Volume 8

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.

Volume 8, Number 2, 2007 Abstracts
© Copyright Erlbaum 2007

The Trader Interaction Effect on the Impact of Overconfidence on Trading Performance: An Empirical Study
Philip Y. K. Cheng – School of Business and Informatics Australian Catholic University, Sydney

This article extends previous research on how overconfidence affects trading performance in two ways. First, we examine whether the degree of impact is different between an electronic trading market (as in a stock market) and an open outcry environment (as in a futures market). Second, we examine the impact of overconfidence from the perspective of miscalibration, market confidence, the better than average effect, and risk attitudes. The significant findings (5%) indicate that higher overconfidence leads to poorer trading performance generally. However, the degree of impact is higher in an open outcry environment, where there are visual, verbal, and emotional interactions between traders, than in an electronic trading environment, where a trader operates primarily in an isolated setting. Likewise, the traders who choose to trade in an open outcry environment are generally more overconfident than those who trade in a more isolated setting. The contribution of our study is therefore to highlight the importance of interactions between traders in the studies of overconfidence on trading performance. Our findings are based on the trading performance of a sample of 159 tertiary students in a simulated trading environment over six weeks.

Affect and Financial Decision-Making: How Neuroscience Can Inform Market Participants
Richard L. Peterson – Market Psychology Consulting

We review recent neuroscience literature on the influences of moods, attitudes, and emotions (affects) on financial decision-making. Evidence indicates the existence of separate brain systems, linked to affect processing, that are responsible for risk-taking and risk-avoiding behaviors in financial settings. Excessive activation or suppression of either system can lead to errors in investment choices and trading behaviors. We suggest ways for market participants to become aware of the potential impact of affect on their behavior in order to avoid suboptimal financial decisions. This paper has two overall aims: to educate financial practitioners about the origins of emotions that can adversely impact their performance, and to teach investors how to make better financial decisions.

Mental Liquidity
Kenneth L. Fisher – Fisher Investments, Inc.
Meir Statman – Santa Clara University

The Financial/Economic Dichotomy in Social Behavioral Dynamics: The Socionomic Perspective
Robert R. Prechter Jr. – Socionomics Institute, Gainesville, Georgia
Wayne D. Parker – Socionomics Foundation, Gainesville, Georgia

Neoclassical economics does not offer a useful model of finance, because economic and financial behavior have different motivational dynamics. The law of supply and demand operates among rational valuers to produce equilibrium in the marketplace for utilitarian goods and services. The efficient market hypothesis (EMH) is a related model applied to financial markets. The socionomic theory of finance (STF) posits that contextual differences between economics and finance produce different behavior, so that in finance the law of supply and demand is irrelevant, and EMH is inappropriate. In finance, uncertainty about valuations by other homogeneous agents induces unconscious, non-rational herding, which follows endogenously regulated fluctuations in social mood, which in turn determine financial fluctuations. This dynamic produces non-mean-reverting dynamism in financial markets, not equilibrium.

"New Economy" Firms and Momentum
Luis Muga – Public University of Navarre, Spain
Rafael Santamar – Public University of Navarre, Spain

This article evaluates how "new economy" stocks may contribute to the momentum effect. Our results reveal that, by virtue of their distinct characteristics, these assets are more likely to generate momentum returns, and thus to increase the concentration of momentum traders. The combination of these two factors makes the momentum effect stronger in the new economy than in other industries.

Volume 8, Number 3, 2007 Abstracts
© Copyright Erlbaum 2007

Quantifying the Information Content of Investment Decisions in a Multiple Partial Moment Framework: Formal Definition and Applications of Generalized Conditional Risk Attribution
Noriyuki Okuyama - Pareto Investment Management Limited in London
Gavin Francis - Pareto Investment Management Limited in London

Investment decisions are based on a trade-off between profit and loss. This paper aims to measure the effectiveness of active investment decision-making processes by comparing the distributions of positive and negative outcomes against those available to a passive investor. A genuinely skillful active manager should generate outcomes with more attractive loss/gain balances than a passive buy-and-hold strategy. Generalized conditional risk attribution is a method of assessing whether a decision-making process has created this benefit.

The Behavior of Japanese Individual Investors During Bull and Bear Markets
Kenneth A. Kim - School of Management, State University of New York at Buffalo
John R. Nofsinger - College of Business, Washington State University

We study Japanese individual investors by contrasting their behavior during a long bull market (1984-1989) to a long bear market (1990-1999). Our main objective is to test whether individuals' attitudes and preferences toward stock risk, book-to-market valuation, and past returns, are different between market conditions. We also assess individuals' investing performance. Overall, we identify some striking differences in investing behavior between the bull and the bear market. These behaviors are associated with poor investment performance. Some of our findings are consistent with existing behavioral theories, but some of our findings are not.

Reporting Frequency and Sample Size: Effects on Prediction, Confidence Levels, and Confidence Intervals
Terence J. Pitre - Graduate School of Business

Very little research has examined the possible consequences of more frequent financial reporting. Using a between-subjects experiment, I examine one possible consequence—increased sample size of data—and its effect on non-professional investor uncertainty (as measured by confidence intervals and confidence levels) and predictions. I report three principal findings: 1) Confidence intervals increase with larger sample sizes, rather than decrease as statistical theory suggests, 2) confidence levels are unaffected by sample size when the investor does not view it as important for accuracy, and 3) estimates generated from larger sample sizes are nearer to the sample mean and significantly different from those from smaller samples, which also contradicts statistical theory.

