106 research outputs found

    Eliciting ambiguity aversion in unknown and in compound lotteries: A smooth ambiguity model experimental study.

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    Coherent-ambiguity aversion is defined within the (Klibanoff et al., Econometrica 73:1849–1892, 2005) smooth-ambiguity model (henceforth KMM) as the combination of choice-ambiguity and value-ambiguity aversion. Five ambiguous decision tasks are analyzed theoretically,where an individual faces two-stage lotteries with binomial, uniform, or unknown second-order probabilities. Theoretical predictions are then tested through a 10-task experiment. In (unambiguous) tasks 1–5, risk aversion is elicited through both a portfolio choice method and a BDM mechanism. In (ambiguous) tasks 6–10, choice-ambiguity aversion is elicited through the portfolio choice method, while value-ambiguity aversion comes about through the BDM mechanism. The behavior of over 75% of classified subjects is in line with the KMM model in all tasks 6–10, independent of their degree of risk aversion. Furthermore, the percentage of coherent-ambiguity-averse subjects is lower in the binomial than in the uniform and in the unknown treatments, with only the latter difference being significant. The most part of coherent-ambiguity-loving subjects show a high risk aversion

    Emerging IT risks: insights from German banking

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    How do German banks manage the emerging risks stemming from IT innovations such as cyber risk? With a focus on process, roles and responsibilities, field data from ten banks participating in the 2014 ECB stress test were collected by interviewing IT managers, risk managers and external experts. Current procedures for handling emerging risks in German banks were identified from the interviews and analysed, guided by the extant literature. A clear gap was found between enterprise risk management (ERM) as a general approach to risks threatening firms’ objectives and ERM’s neglect of emerging risks, such as those associated with IT innovations. The findings suggest that ERM should be extended towards the collection and sharing of knowledge to allow for an initial understanding and description of emerging risks, as opposed to the traditional ERM approach involving estimates of impact and probability. For example, as cyber risks emerge from an IT innovation, the focus may need to switch towards reducing uncertainty through knowledge acquisition. Since individual managers seldom possess all relevant knowledge of an IT innovation, various stakeholders may need to be involved to exploit their expertise
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