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.     

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.     

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.     

Robust Approximations for Pricing Asian Options and Volatility Swaps Under Stochastic Volatility

Abstract

We show that if the discounted Stock price process is a continuous martingale, then there is a simple relationship linking the variance of the terminal Stock price and the variance of its arithmetic average. We use this to establish a model-independent upper bound for the price of a continuously sampled fixed-strike arithmetic Asian call option, in the presence of non-zero time-dependent interest rates (Theorem 1.2). We also propose a model-independent lognormal moment-matching procedure for approximating the price of an Asian call, and we show how to apply these approximations under the Black–Scholes and Heston models (subsection 1.3). We then apply a similar analysis to a time-dependent Heston stochastic volatility model, and we show how to construct a time-dependent mean reversion and volatility-of-variance function, so as to be consistent with the observed variance swap curve and a pre-specified term structure for the variance of the integrated variance (Theorem 2.1). We characterize the small-time asymptotics of the first and second moments of the integrated variance (Proposition 2.2) and derive an approximation for the price of a volatility swap under the time-dependent Heston model ( Equation (52)), using the Brockhaus–Long approximation (Brockhaus, and Long, 2000 Brockhaus, O. and Long, D. 2000. Volatility Swaps made simple. Risk, 13(1) January: 92–96.  [Google Scholar]). We also outline a bootstrapping procedure for calibrating a piecewise-linear mean reversion level and volatility-of-volatility function (Subsection 2.3.2).     

MC方差减小技术在算术平均亚式外汇期权定价中的应用

建立了利率和汇率波动率均为随机情形下算术平均亚式外汇期权的定价模型.由于其定价问题求解十分困难,运用蒙特卡罗(Monte Carlo)方法并结合控制变量方差减小技术进行模拟,有效地减小了模拟方差,得到了期权定价问题的数值结果.     

基于GARCH-GH模型的上证50ETF期权定价研究

上证50ETF期权是中国推出的首支股票期权.为描述上证50ETF收益率偏态、尖峰、时变波动率等特征,结合GARCH模型和广义双曲(Generalized Hyperbolic,GH)分布两方面的优势,建立GARCH-GH模型为上证50ETF期权定价.在等价鞅测度下,利用蒙特卡罗方法估计上证50ETF欧式认购期权价格.实证表明,相比较Black-Scholes模型和GARCH-Gaussian模型,GARCH-GH模型得到的结果更接近于上证50ETF期权的实际价格,其定价误差最小.     

基于混合规避策略的期权定价及其数值分析

考虑现实市场中红利的存在、波动率等参数随时间变化以及交易时间不连续产生的对冲风险不可忽略,研究离散时间、支付红利条件下基于混合规避策略的期权定价模型.由平均自融资-极小方差规避策略得到相应欧式看涨期权定价方程,并且分别使用偏微分方法和概率论方法得到统一的闭形解.数值分析表明,与经典的期权定价模型相比,新模型中的期权价格更接近对冲成本.     

随机利率下期权定价的探讨

利用Ho-Lee和Vasicek模型的简化形式推导出了Black-Scholes假设下的随机利率欧式期权定价公式,对无风险利率是常数的期权定价模型进行扩展,并与一般情况进行了分析与比较。     

Asset Pricing with Stochastic Volatility

In this paper we study the asset pricing problem when the volatility is random. First, we derive a PDE for the risk-minimizing price of any contingent claim. Secondly, we assume that the volatility process \si _t is observed through an observation process Y _t subject to random error. A price formula and a PDE are then derived regarding the stock price S _t and the observation process Y _t as parameters. Finally, we assume that S _t is observed. In this case we have a complete market and any contingent claim is then priced by an arbitrage argument instead of by risk-minimizing. Accepted 15 August 2000. Online publication 8 December 2000.     

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.     

光滑树图期权定价模型的叉熵分析法

为了克服CRR模型收敛的波动性,以及强调历史信息的预测作用的情况,提出了一个新奇的光滑收敛的树图模型.新模型基于历史信息,运用最小叉熵原理
来推导树图的关键参数p,u,d, 然后使用倒推法推断期权的价格.显然,新模型所得的期权的价格隐含着历史信息.由于最小叉熵原理是一个凸规划问题,能求得唯一的最优解,所以,新模型也适用于不完全金融市场期权定价.最后,数值算例表明,相比于CRR模型,新模型收敛光滑平稳且有更高的计算精度;对上涨(下跌)的二元期权、欧式期权,新模型都能光滑收敛于B-S公式.     

