摘要
随机波动率模型由于放松了Black-Sholes模型的假定而更符合市场情况,因此成为研究金融衍生品定价的热点。Heston随机波动率不同于其他随机波动率模型之处在于其存在闭形式解。Heston期权定价模型在应用中需要确定五个待估参数,此问题通常比较困难。本文采用模拟退火算法并利用最小化残差平方和来估算,该算法以一定概率跳出局部极小值,从而以概率1收敛到全局极小值,最终得到Heston模型的待估参数。在实证研究中,本文利用香港恒生股票指数期权在2010年10月15日交易的数据,得到待估参数,并用该参数对2010年10月18日期权进行了模拟定价。
Stochastic Volatility Model （SVM） for option pricing relaxes the assumptions of the BS model. Heston＇s option pricing model, which differs from other similar stochastic models, has a closed-form solution. However, it is usually difficult to determine the input parameters when the model is employed. In this pa- per, we use the Simulated Annealing Method together with the minimum residual sum of squares to estimate the 5 parameters in Heston model. The simulated annea- ling method can jump out of the local minimal values at certain probability, then converge with a probability 1 to the global minimal value. This method allows us to calibrate suitable parameters for Heston model. In the empirical study, we have de- termined the suitable parameters for Heston model by using Hang Kong Hangsh- eng equity index option data on October 15, 2010 and we have also used these pa- rameters to price the index options for October 18, 2010.
出处
《数量经济技术经济研究》
CSSCI
北大核心
2011年第9期131-139,153,共10页
Journal of Quantitative & Technological Economics
关键词
Heston模型
模拟退火算法
非线性最小二乘
Heston＇s Stochastic Volatility Model
Simulated Annealing Algo- rithm
Nonlinear Least Square Function
