How Persistent are the Effects of Experience Sampling on Investor Behavior?, Journal of Banking & Finance 88, pp. 61-79 (2019) with M. Bradbury and T. Hens
All’s Well That Ends Well? On the Importance of how Returns are Achieved, Journal of Banking & Finance 87, pp. 397-410 (2018) with D. Grosshans
Do We Measure Overconfidence? A Closer Look at the interval Production Task, Journal of Economic Behavior & Organization 128, pp. 121-133 (2016) with F. Langnickel
Improving Investment Decisions with simulated experience, Review of Finance 19, pp. 1019-1052 (2015) with M. Bradbury and T. Hens
The impact of monetary policy on stock market bubbles and trading behavior: evidence from the lab, Journal of Economic Dynamics and Control 37, pp. 2104-2122 (2013) with U. Fischbacher and T. Hens
Measuring the Time Stability of Prospect Theory Preferences, Theory and Decision 72, pp. 359-386 (2012) with D. Vrecko and T. Langer
Why does myopia decrease the willingness to invest? Is it Myopic Loss Aversion or Myopic Loss Aversion Probability?, Theory and Decision 72, pp. 35-50 (2012) with T. Langer and M. Weber
Investment Horizon and the Attractiveness of Investment Strategies: A Behavioral Approach, Journal of Banking & Finance 34, pp. 1032-1046 (2010) with M. Dierkes and C. Erner
A Note on Myopic Loss Aversion and the Equity Premium Puzzle, Finance Research Letters 4, pp. 127-136 (2007) with M. Trede and T. Langer
The Role of Beliefs in Trading Decisions (2018) with F. Langnickel and D. Grosshans
This study provides new insights on how investors form beliefs about future asset prices and how they use these beliefs for their trading decisions. Compared to the objective Bayesian benchmark, investors become overly optimistic when they face a paper loss. In addition, selling decisions are less sensitive to beliefs than purchase decisions. This difference is driven by selling behavior in the presence of paper losses. Our insights stem from a laboratory experiment in which participants are price-takers and trade a stock governed by a persistent two-state Markov chain. At each point in time, we elicit incentivized beliefs about the probability that the stock price will increase in the next period.
Does Investor Risk Perception Drive Asset Prices in Markets? Experimental Evidence (2018) with J. Huber and S. Palan
What people perceive as risk clearly goes beyond variance. Several papers have shown that, e.g., probability of loss plays a more prominent role in perceived risk than does variance. We are the first to explore how individual risk perception influences prices and trading behavior in a market setting by exposing subjects to a number of differently shaped return distributions which they then trade on. We first elicit subjects’ individual risk perceptions, finding results in line with earlier papers. We then let subjects trade assets with these return distributions on a continuous double auction market. In the markets we observe active trading and prices strongly driven by average risk perception. While standard finance theory predicts identical prices for most of our assets we find average prices to vary by up to 20 percent, with assets perceived as being less risky trading at significantly higher prices.
In a series of experiments we demonstrate that people pay explicit attention to the probability of losing. Participants’ willingness to take risks and choice behavior is considerably influenced by loss probabilities, and performance feedback seems unable to mitigate this effect. This behavior contradicts predictions of normative and descriptive decision theories such as Expected Utility Theory and (Cumulative) Prospect Theory for typically assumed preference parameters and functional forms. Our results hold for investment, allocation and choice tasks, for repeated decisions and one-shot ones as well as for decision from experience and decisions based on description.
What drives risk perception? A global survey with financial professionals and laymen (with F. Holzmeister, J. Huber, F. Lindner, M. Kirchler and U. Weitzel)
While risk is quite a important in many domains of life, not much is known about how risks are actually perceived by financial professionals. In a large-scale experiment with 2,000+ finance professionals and 4,500+ lay people in nine countries (representing 50% of world population and more than 60% of world gross domestic product) we presented exposed participants with return distributions that had equal expected return and systematically varied the variance, skewness and kurtosisof the return distribution. Of these three moments, skewness turns out to be the only one that systematically affects participants’ perception of financial risk, and variance hardly influences the perception of risk, despite the fact that return volatility most frequently used in finance, in both academia and the industry. Generally, there are hardly any differences between financial professionals and lay people. Our results hold similarly for investment propensity. When testing compound risk measures, the probability of losing has the highest influence on risk perception.
Do changes in reporting frequency really influence investors’ risk taking behavior? Myopic loss aversion revisited (2015) with T. Langer and M. Weber
According to the behavioral concept of myopic loss aversion (MLA), investors are more willing to take risks if they are less frequently informed about their portfolio performance. This prediction of MLA has been confirmed in various experimental studies and the conclusion has been drawn that banks could in fact influence investors’ risk taking behavior by adjusting the frequency with which they give feedback. However, none of the existing studies has really provided an explicit test of this dynamic prediction. Instead it is simply assumed that the results from between-subject experiments translate to a within-subject scenario in which feedback frequency changes over time. To examine the scope of the phenomenon and to assess its practical relevance, we present the first experimental study of MLA that directly addresses the dynamic prediction and manipulates feedback frequency (and investment flexibility) within-subject. Our analysis reveals that the impact of such dynamic changes is not as straightforward as commonly assumed. Stickiness and a general introspection component superimpose the standard MLA effect and generate unexpected dynamic patterns of risk taking behavior.
What is Risk? How investors perceive risk in return distributions
We investigate the determinants of risk perception and investment propensity in a financial context. In a series of experiments, participants are presented with return distributions. Our study design allows to separate various risk measures such as variance of returns, skewness, probability of losing or the maximum possible loss. Our results hint to the probability of losing being the main driver of risk perception and investment propensity. Volatility, which is typically used by researchers, financial advisors and the regulator, does not play a major role. Our insights should allow financial advisors and regulators to support an effective and understandable communication of investment risks to prevent suboptimal investment decisions.
What makes a price path risky? (with C. Borsboom)
Greed and Bubbles (with S. Breugelman, K. Hoyer, T. Seuntjens and M. Zeelenberg)
How investors cope with crashes (with S. Andraszewicz, C. Hölscher, D. Kaszás)
Management Guidance – bevorzugen professionnelle Kapitalmarktteilnehmer wirklich Punktprognosen?, Journal of Management Control 21, 349-364 (2011) with Lammert, J. and C. Watrin