随机波动率和随机利率下的美式复合期权价格评价

IF 0.8 4区 经济学 Q4 BUSINESS, FINANCE Journal of Computational Finance Pub Date : 2013-09-01 DOI:10.21314/JCF.2013.264
C. Chiarella, Boda Kang
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引用次数: 25

摘要

复合期权(母期权)赋予持有者购买(做多)或卖出(做空)标的期权(子期权)的权利,而不是义务。本文研究了在Cox-Ingersoll-Ross过程驱动下,基础动力服从Heston随机波动率和随机利率的美式复合期权定价问题。我们使用偏微分方程(PDE)方法来获得数值解。通过稀疏网格法求解两道自由边界PDE问题,与基于最小二乘蒙特卡罗模拟结合投影逐次过松弛法的基准解的结果相比,发现该问题的求解是准确和高效的。
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The evaluation of American compound option prices under stochastic volatility and stochastic interest rates
A compound option (the mother option) gives the holder the right, but not the obligation, to buy (long) or sell (short) the underlying option (the daughter option). In this paper, we consider the problem of pricing American-type compound options when the underlying dynamics follow Heston’s stochastic volatility and with stochastic interest rate driven by Cox–Ingersoll–Ross processes. We use a partial differential equation (PDE) approach to obtain a numerical solution. The problem is formulated as the solution to a two-pass free-boundary PDE problem, which is solved via a sparse grid approach and is found to be accurate and efficient compared with the results from a benchmark solution based on a least-squares Monte Carlo simulation combined with the projected successive over-relaxation method.
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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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