Valid from: Autumn 2020
Decided by: Professor Thomas Johansson
Date of establishment: 2020-05-19
Division: Mathematical Statistics
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: FMSN25
Teaching language: English
The student should get a thorough understanding and insight in the economical and mathematical considerations which underlie the valuation of derivatives on financial markets. The student should get knowledge about and ability to handle the models and mathematical tools that are used in financial mathematics. The student should also get a thorough overview concerning the most important types of financial contracts used on the stock- and the interest rate markets and moreover get a solid base for understanding contracts that have not been explicitely treated in the course.
Knowledge and Understanding
For a passing grade the doctoral student must
Competences and Skills
For a passing grade the doctoral student must
Judgement and Approach
For a passing grade the doctoral student must
The course consists of two related parts. In the first part we will look at option theory in discrete time. The purpose is to quickly introduce fundamental concepts of financial markets such as free of arbitrage and completeness as well as martingales and martingale measures. We will use tree structures to model time dynamics of stock prices and information flows. In the second part we will study models formulated in continuous time. The models we focus on are formulated as stochastic differential equations (SDE:s). The theories behind Brownian motion, stochastic integrals, Ito-'s formula, measures changes and numeraires are presented and applied to option theory both for the stock and the interest rate markets. We derive e.g. the Black-Scholes formula and how to create a replicating portfolio for a derivative contract.
Types of instruction: Lectures, laboratory exercises, exercises
Examination formats: Written exam, written assignments
Grading scale: Failed, pass
Examiner:
Admission requirements: FMSF10 Stationary Stochastic Processes or FMSF15 Markov Processes. Knowledge corresponding to FMSF05 Probability Theory helps.
Course coordinator: Magnus Wiktorsson <magnus.wiktorsson@matstat.lu.se>
Web page: www.maths.lth.se/matstat/kurser/fmsn25/