Maximum entropy models for financial systems

Almog, A. (2017)

Doctoral Thesis

Complex systems, from financial markets to the brain, exhibit heterogeneous
structures and non-stationary dynamics. These characteristics manifest themselves in the diversity of the elements in a system, and in the changing behaviour over time. Capturing and understanding this heterogeneity via appropriate models, can have important implications not only for science, but also for societal challenges like predicting the next financial crisis or developing advanced brain imaging techniques. In this thesis, we use the maximum-entropy approach to introduce a new class of statistical models, which captures part of the observed
structural and/or temporal heterogeneity in the system. The models are applied
to various real-world complex systems, and are used to address different problems.

• Network theory
• Maximum-entropy ensembles
• Complex networks

• All authors: Almog, A.
• Supervisor: Eliel, E.R.; Saarloos, W. van
• Co-supervisor: Garlaschelli, D.
• Committee: Stanley, H.E.; Lelyveld, I. van; Hollander, W.T.F. den; Meijer, J.H.; Ruitenbeek, J.M. van; Denteneer, P.J.H.
• Qualification: Doctor (dr.)
• Awarding Institution: Institute of Physics (LION), Science, Leiden University
• Date: 2017-01-13
• Title of host publication: Casimir PhD Series
• ISBN (print): 9789085932833
• Name: 2016-38