SOAS University of London

School of Finance and Management

Mathematics and Statistics for Finance Pre-sessional Course

Module Code:
15PFMC098
Credits:
0
FHEQ Level:
7
Year of study:
Any
Taught in:
Term 1

The course on Mathematics and Statistics for Finance is taught in early September before the formal start of the academic year. Each course is 12 hours per week for three weeks (8 hours of lectures and 4 hours of tutorials), concluding with a 2-hour examination. Attendance is strongly recommended since the concepts covered in the course will be assumed when you begin your degree programme.

The Mathematics and Statistics for Finance course presents the main ideas and methods in mathematics and statistics for financial analysis. The topics include matrix algebra, probability and random variables, univariate and multivariate distributions, statistical inference, time series, stochastic calculus, and asset pricing. The emphasis is throughout on the applications to finance. The course equips the students with the main analytical tools required for the MSc in Finance.

Objectives and learning outcomes of the module

At the end of this course students should be ready to progress onto the MSc in Finance. They will be able to:

  • Demonstrate familiarity with the main concepts and definitions in financial analysis;
  • Address problems in finance by using mathematical and statistical concepts and tools;
  • Interpret the mathematical and statistical results in terms of financial analysis;
  • Develop the analytical skills required for financial analysis;
  • Solve mathematical and statistical problems in relation to financial applications.

Scope and syllabus

The syllabus of the course covers the following topics:

  1. Vectors, matrices, determinants, linear combinations
  2. Rank, systems of linear equations, eigenvalues and eigenvectors, trace of a matrix
  3. Probability, random variables and distributions
  4. Univariate and multivariate distributions
  5. Sample moments, sampling distributions and the law of large numbers
  6. Estimation, estimators and hypothesis testing
  7. Time series
  8. Introduction to stochastic calculus: martingales, brownian motion
  9. Notable definitions in finance, no arbitrage condition
  10. Introduction to asset pricing

Method of assessment

This three week course is assessed 100% by examination only.

Suggested reading

  • Alpha C. Chiang, Kevin Wainwright. Fundamental Methods of Mathematical Economics. 4th ed. New York: McGraw-Hill Irwin, 2005.
  • William H. Green. Econometric Analysis. 2nd ed. New York: Oxford: Macmillan, 1993.
  • Douglas Kennedy. Stochastic Financial Models. Boca Raton, FL: Chapman & Hall/CRC, 2010.
  • Jeffrey M. Wooldridge. Introductory Econometrics: A Modern Approach. International Student Edition. 4th ed. Mason (OH): South-Western, Cengage Learning, 2009.

Disclaimer

Important notice regarding changes to programmes and modules