanation and the first empirical analysis of contingent value rights (CVRs), which have been used as a means of payment in acquisitions, exchange offers, debt restructurings, Chapter 11 reorganizations, and lawsuit settlements. A CVR is a put option committing to pay additional cash or securities to CVR holders, contingent on the issuer's share price falling below a prespecified reference level. In this paper, we develop a model to show that CVRs can help a higher-intrinsic-value firm to reveal its firm type when the firm faces an asymmetric information problem. Our model predicts that i) when CVRs are offered along with cash or stock, the announcement period abnormal stock return is greater than that in stock offers, ii) firms facing more severe asymmetric information problems are more likely to offer CVRs to signal their firm type, and iii) firms that are relatively more cash-constrained are more likely to offer CVRs rather than cash. We test all three predictions using a sample of mergers and acquisitions. Our empirical results are consistent with the predictions of the model.

Abstract A significant but unresolved question in the current debate about the role of intermediaries in financial markets is whether intermediaries behave as passive traders or whether they actively seek and trade on information. We address this issue by explicitly comparing the informational advantages of intermediaries with those of other investors in the market. We find that intermediaries account for greater price discovery than other institutional and individual investors in spite of initiating fewer trades and volume. Furthermore, intermediary information does not arise from inappropriate handling of customer orders by intermediaries. We propose that our findings are consistent with noisy rational expectations models, where agents extract valuable information from past prices. Intermediaries bear little or no opportunity cost of monitoring market conditions, which gives them an advantage in making profitable price-contingent trades. Lower trading costs may also enable intermediaries to trade more effectively and frequently on their information.

Abstract Tests for the existence and the sign of the volatility risk premium are often based on expected option hedging errors. When the hedge is performed under the ideal conditions of continuous trading and correct model specification, the sign of the premium is the same as the sign of the mean hedging error for a large class of models. We show that discrete trading and model misspecification may cause the standard test to yield unreliable results. In particular, ignoring jump risk premia can lead to incorrect conclusions. We also show that delta-gamma hedges do not increase the reliability of the test.

Abstract This paper provides an analysis of the predictability of stock returns using market-, industry-, and firm-level earnings. Contrary to Lamont (1998), we find that neither dividend payout ratio nor the level of aggregate earnings can forecast the excess market return. We show that these variables do not have robust predictive power across different stock portfolios and sample periods. In contrast to the aggregate-level findings, earnings yield has significant explanatory power for the time-series and cross-sectional variation in firmlevel stock returns and the 48 industry portfolio returns. The mean reversion of stock prices as well as the earnings' correlation with expected stock returns are responsible for the forecasting power of earnings yield. These results are robust after controlling for bookto-market, size, price momentum, and post-earnings announcement drift. At the aggregate level, the information content of firm-level earnings about future cash flows is diversified away and higher aggregate earnings do not forecast higher returns.

Abstract This paper examines a firm's debt level, investment timing, and investment scale choices in a continuous-time model where the output price of a good that the firm produces depends on a stochastic demand-shift variable and the total industry supply of the good. Using the simple symmetric Cournot-Nash equilibrium assumption that all firms are identical and therefore follow the same financing and investment strategies, we show that competition decreases the output price and hence encourages a firm to wait for a higher demand level before it is profitable to invest. We also demonstrate how uncertainty, bankruptcy costs, and corporate taxation affect the firm's financing and investment decisions.

Abstract We apply an event-study methodology on over 10,000 Morningstar star rating changes and find that Morningstar has subsantial independent influence on the investment allocation decisions of retail mutual fund investors. It is the discrete change in the star rating itself and not the change in the underlying performance measures that drives frow. We document econnomically and statistically significant positive abnormal flow following rating upgrades, and negative abnormal flow following rating downgrades. In contrast to the cross-sectional flow performance literature, we find evidence of investor punishment of performance declines, some of which is evident immediately in the month of the rating change.