非仿射随机波动率跳扩散模型的利差期权定价

在两标的资产价格满足一类随机利率、随机波动率及跳跃均存在于资产价格和波动率的非仿射跳扩散模型下考察了利差期权的定价.首先,利用泰勒公式将非线性微分方程线性化,得到了两标的资产对数价格的近似联合密度特征函数;然后,使用Fourier逆变换等方法,获得了利差期权定价理论的半封闭公式,并将其推广到价差期权的定价.最后,通过数值实验,表明非仿射随机波动率跳扩散的利差期权定价模型比仿射随机波动率模型具有更高的精确性,并且扩散波动和跳跃波动对期权价格影响显著.     

随机波动率跳跃扩散模型下复合期权定价

复合期权是一类以期权作为标的物的奇异型合约,它已广泛应用于许多金融实践。本文在股价满足一类随机波动率及跳跃均存在于股价和波动率的仿射跳跃扩散模型下(也称随机波动率混合跳跃扩散模型)考察了复合期权的定价。应用二维特征函数和Fourier反变换方法获到了标的为欧式标准看涨期权的欧式复合看涨期权的定价半封闭公式,并将其应用于推导扩展期权的定价。最后,借助于离散快速Fourier变换法(FFT)数值计算定价公式,并用数值实例分析了期权价格对波动率的敏感性。数值结果表明扩散波动和跳跃波动对期权价格都有正的影响,而且跳跃波动的冲击非常显著。     

带跳随机利率与波动率模型的远期生效期权定价

本文研究了市场利率,基础资产价格及其波动率过程满足一类多元仿射跳扩散模型的远期生效期权定价问题,其中市场利率和波动率过程与基础资产相关且具有共同跳跃风险成分.利用Fourier反变换和远期测度技术,获得了欧式远期生效看涨期权价格的解析显示解.应用数值计算比较了利率,波动率过程对期权价格的不同表现,并分析了模型中主要参数对期权价格和对冲策略的影响.数值结果表明,利率和波动率因素,以及跳跃风险参数对期权价格有显著作用,这表明了多元仿射跳扩散模型具有较好拟合实际的能力.     

高维欧式期权定价模型的奇摄动解

讨论了一类欧式期权定价问题的随机波动率模型,其随机波动率采用快速均值回归的随机波动率模型.通过采用奇摄动方法,得到了多风险资产欧式期权价格的形式渐近展开式,得到该合成展开式的一致有效误差估计.     

基于随机波动率状态转移特征的上证50ETF期权定价

期权定价模型的构建过程中，单因子随机波动率模型生成的波动率曲线形状与波动率水平相关性微弱，且无法确切反映波动过程的状态转移特征。为此，本文使用连续马尔可夫链刻画波动状态，在Heston模型的基础上，针对其方差动态过程中所有参数均为波动状态任意函数的情景，得到了一类具有状态转移特征的随机波动率模型；进一步，根据条件仿射模型的特征函数，结合波动路径的蒙特卡罗模拟，实现了欧式期权半解析定价，其中，采用基于粒子滤波的极大似然估计方法估计模型参数；特别地，对上证50ETF期权进行了实证研究。结果表明：具有状态转移特征且方差的基准长期均值及波动率均依赖于波动状态的随机波动率模型，能够显著提升上证50ETF期权定价的准确性和稳健性。     

分数跳-扩散模型下的互换期权定价

用保险精算法,在标的资产价格服从分数跳-扩散过程,且风险利率、波动率和期望收益率为时间的非随机函数的情况下,给出了一类多资产期权——欧式交换期权的定价公式．该公式是标准跳扩散模型下的欧式期权及欧式交换期权定价公式的推广．     

服从分数跳-扩散过程的复合期权定价

用保险精算法,在标的资产价格服从分数跳-扩散过程,且风险利率、波动率和期望收益率为时间的非随机函数的情况下,给出了欧式复合期权的定价公式.结果推广了Gukhal以及Li等关于传统跳-扩散模型下的欧式复合期权的定价公式.     

一类非光滑条件下欧式期权定价模型

在本文中,我们考虑欧式期权定价问题的随机波动率模型.在非光滑收益函数的假设下,通过摄动分析和磨光逼近技巧,我们解带有小参数的倒向偏微分方程,并得到欧式期权价格的一致渐近展式及其一致有效的误差估计.     

