Stochastic Dominance and Cumulative Prospect Theory
将期望效用中的二阶随机优势条件推广到累积前景理论，提出新定义并设计实验检验价值函数和概率权重函数的联合假设，发现S形价值函数比反S形更符合数据，且损失厌恶得到支持。
We generalize and extend the second-order stochastic dominance condition for expected utility to cumulative prospect theory. The new definitions include preferences represented by S-shaped value functions, inverse S-shaped probability weighting functions, and loss aversion. The stochastic dominance conditions supply a framework to test different features of cumulative prospect theory. In the experimental part of the paper, we offer a test of several joint hypotheses on the value function and the probability weighting function. Assuming empirically relevant weighting functions, we can reject the inverse S-shaped value function recently advocated by Levy and Levy (2002) in favor of the S-shaped form. In addition, we find generally supporting evidence for loss aversion. Violations of loss aversion can be explained by subjects using the overall probability of winning as a heuristic.