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, the Capital Asset Pricing Model, log-optimal portfolios and the Kelly criterion; dynamical programming. 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 MATLAB. Minimal computing experience will be required.
3x1-hr lectures; 1x1-hr tutorial; and 1x1-hr computer lab/wk
1 x2 exam (70%) , 1 x assignments (10%), 1 x quizzes (10%); 1 x computational project (10%). To pass the course at least 50% in the final exam is necessary.
Students may enrol in both MATH2070 and MATH3075 in the same semester
MATH1X23 or MATH1933 or MATH1X03 or MATH1907
(MATH1X21 or MATH1011 or MATH1931 or MATH1X01 or MATH1906) and (MATH1014 or MATH1X02)Prohibitions
MATH2010 or MATH2033 or MATH2933 or MATH2970 or ECMT3510