有红利美式看跌期权定价的Crank-Nicolson有限差分法

本文基于B-S微分方程,采用Crank-Nicolson差分格式(简称C-N差分格式)求解支付固定红利的美式看跌期权价值,给出实证分析,并对C-N差分格式和隐含的差分格式进行了比较.结果表明,用C-N差分格式可以得到更加精确、有效的数值解.     

规定水平下重置期权的有限差分解

利用Black—Scholes偏微分方程,结合重置期权与关卡期权的关系,建立了规定水平下的重置期权定价模型,最后运用C—N格式和θ法构造该模型的有限差分格式．     

欧氏看涨期权定价问题的一种有效七点差分GMRES方法

用有限差分方法研究欧氏看涨期权定价问题.首先,将Black-Scholes方程通过等价代换化成一个标准的抛物型偏微分方程.其次,在求解区域构造时间精度为O（△τ^3）、空间精度为O（h^6）的差分格式,并通过Fourier分析方法证明该差分格式是无条件稳定的;边界区域选用精度较高、稳定性好的Crank-Nicolson格式,建立迭代方程.然后,用GMRES（generalized minimal residual）方法求解该方法.最后,给出一个欧氏看涨期权的数值算例,并与解析解进行比较,验证差分格式的有效性.     

CEV过程下回望期权定价的高精度收敛差分算法

主要研究了CEV过程下一类回望期权的定价的数值解法问题.首先对期权价格所满足的微分方程中的空间变量进行半离散化处理,得到了具体的半离散化差分格式,然后证明了该差分格式具有稳定性和收敛性.数值试验表明本文算法是一个稳定收敛的算法.     

基于近似对冲跳跃风险的美式看跌期权定价及数值解法研究

考虑了基于近似对冲跳跃风险的美式看跌期权定价问题。首先,运用近似对冲跳跃风险、广义It 公式及无套利原理,得到了跳-扩散过程下的期权定价模型及期权价格所满足的偏微分方程。然后建立了美式看跌期权定价模型的隐式差分近似格式,并且证明了该差分格式具有的相容性、适定性、稳定性和收敛性。最后,数值实验表明,用本文方法为跳-扩散模型中的美式期权定价是可行的和有效的。     

永久美式期权定价的有限体积元方法

通常情况下,期权定价研究都假定股票价格的波动率和期望收益率为常数.基于此,假定波动率和期望收益率为股票价格的一般函数.利用体积有限元方法研究了上述假定模型下的Black-Scholes偏微分方程,获得了永久美式期权所满足的较高精度的隐式差分格式以及显示差分格式,最后,给出了该方法的误差估计.     

自适应隐式有限差分方法求解美式期权定价问题

本文针对美式期权的定价问题设计了基于有限差分方法的预估-校正数值算法.该算法采用显式离散格式先对自由边界条件进行预估,再对经过变量替换后的关于期权价格的偏微分方程采用隐式格式离散,并用Fourier方法分析了此离散格式的稳定性.接下来,引入基于Richardson外推法的后验误差指示子.这个后验误差指示子能够在给定的误差阈值范围内,针对期权价格和自由边界找到合适的网格划分.最后,通过设计多组数值实验并与Fazio^[1]采用显式离散格式算得的数值结果相比较,验证了所提算法的有效性,稳定性和收敛性.     

双币种期权定价模型的一个新ADI并行差分方法

双币种期权是一种重要的金融衍生产品,其定价模型是一个含有混合导数项的二维Black-Scholes方程,研究它的数值解法有着非常重要的理论意义和实际价值.本文给出求解双币种期权定价模型的基于Craig-Sneyd分裂法的一个新ADI差分方法(C-S ADI),该方法首先将二维B1ack-Scholes方程分裂为两个一维方程和一个含有混合导数的二维方程,然后分别对一维方程构造半隐式格式,对含混合导数的二维方程构造显式格式进行计算.C-S ADI差分方法具有以下优点:并行性,无条件稳定性,收敛性及空间二阶、时间一阶的计算精度.理论分析与数值试验表明,相比于经典的Crank-Nicolson差分格式和已有的基于Douglas Rachford分裂法的ADI差分格式(D-R ADI),本文格式计算精度更高,并且由于其具有天然的并行特性,本文格式比串行的Crank-Nicolson格式节省了近1/5的计算时间,证实了该方法对求解双币种期权定价模型是有效的.     

美式期权定价的有限体积元方法

通常情况下,期权定价研究都假定股票价格的波动率和期望收益率为常数.假定波动率和期望收益率为股票价格的一般函数.利用体积有限元方法研究了美式期权定价模型下的Black-Scholes偏微分方程,获得了美式期权所满足的较高精度的隐式差分格式,最后,给出了该方法的误差估计.     

CEV跳-扩散模型中期权定价研究

考虑了CEV与Kou双指数跳-扩散组合模型中的期权定价问题.首先,运用Ito公式和期权定价的无套利原理,得到了模型下期权价格所满足的偏积-微分方程.然后,运用中心差分和Lagrange线性插值,分别对偏积-微分方程中的微分项和积分项进行离散化处理,再由Euler法,最终得了偏积-微分方程的有限差分格式,并且对差分方法的误差和收敛性进行了分析.最后数值实验验证了该算法是一个稳定且收敛的算法.     

