Empirical likelihood inference for the second-order jump-diffusion model

2013 ◽  
Vol 83 (1) ◽  
pp. 184-195 ◽  
Author(s):  
Yuping Song ◽  
Zhengyan Lin
Keyword(s):  
Diffusion Model ◽  
Empirical Likelihood ◽  
Jump Diffusion ◽  
Second Order ◽  
Likelihood Inference ◽  
Jump Diffusion Model

scholarly journals Estimation for a Second-Order Jump Diffusion Model from Discrete Observations: Application to Stock Market Returns

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Tianshun Yan ◽  
Yanyong Zhao ◽  
Shuanghua Luo
Keyword(s):  
Stock Market ◽  
Diffusion Model ◽  
Jump Diffusion ◽  
Second Order ◽  
Model Parameters ◽  
Ratio Test ◽  
Market Returns ◽  
Discrete Observations ◽  
Stock Market Returns ◽  
Jump Diffusion Model

This paper proposes a second-order jump diffusion model to study the jump dynamics of stock market returns via adding a jump term to traditional diffusion model. We develop an appropriate maximum likelihood approach to estimate model parameters. A simulation study is conducted to evaluate the performance of the estimation method in finite samples. Furthermore, we consider a likelihood ratio test to identify the statistically significant presence of jump factor. The empirical analysis of stock market data from North America, Asia, and Europe is provided for illustration.

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