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 historical and pricing return dynamics enhancing the model flexibility to fit market option prices. An extensive...

Regulators charged with monitoring systemic risk need to focus on sentiment as well as narrowly defined measures of systemic risk. This chapter describes techniques for jointly monitoring the co-evolution of sentiment and systemic risk. To measure systemic risk, we use Marginal Expected...

We combine two approaches to the pricing kernel, one empirical and one theoretical, which relax the restriction that the objective return distribution and risk neutral distribution share the same volatility and higher order moments. The empirical approach provides estimates for the evolution of...

We consider modeling errors in the hedging of a portfolio composed from BBB-rated bonds. By doing this, we open a new perspective to the debate on the relationship between corporate bonds and CDS spreads. We find that in ordinary times the added value of indexlinked credit derivatives is very...

Regulators dedicate much attention to the option that financial institutions in distress have to transfer losses to their creditors. It is generally recognized that the existence of this option provides intermediaries with a powerful incentive to keep firm capital close to the minimal...

The article presents a Bayesian nonparametric approach to model the Pricing Kernel (PK), defined as the present value of the ratio between the risk neutral density, q, and a modified physical density, p*. The risk neutral density is estimated from option data and the modified physical density is...