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An Integrated Quasi-Monte Carlo Method for Handling High Dimensional Problems with Discontinuities in Financial Engineering

机译:一种集成的准蒙特卡罗方法,用于处理金融工程中不连续性的高维问题

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摘要

Quasi-Monte Carlo (QMC) method is a useful numerical tool for pricing and hedging of complex financial derivatives. These problems are usually of high dimensionality and discontinuities. The two factors may significantly deteriorate the performance of the QMC method. This paper develops an integrated method that overcomes the challenges of the high dimensionality and discontinuities concurrently. For this purpose, a smoothing method is proposed to remove the discontinuities for some typical functions arising from financial engineering. To make the smoothing method applicable for more general functions, a new path generation method is designed for simulating the paths of the underlying assets such that the resulting function has the required form. The new path generation method has an additional power to reduce the effective dimension of the target function. Our proposed method caters for a large variety of model specifications, including the Black-Scholes, exponential normal inverse Gaussian Levy, and Heston models. Numerical experiments dealing with these models show that in the QMC setting the proposed smoothing method in combination with the new path generation method can lead to a dramatic variance reduction for pricing exotic options with discontinuous payoffs and for calculating options' Greeks. The investigation on the effective dimension and the related characteristics explains the significant enhancement of the combined procedure.
机译:Quasi-Monte Carlo(QMC)方法是复杂金融衍生物的定价和对冲的有用数值工具。这些问题通常是高度和不连续性的。这两个因素可能会显着恶化QMC方法的性能。本文开发了一种综合的方法,克服了高度和不连续性的挑战。为此目的,提出了一种平滑方法,以消除金融工程所产生的一些典型功能的不连续性。为了使平滑方法适用于更通用的功能,设计了一种新的路径生成方法,用于模拟底层资产的路径,使得所得到的函数具有所需的形式。新的路径生成方法具有额外的功率来减少目标功能的有效维度。我们提出的方法适用于各种模型规格,包括Black-Scholes,指数正常逆高斯征收和Heston模型。处理这些模型的数值实验表明,在QMC设置中,所提出的平滑方法与新的路径生成方法相结合,可以导致具有不连续收益的异国情调选项和计算选项'希腊语的戏剧性方差。对有效维度的调查和相关特征解释了组合程序的显着提高。

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