Trading Volumes in Dynamically Efficient Markets

The classic Lucas asset pricing model with complete markets stresses aggregate risk and, hence, fails to investigate the impact of agents heterogeneity on the dynamics of the equilibrium quantities and measures of trading volume. In this paper, we investigate under what conditions non-informational heterogeneity, i.e. differences in preferences and endowments, leads to non trivial trading volume in equilibrium. Our main result comes in form of a non-informational no trade theorem which provides necessary and sufficient conditions for zero trading volume in a dynamically efficient, continuous time Lucas market model with multiple goods and securities.General Equilibrium, Trading Volume; heterogenous agents; multiple goods; incomplete markets; no-trade theorem.

Incomplete Information, Heterogeneity, and Asset Pricing

We consider a pure exchange economy where the drift of aggregate consumption is unobservable. Agents with heterogeneous beliefs and preferences act competitively on financial and goods markets. We discuss how equilibrium market prices of risk differ across agents, and in particular we discuss the properties of the market price of risk under the physical (objective) probability measure. We propose a number of specifications of risk aversions and beliefs where the market price of risk is much higher, and the riskless rate of return lower, than in the equivalent full information economy (homogeneous and heterogeneous preferences) and thus can provide an(other) answer to the equity premium and risk-free rate puzzles. We also derive a representation of the equilibrium volatility and numerically assess the role of heterogeneity in beliefs. We show that a high level of stock volatility can be obtained with a low level of aggregate consumption volatility when beliefs are heterogeneous. Finally, we discuss how incomplete information may explain the apparent predictability in stock returns and show that in-sample predictability cannot be exploited by the agents, as it is in fact a result of their learning processes. Copyright 2006, Oxford University Press.

Bounded Rationality and Asset Pricing

We consider a pure exchange economy with incomplete information. Some agents in the economy display learning bias and over- or underreact to the arrival of new information. We study, by simulation, the distribution of irrational agents’ consumption shares. We find that over a reasonable horizon (50 years) under- or over-reaction has little impact on an agent’s consumption share, when parameters of the model are chosen to fit aggregate consumption data in the US. We also show that agents’impact on prices is increasing in their consumption share and conclude that biased agents can significantly influence equilibrium quantities.Bounded rationality, incomplete information, equilibrium

Incomplete information, idiosyncratic volatility and stock returns

When investors have incomplete information, expected returns, as measured by an econometrician, deviate from those predicted by standard asset pricing models by including a term that is the product of the stock's idiosyncratic volatility and the investors' aggregated forecast errors. If investors are biased this term generates a relation between idiosyncratic volatility and expected stocks returns. Relying on forecast revisions from IBES, we construct a new variable that proxies for this term and show that it explains a significant part of the empirical relation between idiosyncratic volatility and stock returns. (C) 2012 Elsevier B.V. All rights reserved