Syllabus
Quantitative
methods for financial management
[C219]
This course introduces some of
the quantitative methods of
financial management which are
commonly used by financial
analysts, firms’ managers and
individual investors. It
examines techniques for the
valuation of different classes
of securities, analyses criteria
for guiding investment
decisions, considers the
measurement of asset risk and
return and discusses statistical
techniques of forecasting. The
MICROFIT computer package is
provided for regression analysis
and diagnostic procedures. The
aim of the course is to give
students confidence and skill in
the use of the mathematical and
statistical methods used in the
analysis of financial
instruments and financial
markets, including the
calculation of financial market
yields and prices, frequency
distributions, risk and
probability, correlation and
regression analysis. Statistical
inference, the multiple linear
regression model,
autocorrelation, and risk
reassessment and investment are
all topics covered in the
course, which teaches not only
the relevant theoretical
concepts but, in the belief that
quantitative techniques can only
be learned by doing, gives
abundant practice in the
manipulation of numerical
material with problems and
exercises.
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Econometric
principles and data analysis
[C230]
This course examines the
interaction and confrontation
between economic theory and
economic data. It is concerned
with the use of statistical and
mathematical methods in
analysing economic data, with
the aim of providing economic
theories with sufficient
empirical foundation to enable
them to be verified or refuted.
Central attention is given to
regression analysis — the major
tool of statistical analysis in
econometrics, to hypothesis
testing and the treatment of
heteroscedasticity and
autocorrelation. The MICROFIT
computer package is provided for
regression analysis and
diagnostic procedures.
Econometrics is concerned with
quantifying economic relations,
with the provision of numerical
estimates of the parameters
involved and testing hypotheses
embodied in economic
relationships. This course aims
to provide a basic introduction
to econometric analysis, to
enable students to examine
economic theories with empirical
data. In doing so, it examines
the difficulties inherent in
confronting theory with economic
data in order to quantify
economic relationships, in
dealing with errors and problems
in variables which can be only
observed but not controlled, and
the means of compensating for
uncertainty in data.
Econometric principles and data
analysis is extended by
Econometric analysis and
applications, which teaches
more advanced techniques in
quantitative methods. This
course can be studied in its own
right but normally expected to be taken as part of
the MSc or Postgraduate Diploma
programme which provides the
theoretical background required
to interpret empirical data
using statistical techniques.
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Econometric
analysis and applications
[C232]
This is the second econometrics
course that can be taken as part
of the MSc. It extends the basic
introduction to econometric
analysis developed in the core
course, Econometric principles
and data analysis. This course
teaches the more advanced
techniques of dummy variables,
lags and expectations,
simultaneous equation models,
non-stationarity and
co-integration and forecasting.
The course ends with a brief
discussion of ‘further topics
for econometrics’ for students
who are particularly keen to
develop their quantitative
skills beyond the course. It
assumes that students have
studied the classical linear
regression model at an
introductory level and that are
familiar with the assumptions
which underlie the model. It is
also assumed that they have a
basic working knowledge of the
econometric software, MICROFIT.
There are many examples to
illustrate the main themes in a
way which will help you in both
understanding the econometrics
and putting the theory to use
with data. This course aims to
broaden knowledge and extend
understanding of econometrics.
By the end of the course
students should be able to: make
progress with qualitative
regressors, dummy variables and
the identification and
estimation of simultaneous
econometric models; show how
lags and expectations can be
incorporated in dynamic models;
and forecast with both
econometric and time series
models.
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Financial econometrics
(currently under development)
Financial markets and others
generate vast amounts of data on
asset returns, their volatility,
and other financial variables in
long and high-frequency time
series. The ability to analyse
market behaviour requires
knowledge of the properties of
time series and appropriate
estimation methods. Since the
early 1980s techniques for
analysing time series which
exhibit auto-regression have
yielded important studies of
financial markets, increasing
our knowledge of financial
variables’ volatility. In this
course you study time series
techniques and their application
to financial markets. Before
starting this course students
should normally have completed
the course Econometric Analysis
and Applications [C232].
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Risk management:
principles and applications
[C223]
Risk management: principles and
applications examines the
techniques and the foundation of
risk management in corporations.
It covers the use of
derivatives, portfolio
allocation, the value of risk,
and the management of credit
risk and operations risk. This
course has four main aims: to
illustrate the main types of
risk; to present the most
important ideas and methods used
in the analysis of portfolios of
financial securities, (including
stocks and bonds); to explain
how rational investors can use
financial derivatives (mainly
futures and options) in order to
alter the risk of their
investment position; and to
illustrate some more specialised
risk management techniques (such
as Value at Risk and Credit
Risk).
Unit 1 Introduction to risk
management
Unit 2 Portfolio analysis
Unit 3 Management of bond
portfolios
Unit 4 Futures markets
Unit 5 Options markets
Unit 6 Risk management with
options
Unit 7 Value at risk
Unit 8 Credit risk
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Derivatives (currently under
development)
The expansion of financial
markets since 1973 has been
founded on the growth of
derivatives, both over the
counter derivative contracts and
exchange traded contracts. It
was made possible by the
development of models for
valuing derivatives based upon
the mathematics of stochastic
calculus. In this course you
learn the application of those
principles to the valuation of
derivatives.
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Modelling firms and markets
(currently under development)
You will study not only the
behaviour of individual firms,
but also how firms interact with
each other in competitive and
non-competitive markets. The
course will look at models of
stratgeic behaviour based on the
tools of game theory and how
firms inteact under conditions
of imperfect formation. Please
check back here soon for more
information about the course.
This course is currently under
development. Please check back
here soon for more information
about the course.
