MATHEMATICAL MODELS IN FINANCE
Learning outcomes of the course unit
- To learn numerical methods for solving financial problems of differential character
- To acquire competence in the analysis of numerical results
To provide to the students some specific tools in order to properly investigate current research topics in the frame of kinetic equations for socio-economic sciences.
Course contents summary
Mod. 1: Numerical methods for differential problems linked to the Black-Scholes equations for the evaluation of financial options.
Introduction to kinetic equations for a simple market economy.
Investigation (from a modelling and an analytical point of view) of several interaction models for wealth exchange:
- basic deterministic model;
- model with random variables;
- model with taxation and redistribution.
La maggior parte del programma è basato su:
- P.Wilmott, J. Dewynne and S. Howison, 'Option Pricing', Oxford Financial Press, 1993
- R. Seydel, 'Tools for Computational Finance', Springer, 2009
Books or extended reviews:
- B. During, D. Matthes, G. Toscani, "A Boltzmann-type approach to the formation of wealth distribution curves", Riv. Mat. Univ. Parma 1 (2009) 199–261.
- L. Pareschi, G. Toscani, "Interacting multiagent systems. Kinetic equations and Monte Carlo methods", Oxford University Press (2013).
- A. Chakraborti, B.K. Chakrabarti, "Statistical mechanics of money: how saving propensity affects its distributions", Eur. Phys. J. B. 17 (2000), 167-170.
- S. Cordier, L. Pareschi, G. Toscani, "On a kinetic model for a simple market economy", J. Stat. Phys 120 (2005) 253–277.
- D. Matthes, G. Toscani, "On steady distributions of kinetic models of conservative economies", J. Stat. Phys. 130 (2008), 1087-1117.
- M. Bisi, G. Spiga, G. Toscani, "Kinetic models of conservative economies with wealth redistribution", Comm. Math. Sci. 7 (2009) 901–916.
Lectures and laboratory
Assessment methods and criteria
Oral exam with any term paper.