A robust finite difference scheme for pricing American put options with Singularity-Separating method

In this paper we present a stable numerical method for the linear complementary problem arising from American put option pricing. The numerical method is based on a hybrid finite difference spatial discretization on a piecewise uniform mesh and an implicit time stepping technique. The scheme is stable for arbitrary volatility and arbitrary interest rate. We apply some tricks to derive the error estimates for the direct application of finite difference method to the linear complementary problem. We use the Singularity-Separating method to remove the singularity of the non-smooth payoff function. It is proved that the scheme is second-order convergent with respect to the spatial variable. Numerical results support the theoretical results.     

A robust and accurate finite difference method for a generalized Black-Scholes equation

In this paper we present a numerical method for a generalized Black-Scholes equation, which is used for option pricing. The method is based on a central difference spatial discretization on a piecewise uniform mesh and an implicit time stepping technique. Our scheme is stable for arbitrary volatility and arbitrary interest rate, and is second-order convergent with respect to the spatial variable. Furthermore, the present paper efficiently treats the singularities of the non-smooth payoff function. Numerical results support the theoretical results.     

A new predictor-corrector scheme for valuing American puts

In this paper, we present a new numerical scheme, based on the finite difference method, to solve American put option pricing problems. Upon applying a Landau transform or the so-called front-fixing technique [19] to the Black-Scholes partial differential equation, a predictor-corrector finite difference scheme is proposed to numerically solve the nonlinear differential system. Through the comparison with Zhu’s analytical solution [35], we shall demonstrate that the numerical results obtained from the new scheme converge well to the exact optimal exercise boundary and option values. The results of our numerical examples suggest that this approach can be used as an accurate and efficient method even for pricing other types of financial derivative with American-style exercise.     

The Minimal Entropy Martingale Measure and Numerical Option Pricing for the Barndorff–Nielsen–Shephard Stochastic Volatility Model

Abstract

We develop and apply a numerical scheme for pricing options in the stochastic volatility model proposed by Barndorff–Nielsen and Shephard. This non-Gaussian Ornstein–Uhlenbeck type of volatility model gives rise to an incomplete market, and we consider the option prices under the minimal entropy martingale measure. To numerically price options with respect to this risk neutral measure, one needs to consider a Black and Scholes type of partial differential equation, with an integro-term arising from the volatility process. We suggest finite difference schemes to solve this parabolic integro-partial differential equation, and derive appropriate boundary conditions for the finite difference method. As an application of our algorithm, we consider price deviations from the Black and Scholes formula for call options, and the implications of the stochastic volatility on the shape of the volatility smile.     

Numerical Solutions for Option Pricing Models Including Transaction Costs and Stochastic Volatility

The option pricing problem when the asset is driven by a stochastic volatility process and in the presence of transaction costs leads to solving a nonlinear partial differential equation. The nonlinear term in the PDE reflects the presence of transaction costs. Under a particular market completion assumption we derive the nonlinear PDE whose solution may be used to find the price of options. In this paper under suitable conditions, we give an algorithmic scheme to obtain the solution of the problem by an iterative method and provide numerical solutions using the finite difference method.     

Rational Krylov methods in exponential integrators for European option pricing

The aim of this paper is to analyze efficient numerical methods for time integration of European option pricing models. When spatial discretization is adopted, the resulting problem consists of an ordinary differential equation that can be approximated by means of exponential Runge–Kutta integrators, where the matrix‐valued functions are computed by the so‐called shift‐and‐invert Krylov method. To our knowledge, the use of this numerical approach is innovative in the framework of option pricing, and it reveals to be very attractive and efficient to solve the problem at hand. In this respect, we propose some a posteriori estimates for the error in the shift‐and‐invert approximation of the core‐functions arising in exponential integrators. The effectiveness of these error bounds is tested on several examples of interest. They can be adopted as a convenient stopping criterion for implementing the exponential Runge–Kutta algorithm in order to perform time integration. Copyright © 2013 John Wiley & Sons, Ltd.     

High-order compact finite difference scheme for option pricing in stochastic volatility models

We derive a new high-order compact finite difference scheme for option pricing in stochastic volatility models. The scheme is fourth order accurate in space and second order accurate in time. Under some restrictions, theoretical results like unconditional stability in the sense of von Neumann are presented. Where the analysis becomes too involved we validate our findings by a numerical study. Numerical experiments for the European option pricing problem are presented. We observe fourth order convergence for non-smooth payoff.     

Asset pricing for an affine jump‐diffusion model using an FD method of lines on nonuniform meshes

We present a novel numerical scheme for the valuation of options under a well‐known jump‐diffusion model. European option pricing for such a case satisfies a 1 + 2 partial integro‐differential equation (PIDE) including a double integral term, which is nonlocal. The proposed approach relies on nonuniform meshes with a focus on the discontinuous and degenerate areas of the model and applying quadratically convergent finite difference (FD) discretizations via the method of lines (MOL). A condition for observing the time stability of the fully discretized problem is given. Also, we report results of numerical experiments.