The relative contribution of conditional mean and volatility in bivariate returns to international stock market indices

We compare the relative contribution of conditional mean and conditional volatility terms in vector autoregression-exponential generalized autoregression conditional heteroskedasticity models of bivariate returns to international stock indices. Conditional mean terms are relatively unimportant for bivariate returns to country pairs that trade synchronously such as Australia/Japan, where they account for only 8% of the increase in log-likelihood over an unconditional model, on average. They are more important in nonsynchronous domestic/world-ex-domestic series such as Japan/world-ex-Japan, where they account for 24% of the increase in log-likelihood over an unconditional model, on average. Despite their increased prominence in the domestic/world-ex-domestic series, conditional mean terms detract from residual behaviours in these series. They also detract from some out-of-sample return and volatility predictions in both synchronous and nonsynchronous series.