98057 - Stochastic Methods for Applications

Academic Year 2024/2025

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Mathematics (cod. 8010)

Learning outcomes

At the end of the course, the student knows the basic elements of the theory of discrete-time stochastic processes, particularly Markov processes and martingales. They can apply this knowledge to various scientific areas, including mathematical finance, stochastic optimization, and data science.

Course contents

Introduction to pricing and hedging of financial derivatives in a one-period market: options, arbitrages, Put-Call parity formula, arbitrage and risk-neutral price, incomplete markets.

Elements of martingale theory: Sigma-algebras and filtrations, conditional expectation, discrete-time stochastic processes, martingales, stopping times, Doob decomposition Th., Markov property, discrete Markov chains.

Pricing and hedging in discrete market models: self-financing and admissible strategies, equivalent martingale measure and First Fundamental Theorem of Asset Pricing, arbitrage-free markets and arbitrage price, completeness and Second Fundamental Theorem of Asset Pricing.

Binomial market model: binomial tree, absence of arbitrage and completeness, arbitrage price and hedging strategies, binomial algorithm, stability and convergence to Black-Scholes model, trinomial model and incomplete markets, examples: European options.

Elements of stochastic optimal control: introduction to dynamic programming method. Bellman's equation and applications. 

Prerequisites: probability theory

Readings/Bibliography

- Pascucci, Andrea, and Wolfgang J. Runggaldier. Finanza matematica: teoria e problemi per modelli multiperiodali. Springer Science & Business Media, 2009.

- Pascucci, Andrea. Calcolo stocastico per la finanza. Springer Science & Business Media, 2008.

Teaching methods

Lectures on the board.

Assessment methods

Oral examination with questions on the topics covered in the lectures. The first topic is chosen by the student. Possibly, brief exercises to test the ability of applying the acquired knowledge.

Teaching tools

Lecture notes (PDF) covering some parts of the program available on the website virtuale.unibo.it

Office hours

See the website of Stefano Pagliarani