We study the effects of stock market volatility on risk-taking and financial crises by constructing a cross-country database spanning up to 211 years and 60 countries. Prolonged periods of low volatility have strong in-sample and out-of-sample predictive power over the incidence of banking...

Large data sets in finance with millions of observations have becomewidely available. Such data sets enable the construction of reliablesemi-parametric estimates of the risk associated with extreme pricemovements. Our approach is based on semi-parametric statisticalextreme value analysis, and...

Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...