Publication Date: June 2009
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 non-parametric 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.
Asymptotic leptokurtosis, Inﬁnite density at the median, Least absolute deviations, Kernel density estimation, Stock returns, Stylized facts
JEL Classification Codes: C12, G11
See CFP: 1338