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Numerical methods for nonlinear equations in option pricing.

机译:期权定价中非线性方程的数值方法。

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摘要

This thesis explores numerical methods for solving nonlinear partial differential equations (PDEs) that arise in option pricing problems. The goal is to develop or identify robust and efficient techniques that converge to the financially relevant solution for both one and two factor problems. To illustrate the underlying concepts, two nonlinear models are examined in detail: uncertain volatility and passport options.; For any nonlinear model, implicit timestepping techniques lead to a set of discrete nonlinear equations which must be solved at each timestep. Several iterative methods for solving these equations are tested. In the cases of uncertain volatility and passport options, it is shown that the frozen coefficient method outperforms two different Newton-type methods. Further, it is proven that the frozen coefficient method is guaranteed to converge for a wide class of one factor problems.; A major issue when solving nonlinear PDEs is the possibility of multiple solutions. In a financial context, convergence to the viscosity solution is desired. Conditions under which the one factor uncertain volatility equations are guaranteed to converge to the viscosity solution are derived. Unfortunately, the techniques used do not apply to passport options, primarily because a positive coefficient discretization is shown to not always be achievable.; For both uncertain volatility and passport options, much work has already been done for one factor problems. In this thesis, extensions are made for two factor problems. The importance of treating derivative estimates consistently between the discretization and an optimization procedure is discussed.; For option pricing problems in general, non-smooth data can cause convergence difficulties for classical timestepping techniques. In particular, quadratic convergence may not be achieved. Techniques for restoring quadratic convergence for linear problems are examined. Via numerical examples, these techniques are also shown to improve the stability of the nonlinear uncertain volatility and passport option problems.; Finally, two applications are briefly explored. The first application involves static hedging to reduce the bid-ask spread implied by uncertain volatility pricing. While static hedging has been carried out previously for one factor models, examples for two factor models are provided. The second application uses passport option theory to examine trader compensation strategies. By changing the payoff, it is shown how the expected distribution of trading account balances can be modified to reflect trader or bank preferences.
机译:本文探讨了求解期权定价问题中出现的非线性偏微分方程(PDE)的数值方法。目标是开发或确定强大而有效的技术,以融合到针对一因素和两因素问题的财务相关解决方案。为了说明基本概念,我们详细研究了两个非线性模型:不确定性波动率和护照选择权。对于任何非线性模型,隐式时间步技术会导致一组离散的非线性方程,这些方程必须在每个时间步求解。测试了几种求解这些方程的迭代方法。在不确定的波动性和护照选择权的情况下,表明冻结系数法的性能优于两种不同的牛顿型方法。进一步证明,冻结系数法可以保证针对一类广泛的单因素问题收敛。解决非线性PDE时的主要问题是可能存在多种解决方案。在财务上,希望收敛到粘度溶液。推导出保证一因素不确定性波动方程收敛到粘度解的条件。不幸的是,所使用的技术不适用于护照选择,主要是因为显示出并非总是可以实现正系数离散化。对于不确定的波动性和护照选择权,针对一个因素的问题已经做了很多工作。本文对两个因素问题进行了扩展。讨论了在离散化和优化程序之间一致地对待导数估计的重要性。对于一般的期权定价问题,不平滑的数据可能会导致经典时步技术的收敛困难。特别是,可能无法实现二次收敛。研究了针对线性问题恢复二次收敛的技术。通过数值示例,这些技术还可以提高非线性不确定性波动率和护照选择权问题的稳定性。最后,简要探讨了两个应用程序。第一个应用程序涉及静态对冲,以减少不确定性波动定价所隐含的买卖差价。虽然先前已经对一个因子模型进行了静态套期,但提供了两个因子模型的示例。第二个应用程序使用护照选项理论来检查交易者的补偿策略。通过更改收益,显示了如何修改交易帐户余额的预期分布以反映交易者或银行的偏好。

著录项

  • 作者

    Pooley, David.;

  • 作者单位

    University of Waterloo (Canada).;

  • 授予单位 University of Waterloo (Canada).;
  • 学科 Mathematics.; Computer Science.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 155 p.
  • 总页数 155
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 数学;自动化技术、计算机技术;
  • 关键词

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