Conditional value-at-risk (CVaR) precisely characterizes the influence that rare, catastrophic events can exert over decisions. Such characterizations are important for both normal decision-making and for psychiatric conditions such as anxiety disorders -- especially for sequences of decisions that might ultimately lead to disaster. CVaR, like other well-founded risk measures, compounds in complex ways over such sequences -- and we recently formalized three structurally different forms in which risk either averages out or multiplies. Unfortunately, existing cognitive tasks fail to discriminate these approaches well; here, we provide examples that highlight their unique characteristics, and make formal links to temporal discounting for the two of the approaches that are time consistent. These examples can ground future experiments with the broader aim of characterizing risk attitudes, especially for longer horizon problems and in psychopathological populations.
翻译:有条件的高风险价值(CVaR)精确地描述罕见的灾难性事件对决策的影响,这种特征对于正常决策和焦虑症等精神病状况都很重要,特别是对于最终可能导致灾难的决定序列而言。 CVaR与其他有充分依据的风险措施一样,在这类序列中以复杂的方式复合 -- -- 我们最近正式确定了三种结构上不同的形式,这种形式有平均风险或倍增风险。 不幸的是,现有的认知任务没有很好地区分这些方法;在这里,我们提供一些例子,突出这些方法的独特性,并正式联系到时间一致的两种方法的时间折扣。这些例子可以把未来试验的更广泛目标放在确定风险态度的特征上,特别是针对长期问题和精神病学人群。