In this paper, we study the aggregated risk from dependent risk factors under the multivariate Extreme Value theory (EVT) framework. We consider the heavy-tailness of the risk factors as well a non-parametric tail dependence structure. This allows a large scope of models on the dependency. We...

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 empirical evidence of heavy tails in stock return data is recognised by risk managers as an important factor in assessing the Value-at-Risk and risk profile of investment portfolios. Tail index estimation appears to be a tailor-made tool for estimating the extreme quantiles of heavy tailed...

We present a new method to examine financial contagion, defined as a sudden strengthening of shock transmission between financial markets. In particular, we develop a correlation-like measure of synchronicity between markets that is straightforward to implement while being insensitive to...

This paper studies the effects of verbal interventions by European cen-tral bankers on high-frequency euro-dollar exchange rates. We find that ECB verbal interventions have had only small and short-lived effects. Ver- bal interventions which are reported in news report headlines are more likely...

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...

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...

We analyze the distribution of regional unemployment in Europe over the last three decades using non-parametric kernel densities and stochastic kernels. In addition, we employ a multi-level factor model to separate European, country, and region-specific unemployment fluctuations. Three phases of...

This paper employs concepts from information theory to choosing the dimension of a data set. We calculate relative measures of information in the data in terms of eigenvalues and derive criteria to determine the `optimal' size of the data set, in particular whether an extra variable adds...