[The article develops a dynamic model that nests the rational expectations (RE) and differences of opinion (DO) approaches to study how investors use prices to update their valuations. When investors condition on prices (RE), investor disagreement is related positively to expected returns, return volatility, and market beta, but negatively to return autocorrelation. When investors do not use prices (DO), these relations are reversed. Tests of these predictions on the cross-section of stocks using analyst forecast dispersion and volume as proxies for disagreement provide empirical evidence that is consistent with investors using prices on average.]

The article develops a dynamic model that nests the rational expectations (RE) and differences of opinion (DO) approaches to study how investors use prices to update their valuations. When investors condition on prices (RE), investor disagreement is related positively to expected returns, return volatility, and market beta, but negatively to return autocorrelation. When investors do not use prices (DO), these relations are reversed. Tests of these predictions on the cross-section of stocks using analyst forecast dispersion and volume as proxies for disagreement provide empirical evidence that is consistent with investors using prices on average. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

[Motivated by the insight of Keynes (1936) on the importance of higher-order beliefs in financial markets, we examine the role of such beliefs in generating drift in asset prices. We show that in a dynamic setting, a higher-order difference of opinions is necessary for heterogeneous beliefs to generate price drift. Such drift does not arise in standard difference of opinion models, since investors' beliefs are assumed to be common knowledge. Our results stand in contrast to those of Allen, Morris, and Shin (2006) and others, as we argue that in rational expectation equilibria, heterogeneous beliefs do not lead to price drift.]

[Firm-specific information can affect expected returns if it affects investor uncertainty about risk-factor loadings. We show that a stock's expected return is decreasing in factor-loading uncertainty, controlling for the average level of its factor loading. When loadings are persistent, learning by investors can induce time-series variation in price-dividend ratios, expected returns, and idiosyncratic volatility, even when the aggregate risk-premium is constant and fundamental shocks are homoscedastic. Consistent with our predictions, we estimate that average annual returns of a firm with the median level of factor-loading uncertainty are 400 to 525 basis points lower than a comparable firm without factor-loading uncertainty.]

Regulatory restrictions and market frictions can constrain the aggregate quantity of long and short positions in a security. When these constraints bind, we refer to the security as scarce, and its price becomes distorted relative to its value in a frictionless market. We show that an otherwise redundant derivative can reduce the price distortion of the underlying security by relaxing its scarcity. We also show that it is especially important to analyze the underlying and derivative markets jointly when evaluating the impact of regulation, such as short-sales bans and position limits in derivatives, that restricts trade.

ABSTRACT The empirical evidence on investor disagreement and trading volume is difficult to reconcile in standard rational expectations models. We develop a dynamic model in which investors disagree about the interpretation of public information. We obtain a closed‐form linear equilibrium that allows us to study which restrictions on the disagreement process yield empirically observed volume and return dynamics. We show that when investors have infrequent but major disagreements, there is positive autocorrelation in volume and positive correlation between volume and volatility. We also derive novel empirical predictions that relate the degree and frequency of disagreement to volume and volatility dynamics.

Motivated by the insight of Keynes (1936) on the importance of higher-order beliefs in financial markets, we examine the role of such beliefs in generating drift in asset prices. We show that in a dynamic setting, a higher-order difference of opinions is necessary for heterogeneous beliefs to generate price drift. Such drift does not arise in standard difference of opinion models, since investors' beliefs are assumed to be common knowledge. Our results stand in contrast to those of Allen, Morris, and Shin (2006) and others, as we argue that in rational expectation equilibria, heterogeneous beliefs do not lead to price drift.

ABSTRACT Standard models of liquidity argue that the higher price for a liquid security reflects the future benefits that long investors expect to receive. We show that short‐sellers can also pay a net liquidity premium if their cost to borrow the security is higher than the price premium they collect from selling it. We provide a model‐free decomposition of the price premium for liquid securities into the net premiums paid by both long investors and short‐sellers. Empirically, we find that short‐sellers were responsible for a substantial fraction of the liquidity premium for on‐the‐run Treasuries from November 1995 through July 2009.

In a SPAC transaction, a sponsor raises financing from investors using redeemable shares and rights. When investors are sophisticated, these features dilute the sponsor's stake and can lead to underinvestment in profitable targets. However, when investors are overconfident about their ability to respond to interim news, the optionality in such features is overpriced, and SPACs can lead to over-investment in unprofitable targets. Consistent with empirical evidence, the model predicts different returns for short-term and long-term investors and overall underperformance. While some policy interventions (e.g., eliminating redemption rights, limiting investor access, and restricting warrants) improve returns for unsophisticated investors, others (e.g., increased disclosure) can be counterproductive.

We develop a model where some investors are uncertain whether others are trading on informative signals or noise. Uncertainty about others leads to a nonlinear price that reacts asymmetrically to news. We incorporate this uncertainty into a dynamic setting where traders gradually learn about others and show that it generates empirically relevant return dynamics: expected returns are stochastic but predictable, and volatility exhibits clustering and the “leverage” effect. The model nests both the rational expectations (RE) and differences of opinions (DO) approaches and highlights a link between disagreement about fundamentals and uncertainty about other traders.