Order Flow, Transaction Clock, and Normality of Asset Returns
通过随机时间变换恢复资产收益的正态性，发现累计交易次数比成交量更优，并允许非参数建模，对金融资产收益分布研究有参考价值。
The goal of this paper is to show that normality of asset returns can be recovered through a stochastic time change. Clark (1973) addressed this issue by representing the price process as a subordinated process with volume as the lognormally distributed subordinator. We extend Clark's results and find the following: (i) stochastic time changes are mathematically much less constraining than subordinators; (ii) the cumulative number of trades is a better stochastic clock than the volume for generating virtually perfect normality in returns; (iii) this clock can be modeled nonparametrically, allowing both the time‐change and price processes to take the form of jump diffusions.