题  目：EXTREME RETURNS AND INTENSITY OF TRADING

报告人：林  蔚  副教授 首都经贸大学

主持人：罗德明  教授   浙江大学经济学院

时  间：2016年11月18日   星期五   13:30-15:00

地  点：浙大玉泉校区经济学院418室

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Abstract：

Asymmetric information models of market microstructure claim that variables like trading intensity are proxies for latent information on the value of _nancial assets. We consider the intervalvalued time series (ITS) of low/high returns and explore the relationship between these extreme returns and the intensity of trading. We assume that the returns (or prices) are generated by a latent process with some unknown conditional density. At each period of time, from this density, we have some random draws (trades) and the lowest and highest returns are the realized extreme observations of the latent process over the sample of draws. In this context, we propose a semiparametric model of extreme returns that exploits the results provided by extreme value theory. If properly centered and standardized extremes have well de_ned limiting distributions, the conditional mean of extreme returns is a highly nonlinear function of conditional moments of the latent process and of the conditional intensity of the process that governs the number of draws. We implement a two-step estimation procedure. First, we estimate parametrically the regressors that will enter into the nonlinear function, and in a second step, given the generated regressors, we estimate nonparametrically the conditional mean of extreme returns. Unlike current models for ITS, the proposed semiparametric model is robust to misspeci_cation of the conditional density of the latent process. We _t several nonlinear and linear models to the 5-min low/high returns to three major bank stocks, Wells Fargo, Bank of America, and J.P. Morgan, and _nd that, either in-sample or out-of-sample, the nonlinear speci_cation is superior to the current linear models and that the conditional standard deviation of the latent process and the conditional intensity of the trading process are major drivers of the dynamics of extreme returns.

CRPE秘书处

2016-11-14