模糊集理论在随机波动率期权定价中的应用

目的是对基于随机波动率模型的期权定价问题应用模糊集理论.主要思想是把波动率的概率表示转换为可能性表示,从而把关于股票价格的带随机波动率的随机过程简化为带模糊参数的随机过程.然后建立非线性偏微分方程对欧式期权进行定价.     

有限状态Q过程波动率与跳组合情形的期权定价

引入了有限状态Q过程随机波动率与复合Poisson过程组合的资产价格动态模型,得到了该组合模型下欧式看涨期权定价的一般公式,推广了Hull和White的结论.最后通过数值模拟,充分体现了期权价格对初始时刻波动率大小的依赖.     

快速均值回归随机波动率模型参数估计及应用

基于快速均值回归随机波动率模型, 研究双限期权的定价问题, 同时推导了考虑均值回归随机波动率的双限期权的定价公式。 根据金融市场中SPDR S&P 500 ETF期权的隐含波动率数据和标的资产的历史收益数据, 对快速均值回归随机波动率模型中的两个重要参数进行估计。 利用估计得到的参数以及定价公式, 对双限期权价格做了数值模拟。 数值模拟结果发现, 考虑了随机波动率之后双限期权的价格在标的资产价格偏高的时候会小于基于常数波动率模型的期权价格。     

Unifying pricing formula for several stochastic volatility models with jumps

In this paper, we introduce a unifying approach to option pricing under continuous‐time stochastic volatility models with jumps. For European style options, a new semi‐closed pricing formula is derived using the generalized complex Fourier transform of the corresponding partial integro‐differential equation. This approach is successfully applied to models with different volatility diffusion and jump processes. We also discuss how to price options with different payoff functions in a similar way. In particular, we focus on a log‐normal and a log‐uniform jump diffusion stochastic volatility model, originally introduced by Bates and Yan and Hanson, respectively. The comparison of existing and newly proposed option pricing formulas with respect to time efficiency and precision is discussed. We also derive a representation of an option price under a new approximative fractional jump diffusion model that differs from the aforementioned models, especially for the out‐of‐the money contracts. Copyright © 2017 John Wiley & Sons, Ltd.     

Market calibration under a long memory stochastic volatility model

In this article, we study a long memory stochastic volatility model (LSV), under which stock prices follow a jump-diffusion stochastic process and its stochastic volatility is driven by a continuous-time fractional process that attains a long memory. LSV model should take into account most of the observed market aspects and unlike many other approaches, the volatility clustering phenomenon is captured explicitly by the long memory parameter. Moreover, this property has been reported in realized volatility time-series across different asset classes and time periods. In the first part of the article, we derive an alternative formula for pricing European securities. The formula enables us to effectively price European options and to calibrate the model to a given option market. In the second part of the article, we provide an empirical review of the model calibration. For this purpose, a set of traded FTSE 100 index call options is used and the long memory volatility model is compared to a popular pricing approach – the Heston model. To test stability of calibrated parameters and to verify calibration results from previous data set, we utilize multiple data sets from NYSE option market on Apple Inc. stock.     

Testing robustness in calibration of stochastic volatility models

Many numerical aspects are involved in parameter estimation of stochastic volatility models. We investigate a model for stochastic volatility suggested by Hobson and Rogers [Complete models with stochastic volatility, Mathematical Finance 8 (1998) 27] and we focus on its calibration performance with respect to numerical methodology.In recent financial literature there are many papers dealing with stochastic volatility models and their capability in capturing European option prices; in Figà-Talamanca and Guerra [Towards a coherent volatility pricing model: An empirical comparison, Financial Modelling, Phisyca-Verlag, 2000] a comparison between some of the most significant models is done. The model proposed by Hobson and Rogers seems to describe quite well the dynamics of volatility.In Figà-Talamanca and Guerra [Fitting the smile by a complete model, submitted] a deep investigation of the Hobson and Rogers model was put forward, introducing different ways of parameters' estimation. In this paper we test the robustness of the numerical procedures involved in calibration: the quadrature formula to compute the integral in the definition of some state variables, called offsets, that represent the weight of the historical log-returns, the discretization schemes adopted to solve the stochastic differential equation for volatility and the number of simulations in the Monte Carlo procedure introduced to obtain the option price.The main results can be summarized as follows. The choice of a high order of convergence scheme is not fully justified because the option prices computed via calibration method are not sensitive to the use of a scheme with 2.0 order of convergence or greater. The refining of the approximation rule for the integral, on the contrary, allows to compute option prices that are often closer to market prices. In conclusion, a number of 10 000 simulations seems to be sufficient to compute the option price and a higher number can only slow down the numerical procedure.     

