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.