摘要
为了更好地解决期权定价中存在的问题,研究了带有Heston随机波动率模型的期权定价问题,对美式期权的最佳实施边界及其提前执行的条件进行了分析和讨论。鉴于美式期权不存在解析定价公式,通过离散化参数空间将带有Heston随机波动率的美式期权价格所满足的随机偏微分方程转化为相应的差分方程,进而采用高阶紧式有限差分方法进行求解,得到了期权价格的数值解。通过数值实验对理论结果进行验证和模拟,对带有常数波动率和随机波动率条件下的两种最佳实施边界进行比较,发现最佳实施边界也具有随机波动性;在设定参数下对波动率的行为和性质进行分析,模拟出波动率曲线,并对高阶紧差分方法的计算结果进行比较,得到了期权的数值解,验证了算法的有效性。此方法对解决随机波动率下的期权定价其他问题,如:随机波动率下的多标的资产期权定价、障碍期权定价的研究具有借鉴价值。
In order to solve the problem of option pricing more perfectly,the option pricing problem with Heston stochastic volatility model is considered.The optimal implementation boundary of American option and the conditions for its early execution are analyzed and discussed.In view of the fact that there is no analytical American option pricing formula,through the space discretization parameters,the stochastic partial differential equation satisfied by American options with Heston stochastic volatility is transformed into the corresponding differential equations,and then using high order compact finite difference method,numerical solutions are obtained for the option price.The numerical experiments are carried out to verify the theoretical results and simulation.The two kinds of optimal exercise boundaries under the conditions of the constant volatility and the stochastic volatility are compared,and the results show that the optimal exercise boundary also has stochastic volatility.Under the setting of parameters,the behavior and the nature of volatility are analyzed,the volatility curve is simulated,the calculation results of high order compact difference method are compared,and the numerical option solution is obtained,so that the method is verified.The research result provides reference for solving the problems of option pricing under stochastic volatilitysuch as multiple underlying asset option pricing and barrier option pricing.
出处
《河北科技大学学报》
CAS
2017年第6期542-547,共6页
Journal of Hebei University of Science and Technology
基金
陕西省自然科学基金(2016JM1009)
陕西省教育厅专项科研计划基金(15JK2183
15JK2134)
关键词
金融市场
随机分析
美式期权
随机波动率
自由边界
有限差分法
finance markets
stochastic analysis
American option
stochastic volatility
free boundary
finite difference method
