An econometric analysis of nonsynchronous trading

Abstract

We develop a stochastic model of nonsynchronous asset prices based on sampling with random censoring. In addition to generalizing existing models of non-trading our framework allows the explicit calculation of the effects of infrequent trading on the time series properties of asset returns. These are empirically testable implications for the variances, autocorrelations, and cross-autocorrelations of returns to individual stocks as well as to portfolios. We construct estimators to quantify the magnitude of non-trading effects in commonly used stock returns data bases, and show the extent to which this phenomenon is responsible for the recent rejections of the random walk hypothesis.

Realized Volatility: A Review

“…In a related work, Martens (2005) evaluated the MSE properties of a number of covariance estimators through simulations based on Lo and MacKinlay's (1990) nonsynchronous trade model.…”

Do foreigners facilitate information transmission in emerging markets?

“…An obvious explanation is the nonsynchronous trading that stock prices are sampled nonsynchronously, which induces spurious lead-lag effects (Boudoukh, Richardson and Whitelaw (1994)). However, Lo and MacKinlay (1990b) show that one has to believe in unrealistically thin markets for nonsynchronous trading to account for the magnitude of observed cross-correlations.…”

Autoregressive Conditional Heteroscedasticity (ARCH) Models: A Review

“…So, it is falsely assumed that the daily prices are equally spaced at 24-hour intervals. The importance of non-synchronous trading was first recognized by Fisher [129] and further developed by many researchers such as Atchison et al [16], Cohen et al [83], Cohen et al [81,82], Dimson [97], Lo and MacKinlay [210,211,212], Scholes and Williams [273].…”