基于偏微分方程方法的两随机因素电力市场波动期权定价

IF 0.8 4区 经济学 Q4 BUSINESS, FINANCE Journal of Computational Finance Pub Date : 2016-07-15 DOI:10.21314/JCF.2016.317
M. Calvo-Garrido, Matthias Ehrhardt, Carlos Vázquez Cendón
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引用次数: 7

摘要

本文基于双因素模型,研究电力市场波动期权的数值估值问题。这些类型的契约被建模为具有多个行使权的路径依赖选项。从数学的角度来看,这些产品的估值被视为一系列自由边界问题,其中两个行使权利被一段时间分开。为了解决定价问题,我们提出了基于Crank-Nicolson半拉格朗日方法结合双二次拉格朗日有限元对偏微分方程进行离散化的合适数值方法。此外,我们使用增广拉格朗日活动集方法来处理出现的早期运动特征。此外,我们还推导出适当的人工边界条件来数值处理无界区域。最后,我们给出了一些数值结果来说明数值格式的正确行为。
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Pricing Swing Options in Electricity Markets with Two Stochastic Factors Using a Partial Differential Equation Approach
In this paper, we consider the numerical valuation of swing options in electricity markets based on a two-factor model. These kinds of contracts are modeled as path dependent options with multiple exercise rights. From a mathematical point of view, the valuation of these products is posed as a sequence of free boundary problems, where two exercise rights are separated by a time period. In order to solve the pricing problem, we propose appropriate numerical methods based on a Crank-Nicolson semi-Lagrangian method combined with biquadratic Lagrange finite elements for the discretization of the partial differential equation. In addition, we use an augmented Lagrangian active set method to cope with the early exercise feature when it appears. Moreover, we derive appropriate artificial boundary conditions to treat the unbounded domain numerically. Finally, we present some numerical results to illustrate the proper behavior of the numerical schemes.
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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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