The class of Markov-functional models (MFMs) provides a framework that can be used to define interest-rate models of finite dimension calibrated to any arbitrage-free formula for caplet or swaption prices. Because of their computational efficiency, one-factor MFMs are of particular interest. So far, the literature has focused on models driven by a Gaussian process. The aim of this paper is to move away from this Gaussian assumption and to provide new algorithms that can be used to implement an MFM driven by a more general class of one-dimensional diffusion processes. We provide additional insight into the role of the driving process by presenting a simple copula-based criterion that can be used to distinguish between models. Finally, we offer further insight into the dynamics of one-dimensional MFMs by relating them to separable local-volatility Libor market models and demonstrate this with a practical example.

中文翻译：

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由非高斯驱动器驱动的一维马尔可夫函数模型

马尔可夫函数模型 (MFM) 类提供了一个框架，可用于定义有限维度的利率模型，该模型校准到任何无套利的 caplet 或掉期价格公式。由于它们的计算效率，单因子 MFM 是特别令人感兴趣的。到目前为止，文献都集中在由高斯过程驱动的模型上。本文的目的是摆脱这种高斯假设，并提供可用于实现由更一般的一维扩散过程类驱动的 MFM 的新算法。我们通过提出一个简单的基于 copula 的标准来提供对驱动过程作用的额外洞察，该标准可用于区分模型。最后，