Abstract not found

We build a model that helps explain why increases in liquidity⎯such as lower bid-ask spreads, a lower price impact of trade, or higher turnover⎯predict lower subsequent returns in both firm-level and aggregate data. The model features a class of irrational investors, who underreact to the information contained in order flow, thereby boosting liquidity. In the presence of short-sales constraints, high liquidity is a symptom of the fact that the market is dominated by these irrational investors, and hence is overvalued. This theory can also explain how managers might successfully time the market for seasoned equity offerings, by simply following a rule of thumb that involves issuing when the SEO market is particularly liquid. Empirically, we find that: i) aggregate measures of equity issuance and share turnover are highly correlated; yet ii) in a multiple regression, both have incremental predictive power for future equal-weighted market returns.

This paper considers learning when the distinction between risk and ambiguity matters. It first describes thought experiments, dynamic variants of those provided by Ellsberg, that highlight a sense in which the Bayesian learning model is extreme-it models agents who are implausibly ambitious about what they can learn in complicated environments. The paper then provides a generalization of the Bayesian model that accommodates the intuitive choices in the thought experiments. In particular, the model allows decision-makers ’ confidence about the environment to change — along with beliefs — as they learn. A portfolio choice application compares the effect of changes in confidence under ambiguity versus changes in estimation risk under Bayesian learning. The former is shown to induce a trend towards more stock market participation and investment even when the latter does not. 1

When ambiguity averse investors process news of uncertain quality, they act as if they take a worst-case assessment of quality. As a result, they react more strongly to bad news than to good news. They also dislike assets for which information quality is poor, especially when the underlying fundamentals are volatile. These effects induce negative skewness in asset returns, increase price volatility and induce ambiguity premia that depend on idiosyncratic risk in fundamentals. Moreover, shocks to information quality can have persistent negative effects on prices even if fundamentals do not change. This helps to explain the reaction of markets to events like 9/11/2001. 1

Abstract: We study the implications of learning in an environment where the true model of the world is a multivariate one, but where agents update only over the class of simple univariate models. If a particular simple model does a poor job of forecasting over a period of time, it is eventually discarded in favor of an alternative—yet equally simple—model that would have done better over the same period. This theory makes several distinctive predictions, which, for concreteness, we develop in a stock-market setting. For example, starting with symmetric and homoskedastic fundamentals, the theory yields forecastable variation in the size of the value/glamour differential, in volatility, and in the skewness of returns. Some of these features mirror familiar accounts of stock-price bubbles.

www.cepr.org Available online at: www.cepr.org/pubs/dps/DP3941.asp www.ssrn.com/xxx/xxx/xxx ISSN 0265-8003

We estimate a dynamic asset pricing model characterized by heterogeneous boundedly rational agents. The fundamental value of the risky asset is publicly available to all agents, but they have different beliefs about the persistence of deviations of stock prices from the fundamental benchmark. An evolutionary selection mechanism based on relative past profits governs the dynamics of the fractions and switching of agents between different beliefs or forecasting strategies. A strategy attracts more agents if it performed relatively well in the recent past compared to other strategies. We estimate the model to annual US stock price data from 1871 until 2003. The estimation results support the existence of two expectation regimes, and a bootstrap F-test rejects linearity in favor of our nonlinear two-type heterogeneous agent model. One regime can be characterized as a fundamentalists regime, because agents believe in mean reversion of stock prices toward the benchmark fundamental value. The second regime can be characterized as a chartist, trend following regime because agents expect the deviations from the fundamental to trend. The fractions of agents using the fundamentalists and trend following forecasting rules show substantial time variation and switching between predictors. The model offers an explanation for the recent stock prices run-up. Before the 90s the trend following regime was active only occasionally. However, in the late 90s the trend following regime persisted and created an extraordinary deviation of stock prices from the fundamentals. Recently, the activation of the mean reversion regime has contributed to drive stock prices back closer to their fundamental valuation.

I test whether there is a link between the poor post-event performance of SEOs and shortsale constraints. I find that SEOs have a higher and statistically significant probability of being on special (high short-sale costs) in the 36 months after issuance. Thus, shorting demand appears to be high for issuers in the post-issuance period. I also provide indirect evidence using potential proxies for opinion divergence. Issuers with high pre-event volume, high preevent dispersion in analysts ’ forecasts, or large reductions in ownership breadth experience significantly low subsequent returns. However, issuers with low pre-event volume, dispersion in analysts ’ forecasts, or no reduction in ownership breadth do not significantly underperform. I also find that the post-event performance of issuers is not unique. Most of the abnormal performance of issuers is explained by the performance of non-issuers with similar market equity and trading volume.

at the University of Michigan, for valuable comments and/or discussions. Any remaining Information, Expected Utility, and Portfolio Choice We study the consumption-investment problem of an agent with a constant relative risk aversion preference function, who possesses noisy information about the future prospects of a stock. We also solve for the value of information to the agent in closed-form. We find that information can significantly alter consumption and asset allocation decisions. For reasonable parameter ranges, information increases consumption in the vicinity of 25%. Information can shift the portfolio weight on a stock from zero to around 70%. Thus, depending on the stock beta, the weight on the market portfolio can be considerably reduced with information, causing the appearance of under-diversification. The model indicates that stock holdings of informed agents are positively related to wealth, unrelated to systematic risk, and negatively related to idiosyncratic uncertainty. We also show that the dollar value of information to the agent depends linearly on his wealth and decreases with both the propensity to intermediate consumption and risk aversion. Information is an important feature of financial market settings. For example, investing

This paper develops a model of trading in stocks and options based on differences of opinion of public information among risk-averse investors. It shows that both additional trading sessions and the introduction of options enhance investors ’ perceived welfare and that in the presence of options, the trading volume of the underlying stock is positive even if the stock price remains unchanged. Some unique empirical implications are that the trading volume of options increases with both the arrival of public information and the dispersion of investors ’ interpretation of it, and that the introduction of options makes the trading volume of the underlying stock both higher and more sensitive to the price changes of the underlying stock.