Financial Anomalies Research Articles

Efficient markets and Bayes? rule

A series of financial anomalies motivated the development of new theories that modify the rational expectations ideal. Two possibilities have been systematically explored. The literature on behavioral finance relaxes the assumption that agents form beliefs according to the laws of probability and assume, instead, that simpler heuristic rules are used. Another stream of the literature assumes that agents process information according to Bayes’ rule, but do not posses sufficient information to know the true data generating process. In this paper, Bayesian and Behavioral agents coexist and trade in a standard dynamic asset pricing model. A long-standing conjecture is demonstrated. It is shown that, under suitable assumptions, Bayesian agents drive Behavioral, non-Bayesian agents out of the market. Hence, asset prices are eventually determined under the Bayesian paradigm.

How do Investors' Expactations Drive Asset Prices?

Asset price processes are completely described by information processes and investors' preferences. In this paper we derive the relationship between the process of investors' expectations of the terminal stock price and asset prices in a general continuous time pricing kernel framework. To derive the asset price process we make use of the modern technique of forward-backward stochastic differential equations. With this approach it is possible to show the driving factors for stochastic volatility of asset prices and to give theoretical arguments for empirically well documented facts. We show that stylized facts that look at first hand like financial market anomalies may be explained by an information process with stochastic volatility.

Psychologie de marché et anomalies financières

Cet article développe un modèle d’évaluation schématique dans lequel la dynamique des prix d’actifs est influencée par les «prophéties auto-réalisatrices» des investisseurs. On dégage une famille de solutions susceptible d’engendrer simultanément deux anomalies financières largement documentées par les études économétriques, à savoir la volatilité excessive des prix d’actifs et la prévisibilité des rendements liés à leur détention. Comme ces phénomènes apparaissent compatibles avec la rationalité des anticipations, le modèle théorique remet en question l’opposition traditionnelle entre l’hypothèse d’efficience informationnelle des marchés d’une part, et l’idée selon laquelle les croyances arbitraires des investisseurs peuvent influencer les prix d’actifs, d’autre part.

Security Analyst Experience and Post-Earnings-Announcement Drift

Prior research suggests that various financial anomalies are related to investors' inability to process historical earnings and price information. In particular, analysts' failure to incorporate appropriately the serial correlation in earnings surprises provides at least a partial explanation for post-earnings-announcement drift. Because prior work documents that analysts more fully incorporate the information in prior earnings surprises as they gain experience, we examine if firms followed by more experienced analysts exhibit less drift. Measuring analyst firm-specific forecasting experience as the number of prior quarters for which the analyst has issued an earnings forecast for the firm, we find that post-earnings-announcement drift associated with firms with a more experienced analyst following is 18 percent less than that for firms with a less experienced analyst following. This result suggests that the efficiency of a firm's market price is affected by the aggregate experience level of its analyst following.

Financial Distress, Market Anomalies and Single and Multifactor Asset Pricing Models: New Evidence

Data snooping and the nature of the distress premium are unresolved issues for the Fama and French three-factor model. These are addressed using UK data to create and test the model on portfolios based on market anomalies. We explore the apparent distress premium identified in prior research with particular reference to negative book equity-to-market equity (BE/ME) stocks. Although neglected in the prior research, we argue that these stocks offer new insights into the nature of the distress premium. We conclude that the distress premium is real and the three-factor model is an improvement on CAPM for all portfolios tested including the negative (BE/ME) portfolio. Unlike other distressed portfolios there is no compensation with high abnormal returns for this portfolio.

Competing Theories of Financial Anomalies

We compare two competing theories of financial anomalies: “behavioral” theories built on investor irrationality, and “rational structural uncertainty” theories built on incomplete information about the structure of the economic environment. We find that although the theories relax opposite assumptions of the rational expectations ideal, their mathematical and predictive similarities make them difficult to distinguish. Even if irrationality generates financial anomalies, their disappearance still may hinge on rational learning—that is, on the ability of rational arbitrageurs and their investors to reject competing rational explanations for observed price patterns.

Discussion of “Competing Theories of Financial Anomalies”

[Efficient markets and asset pricing] research ... did not begin with the development of a theory of price formation which was then subjected to empirical tests. Rather, the impetus ... came from the accumulation of evidence ... that the behavior ... of speculative prices could be well approximated by a random walk ... Faced with the evidence, economists felt compelled to offer some rationalization .... In short, there existed a large body of empirical results in search of a rigorous theory.

Competing Theories of Financial Anomalies

We compare two competing theories of financial anomalies: (1) behavioral theories built on investor irrationality; and (2) rational structural uncertainty theories built on incomplete information about the structure of the economic environment. We find that although the theories relax opposite assumptions of the rational expectations ideal, their mathematical and predictive similarities make them difficult to distinguish. Interestingly, even if irrationality generates financial anomalies, their disappearance still may hinge on rational learning ? that is, on the ability of rational arbitrageurs and their investors to reject competing rational explanations for observed price patterns.

What is Real Estate Finance

How does real estate finance relate to the core of contemporary finance? What research in real estate might most interest financial economists? What research is suggested by both recurrent financial anomalies and stylized facts in real estate? Some possibilities are discussed.

Forecasting earnings composite variables, financial anomalies, and efficient Japanese and U.S. portfolios

In this study we address the creation of efficient portfolios with particular emphasis on earnings forecast and value strategies in Japan and the U.S. We show that market-neutral portfolios produce much higher returns for a given level of risk than merely creating efficient (long) portfolios. Thus use of a multi-factor risk model is useful for the 1988–1997 period for creating market-neutral portfolios and one can create the market-neutral equity selection and portfolio construction models. We find that the inclusion of consensus I/B/E/S forecasts, revisions, and momentum substantially increases the market-neutral portfolio average annual returns of Japanese and U.S. portfolios. A value-only model works quite well in a Japanese market-neutral strategy and the use of I/B/E/S forecasts significantly enhances the returns; however, in the U.S., we find that the I/B/E/S forecasts are necessary for an effective market-neutral strategy.

Neural network applications in financial asset management

Modelling of financial systems has traditionally been done in partial equilibrium. Such models have been very useful in expanding our understanding of the capital markets; nevertheless, many empirical financial anomalies have remained unexplainable. It is possible that this may be due to the partial equilibrium nature of these models. Attempting to model financial markets in a general equilibrium framework still remains analytically intractable. Because of their inductive nature, dynamical systems such as neural networks can bypass the step of theory formulation, and they can infer complex non-linear relationships between input and output variables. Neural networks have now been applied to a number of live systems, and have demonstrated far better performance than conventional approaches. This paper reviews the state-of-the-art in financial modelling using neural networks, and describes typical applications in key areas of forecasting, classification and pattern recognition. The applications cover areas such as asset allocation, foreign exchange, stock ranking and bond trading.

Noise Trader Risk in Financial Markets

We present a simple overlapping generations model of an asset market in which irrational noise traders with erroneous stochastic beliefs both affect prices and earn higher expected returns. The unpredictability of noise traders' beliefs creates a risk in the price of the asset that deters rational arbitrageurs from aggressively betting against them. As a result, prices can diverge significantly from fundamental values even in the absence of fundamental risk. Moreover, bearing a disproportionate amount of risk that they themselves create enables noise traders to earn a higher expected return than rational investors do. The model sheds light on a number of financial anomalies, including the excess volatility of asset prices, the mean reversion of stock returns, the underpricing of closed-end mutual funds, and the Mehra-Prescott equity premium puzzle.