Volume 8, Number 1, 2007 Abstracts
© Copyright Erlbaum 2007

Yes, Wall Street, There Is A January Effect! Evidence from Laboratory Auctions
Lisa R. Anderson - Associate Professor in the Department of Economics at the College of William and Mary
Jeffrey R. Gerlach - Associate Professor in the Department of Economics at the College of William and Mary
Francis J. DiTraglia - Postgraduate student at the Mathematical Institute of the University of St. Andrews

There is a large literature using financial market data on the causes of a "January effect," which produces higher stock prices in January than in other months of the year. We present the first experimental study of this phenomenon in the context of two well-known auction experiments. After controlling for variables that could influence subject bids, such as differences in private values, cumulative earnings, and learning effects, the prices in the January markets were systematically higher than those in December, a difference that is economically large and statistically significant. The results provide support for the conjecture that psychological factors may contribute to the well-documented January effect in empirical stock market data.

Motivational and Cognitive Determinants of Buy-Side and Sell-Side Analyst Earnings Forecasts: An Experimental Study
Robert H. Ashton - Palmer Fox Professor of Accounting, at Duke University's Fuqua School of Business
Anna M. Cianci - Assistant Professor of Accounting, at Drexel University's LeBow College of Business

This paper provides experimental evidence about the differences between buy-side analyst (BSA) and sell-side analyst (SSA) earnings forecasts, and investigates both motivational and cognitive determinants of these differences. Regarding motivational determinants, we argue that the SSA work environment contains greater incentives for optimistic forecasts than does the BSA work environment. Regarding cognitive determinants, we examine whether three characteristics of the information on which analysts base their forecasts (trend, variability, and recency) contribute to optimism. We also examine whether forecasts are more optimistic over longer forecast horizons. Results indicate that, as expected, SSAs make more favorable earnings forecast revisions than BSAs, and, consistent with prior research, analyst forecasts are greater as forecast horizon increases. In addition, while information variability does not contribute to optimism, differences in trend and recency do. Specifically, analysts act as if they discount both past earnings information with a decreasing trend and negative recent information when revising their forecasts. Directions for additional research on motivational and cognitive determinants of analyst forecasts are offered.

Prior Performance and Risk-Taking of Mutual Fund Managers: A Dynamic Bayesian Network Approach
Manuel Ammann - Swiss Institute of Banking and Finance, University of St. Gallen
Michael Verhofen - Swiss Institute of Banking and Finance, University of St. Gallen

We analyze the behavior of mutual fund managers with a special focus on the impact of prior performance. In contrast to previous studies, we do not focus solely on volatility as a risk measure, but also consider alternative definitions of risk and style. Using a dynamic Bayesian network, we are able to capture non-linear effects and to assign exact probabilities to the mutual fund managers' adjustment of behavior. In contrast to theoretical predictions and some existing studies, we find that prior performance has a positive impact on the choice of risk level, i.e., successful fund managers take on more risk in the following calendar year. In particular, they increase volatility, beta, and tracking error, and assign a higher proportion of their portfolio to value stocks, small firms, and momentum stocks. Overall, poor-performing fund managers switch to passive strategies.

Volatility in Returns from Trading
Richard Heaney - School of Economics and Finance, RMIT University
F. Douglas Foster - School of Banking and Finance, University of New South Wales
Shirley Gregor - School of Accounting and Business Information Systems, Australian National University
Terry O'Neill - School of Finance & Applied Statistics, Australian National University
Robert Wood - Accelerated Learning Laboratory, Australian Graduate School of Management, University of New South Wales

Odean [1999] observes that naive investors tend to trade too often, but we know little about what motivates them and why their performance is often so poor. This paper describes an experiment where naive traders take part in a share market game with limited information, unlimited credit, and unlimited short-selling. We find that trading profit volatility is positively correlated with the level of understanding of the market, the level of self-efficacy or self-confidence, and the level of trading. Large profits and losses tend to be earned by individuals who trade heavily and have a reasonable understanding of how the market works and how shares are valued. There is also some evidence that a high level of self-efficacy is positively correlated with trading profit volatility.

Some Determinants of the Socially Responsible Investment Decision: A Cross-Country Study
Geoffrey Williams - OWW Consulting Pte, Ltd and University of Bath

This paper develops a general model of investor choice to analyze socially responsible investment (SRI). Drawing on data from a large survey of investors across five countries, we show that SRI may be driven more by investor attitudes toward the social aims of firms rather than by financial returns. We also show that investors who are concerned about social issues as consumers appear to extend this behavior into their portfolio strategies. We find little evidence that demographic factors affect SRI, but some indirect evidence that market context in terms of institutional ownership and the regulatory environment may play a role.

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