Heterosedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume - i.e. unexpected above-avergae trading activity - which is derived from uncorrelated volume innovations. Assuming eakly exogenous volume, we extend the Lamoureux and...

Accurate modeling of extreme price changes is vital to financial risk management. We examine the small sample properties of adaptive tail index estimators under the class of student-t marginal distribution functions including GARCH and propose a model-based bias-corrected estimation approach....

Heteroskedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume - i.e. unexpected above-average trading activity - which is derived from uncorrelated volume innovations. Assuming weakly exogenous volume, we extend the Lamoureux and...

Estimation of the tail index of stationary, fat-tailed return distributions is non-trivial since the well-known Hill estimator is optimal only under iid draws from an exact Pareto model. We provide a small sample simulation study of recently suggested adaptive estimators under ARCH-type...

This paper reconsiders return-volume dependence for the U.S. and six international equity markets. We contribute to previous work by proposing surprise volume as a new proxy for private information flow and apply extreme value theory in studying dependence for large volume and return, i.e. under...

Heteroskedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume—i.e. unexpected above-average trading activity—which is derived from uncorrelated volume innovations. Assuming weakly exogenous volume, we extend the Lamoureux and...

Accurate modeling of extremal price changes is vital to financial risk management. We examine the small sample properties of adaptive tail index estimators under the class of student-t marginal distribution functions including GARCH and propose a model-based bias-corrected estimation approach....