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.
Unit details and rules
Academic unit | Mathematics and Statistics Academic Operations |
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Credit points | 6 |
Prerequisites
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(MATH1061 or MATH1961 or MATH1971) or [(MATH1X21 or MATH1011 or MATH1931 or MATH1X01 or MATH1906) and (MATH1014 or MATH1X02)] |
Corequisites
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None |
Prohibitions
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MATH2970 |
Assumed knowledge
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MATH1X23 or MATH1933 or MATH1X03 or MATH1907 |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | Caroline Wormell, caroline.wormell@sydney.edu.au |
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Lecturer(s) | Caroline Wormell, caroline.wormell@sydney.edu.au |