We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework...

In this paper we propose a smooth transition tree model for both the conditional mean and the conditional variance of the short-term interest rate process. Our model incorporates the interpretability of regression trees and the flexibility of smooth transition models to describe regime switches...

By proposing a measure for cross-market rebalancing effects, we provide new insights into the different sources of currency crises. We address three interrelated questions: (i) How can we best capture contagion; (ii) Is the contagion of currency crisis a regional or global phenomenon?; and (iii)...

We propose a general robust semiparametric bootstrap method to estimate conditional predictive distributions of GARCH-type models. Our approach is based on a robust estimator for the parameters in GARCH-type models and a robustified resampling method for standardized GARCH residuals, which...

This paper provides a new estimation method for the marginal expected shortfall (MES) based on multivariate extreme value theory. In contrast to previous studies, the method does not assume specific dependence structure among bank equity returns and is applicable to both large and small systems....

Price risk is among the most substantial risk factors for farmers. Through a two-sector general equilibrium model, we describe how fat tails in agricultural prices may occur endogenously as a result of productivity shocks. Using thirty years of daily futures price data, we show that the returns...

We test for the presence of a systematic tail risk premium in the cross-section of expected returns by applying a measure on the sensitivity of assets to extreme market downturns, the tail beta. Empirically, historical tail betas help to predict the future performance of stocks under extreme...

Extreme losses are the major concern in risk management. The dependence between financial assets and the market portfolio changes under extremely adverse market conditions. We develop a measure of systematic tail risk, the tail regression beta , defined by an asset's sensitivity to large...

The aim of this paper is to show that measures on tail dependence can be estimated in a convenient way by regression analysis. This yields the same estimates as the non-parametric method within the multivariate Extreme Value Theory framework. The advantage of the regression approach is contained...