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| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Improving the Comprehension of Return Distributions and Risk - Are Interactive State-Charts an Alternative to Experience Sampling? |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 51 |
| Date | 2018 |
| Zusammenfassung | Providing financial advice assumes comprehension of risk and return. However, behavioral research of subjects confronted with financial decisions contradicts the classical assumption of informed and rational investors. In general, people lack the intuition to process statistical information properly. In financial context, a severe consequence is the overestimation of the probability of a loss induced by descriptive methods of risk communication. Furthermore, different presentation formats of the same risk-return profile vary the risk and return perceived by individuals. Considering that subjective risk measures seem to influence risk-taking more than objective measures, such as variance or standard deviation, this eventually leads to biased investment decisions. Concluding, communicating risk to the investor by description-based methods does not deliver satisfying results. Thus, recent studies aim at finding the most appropriate method which helps investors align their perception of risk and return with the actual profile of the underlying distribution. Better comprehension of risk should reduce the overestimation of rare events and improve the accuracy of expected outcome estimates, which in turn should lead to riskier portfolio allocations. A key finding is the so-called description-experience gap: Risk perception can differ significantly depending on whether individuals acquire information through description or experience. Simulated experience is able to improve the comprehension of return distributions significantly. However, a common criticism is that simulated experience can be prone to sampling biases if the sample size is small. Obviously, this can be avoided by sampling larger sizes which represent the distribution accurately. As a consequence, the process of information acquisition gets extended. This is time-costly and thus not very practical. In addition, it can lead to another potential bias, the recency effect. This is where this master thesis tries to add value by introducing a new risk communication tool called interactive state-charts. Instead of simulating random outcomes of the underlying distribution, one could divide the return distribution in five equally likely states and interactively illustrate the average outcome of each state. The purpose of this thesis is to examine whether interactive state-charts are able to provide similar results as experience sampling while overcoming the issue of sampling biases with a simpler presentation format. Overall, this thesis extends previous research in three main ways: Interactive state-charts are presented as a new possibility to communicate risk, risk comprehension is assessed more thoroughly, and the effect of the tools is analyzed on two differently risky products. |
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