Information flows, stock market volatility, and the systemic risk in global finance

Information flows are a theoretical explanation for stock market volatility, but controversy remains regarding how to measure them. Based on cross-sectional and temporal properties of information flows, we decompose total trading volume into four types: cross-country shocks and country-specific shocks due to arrivals of private information, and trading volume shocks and stock volatility shocks due to public information. We then use a Structural Vector Autoregressive model to reconstruct historical trading volume resulted from the four types of information shocks. The evidence shows that the historical trading volumes due to private information flow can explain volatility clustering of stock markets. By analysing sources of information flow, we find private information flow reflects systemic risk in the global financial system. The result conforms to Mixture of Distribution Hypothesis and finds that quality of information content is what differentiates privately informed trading from public information trading. It further suggests the main drivers of stock market volatility are uncertainties about fundamental values of assets and about other investors’ behaviours.