Infinite Density at the Median and the Typical Shape of Stock Return Distributions
开发了检验概率密度在中位数处是否存在渐近不连续性（无限密度或尖峰）的统计方法，结合Knight的L1估计渐近理论与非参数核密度估计，通过模拟评估检验效果，并应用于美国主要行业龙头股的收益数据，证实了中位数处无限密度作为股票收益分布的新显著经验证据。
Statistics are developed to test for the presence of an asymptotic discontinuity (or infinite density or peakedness) in a probability density at the median. The approach makes use of work by Knight (1998) on L1 estimation asymptotics in conjunction with nonparametric kernel density estimation methods. The size and power of the tests are assessed, and conditions under which the tests have good performance are explored in simulations. The new methods are applied to stock returns of leading companies across major U.S. industry groups. The results confirm the presence of infinite density at the median as a new significant empirical evidence for stock return distributions.