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

Abstract EN

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.