随机波动率与双指数跳扩散组合模型的美式期权定价

在股价满足Cox-Ingersoll-Ross(CIR)随机波动率与Kou的双指数跳扩散组合模型下,利用随机分析方法讨论了美式看跌期权函数及最佳实施边界的性质.应用一阶线性近似实施边界获得了期权价格的拟解析式和实施边界满足的非线性方程.进一步,应用梯形法离散处理方程式内积分表达式,建立了期权最佳实施边界和价格的数值算法.最后分别给出了常数波动率或CIR随机波动率的数值实例.     

基于随机波动率模型的上证50ETF期权定价研究

传统上,期权定价主要基于Black-Scholes (B-S)模型。但B-S模型不能描述时变波动率以及解释"波动率微笑"现象,导致期权定价存在较大的误差。随机波动率模型克服了B-S模型的这些缺陷,能够合理地刻画波动率动态性和波动率微笑。基于此,本文考虑随机波动率模型下的期权定价问题,并针对我国上证50ETF期权进行实证分析。为了解决定价模型的参数估计问题,采用上证50ETF及其期权价格数据,建立两步法对定价模型的参数进行估计。该估计方法保证了定价模型在客观与风险中性测度下的一致性。采用2016年1月到2017年10月的上证50ETF期权价格数据为研究样本,对随机波动率模型进行了实证检验。结果表明,无论是在样本内还是样本外,随机波动率模型相比传统的常数波动率B-S模型都能够获得明显更为精确和稳定的定价结果,B-S模型的定价误差总体偏大且呈现较高波动,凸显了随机波动率对于期权定价的重要性。另外,随机波动率模型对于短期实值期权的定价相比对于其它期权的定价要更精确。     

不确定环境下的欧式期权定价

正1引言Black-Scholes~([1])(B-S)期权定价模型是金融市场上为人所熟知的研究期权价格的经典模型.然而,实证研究表明B-S模型暴露出一些与市场实际信息相违背的现象,其中有两点引起市场的广泛关注.第一点是基础资产,如股票的价格与B-S假设的正态分布相比表现的是偏峰厚尾的特性;其次是波动率曲线是敲定价格的凸曲线,即波动率微笑.为了在B-S模型中引入偏峰厚尾特性,一些模型和理论,如分数布朗运动及一些广义双曲模型~([2,3])描述基础资产的价格.另一方面,为了解释波动率微笑,一些自回归异方差(ARCH)~([4])、常弹性模型(CEV)~([5])等期权定价理论被相继提出.Merton~([6])为了同时考虑基础资产的偏     

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.     

基于时变波动率的50ETF参数欧式期权定价

以上海证券交易所的首个股票期权品种50ETF为例,首先以时变波动率对经典BlackScholes期权定价公式常数波动率假设修正,然后基于正态分布、广义学生t分布和融入高阶矩的Edgeworth expansion渐近分布构建三种参数期权定价模型,最后采用参数显著性检验(Significance testing)、定价误差(Mispricing)、预测偏差(Forecastability)、对冲误差(Hedging errors)和波动率偏离修正(Volatility skew correction)5种严谨系统的评价标准,实证对比了在3种参数期权定价模型下的定价精度。研究结果表明:在时变波动率下,基于广义学生t分布和Edgeworth expansion渐近分布相比于正态分布显著提高了参数期权定价模型的定价精度。论文的研究成果为投资商和监管者提供了相对更为精确的期权定价模型。同时在相对更为准确的定价方法下,进一步利于50ETF期权在我国金融市场发挥价格发现和风险管理的作用。     

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。     

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下考虑突发事件影响的有交易费用的交换期权定价

在股票价格满足CEV且受布朗运动和泊松过程共同驱动的模型下,对支付交易费用的交换期权定价进行研究,给出了期权价格满足的偏微分方程,并发现定价模型中股票价格的幂指数与波动率弹性α的选取有关,同时交易费用受泊松强度参数λ的影响,且随着λ的变大而变小.     

中国股市期权波动率微笑特征的实证分析

波动率微笑现象显示了期权隐含波动率和执行价格之间的关系.在理想的完全符合Black-Scholes期权定价模型假设的情况下,期权隐含波动率关于执行价格应该是一条水平线.然而,在实证分析中,对隐含波动率和执行价格进行拟合并绘制曲线,会产生一个倾斜或微笑形状的曲线,证明Black-Scholes期权定价模型存在一定的缺陷....     

双跳跃仿射扩散模型的美式看跌期权定价北大核心CSCD

美式期权是一类具有提前实施权利的奇异型合约.2000年Duffie等人提出了一类双跳跃仿射扩散模型,假定标的资产及其波动率过程具有相关的共同跳跃,且波动率过程的跳跃大小服从指数分布.文章扩展了该模型,允许波动率过程的跳跃大小服从伽玛分布,并在具有跳跃风险的随机利率环境下研究美式看跌期权的定价.应用Bermudan期权和Richardson插值加速方法给出了美式看跌期权价格计算的解析近似公式.用数值计算实例,以最小二乘蒙特卡罗模拟法检验文章结果的准确性和有效性.最后,分析了常利率与随机利率情形下波动率过程中的相关系数对期权价格的影响.结果表明,相关系数对美式期权价格的作用是反向的.文章结果可以应用于利率与信用衍生品的定价研究.     

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.     

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．     

Pricing perpetual American options under multiscale stochastic elasticity of variance

This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk.     

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.     

American option pricing under stochastic volatility: an empirical evaluation

Over the past few years, model complexity in quantitative finance has increased substantially in response to earlier approaches that did not capture critical features for risk management. However, given the preponderance of the classical Black–Scholes model, it is still not clear that this increased complexity is matched by additional accuracy in the ultimate result. In particular, the last decade has witnessed a flurry of activity in modeling asset volatility, and studies evaluating different alternatives for option pricing have focused on European-style exercise. In this paper, we extend these empirical evaluations to American options, as their additional opportunity for early exercise may incorporate stochastic volatility in the pricing differently. Specifically, the present work compares the empirical pricing and hedging performance of the commonly adopted stochastic volatility model of Heston (Rev Financial Stud 6:327–343, 1993) against the traditional constant volatility benchmark of Black and Scholes (J Polit Econ 81:637–659, 1973). Using S&P 100 index options data, our study indicates that this particular stochastic volatility model offers enhancements in line with their European-style counterparts for in-the-money options. However, the most striking improvements are for out-of-the-money options, which because of early exercise are more valuable than their European-style counterparts, especially when volatility is stochastic.     

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.     

连续SV模型下衍生证券定价

1973年 Black- Scholes公式的出现极大推动衍生证券的发展 ,该公式的不足是假设影响标的资产价格波动的扩散系数为常数 ;80年代后期的 SV模型是针对该问题的离散统计模型。本文在两者的基础上讨论SV模型和 Black- Scholes公式结合。在讨论一般化衍生证券定价的基础上 ,通过 SV模型的连续化 ,构造一个2维随机微分方程 ,最后讨论了一种可以接受的数值计算方法     

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.     

A new fourth-order numerical scheme for option pricing under the CEV model

The empirically observed negative relationship between a stock price and its return volatility can be captured by the constant elasticity of variance option pricing model. For European options, closed form expressions involve the non-central chi-square distribution whose computation can be slow when the elasticity factor is close to one, volatility is low or time to maturity is small. We present a fast numerical scheme based on a high-order compact discretisation which accurately computes the option price. Various numerical examples indicate that for comparable computational times, the option price computed with the scheme has higher accuracy than the Crank–Nicolson numerical solution. The scheme accurately computes the hedging parameters and is stable for strongly negative values of the elasticity factor.