Financial Econometrics: Either: Koop, G. (2005): Analysis of Financial Data New York: Wiley and Sons. Ch. 1-12. Koop assumes less and is more appropriate if you are new to statistics or econometrics. Brooks, C. (2002): Introductory Econometrics for Finance Cambridge: Cambridge University Press. Ch. 1, 3-5, 6.12-6.14 and 7-8. Sections specific to a software package can be ignored. Brooks goes into more detail than Koop and may be difficult if you do not have some familiarity with econometrics. Matrix Algebra is also used when appropriate in the course, and students unfamiliar with it should consult chapters 15 – 18 of Anthony and Biggs (see below). Economics:
Economics. The course is open to students who have not previously taken economics courses, but students without an economics-related degree are strongly advised to read one of the two textbooks listed below before they start the course. Lecturers will assume some familiarity with basic economic concepts, and the pace of teaching is rapid. As introductory textbooks, the following are recommended:
Begg, D. (2006): Foundations of Economics, third edition. McGraw-Hill.
This is short (379 pages) by the standards of economics textbooks and provides a lot of real-world examples. If you find this too easy, then we suggest a more advanced book, which emphasises the analytical core of economics:
Witztum, A. (2006): Economics: An analytical introduction. Oxford University Press. For those with no economics background at all, a gentle start is provided by one of the following “bedtime reading” books:
Harford, T. (2006): The undercover economist. Oxford University Press.
Dixit, A. K. and B. Nalebuff (1991): Thinking strategically: the competitive edge in business, politics, and everyday life. Norton, New York.
Mathematics. We use basic mathematical tools. Ideally, students should be familiar with: algebraic manipulation; solving and simplifying equations and inequalities; sequences, series, and limits; functions; differentiation; simple unconstrained optimization; partial differentiation; constrained optimization; integration; basic probability; random variables; common probability distributions. More generally, students should be comfortable with the expression of precise arguments in a mathematical form. As a guide, students may wish to refer to:
Anthony, M. and N. Biggs (1996): Mathematics for economics and finance: methods and modelling. Cambridge University Press, Cambridge. | 
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