Option pricing with mean reversion and stochastic volatility

Many underlying assets of option contracts, such as currencies, commodities, energy, temperature and even some stocks, exhibit both mean reversion and stochastic volatility. This paper investigates the valuation of options when the underlying asset follows a mean-reverting lognormal process with stochastic volatility. A closed-form solution is derived for European options by means of Fourier transform. The proposed model allows the option pricing formula to capture both the term structure of futures prices and the market implied volatility smile within a unified framework. A bivariate trinomial lattice approach is introduced to value path-dependent options with the proposed model. Numerical examples using European options, American options and barrier options demonstrate the use of the model and the quality of the numerical scheme.     

Uniform Asymptotic Expansions for Pricing European Options

Starting with a stochastic volatility model, in which the volatility depends on a nonlinear function of a fast varying diffusion, and assuming the fast diffusion is mean reverting, the problem of pricing European options is considered in this paper. Uniform asymptotic expansions of the option price are obtained. The formal expansions are justified and the uniform error bounds are derived using outer and inner expansions of the option prices.     

Passport options with stochastic volatility

A passport option is a call option on the profits of a trading account. In this article, the robustness of passport option pricing is investigated by incorporating stochastic volatility. The key feature of a passport option is the holders' optimal strategy. It is known that in the case of exponential Brownian motion the strategy is to be long if the trading account is below zero and short if the account is above zero. Here this result is extended to models with stochastic volatility where the volatility is defined via an autonomous SDE. It is shown that if the Brownian motions driving the underlying asset and the volatility are independent then the form of the optimal strategy remains unchanged. This means that the strategy is robust to misspecification of the underlying model. A second aim of this article is to investigate some of the biases which become apparent in a stochastic volatility regime. Using an analytic approximation, comparisons are obtained for passport option prices using the exponential Brownian motion model and some well-known stochastic volatility models. This is illustrated with numerical examples. One conclusion is that if volatility and price are uncorrelated, then prices are sometimes lower in a model with stochastic volatility than in a model with constant volatility.     

A partial differential equation connected to option pricing with stochastic volatility: Regularity results and discretization

This paper completes a previous work on a Black and Scholes equation with stochastic volatility. This is a degenerate parabolic equation, which gives the price of a European option as a function of the time, of the price of the underlying asset, and of the volatility, when the volatility is a function of a mean reverting Orstein-Uhlenbeck process, possibly correlated with the underlying asset. The analysis involves weighted Sobolev spaces. We give a characterization of the domain of the operator, which permits us to use results from the theory of semigroups. We then study a related model elliptic problem and propose a finite element method with a regular mesh with respect to the intrinsic metric associated with the degenerate operator. For the error estimate, we need to prove an approximation result.

     

A delayed stochastic volatility correction to the constant elasticity of variance model

The Black-Scholes model does not account non-Markovian property and volatility smile or skew although asset price might depend on the past movement of the asset price and real market data can find a non-flat structure of the implied volatility surface. So, in this paper, we formulate an underlying asset model by adding a delayed structure to the constant elasticity of variance (CEV) model that is one of renowned alternative models resolving the geometric issue. However, it is still one factor volatility model which usually does not capture full dynamics of the volatility showing discrepancy between its predicted price and market price for certain range of options. Based on this observation we combine a stochastic volatility factor with the delayed CEV structure and develop a delayed hybrid model of stochastic and local volatilities. Using both a martingale approach and a singular perturbation method, we demonstrate the delayed CEV correction effects on the European vanilla option price under this hybrid volatility model as a direct extension of our previous work [12].