Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2026-2027

Module MATH3301: Mathematical Finance III

Department: Mathematical Sciences

MATH3301: Mathematical Finance III

Type Open Level 3 Credits 20 Availability Available in 2026/2027 Module Cap Location Durham

Prerequisites

  • Probability II (MATH2647) OR Probability II (MATH2751)

Corequisites

  • One 20 credit Level 3 mathematics module.

Excluded Combination of Modules

    Aims

    • To provide an introduction to the mathematical modelling of financial derivative products.

    Content

    • An introduction to options and markets.
    • Asset price random walks.
    • The Black-Scholes model and the Black-Scholes pricing formula.
    • Brownian motion.
    • Stochastic calculus: Itô processes and Itô's formula.
    • Self-financing, replicating portfolios and martingale measures.
    • Risk-neutral valuation.

    Learning Outcomes

    Subject-specific Knowledge:
    • By the end of the module students will be able to:
    • Demonstrate an understanding of the mathematics of pricing in basic financial markets in discrete and continuous time, based on fundamental principles of no-arbitrage, risk-neutral measures, and replicating portfolios.
    • Use the underlying probabilistic models to solve relevant financial problems; work with probability and change-of-measure computations; prove and apply pricing theorems in the context of binomial-tree markets and Black-Scholes markets.
    • Apply the theory of Brownian motion and stochastic calculus; derive properties of continuous-time stochastic processes; work with Ito’s lemma and Girsanov’s theorem.
    Subject-specific Skills:
    • Students will have enhanced mathematical skills in the following areas: modelling, computation. Moreover, students will have developed an appreciation of, and ability in, mathematical modelling in the financial world.
    Key Skills:
    • Students will have basic mathematical skills in the following areas: problem solving, modelling, computation.

    Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

    • Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
    • Problem classes show how to solve example problems in an ideal way, revealing also the thought processes behind such solutions.
    • Formative assessments provide feedback to guide students in the correct development of their knowledge and skills in preparation for the summative assessment.
    • The end-of-year examination assesses the knowledge acquired and the ability to solve predictable and unpredictable problems.

    Teaching Methods and Learning Hours

    Activity Number Frequency Duration Total/Hours Attendance Monitored
    Lectures 40 2 per week in Michaelmas and Epiphany 1 Hour 40
    Problem Classes 10 Fortnightly in Michaelmas and Epiphany; 2 in Easter 1 Hour 10 Yes
    Preparation and Reading 150
    Total 200

    Summative Assessment

    Component: Examination Component Weighting: 70%
    Element Length / duration Element Weighting Resit Opportunity
    On Campus Written Examination 2 hours 100%
    Component: Summative Assignments Component Weighting: 30%
    Element Length / duration Element Weighting Resit Opportunity
    Assignment 4 assignments 100%

    Formative Assessment:

    Four assignments to be submitted.


    Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.