Risk Taking and Information Handling in Consumer Behavior

Abstract. The Balloon-Analogue Risk Task (BART; Lejuez et al., 2002 ) is one of the most popular behavioral tasks suggested to assess risk-taking in the laboratory. Previous research has shown that the conventionally computed score is predictive, but neglects available information in the data. We suggest a number of alternative scores that are motivated by theories of risk-taking and that exploit more of the available data. These scores can be grouped around (1) risk-taking, (2) task performance, (3) impulsive decision making, and (4) reinforcement sequence modulation. Their theoretical rationale is detailed and their validity is tested within the nomological network of risk-taking, deviance, and scholastic achievement. Two multivariate studies were conducted with youths (n = 435) and with adolescents/young adults (n = 316). Additionally, we tested formal models suggested for the BART that decompose observed behavior into a set of meaningful parameters. A simulation study with parameter recovery was conducted, and the data from the two studies were reanalyzed using the models. Most scores were reliable and differentially predictive of criterion variables and may be used in basic research. However, task specificity and the generally moderate validity do not warrant use of the experimental paradigm for diagnostic purposes.

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The Vienna Risk-Taking Test - Traffic

Journal of Individual Differences ◽

10.1027/1614-0001.28.4.198 ◽

2007 ◽

Vol 28 (4) ◽

pp. 198-204 ◽

Cited By ~ 11

Author(s):

Andreas Hergovich ◽

Martin E. Arendasy ◽

Markus Sommer ◽

Bettina Bognar

Keyword(s):

Construct Validity ◽

Personality Trait ◽

Risk Taking ◽

Personality Test ◽

Educational Levels ◽

Item Level ◽

Degree Of Risk ◽

And Gender ◽

Homeostasis Theory

Abstract. The study reports results regarding the dimensionality and construct validity of a newly developed, objective, video-based personality test that assesses the willingness to take risks in traffic situations. On the basis of the theory of risk homeostasis developed by Wilde, different traffic situations with varying degrees of objective danger were filmed. During the test the respondents are asked to indicate at which point the action that is contingent on the described situation will become too dangerous to carry out. Latencies at the item level were recorded as a measure for the subjectively accepted degree of a person's willingness to take risks in the sense of the risk homeostasis theory by Wilde. In a study on 274 people with different educational levels and gender, the unidimensionality of the test as corresponding to the latency model by Scheiblechner was investigated. The results indicate that the Vienna Risk-Taking Test - Traffic assesses a unidimensional, latent personality trait that can be interpreted as subjectively accepted degree of risk (target risk value).

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Predicting Stock Market Performance

Journal of Individual Differences ◽

10.1027/1614-0001/a000330 ◽

2020 ◽

pp. 1-10

Author(s):

Thomas Plieger ◽

Thomas Grünhage ◽

Éilish Duke ◽

Martin Reuter

Keyword(s):

Stock Market ◽

Risk Taking ◽

Life Stress ◽

Price Volatility ◽

Individual Characteristics ◽

Self Report ◽

Financial Behavior ◽

Market Simulation ◽

Stock Market Performance ◽

Risk Taking Behavior

Abstract. Gender and personality traits influence risk proneness in the context of financial decisions. However, most studies on this topic have relied on either self-report data or on artificial measures of financial risk-taking behavior. Our study aimed to identify relevant trading behaviors and personal characteristics related to trading success. N = 108 Caucasians took part in a three-week stock market simulation paradigm, in which they traded shares of eight fictional companies that differed in issue price, volatility, and outcome. Participants also completed questionnaires measuring personality, risk-taking behavior, and life stress. Our model showed that being male and scoring high on self-directedness led to more risky financial behavior, which in turn positively predicted success in the stock market simulation. The total model explained 39% of the variance in trading success, indicating a role for other factors in influencing trading behavior. Future studies should try to enrich our model to get a more accurate impression of the associations between individual characteristics and financially successful behavior in context of stock trading.

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