An asymmetric information model of the bid–ask spread is developed for a foreign exchange market subject to occasional government interventions. Traditional tests of the unbiasedness of the forward rate as a predictor of the future spot rate are shown to be inconsistent when the rates are measured as the average of their respective bid and ask quotes. Larger bid–ask spreads on Fridays are documented. Reliable evidence of asymmetric bid–ask spreads for all days of the week, albeit more pronounced on Fridays, are presented. The null hypothesis that the forward rate is an unbiased predictor of the future spot rate continues to be rejected. The regression slope coefficients increase toward unity, however, indicating a less variable risk premium.

There appear to be no anomalies in the aftermarket of a sample of 4,848 U.S. IPOs over the period 1975 to 1995, except issues offered below $6. Risk is priced in the aftermarket in accordance with Rubin-stein's asset-pricing model. Unlike under the efficient markets hypothesis (EMH), however, market priors about the probability of future default are not unbiased at the IPO date. Still, subsequent learning is rational: the market uses Bayes' law with a correct-likelihood function (of news given the eventual fate of an issue). That is, the hypothesis of an efficiently learning market (ELM) cannot be rejected. We produce direct evidence in support of these statements, based on a new class of tests. We also provide indirect evidence, by documenting a gradual convergence of IPO prices towards EMH as issues mature.

Neoclassical finance assumes that investors are Bayesian. In many realistic situations, Bayesian learning is challenging. Here, we consider investment opportunities that change randomly, while payoffs are observable only when invested. In a stylized version of the task, we wondered whether performance would be affected if one were to follow reinforcement learning principles instead. The answer is a definite yes. When asked to perform our task, participants overwhelmingly learned in a Bayesian way. They stopped being Bayesians, though, when not nudged into paying attention to contingency shifts. This raises an issue for financial markets: who has the incentive to nudge investors?

[This paper studies the impact of ambiguity and ambiguity aversion on equilibrium asset prices and portfolio holdings in competitive financial markets. It argues that attitudes toward ambiguity are heterogeneous across the population, just as attitudes toward risk are heterogeneous across the population, but that heterogeneity of attitudes toward ambiguity has different implications than heterogeneity of attitudes toward risk. In particular, when some state probabilities are not known, agents who are sufficiently ambiguity averse find open sets of prices for which they refuse to hold an ambiguous portfolio. This suggests a different cross section of portfolio choices, a wider range of state price/probability ratios, and different rankings of state price/probability ratios than would be predicted if state probabilities were known. Experiments confirm all of these suggestions. Our findings contradict the claim that investors who have cognitive biases do not affect prices because they are inframarginal: ambiguity-averse investors have an indirect effect on prices because they change the per capita amount of risk that is to be shared among the marginal investors. Our experimental data also suggest a positiveS= correlation between risk aversion and ambiguity aversion that might explain the "value effect" in historical data.]

We derive and test a dynamic discrete-time model of asset returns. Both the risks of individual securities and equilibrium risk premia change predictably in the model, but these changes can be attributed to movements in the returns and prices of only two well-diversified portfolios. Any other components of returns should be unpredictable. Using the generalized method of moments, the model is estimated and tested on portfolios of equities. We find the data supportive of the model’s restrictions, even when instruments designed to capture the January effect are employed.

Abstract We report on two sets of large-scale financial markets experiments that were designed to test the central proposition of modern asset pricing theory, namely, that risk premia are solely determined by covariance with aggregate risk. We analyze the pricing within the framework suggested by two theoretical models, namely, the (general) Arrow and Debreu's complete-markets model, and the (more specific) Sharpe-Lintner-Mossin Capital Asset Pricing Model (CAPM). Completeness of the asset payoff structure justifies the former; the small (albeit non-negligible) risks justifies the latter. We observe swift convergence towards price patterns predicted in the Arrow and Debreu and CAPM models. This observation is significant, because subjects always lack the information to deliberately set asset prices using either model. In the first set of experiments, however, equilibration is not always robust, with markets temporarily veering away. We conjecture that this reflects our failure to control subject' beliefs about the temporal independence of the payouts. Confirming this conjecture, the anomaly disappears in a second set of experiments, where states were drawn without replacement. We formally test whether CAPM and Arrow–Debreu equilibrium can be used to predict price movements in our experiments and confirm the hypothesis. When multiplying the subject payout tenfold (in real terms), to US $ 500 on average for a 3-h experiment, the results are unaltered, except for an increase in the recorded risk premia.

We attempt to translate Neo‐Austrian ideas about the workings of financial markets, as originally advanced by F. A. Hayek, into the standard probabilistic language of modern finance. We focus on an apparent paradox, namely the insistence of Neo‐Austrians on order (i.e., stationarity) together with ever‐reemerging inefficiencies . The paper's findings have implications beyond Neo‐Austrian theory: They demonstrate how easy it is to reject market efficiency, but how much more difficult it is to discern the nature of the inefficiency . We illustrate our findings with price data from the U.S. Treasury bill market over the period 1962 to 1999. There is ample evidence that the price of a three‐month Treasury bill is not a random walk, yet the sign of the average price change is erratic, so that inference about the nature of the inefficiency is unreliable.

We analyze theoretically and empirically the implications of information asymmetry for equilibrium asset pricing and portfolio choice. In our partially revealing dynamic rational expectations equilibrium, portfolio separation fails, and indexing is not optimal. We show how uninformed investors should structure their portfolios, using the information contained in prices to cope with winner’s curse problems. We implement empirically this price- contingent portfolio strategy. Consistent with our theory, the strategy outperforms economically and statistically the index. While momentum can arise in the model, in the data, the momentum strategy does not outperform the price-contingent strategy, as predicted by the theory.

Abstract Two theoretical literatures, one using Bayesian Nash equilibrium (BNE), and the other using noisy rational expectations equilibrium (NREE), both provide a foundation for understanding how private information is impounded into asset prices, yet some of their predictions are conflicting. Here, we compare for the first time, the two theories using data from carefully controlled laboratory asset markets. In the dynamics, we find strong evidence for BNE theory, although final prices support predictions of the NREE theory. Finally, we document that price volatility increases when information is being impounded in prices.

This article derives testable restrictions on equilibrium asset prices when investors have the option to time the realization of their capital gains and losses for tax purposes. The tax-timing option alters both the magnitude and timing of equity returns relative to those in a tax-free model. The tax-induced restrictions are empirically examined, and the tax rates and preference parameters are estimated. While the tax-free model can be rejected in favor of the tax-based model as the specified alternative, the tax-based model is still unable to adequately explain cross-sectional differences in asset returns. Copyright 1994 by American Finance Association.(This abstract was borrowed from another version of this item.)