An international study of causality-in-variance: Interest rate and financial sector returns

We demonstrate that causality-in-variance test could be employed to model the direction and lags in information flow between two variables and to avoid misspecifications. We apply this methodology to test the causality between the financial sector returns and interest rates of the G7 countries and show that the direction and the lead/lag structure of causality in the mean and the variance are more complex and dynamic than that have previously been reported. In most cases, we found two-way information flow both at the mean and the volatility level. Causality results give us insights into (i) how and when information is impacted on different market segments, and (ii) design more objective bi-variate models with the appropriate lag structure.