Modeling Underlying Assets Log-return in Merton Jump-Diusion Framework

摘要

In this present paper we analyze two exponential L′ evy models, theBlack-Scholes model and the Merton Jump-Diffusion model from theperspective of the investigation of the skewness and excess kurtosispresent in underlying assets log-returns distribution. Calibrating bothmodels on real-world financial data and investigating their various mo-ments and mean square error, we obtain results which show how theMerton jump-diffusion model performs better than the Black-Scholesmodel for modeling log-returns. This conclusion was also confirmed byusing the Diebold-Mariano test to compare the forecast accuracy of thetwo models.