module specification

MA4040 - Financial Mathematics with Statistics 1 (2017/18)

Module specification Module approved to run in 2017/18
Module title Financial Mathematics with Statistics 1
Module level Certificate (04)
Credit rating for module 30
School School of Computing and Digital Media
Total study hours 300
 
81 hours Scheduled learning & teaching activities
219 hours Guided independent study
Assessment components
Type Weighting Qualifying mark Description
In-Course Test 30%   On-line test 1 (1 hour)
In-Course Test 30%   On-line test 2 (1 hour)
In-Course Test 40%   On-line test 3 (2 hours)
Running in 2017/18
Period Campus Day Time Module Leader
Year North Monday Afternoon

Module summary

This module develops the mathematical and statistical tools that are used in mathematics of finance.  It also introduces methods of analysing data using appropriate financial and statistical software. 

Prior learning requirements

GCSE in maths grade C or above

Module aims

This module introduces the basic terminologies used in finance and develops the mathematical techniques to solve problems in the area of finance. Descriptive statistics and statistical techniques that are useful to present, analyse and make inferences about financial data are also introduced. A selection of suitable software (eg. Excel, R and SPSS) will enable students to analyse financial data in order to make informed financial decisions. 

Syllabus

Introduction to statistical methods and applications in finance; Applications of AP and GP in Finance;
Descriptive statistics (measures of central tendency and variability) and their applications in finance (introduction of a package); Introduction to financial measurements including simple and compound interest and the use of Excel built functions; Probability and introduction to the basic statistical distributions and hypotheses testing; Mathematics of finance; Introduction to expected values, mortality rate, index; Introduction to model fitting.
 

Learning and teaching

Students’ learning is supported by blended learning via face-to-face learning activities that include lectures, seminars, individual and group-based case studies and investigations and real data analysis resourced by Weblearn. There is full provision of documents related to the module in electronic format that can be accessed by students all the time. The documents include lecture notes, slides, guidance to packages, On-line exercises, On-line self assessment exercise and tests, data for analysis and feedback.  Students are motivated to analyse real financial and statistical data sets made available to them.

Learning outcomes

On successful completion of this module, students should be able to:
LO 1.    Demonstrate an understanding of the mathematical aspects of interest as applied to financial
             instruments, calculate various rates of interest, PV, FV and make distinctions between them.
LO 2.    Identify different types of data, summarise and present financial data; use sample data to make
             inference about population parameters.
LO 3.    Understand the ideas of probability and the basic probability distributions including discrete and
              continuous; use expected values in a financial context and understand their use in the decision
              making process.
LO 4.     Using appropriate statistical package (such as R, SPSS, Excel) to fit mathematical models to a
              given set of data; and investigate and interpret financial models.

 

Assessment strategy

The assessment consists of three sets of On-line class tests.   In the first test students are tested on their understanding of the basic financial instruments and summary statistics (LO1, LO2). The second test examines the understanding gained by the students regarding the basic discrete and continuous probability  distributions and the various financial models (LO3,LO4). Final test will test LO1-4.

Bibliography

Guthrie, G and Lemon, L (2003) Mathematics of Interest and Finance, Prentice Hall.
Zima, P and Brown, R (1998) Schaum’s Mathematics of Finance, McGraw-Hill.
Kaminsky, K (2003) Financial Literacy: Introduction to the Mathematics of Interest, Annuities.
UPA.
Adams, A, Booth, P, Bowie, D and Freeth, D  (2003) Investment Mathematics, John Wiley.
Jackson, M and Mike Staunton (2001) Advanced Modelling in Finance using Excel and VBA,
John Wiley.
Albright, S., Winston, W. and Zappe,C. (2003) Data Analysis & Decision Making with Microsoft Excel, Thomson.
Winston, W. and  Albright, S. (2001) Practical Management Science (2nd ed.) Duxbury Press.
McClave, T. and  Sincich, T. (2003) A First Course in Statistics, Prentice Hall.
Veaux, R. and  Vellman,P. (2004) Intro Stats,  Addison Wesley ISBN 0-201-70910-4.