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Financial Mathematics
Level: 6
Credits: 10
Teaching Period: 1
Module Tutor: Dr A K Chattopadhyay
Aims: To understand the relevance of mathematics and statistics in financial modelling. In
particular, to inspire in the student an aptitude towards analysing financial markets using
relevant theoretical methods and models.
Interest, Financial Assets and Return:
Mathematical preliminaries: mean, median, mode, variance, covariance
Interests: simple and complex
Saving with Variable Interest Rates
Paying off a Loan with Variable Interest Rates
Present and Future Values
Annuities, amortisation and sinking funds
Financial Bonds
Portfolio Analysis and Derivatives:
Mathematical preliminaries: correlation, regression, probability
Basic mathematics of Options, Futures and other Derivatives.
Portfolio theory
Two parameter model, beta, capital asset prising model.
Risk assessment (only basics)
Lectures 22 hours
Tutorials 11 hours
Self-study and examination 67 hours
Assessment: Continuous Assessment: 10% Class Test
Examination (1.5 hours): 90%
Progress and feedbacks on the module will be given via Class Test evaluation and solutions
of homework problems throughout the module. All such worked out solutions as well as
class room lecture materials will be uploaded regularly on the Blackboard website.
All provisional marks will be available within 4 weeks of the submission of the work.
Combination of the Class Test and Final Examination will be the student mark.
Module Outcomes
What the stsudent should gain
from successful completion of the
Knowledge and Understanding
Lectures / Tutorials Class tests and
 An appreciation of the context
and historical development of
financial mathematics.
 An understanding of the
relevance of mathematics in
financial modelling.
EAS, Aston University – AM Module Specification 2010/11
Last update 09/9/11
 An understanding of some of
the mathematical models used
in practice.
Intellectual Skills
Lectures / Tutorials Class tests and
Develop an ability to mathematically
analyse financial bond option theory
computational methods.
Professional / Subject-specific Skills
Lectures / Tutorials Class tests and
 Implement, test and evaluate
mathematical models.
 Apply mathematical models to
real data analysis.
Transferable Skills
Self study
Self assessment
and tutorials
 Large scale data analysing
 Familiarity with appropriate
including softwares
Reading List Griffiths, H. Financial Investments, McGraw-Hill
Ayres, F. Mathematics of Finance, McGraw-Hill (Schaum series)
Ingersoll, J. Theory of Financial Decision Making, Rowan and Littlefield
Ross, S. M. Mathematical Finance, Cambridge UP
Wilmott, P and Rasmussen, H, New Directions in Mathematical Finance,
John Wiley & Sons
McCutcheon, J. J. and Scott, W. F. Introduction to the Mathematics of
Finance, Butterworth-Heinemann.
Puxty, A. G. and Colin Dodds, J. Financial Management, Chapman & Hall
Brown, K. C. and Reilly, F. K. Investment Analysis and Portfolio
Management, South-Western, Division of Thomson Learning
AM10SP (Statistics and Probability)
AM20MC (Multi Variate Calculus)
AM20IM (Introduction to Numerical Methods)
EAS, Aston University – AM Module Specification 2010/11
Last update 09/9/11