An econometric analysis of nonsynchronous trading

By Andrew W. Lo, A. Mackinlay. 2015

801 citations recorded by the source corpus.

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.

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Citations in the corpus

HAR Modeling for Realized Volatility Forecasting (2012, unknown): “First, in addition to the common microstructure effect biasing realized volatility measures (i.e. bid-ask spread, price discreteness, etc.), the so called non-synchronous trading effect ([60]) strongly affects the estimation of the realized covariance and correlation measures.”
News Announcements, Market Activity and Volatility in the Euro/Dollar Foreign Exchange Market (2005, unknown): “According to Goodhart and Figliuli (1991), the negative autocorrelation stems from constraints in the control of positions, while according to Bollerslev and Domowitz (1993) and Lo and MacKinlay (1990), this feature comes from the computation of asynchronous price series at the interval endpoints.”
Who Cares About Shareholders? Arbitrage-Proofing Mutual Funds (2003, unknown): “On predictability of indices of illiquidly traded domestic securities, see Lo and MacKinlay (1990) and Boudoukh, Richardson, and Whitelaw (1994).”
From value at risk to stress testing : The extreme value approach Franc ß ois (2000, background): “The problem of infrequent trading characterizing assets of illiquid positions may be dealt with by some data adjustment as done in Lo and MacKinlay (1990) and Stoll and Whaley (1990).”
Are "Market Neutral" Hedge Funds Really Market Neutral? (2009, background): “These authors conclude that the most likely causes of serial correlation in hedge fund returns are exposures to illiquid assets, which lead to positive serial correlation due to nonsynchronous trading (see Lo and MacKinlay 1990 ) and/or intentional performance smoothing by hedge fund managers.”
The Adaptive Markets Hypothesis (2004, background): “A decade after Samuelson’s (1965) landmark paper, many others extended his framework to allow for risk-averse investors, yielding a “neoclassical” version of the EMH where price changes, properly weighted by aggregate marginal utilities, must be unforecastable (see, for example, LeRoy, 1973; Rubinst”
Intraday Technical Trading in the Foreign Exchange Market (2003, background): “14 Lo and MacKinlay (1990) derive a formula for the level of serial correlation induced by non-synchronous trading if the true return series follows a random walk with drift.”
Estimating Covariation: Epps Effect, Microstructure Noise (2011, unknown): “Lo and MacKinlay (1990) propose a solution based on a stochastic model of censoring.”
Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression (2016, background): “Lo and MacKinlay [4] attribute the positive autocorrelation in daily stock returns to nonsynchronous trading.”