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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...
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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...
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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...
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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...
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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...
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