We use tools of extreme value theory to extract information about rare events from market prices. We find that such information contributes materially to measures of banks' systemic importance. These measures exhibit strong and intuitive relationships with simple characteristics of banks'...

In the literature the effects of weather on electricity sales are well-documented. However, studies that have investigated the impact of weather on electricity prices are still scarce (e.g. Knittel and Roberts, 2005), partly because the wholesale power markets have only recently been...

This paper examines the predictive power of weather for electricity prices in day-ahead markets in real time. We find that next-day weather forecasts improve the forecast accuracy of day-ahead electricity prices substantially, suggesting that weather forecasts can price the weather premium....

This paper investigates how the downside tail risk of stock returns is differentiated cross-sectionally. Stock returns follow heavy-tailed distributions with downside tail risk determined by the tail shape and scale. If safety-first investors are concerned with sufficiently large downside...

We analyze the cross-sectional differences in the tail risk of equity returns and identify the drivers of tail risk. We provide two statistical procedures to test the hypothesis of cross-sectional downside tail shape homogeneity. An empirical study of 230 US non-financial firms shows that...

This paper empirically analyzes the determinants of banks' systemic importance. In constructing a measure on the systemic importance of financial institutions we find that size is a leading determinant. This confirms the usual "Too big to fail'' argument. Nevertheless, banks with size above a...

In the literature the effects of weather on electricity sales are well-documented. However, studies that have investigated the impact of weather on electricity prices are still scarce (e.g. Knittel and Roberts, 2005), partly because the wholesale power markets have only recently been...

The Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, designed to model volatility clustering, exhibits heavy-tailedness regardless of the distribution of its innovation term. When applying the model to financial time series, the distribution of innovations plays an...

Realized kernels introduced by Barndorff-Nielsen et al. (2008) are consistent estimators of the daily integrated volatility in the presence of microstructure noise. A crucial problem by applying realized kernels is the selection of the bandwidth. This paper proposes an iterative plug-in...

This paper empirically analyses the determinants of banks’ systemic importance. With applying a novel measure on the systemic importance to US bank holding companies in 2000–2010, we show that size is an important determinant of systemic importance, but banks with size above a certain...