On Extensions of the Barone-Adesi & Whaley Method to Price American-Type Options

IF 0.8 4区 经济学 Q4 BUSINESS, FINANCE Journal of Computational Finance Pub Date : 2019-01-13 DOI:10.2139/ssrn.3482064
Ludovic Mathys
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引用次数: 4

Abstract

The present article provides an efficient and accurate hybrid method to price American standard options in certain jump-diffusion models as well as American barrier-type options under the Black & Scholes framework. Our method generalizes the quadratic approximation scheme of Barone-Adesi & Whaley (1987) and several of its extensions. Using perturbative arguments, we decompose the early exercise pricing problem into sub-problems of different orders and solve these sub-problems successively. The obtained solutions are combined to recover approximations to the original pricing problem of multiple orders, with the 0-th order version matching the general Barone-Adesi & Whaley ansatz. We test the accuracy and efficiency of the approximations via numerical simulations. The results show a clear dominance of higher order approximations over their respective 0-th order version and reveal that significantly more pricing accuracy can be obtained by relying on approximations of the first few orders. Additionally, they suggest that increasing the order of any approximation by one generally refines the pricing precision, however that this happens at the expense of greater computational costs.
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Barone-Adesi和Whaley方法对美式期权定价的推广
本文提供了一种有效而准确的混合方法来定价某些跳跃扩散模型中的美国标准期权以及Black&Scholes框架下的美国障碍型期权。我们的方法推广了Barone-Adesi&Whaley(1987)的二次逼近格式及其几个推广。利用扰动自变量,我们将早期行权定价问题分解为不同阶次的子问题,并依次求解这些子问题。将获得的解决方案组合起来,以恢复多个订单的原始定价问题的近似值,第0个订单版本与一般的Barone Adesi和Whaley ansatz匹配。我们通过数值模拟测试了近似的准确性和效率。结果表明,高阶近似在其各自的0阶版本中明显占主导地位,并表明通过依赖前几个阶的近似可以获得显著更高的定价精度。此外,他们认为,将任何近似的阶数增加一通常会提高定价精度,但这是以更高的计算成本为代价的。
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
8
期刊介绍: The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focused on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments. The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions. Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation. Optimization techniques in hedging and risk management. Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis. Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.
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