TITLE:
Pricing Bitcoin under Double Exponential Jump-Diffusion Model with Asymmetric Jumps Stochastic Volatility
AUTHORS:
Ndeye Fatou Sene, Mamadou Abdoulaye Konte, Jane Aduda
KEYWORDS:
Bitcoin, Double Exponential Jump-Diffusion, Stochastic Volatility, Markov Chain Monte Carlo
JOURNAL NAME:
Journal of Mathematical Finance,
Vol.11 No.2,
May
31,
2021
ABSTRACT: The objective of this study is, to show the importance of incorporating jumps in both returns and volatility dynamics for Bitcoin. For that purpose, we introduce the Double Exponential Jump-Diffusion model with Stochastic Volatility (DEJDSVJ) that contains asymmetric jumps. The use of the Markov Chain Monte Carlo methods for estimation has proved the meaningful presence of jumps in Bitcoin price and volatility. Moreover, based on the Bitcoin options market, a comparison between the underlying model, the Double Exponential Jump Diffusion model (DEJD) with Stochastic Volatility (no Jumps) and the Stochastic Volatility (SV) shows the goodness of the DEJDSVJ model’s calibration over others for pricing Bitcoin options.