Jump and Sharp Cusp Detection by Wavelets
提出一种通过检查数据小波变换在精细尺度上是否有显著大绝对值来检测含噪函数中跳跃和尖锐尖点的方法，并应用于股市回报数据。
A method is proposed to detect jumps and sharp cusps in a function which is observed with noise, by checking if the wavelet transformation of the data has significantly large absolute values across fine scale levels. Asymptotic theory is established and practical implementation is discussed. The method is tested on simulated examples, and applied to stock market return data.