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
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 –
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 –
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
Rafael Santamar –
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
Gavin Francis - Pareto Investment Management Limited in
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,
John R. Nofsinger -
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 -
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 -
George McCabe -
Arun J. Prakash -
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 -
Nigel Harvey -
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.
Volume
8, Number 4, 2007 Abstracts
©
Copyright Taylor & Francis, LLC. 2007
The
Geography of S&P 500 Stock Returns
David Barker -
Tim Loughran -
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
Jeff Smith - Air Force Institute of Technology
In July and August 2004
thousands of messages were left on answering machines across the
Earnings
per Share: Stylized Facts and New Paradigms
Rolando F. Pelaez -
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 -
Sinclair Davidson -
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.