部分信息下股票付息的Black-Scholes期权定价公式和一类最优投资问题

假定金融市场中的投资者仅掌握部分信息,即投资者仅能观测到股票和债券价格,而股票的瞬时回报率和市场的噪声源不能观测.对存款利率和贷款利率不相等的情形,运用凸分析和滤波技术得到了部分信息下股票付红利的Black-Scholes期权定价公式.对部分信息下最大化终端财富的问题,获得了最优投资策略.     

期权定价新型二叉树参数模型的构造

对目前普遍使用的期权定价二叉树模型的缺陷进行了分析,利用矩法构造出新型的二叉树参数模型.新的模型避免了负的概率并且具有很高的计算精度,因而可应用于计算各种期权的价格.     

同质信念与Black-Scholes公式定价偏差——基于期权定价的保险精算方法

本文分析了包括BS的鞅方法在内的四种期权定价方法.Mogens Bldt和郑红给出的保险精算定价方法是非套利定价,缺少足够的理论基础.另外,存在同质信念的市场上BS定价并非完全无套利,如果对不同股票进行分散化投资,只要基础资产种类足够多,也可套取利益.不同投资者的漂移率取同一常数μ体现了他们的同质信念,与弱有效的现实市场情况相符.进一步分析得出结论,即使存在同质信念,如果μt是一个可料过程而非常数,会使得精算定价难以计算确定期望,从而无效.根据SAS软件的模拟结果,在同质信念下,精算套利定价显著高于BS鞅方法定价.通过恒生股指期权的实证检验,说明同质信念下的漂移率更适合取同一常数而不是可料过程,实证检验发现精算套利理论价格与实际价格差距很小,说明此方法比较有效.     

Pricing VIX options in a stochastic vol‐of‐vol model

This paper proposes and makes a study of a new model for volatility index option pricing. Factors such as mean‐reversion, jumps, and stochastic volatility are taken into consideration. In particular, the positive volatility skew is addressed by the jump and the stochastic volatility of volatility. Daily calibration is used to check whether the model fits market prices and generates positive volatility skews. Overall, the results show that the mean‐reverting logarithmic jump and stochastic volatility model (called MRLRJSV in the paper) serves as the best model in all the required aspects. Copyright © 2015 John Wiley & Sons, Ltd.     

“降价补差”承诺期权定价分析

综合应用Δ对冲技巧以及It引理,在风险中性意义的前提下建立了房产开发商"降价补差"承诺期权的偏微分方程定价模型.根据"降价补差"承诺能否在到期前任何一天履约,分别建立了欧式承诺期权定价模型和美式承诺期权定价模型.对于欧式承诺期权,得到了期权价格的解析公式;对于美式承诺期权,采用基于自适应的有限差分法对上述定价模型进行数值计算,得到了相应的期权价格.并以欧式承诺期权为例,分析了期权价格对参数的依赖关系.最后对两个具体的"降价补差"承诺期权案例进行了期权价格计算.     

Numerical Methods for the Pricing of Swing Options: A Stochastic Control Approach

In the natural gas market, many derivative contracts have a large degree of flexibility. These are known as Swing or Take-Or-Pay options. They allow their owner to purchase gas daily, at a fixed price and according to a volume of their choice. Daily, monthly and/or annual constraints on the purchased volume are usually incorporated. Thus, the valuation of such contracts is related to a stochastic control problem, which we solve in this paper using new numerical methods. Firstly, we extend the Longstaff–Schwarz methodology (originally used for Bermuda options) to our case. Secondly, we propose two efficient parameterizations of the gas consumption, one is based on neural networks and the other on finite elements. It allows us to derive a local optimal consumption law using a stochastic gradient ascent. Numerical experiments illustrate the efficiency of these approaches. Furthermore, we show that the optimal purchase is of bang-bang type.      

Sequential Bayesian learning for stochastic volatility with variance‐gamma jumps in returns

In this work, we investigate sequential Bayesian estimation for inference of stochastic volatility with variance‐gamma (SVVG) jumps in returns. We develop an estimation algorithm that combines the sequential learning auxiliary particle filter with the particle learning filter. Simulation evidence and empirical estimation results indicate that this approach is able to filter latent variances, identify latent jumps in returns, and provide sequential learning about the static parameters of SVVG. We demonstrate comparative performance of the sequential algorithm and off‐line Markov Chain Monte Carlo in synthetic and real data applications.     

Weak Approximation of Stochastic Differential Equations and Application to Derivative Pricing

A new, simple algorithm of order 2 is presented to approximate weakly stochastic differential equations. It is then applied to the problem of pricing Asian options under the Heston stochastic volatility model.

2000 Mathematics Subject Classification, 65C30, 65C05.