Intraday Dynamics of Market Correlation and Impact of Macroeconomic Announcements
Average of correlations between assets in the stock market measures stock price comovement. Understanding the dynamics of average correlation is critical to managing correlation risk. Analyzing the intraday dynamics of correlations among high-frequency returns is challenging due to market microstructure noise (e.g. discretization, asynchronous trading). The task becomes particularly difficult for illiquid periods, such as pre-open and post-close trading sessions. This paper proposes a novel quadrant-based correlation measure that is robust to market microstructure noise and more computationally efficient than the conventional Pearson correlation. I apply this measure to 1-second NASDAQ trade-price data for S&P 500 constituents to examine the intraday dynamics of market correlation, including the pre-open and post-close trading sessions. I also analyze how major macroeconomic announcements influence these intraday correlation patterns. The results show that correlation is lower in the pre-open and post-close sessions compared to active trading hours and correlation increases over the course of the trading day. I also find that correlation response to different macroeconomic announcements differently.