We examine the volatility‐volume relation in futures markets using volume data categorized by type of trader. We find that the positive volatility‐volume relation is driven by the general public, a group of traders who are distant from the trading floor and therefore without precise information on order flow. Clearing members and floor traders who observe order flow often decrease volatility. Our findings are consistent with Shalen's (1993) hypothesis that uninformed traders who cannot differentiate liquidity demand from fundamental value change increase volatility.

We examine the volatility‐volume relation in futures markets using volume data categorized by type of trader. We find that the positive volatility‐volume relation is driven by the general public, a group of traders who are distant from the trading floor and therefore without precise information on order flow. Clearing members and floor traders who observe order flow often decrease volatility. Our findings are consistent with Shalen's (1993) hypothesis that uninformed traders who cannot differentiate liquidity demand from fundamental value change increase volatility.

Previous research claims that low constant correlations among international stock indices create substantial risk-reduction from diversification. We contend that only using constant correlations is too simplistic an approach. We examine international diversification by: (1) using conditional correlations, (2) evaluating tail risk, including the effect of skewness and kurtosis, and (3) examining the possible tradeoffs of standard deviation with correlation, skewness, and kurtosis. We show that conclusions concerning diversification based solely on constant correlations across markets can be misleading, since the diversification benefits are time-varying, are affected by non-normality, and depend on the benchmark (country) employed. Finally, tradeoffs do exist between standard deviation and the other risk factors.

We examine the short-term dynamic relation between the S&P 500 (Nasdaq 100) index return and changes in implied volatility at both the daily and intraday level. Neither the leverage hypothesis nor the volatility feedback hypothesis adequately explains the results. Alternatively, we propose that the behavior of traders (from the representativeness, affect, and extrapolation bias concepts of behavioral finance) is consistent with our empirical results of a strong daily and intraday negative return–implied volatility relation. Moreover, both the presence and magnitude of the negative relation and the asymmetry between return and implied volatility are most closely associated with extreme changes in the index returns. We also show that the strength of the relation is consistent with the implied volatility skew.