Units

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Sample subject outline - Semester 2 2013

Note: Subject outlines often change before the semester begins. Below is a sample outline.

Rationale

Postgraduate students pursuing a career in finance will find that financial modelling is a major area of application of mathematics and statistics. In fact, its models and methods, which draw on recent developments in diverse areas of mathematical sciences such as stochastic analysis, partial differential equations and probability theory, provide needed tools for quantitative modelling and financial analysis. This unit is one of a suite of units in Decision Science, which will equip you with essential skills for pursuing a career in business and finance.

Aims

This unit will present to you the essential elements of statistical inference and stochastic analysis of financial processes. It includes a self-contained development of mathematical tools such as Brownian motion and martingales, Markov processes and stochastic calculus all of which are essential for a rigorous treatment of mathematical finance. Some major statistical tools such as ARCH/GARCH modeling of stochastic volatility, quasi-likelihood estimation of long-range dependence and non-Gaussianity will also be presented. In addition, the application of models and methods developed in some key problems of mathematical finance will be demonstrated to you.

Objectives

Upon successful completion of this unit you should have:

1. Acquired an understanding of the statistical foundation of financial modelling.
2. Learned the application of models and methods developed through practical examples.
3. Acquired a detailed understanding of the analysis and prediction of financial processes.
4. Learned appropriate techniques of written communication.
5. Engaged in analytical thinking skills.

Content

Conditional expectation; Brownian motion; martingales; stochastic integrals and stochastic calculus; equivalent martingale measure.
Stochastic differential equations (SDE); the martingale-SDE approach to option pricing; replicating portfolio.
Statistical estimation of stochastic volatility via ARCH/GARCH-type models.
Quasi-likelihood estimation of long-range dependence and non-Gaussianity in financial processes.

Approaches to Teaching and Learning

The materials are presented in three formal lecture hours per week. Understanding of the concepts, models and techniques is enhanced throughout the lectures in which you will be encouraged to think critically by analysis and review. You will be encouraged to relate the mathematical and statistical theory to the practicalities of the market, to reinforce the relevance of the theoretical material.

Your work will be context-based using a wide variety of examples from different areas of application. The emphasis will be on enabling your learning through experience, providing opportunities to enhance your written communication, and on honing skills and attitudes to promote your life-long learning.

A combination of lecture notes, discussions, working through small and larger real world problems, and derivation of solutions will promote creativity in problem-solving, critical assessment, and intellectual debate. You will be encouraged to engage in aspects of professionalism and ethics in the practice of financial modelling.

Assessment

The assessment is designed to help you manage and optimise your understanding and skills throughout the semester, aiming for achievement of the synergies and synthesis of the unit by the end of the semester.Assessment carried out during the teaching period will be marked, with written comments, and returned promptly to the students. Examination scripts can be perused after the release of official results in the unit. The lecturer will be reasonably available for consultation in case of queries over marking of assessment items.

Assessment name: Examination (Theory)
Description: The final exam will assess you on your knowledge and ability in all sections of lecture content.
Relates to objectives: 1 and 3-5
Weight: 60%
Internal or external: Internal
Group or individual: Individual
Due date: End Semester

Assessment name: Problem Solving Task
Description: There will be an assignment consisting of exercises to solve using the techniques learned in the lectures. You will receive feedback on your performance in these exercises to assist your learning. The timing of the assignment will be negotiated with the student cohort.
Relates to objectives: 1-5
Weight: 40%
Internal or external: Internal
Group or individual: Individual
Due date: TBA

Academic Honesty

QUT is committed to maintaining high academic standards to protect the value of its qualifications. To assist you in assuring the academic integrity of your assessment you are encouraged to make use of the support materials and services available to help you consider and check your assessment items. Important information about the university's approach to academic integrity of assessment is on your unit Blackboard site.

A breach of academic integrity is regarded as Student Misconduct and can lead to the imposition of penalties.

Resource materials

Text:
Lecture notes will be provided.

Reference:
Mikosch T (1998) Elementary Stochastic Calculus with Finance in View, World Scientific.

Risk assessment statement

There are no out of the ordinary risks associated with this unit. You should be conscious of workplace health and safety at all times. Fire exits in classrooms will be indicated in the first class (absentees should obtain advice when they next attend). In the event of a fire alarm sounding, or on a lecturer's instruction, you should leave the room and assemble in the designated area which will be indicated to you. You should not attempt to adjust or repair computer or other electrical equipment, and should report suspected faults to a Computer Systems Officer. Further information on health and safety at QUT can be found at http://hrd.qut.edu.au/healthsafety/healthsafe/index.jsp

Disclaimer - Offer of some units is subject to viability, and information in these Unit Outlines is subject to change prior to commencement of semester.

Last modified: 10-May-2012