Analysis of numerical integration schemes for the Heston model: a case study based on the pricing of investment certificates

Michelangelo Fusaro, P. Giribone, Alessio Tissone
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Abstract

The Heston model is one of the most used techniques for estimating the fair value and the risk measures associated with investment certificates. Typically, the pricing engine implements a significant number of projections of the underlying until maturity, it calculates the pay-off for all the paths thus simulated considering the characteristics of the structured product and, in accordance with the Monte Carlo methodology, it determines its theoretical value by calculating its mean and discounting it at valuation time. In order to generate the future paths, the two stochastic differential equations governing the dynamics of the Heston model should be integrated simultaneously over time: both the one directly associated with the underlying and the one associated with variance. Consequently, it is essential to implement a numerical integration scheme that allows such prospective simulations to be implemented. The present study aims to consider alternatives to the traditional Euler method with the aim of reducing or in some cases eliminating the probability of incurring unfeasible simulated values for the variance. In fact, one of the main drawbacks of the Euler basic integration scheme applied to the Heston bivariate stochastic model is that of potentially generating negative variances in the simulation that should be programmatically corrected each time such undesired effect occurs. The methods which do not intrinsically admit the generation of negative values of the variance proved to be very interesting, in particular the Transformed Volatility scheme.
赫斯顿模型的数值积分方案分析:以投资凭证定价为例
赫斯顿模型是估计投资凭证公允价值和风险度量最常用的技术之一。通常情况下,定价引擎实现了大量的基础预测,直到到期,它计算所有路径的收益,从而考虑到结构化产品的特征,并根据蒙特卡罗方法,它通过计算其平均值并在估值时对其进行贴现来确定其理论价值。为了生成未来的路径,控制赫斯顿模型动力学的两个随机微分方程应该随着时间的推移同时集成:与底层直接相关的方程和与方差相关的方程。因此,有必要实施一种数值积分方案,使这种前瞻性的模拟得以实施。本研究旨在考虑传统欧拉方法的替代方案,目的是减少或在某些情况下消除产生不可行的方差模拟值的概率。事实上,将欧拉基本积分方案应用于赫斯顿二元随机模型的主要缺点之一是,在模拟中可能产生负方差,每次出现这种不希望的影响时,都应该通过编程进行纠正。不允许产生负方差的方法被证明是非常有趣的,特别是转换波动率方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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