非仿射随机波动率的欧式障碍期权定价

研究非仿射随机波动率模型的欧式障碍期权定价问题时,首先介绍了非仿射随机波动率模型,其次利用投资组合和It^o引理,得到了该模型下扩展的Black-Schole偏微分方程.由于这个方程没有显示解,因此采用对偶蒙特卡罗模拟法计算欧式障碍期权的价格.最后,通过数值实例验证了算法的可行性和准确性.     

随机波动率下股价服从O-U过程的期权定价

假设股票价格遵循指数O-U过程,利用随机分析中的鞅方法,得到了具有随机波动率的欧式期权的定价公式,推广了B-S模型.     

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.     

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.     

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.     

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。     

多尺度亚式期权定价模型的奇摄动解

讨论了一类多尺度亚式期权定价随机波动率模型问题,其中随机波动率采用了具有快慢变换的随机波动率模型.通过Feynman-Kac公式,得到了风险资产期权价格所满足的相应的Black-Scholes方程,运用奇摄动渐近展开方法,得到了期权定价方程的渐近解,并得到其一致有效估计.     

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。     

均值回复跳扩散随机波动率模型下的欧式期权定价研究

考虑到金融市场数据波动的不确定性,本文提出了一个新的对数均值回复跳扩散4/2随机波动率(LMRJ-4/2-SV)模型.首先,构建了LMRJ-4/2-SV模型,并利用FFT等方法获得了基于LMRJ-4/2-SV模型的欧式期权定价公式.其次,对实际市场数据进行描述性统计分析,探讨标的资产价格变化特征及LMRJ-4/2-SV模型的适用性,并通过粒子群优化算法估计模型参数.最后,基于LMRJ-4/2-SV模型下的期权定价公式及模型参数估计值对欧式期权进行定价,并将其定价结果与4/2、3/2、Heston模型估计值及市场价格进行对比.结果表明:基于LMRJ-4/2-SV模型的欧式期权定价误差最小,定价结果较其它随机波动率模型而言具有明显优势.     

随机波动率与跳扩散组合模型的双币种期权定价

在股价和汇率满足随机波动率与跳扩散组合模型下应用半鞅Ito公式、多维随机变量的联合特征函数、Girsanov测度变换以及Fourier反变换等随机分析技巧给出了双币种欧式期权价格的封闭式解,并利用数值实例分析了波动参数对期权价格的影响,结果表明:波动率参数对期权价格有显著的影响作用.     

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。     

Investment timing under hybrid stochastic and local volatility

We consider an investment timing problem under a real option model where the instantaneous volatility of the project value is given by a combination of a hidden stochastic process and the project value itself. The stochastic volatility part is given by a function of a fast mean-reverting process as well as a slowly varying process and the local volatility part is a power (the elasticity parameter) of the project value itself. The elasticity parameter controls directly the correlation between the project value and the volatility. Knowing that the project value represents the market price of a real asset in many applications and the value of the elasticity parameter depends on the asset, the elasticity parameter should be treated with caution for investment decision problems. Based on the hybrid structure of volatility, we investigate the simultaneous impact of the elasticity and the stochastic volatility on the real option value as well as the investment threshold.     

动态随机弹性在期权定价中的应用

给出动态随机弹性的概念及运算性质,讨论了动态随机弹性在期权定价模型中的应用.主要结果有:(1)在波动率为常数时,期权价格对的弹性,得到了动态随机弹性服从运动,并给出了相应的经济解释;(2)由于波动率一般不是常数,也是随机过程,因此本文进一步研究了期权价格对波动率的弹性,就股票价格的波动情况给出了数学描述和金融意义上的解释.     

American Options Exercise Boundary When the Volatility Changes Randomly

The American put option exercise boundary has been studied extensively as a function of time and the underlying asset price. In this paper we analyze its dependence on the volatility, since the Black and Scholes model is used in practice via the (varying) implied volatility parameter. We consider a stochastic volatility model for the underlying asset price. We provide an extension of the regularity results of the American put option price function and we prove that the optimal exercise boundary is a decreasing function of the current volatility process realization. Accepted 13 January 1998     

Rare Shock,Two-Factor Stochastic Volatility and Currency Option Pricing

Abstract

In this paper, we develop an option valuation model where the dynamics of the spot foreign exchange rate is governed by a two-factor Markov-modulated jump-diffusion process. The short-term fluctuation of stochastic volatility is driven by a Cox–Ingersoll–Ross (CIR) process and the long-term variation of stochastic volatility is driven by a continuous-time Markov chain which can be interpreted as economy states. Rare events are governed by a compound Poisson process with log-normal jump amplitude and stochastic jump intensity is modulated by a common continuous-time Markov chain. Since the market is incomplete under regime-switching assumptions, we determine a risk-neutral martingale measure via the Esscher transform and then give a pricing formula of currency options. Numerical results are presented for investigating the impact of the long-term volatility and the annual jump intensity on option prices.     

A GARCH option pricing model with α-stable innovations

We develop an option pricing model which is based on a GARCH asset return process with α-stable innovations with truncated tails. The approach utilizes a canonic martingale measure as pricing measure which provides the possibility of a model calibration to market prices. The GARCH-stable option pricing model allows the explanation of some well-known anomalies in empirical data as volatility clustering and heavy tailedness of the return distribution. Finally, the results of Monte Carlo simulations concerning the option price and the implied volatility with respect to different strike and maturity levels are presented.     

广义Black-Scholes模型期权定价新方法--保险精算方法

利用公平保费原则和价格过程的实际概率测度推广了Mogens Bladt和Tina Hviid Rydberg的结果．在无中间红利和有中间红利两种情况下，把Black-Scholes模型推广到无风险资产(债券或银行存款)具有时间相依的利率和风险资产(股票)也具有时间相依的连续复利预期收益率和波动率的情况，在此情况下获得了欧式期权的精确定价公式以及买权与卖权之间的平价关系．给出了风险资产(股票)具有随机连续复利预期收益率和随机波动率的广义Black-Scholes模型的期权定价的一般方法．利用保险精算方法给出了股票价格遵循广义Ornstein-Uhlenback过程模型的欧式期权的精确定价公式和买权和卖权之间的平价关系．     

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.     

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.