Recursive Marginal Quantization (RMQ) allows fast approximation of solutions to stochastic differential equations in one-dimension. When applied to two factor models, RMQ is inefficient due to the fact that the optimization problem is usually performed using stochastic methods, e.g., Lloyd's...

We focus on two particular aspects of model risk: the inability of a chosen model to fit observed market prices at a given point in time (calibration error) and the model risk due to the recalibration of model parameters (in contradiction to the model assumptions). In this context, we use...

I study the relationship between interest rates and interest-rate volatility, particularly the idea of unspanned stochastic volatility (USV): volatility risk that cannot be hedged with bonds or swaps. Simulated data is used to assess the ability of regression-based techniques, popular but...

Certain models of the term structure of interest rates exhibit unspanned stochastic volatility (USV). A model has this property if it involves a source of stochastic variation — called an unspanned factor — that does not affect the model's interest rates directly, but does affect the extent...

As unspanned stochastic volatility (USV) models gain popularity in the literature, bivariate USV models (with one spanned and one unspanned factor) become a fundamental model class: they are the simplest USV models that are potentially useful, and (like general one-factor models) they are...