5.1 Nonsynchronous Trading

We begin with nonsynchronous trading. Stock tradings such as those on the NYSE do not occur in a synchronous manner; different stocks have different trading frequencies, and even for a single stock the trading intensity varies from hour to hour and from day to day. Yet we often analyze a return series in a fixed time interval such as daily, weekly, or monthly. For daily series, the price of a stock is its closing price, which is the last transaction price of the stock in a trading day. The actual time of the last transaction of the stock varies from day to day. As such we incorrectly assume daily returns as an equally spaced time series with a 24-hour interval. It turns out that such an assumption can lead to erroneous conclusions about the predictability of stock returns even if the true return series are serially independent.

For daily stock returns, nonsynchronous trading can introduce (a) lag-1 cross correlation between stock returns, (b) lag-1 serial correlation in a portfolio return, and (c) in some situations negative serial correlations of the return series of a single stock. Consider stocks A and B. Assume that the two stocks are independent, and stock A is traded more frequently than stock B. For special news affecting the market that arrives near the closing hour on one day, stock A is more likely than B to show the effect of the news on the same day simply because A is traded more frequently. The effect of the news on B will eventually appear, ...

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