Introductory Mathematical Finance

FOR10 Introductory Mathematical Finance

Autumn 2018

  • Topics

    The objective of the course is to introduce the theory of mathematical finance and the mathematical tools on which this is based. The focus chosen is on the pricing of financial assets via arbitrage theory. We will concentrate on discrete time models, e.g. Cox-Ross-Rubinstein and multinomial models, and classical assets as European call and put options.

    In the above market models we will also study optimal portfolio problems, that is we study how to obtain a strategy maximizing the expected utility of the final wealth. For this we will concentrate on complete markets.

    The mathematical tools presented in the course belong to the theory of probability and stochastic processes. They include the concepts of probability measures, conditional expectations, and martingales. The concepts, methods, and models discussed have a value by themselves and can be applied beyond the focus of this course. They also constitute the base for follow-up courses at master level.

    Topics

    • Elements of probability theory and stochastic processes: probability measures, conditional expectations, convergences, filtrations, martingales, change of measure
    • Financial assets: derivatives of European type
    • Discrete time models: Cox-Ross-Rubinstein and multinomial models as preparation to the classical Black-Scholes model
    • Pricing methods: concept on arbitrage, risk-neutral evaluation, Snell envelope
    • Optimal portfolio problems via martingale methods

  • Learning outcome

    Introductory Mathematical Finance is a semi-intensive course that equips the students with the foundation of financial modeling in a single and multi-period trading framework. The focus is on the rigorous understanding of how the principles of finance are merged into the models. The focus is on the pricing of financial derivatives.

    At the end of the course the students will acquire:

     KNOWELEDGE

    1. The foundations of financial modeling in single and a multi-period trading time, including the binomial model.
    2.  The definition of arbitrage opportunity and the use of the law-of-one-price to achieve the concept of "fair" pricing.
    3. The concepts of attainability and perfect hedging of a financial claim or risk. The associated models for complete and incomplete markets.
    4. The construction of hedging strategies.
    5. The study of optimal portfolios and optimal consumption and investment schemes in the different market models of single and multiperiod type.

    SKILLS

    The course will provide specific skills in quantitative methods, these include: 

    1. Stochastic processes and the information flow.
    2. Probability measures, probability distributions, change of probabilities: to find the state-price density and the risk-neutral pricing measures.
    3. Expectations and conditional expectations also under change of measure.
    4. Martingales processes.
    5. Stochastic optimal control problems: risk-neutral approach and dynamic programming

    GENERAL COMPETENCE

    The course provides a basic competence in quantitative methods for finance. This enables the students to be aware of the correct models to be applied in the different financial modeling contexts, to be aware of the techniques involved, and to be able to understand the correct power of prediction as a result of the analysis. The students will be able to write problems of optimization in the single and multiperiod setting and to solve them in the case of complete markets.

  • Teaching

    The course will be delivered through a combination of lectures and exercise classes in which some selection of the exercises suggested during lectures are going to be corrected. There will be 32 lectures grouped in in 7-8 days of semi-intensive work according to schedule. Exercises will be posted on the webpage along with their solutions. 

  • Recommended prerequisites

    There are no formal requirements for this course, however any background knowledge or insight in the mathematical directions can facilitate the participation.

    Very useful background knowledge is to be able to solve a linear system of equations. Good knowledge of the concept of random variable, probability distribution, stochastic process, expectation and variance is also helpful.

    For example useful background courses could be: MAT10 Analyse og lineær algebra; MAT11/MAT011 Differense og differensiallikninger; MAT12/MAT013 Matematisk statistikk; MAT13/MAT016 Optimering.

  • Credit reduction due to overlap

    VOA038

  • Requirements for course approval

    2 approved assignments given during the course.

  • Assessment

    3 hour written school exam.

    If nothing else is determined by the course start, the examination can only be written in English.

  • Grading Scale

    A - F

  • Literature

    The course will present selected topics that can be retrived in the following recommended reference books:

    • Derivative Pricing in Discrete Time, by N. Cutland and A. Roux, Springer 2012. ISBN: 978-1-4471-4407-6  (This also available as e-book: ISBN: 978-1-4471-4408-3)
    • Introduction to Mathematical Finance, Discrete Time Models, by S.R. Pliska, Blackwell Publishers 1997. ISBN: 978-1-55786-945-6.

    (This second reference will be used in particular for optimization problems)

    Moreover, lecture notes on selected topics will be made available.

Overview

ECTS Credits
7.5
Teaching language
English
Semester

Spring (biannual).Offered spring 2018.

Written school exam is offered both semesters (according to Regulations for Full-time Study Programmes at the Norwegian School of Economics (NHH), section 3-1).

Course responsible

Professor Giulia di Nunno, Department of Business and Management Science.