摘要
跳跃扩散模型是研究资产收益率分布的一个重要模型,本文在将伽马分布设为跳跃扩散模型的跳幅分布的基础上,选取中国证券市场中比较有代表性的10只股票的对数收益率为研究对象,运用Nelder-Mead方法对模型中的参数进行极大似然估计,得出了伽马跳跃扩散模型拟合高峰度的数据效果较好。
The jump-diffusion process is an important model for the distribution of the rate of return on assets. Based on the jump diffusion models,this paper implies the Gamma distribution for jump magnitudes. We choose 10 representative stocks from China＇s stock market as research subjects. At the same time,we use the Nelder-Mead method to obtain the maximum likelihood estimates of parameters of the model. We find that the Gamma jump-diffusion process performs better in stocks with high kurtosis than in stocks with low kurtosis.
出处
《科技广场》
2016年第5期116-118,共3页
Science Mosaic
关键词
伽马分布
极大似然估计
高峰度
Gamma Distribution
Maximum Likelihood Estimation
High Kurtosis
