Emergence and temporal structure of Lead–Lag correlations in collective stock dynamics

Abstract

Understanding the correlations among stock returns is crucial for reducing the risk of investment in stock markets. As an important stylized correlation, lead–lag effect plays a major role in analyzing market volatility and deriving trading strategies. Here, we explore historical lead–lag relationships among stocks in the Chinese stock market. Strongly positive lagged correlations can be empirically observed. We demonstrate this lead–lag phenomenon is not constant but temporally emerges during certain periods. By introducing moving time window method, we transform the lead–lag dynamics into a series of asymmetric lagged correlation matrices. Dynamic lead–lag structures are uncovered in the form of temporal network structures. We find that the size of lead–lag group experienced a rapid drop during the year 2012, which signaled a re-balance of the stock market. On the daily timescale, we find the lead–lag structure exhibits several persistent patterns, which can be characterized by the Jaccard matrix. We show significant market events can be distinguished in the Jaccard matrix diagram. Taken together, we study an integration of all the temporal networks and identify several leading stock sectors, which are in accordance with the common Chinese economic fundamentals.