Answering Financial Anomalies: Sentiment-Based Stock Pricing
Edward R. Lawrence - Florida International University
George McCabe - University of Nebraska
Arun J. Prakash - Florida International University

The efficient market hypothesis (EMH) assumes that investors are rational and value securities rationally. A rational investor would value a security by its net present value; the price of a stock in this framework is based on the discounted cash flow or the present value model. Although the EMH-based model is partially successful in computing fundamental stock prices, other anomalies such as high trading volume, high volatility, and stock market bubbles remain unexplained. These models assume rational investors who are utility maximizers. But some investors behave irrationally or against the predictions, and in the aggregate they become irrelevant. In this paper, we relax the assumption of investor rationality, and attempt to explain high volatility, high trading volume, and stock market bubbles by incorporating investor sentiment into the already existing asset pricing model.

"Investing" versus "Investing for a Reason": Context Effects in Investment Decisions
Nick Sevdalis - Imperial College London
Nigel Harvey - University College London

Emerging empirical evidence from the field of behavioral finance has established systematic behavioral influences on investment decisions, including investor gender, personality, and cultural profile. Our aim here is to test whether investment intentions are systematically affected by the context of the investment decision (operationalized as investor goals). We hypothesize that if the context of an investment is made salient at the time of the decision, investors are likely to avoid riskier investment options (operationalized as investments that yield potentially high but variable returns). Our three experimental studies supported our hypothesis.

The Geography of S&P 500 Stock Returns
David Barker - University of Iowa
Tim Loughran - University of Notre Dame

Investor bias in favor of geographically close firms has been documented in previous papers. An implication of this bias is that if local events cause nearby investors to trade together, then the correlation of stock returns of pairs of firms will increase as the distance between them decreases. We test this hypothesis using a sample of Standard & Poor's (S&P) 500 companies. After adjusting for industry effects and other factors, we find that the correlation coefficient between two stocks increases 12 basis points for every 100-mile reduction in distance. This result is consistent with local shocks affecting the returns of nearby firms by an average of approximately 43 basis points per month. We conclude these shocks are most likely the result of trading activity by local investors who own shares in nearby firms.

The Hot Stock Tip from Debbie: Implications for Market Efficiency
Kenneth Small - Coastal Carolina University
Jeff Smith - Air Force Institute of Technology

In July and August 2004 thousands of messages were left on answering machines across the United States touting Maui General Stores (MAUG). Interestingly, these messages contained no material information, but the price of MAUG experienced a significant increase in value. According to the Securities and Exchange Commission (SEC), MAUG's market capitalization increased by more than $100 million. However, the price of MAUG returned to its “pre-message” level after the firm's CEO enters the market on the sell side, well before the SEC announced the messages as a scam. We discuss how this event expands our understanding of market efficiently.

Earnings per Share: Stylized Facts and New Paradigms
Rolando F. Pelaez - University of Houston

The paradigm that inspired the equity price bubble of the 1990s is inconsistent with the long-term earnings expectations that a rational agent could draw from the stylized facts available in real time. The paper identifies the stylized facts that characterize the behavior of accounting earnings per share (EPS) that Standard & Poor's has reported for the S&P 500 index since 1935. Estimation of an unobserved components model in state-space form shows that the long-run component of earnings is predictable, and that its growth rate has obeyed a deterministic process for three-quarters of a century. It is impossible to reconcile a deterministic slope in log EPS with the new paradigms and other delusions regarding earnings that periodically generate equity bubbles. The evidence is inconsistent with market rationality, and buttresses a behavioral theory of finance in which folly occasionally occupies center stage.

Information-Adjusted Noise Model: Evidence of Inefficiency on the Australian Stock Market
Vikash Ramiah - RMIT University
Sinclair Davidson - RMIT University

We describe the interaction between noise traders and information traders. We do not assume that information traders are error-free. Instead information traders make mistakes leading to under-reaction and over-reaction. Information traders may even add to pricing errors in the market. These interactions are captured in our information-adjusted noise model. We test our model using data from the Australian Stock Exchange. This market has a continuous information disclosure regime that allows us to determine when information is released to the market. We present evidence consistent with the notion that the market is often informationlly inefficient.

Managerial Overoptimism and the Choice Between Debt and Equity Financing
Michael Gombola - Drexel University
Dalia Marciukaityte - Louisa Tech University

This paper compares long-run stock performance following debt financing and equity financing for a sample of rapidly growing firms. If managers are subject to overly optimistic predictions for their asset acquisitions, they are more likely to finance asset growth by debt rather than by equity. The managerial overoptimism hypothesis predicts worse long-term performance for debt-financed asset acquisitions than equity-financed asset acquisitions. If, on the other hand, managers take advantage of “windows of opportunity” for issuing equity, we expect worse performance following equity issuance than following debt issuance. Consistent with the managerial overoptimism hypothesis, we find that debt financing is followed by significantly worse stock performance than equity financing. Managerial overoptimism seems to be a significant factor affecting the choice between debt and equity financing and post-financing stock performance.