论文标题
在快速均值随机波动率模型下模拟条件期望
Simulation of conditional expectations under fast mean-reverting stochastic volatility models
论文作者
论文摘要
在这篇简短的论文中，我们研究了经过常见的驱动噪声和快速均值回复随机波动性的大型随机过程系统的模拟。该模型可用于描述大量金融实体的公司价值。然后，我们寻求一个有效的估计器，以违约的概率，以低于一定阈值（以共同因素为条件）的企业值表示。我们考虑将包含快速波动率的系数取代的近似值（大量的一种定律），并研究校正项（中心极限定理型）。这些近似值的准确性是通过对路径损失的数值模拟以及在篮子信用导数中出现的回报函数的估计来评估的。
In this short paper, we study the simulation of a large system of stochastic processes subject to a common driving noise and fast mean-reverting stochastic volatilities. This model may be used to describe the firm values of a large pool of financial entities. We then seek an efficient estimator for the probability of a default, indicated by a firm value below a certain threshold, conditional on common factors. We consider approximations where coefficients containing the fast volatility are replaced by certain ergodic averages (a type of law of large numbers), and study a correction term (of central limit theorem-type). The accuracy of these approximations is assessed by numerical simulation of pathwise losses and the estimation of payoff functions as they appear in basket credit derivatives.
