We employ extreme value theory to identify stock price crashes, featuring low-probability events that produce large, firm-specific negative outliers in the conditional distribution. Traditional methods employ approximations under Gaussian assumptions and central moments. This is inherently...

We propose a new method for pricing options based on GARCH models with filtered historical innovations. In an incomplete market framework we allow for different distributions of the historical and the pricing return dynamics enhancing the model flexibility to fit market option prices. An...

We propose a simple class of semiparametric multivariate GARCH models, allowing for asymmetric volatilities and time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of estimates for averaged correlations...