英文标题：
《Interacting Default Intensity with Hidden Markov Process》
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作者：
Feng-Hui Yu, Wai-Ki Ching, Jia-Wen Gu and Tak-Kuen Siu
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最新提交年份：
2016
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英文摘要：
  In this paper we consider a reduced-form intensity-based credit risk model with a hidden Markov state process. A filtering method is proposed for extracting the underlying state given the observation processes. The method may be applied to a wide range of problems. Based on this model, we derive the joint distribution of multiple default times without imposing stringent assumptions on the form of default intensities. Closed-form formulas for the distribution of default times are obtained which are then applied to solve a number of practical problems such as hedging and pricing credit derivatives. The method and numerical algorithms presented may be applicable to various forms of default intensities.
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中文摘要：
在本文中，我们考虑了一个具有隐马尔可夫状态过程的简化形式的基于强度的信用风险模型。在给定观测过程的情况下，提出了一种滤波方法来提取潜在状态。该方法可应用于广泛的问题。基于该模型，我们推导了多个违约时间的联合分布，而无需对违约强度的形式进行严格假设。得到了违约时间分布的封闭式公式，并将其应用于解决一些实际问题，如套期保值和信用衍生品定价。所提出的方法和数值算法可能适用于各种形式的违约强度。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Computational Finance        计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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