Exams Office
UNIVERSITY OF WARWICK
Proposal Form for New or Revised Modules (MA1- version 2)
For consideration by the Undergraduate Studies Committee/Sub-Faculty or Graduate
Studies Committee only.
1.
Title of Module:
Statistics for Finance
2.
New or Revised Module:
New module?
[]
Revised module?
[ ]
Level: M
If this module replaces an existing approved module specify the code and title
of the module to be discontinued and date on which change will occur:
3.
Date of Introduction:
September 2008
4.
Department Responsible for Teaching: Statistics
Name of Module Leader:
Professor A J Lawrance
5.
Availability/Location of module within courses:
Degree Title
Year of
Code
study
MSc Financial Mathematics
6.
Core /
optional
?
1
Option
list
A,B or C
core
Consultation with other Departments:
Mathematics, Business School
7.
Context: Follows first half of ST908 Probability and Stochastic processes
8
CATS*
Exams Office
8.
Module Aims: To present introductory statistics in a quantitative finance
context, taking introductory probability from the first half of ST908 as its
theoretical base and to present relevant aspects of statistical methodology
together with their underlying theory, computational and graphical aspects,
and financial applications. The course deals with statistical data, both as
distributions of single variables and in modelling relationships between
variables. Statistical estimation and formal assessment of uncertainty are
covered. It aims to provide the student with the background and skills to be
able to analyze financial data with standard statistical analysis techniques,
and to critically understand presentations of statistical data in financial
contexts.
9. Learning Outcomes:
Learning outcomes
By the end of the module
the student should be able
to demonstrate a basic
knowledge and
understanding of:
Subject Knowledge and
Understanding
Which teaching and
learning methods enable
students to achieve this
learning outcome?
Which assessment
methods will measure the
achievement of this
learning outcome?
A good understanding of
basic statistical ideas, as
applied in the finance area
Lectures and tutorials
Course exercises - 1
Ability to carry out
statistical analysis of
financial data, both for
single variables and for
relationships between
variables
Lectures and course
assessment exercises in
analysing financial data
Course exercises - 2
Ability to efficiently and
critically use statistical
software to carry out and
graphically present
statistically-based
conclusions
Lectures and use of
statistical software in
course assessment
exercises; experience
from earlier marked
exercises
Course mini-project
Lectures and tutorials
Course exercises and
mini- project
Cognitive Skills
Be able to appreciate the
relevance of statistical
analysis to the
understanding of financial
data
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Subject - specific/
professional skills
Be able to understand the
theoretical basis of various
methods of statistical
analysis in finance
Key Skills
Be able to handle and
analyze statistical data in
respect of its financial
implications using
statistical software
10.
Lectures tutorials, and
marked exercises
Course exercises and
mini- project
Tutorials, exercises and
mini-project
Course exercises and
mini- project
Syllabus:
1. The population-sample paradigm of statistics, inductive/deductive aspects, relationship
to probability theory. Random variables as models of data. Graphical aspects of data
distributions, such as probability plots.
2. Probability distributions, such as Normal, logNormal, t , high kurtosis distributions and
fat tail distributions for extreme behaviour; mathematical calculation of distributional
properties, and their particular financial applicabilities.
3. Matching distributions to data and the need for parameter estimation.
Idea of
likelihood and its use in estimating parameters.
4. Statistical relationships between variables by regression. Ideas of residuals to explore
inadequacies and improve analysis.
5. Formal assessment of uncertainty in statistics, confidence intervals, tests of
significance.
11.
Illustrative Bibliography:
D Rupert, Statistics and Finance: An Introduction, Springer Verlag, 2006
J Franke, W Hardle, C Hafner, Statistics of Financial Markets, Springer,
2004
A J McNeil, R Frey & P Embrechts, Quantitative Risk Management,
Princeton University Press, 2005
12.
Teaching:
Lectures per week
Seminars per week
Tutorials per week
Laboratory sessions
Total contact hours
Module duration (weeks, if applicable)
Other (please describe):e.g. distancelearning, intensive weekend teaching
10
1 x 2 hour lecture
0
1
0
15
5
Exams Office
13.
Assessment Methods:
Type of assessment
Examination
Course assessed exercises
14.
Length
One-hour of ST906
% weighting
90
10%
Resources:
Signature of Module Leader:
Tony Lawrance
29 August 2007
Date
Signature of Chair of Department:
Date
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