Master of Actuarial Science

Topics include data analysis, the principles of actuarial modelling, the description of financial transactions; the understanding of real and nominal interest rates, the time value of money, the present value and accumulated value for a given cashflow, the term structure of interest rates; the duration, convexity and immunisation of cashflows; the equation of value and its usage to solve various practical problems, project appraisals.

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Topics include: measures of investment risk, portfolio theory, models of asset returns, asset liability modelling, equilibrium models, the efficient markets hypothesis, stochastic models of security prices, and Brownian Motion and its application.

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This subject aims to provide students with grounding in advanced financial mathematics, covering option pricing under the binomial model; risk‐neutral pricing of derivative securities; Brownian motion; introduction to Itô΄ formula and SDEs; stochas􀆟 asset models; Black‐Scholes model; arbitrage and hedging; interest‐rate models; actuarial applications and simple models for credit risk.

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Topics include survival models concepts; estimation procedures for lifetime distributions; multiple state models; multiple decrements; binomial and Poisson model of mortality; actuarial applications of continuous‐time and discrete‐time Markov processes; exact and census methods for estimating transition intensities based on age.

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This subject provides the groundwork for the capstone subject Life Contingencies. It provides students with a framework for actuarial modelling. The subject also expands students’ existing knowledge of mortality modelling by introducing the important ideas of mortality variation in a population and selection effects, which have implications for the applied topic of pricing life insurance products. Building on this, models used for mortality projections and forecasting, and elementary principles of machine learning are provided.

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Topics include distributions of accumulations and present values; stochastic interest rate models; time series models; an introduction to ruin theory; claim run-off triangles; stochastic simulation.

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This subject has two primary aims:

To provide fundamental principles of actuarial modelling.

To discuss techniques used to model and value cashflows dependent on death, survival, or other uncertain risks.

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Topics include loss distribution with and without risk sharing; collective risk model, calculation of moments and moment generating function of aggregate claims, recursion formulae, effect of reinsurance; individual risk model, recursion formulae and approximations; copulas; extreme value theorems; time series.

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This subject has two main objectives. Firstly, it is designed to enable students to have the ability to analysis and interpret the financial statements of companies and financial institutions. Secondly, to provide a basic understanding of corporate finance including a knowledge of the instrument used by companies to raise finance and manage financial risks.

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This subject aims to provide students with basic training on modern data analytics methods, which include linear regression, classification, resampling methods, spline-based methods, generalised additive models and support vector machines. This subject focuses on applying the above methods to modelling non-life insurance claims frequency and severity.

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Topics include multiple linear regression; Spearman´s and Kendall´s measures of correlation; principal component analysis; generalised linear models; bootstrap method; Bayesian statistics; credibility theory.

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This subject introduces core economic principles and how these can be used in a business environment to help decision making and behaviour. It provides the fundamental concepts of microeconomics that explain how economic agents make decisions and how these decisions interact. It explores the principles underlying macroeconomics that explain how the economic system works, where it fails and how decisions taken by economic agents affect the economic system.

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This subject involves the completion of a professional work placement (internship) either:

off campus at an approved host organisation in Australia or overseas OR

on campus at the 'WorkHub'

Integrating academic learning in business & economics areas of study, students will gain an improved knowledge of employability skills, workplace culture, and career pathways. Students will be required to undertake pre-placement online modules designed to equip students with employability skills and techniques for creative problem solving, as well as learning tasks throughout the placement period. The placement will draw on students' specific discipline skills associated with the specialisation of their degree.

Internships may be paid, or unpaid provided they comply with the Fair Work Act.

This subject is intended to provide students with the opportunity to apply their business knowledge in an industry setting under the joint supervision of an industry and an academic mentor. Students can either apply for a University-sourced internship or apply to have a self-sourced internship approved for credit. Applications should be submitted by the due dates published on the MBS website. Selection into this subject is based on suitability of the placement, and demonstrated motivation to benefit from the program, and timely submission of the application.

The on-campus 'WorkHub' provides a modern collaborative and supportive office environment for students to complete internship tasks in groups, and connect with industry professionals both on-campus, virtually, and at the host organisation.

Students will either enrol in the off campus or on campus availability following selection.

The subject coordinator will have final approval of all selected students. Enrolment will be capped and subject to meeting the relevant academic program requirements and availability of appropriate internship opportunities.

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