A note on optimal experimentation under risk aversion
在标准双臂赌博机模型中，研究发现更厌恶风险的决策者反而可能更愿意冒险，因为冒险能获取环境信息从而降低未来风险，这提醒我们观察到的冒险行为可能反映的是更高的风险厌恶。
In a standard two-armed bandit setup, this paper shows – counterintuitively – that a more risk-averse decision maker might be more willing to take risky actions. The reason relates to the fact that pulling the risky arm in bandit models produces information on the environment – thereby reducing the risk that a decision maker will face in the future. This finding gives reason for caution when inferring risk preferences from observed actions: in a bandit setup, observing a greater appetite for risky actions can actually be indicative of more risk aversion, not less.