Numerical Techniques in Finance

This subject has the following teaching availabilities in 2015:

Admission into BH-COM and

None

Please refer to Prerequisites and Corequisites.

None

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/

Numerical techniques focuses on the theory and application of numerical methods for solving financial problems. The applications may include option valuation, value at risk, term structure modelling, portfolio simulation and optimisation and capital budgeting. These applications motivate the study of matrix methods, the solutions of linear and nonlinear equations, interpolation and approximation methods, numerical integration and Monte Carlo methods. No prior programming experience is required as the principles of programming are covered.

• Explain the principles of object-orientated programming.
• Design computer programs that implement solutions in an efficient and effective manner.
• Analyse the effects of numerical errors on computer-based finance models.
• Use a variety of numerical procedures to solve quantitative finance problems.
• Identify and analyse the assumptions, limitations and implementations of computer-based financial.
  models.
• Evaluate the applicability of various mathematical techniques to classes of finance problems

A two-hour end-of-semester examination (30%) and assignments totalling 4000 words, or equivalent, due in weeks 10 to 12 (70%)

You will be advised of prescribed texts by your lecturer.

This subject is not available as a breadth subject.

• High level of development: problem solving; application of theory to practice; use of computer software; accessing data and other information from a range of sources.

• Moderate level of development: team work; interpretation and analysis.

• Some level of development: written communication; statistical reasoning; critical thinking; synthesis of data and other information; evaluation of data and other information.