Problems in industry and commerce often involve maximising profits or minimising costs subject to constraints arising from resource limitations. The first part of this unit looks at programming problems and their solution using the simplex algorithm; nonlinear optimisation and the Kuhn Tucker conditions. The second part of the unit deals with utility theory and modern portfolio theory. Topics covered include: pricing under the principles of expected return and expected utility; mean-variance Markowitz portfolio theory and the Capital Asset Pricing Model. Some understanding of probability theory including distributions and expectations is required in this part. Theory developed in lectures will be complemented by computer laboratory sessions using Python. Minimal computing experience will be required.
|Academic unit||Mathematics and Statistics Academic Operations|
|(MATH1X21 or MATH1011 or MATH1931 or MATH1X01 or MATH1906) and (MATH1014 or MATH1X02)|
|MATH1X23 or MATH1933 or MATH1X03 or MATH1907|
At the completion of this unit, you should be able to:
Unit outlines will be available 2 weeks before the first day of teaching for the relevant session.
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
Enrolment, course planning, fees, graduation, support services, student IT
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
Academic appeals process, special consideration, rules and guidelines, advice and support
Policy register, policy search
Scholarships, interest free loans, bursaries, money management
Learning Centre, faculty and school programs, Library, online resources
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing