Information geometry of L\'evy processes and financial models

We explore the information geometry of L\'evy processes. As a starting point, we derive the $\alpha$-divergence between two L\'evy processes. Subsequently, the Fisher information matrix and the $\alpha$-connection associated with the geometry of L\'evy processes are computed from the $\alpha$-divergence. In addition, we discuss statistical applications of this information geometry. As illustrative examples, we investigate the differential-geometric structures of various L\'evy processes relevant to financial modeling, including tempered stable processes, the CGMY model, and variance gamma processes.