ACTL30001 Actuarial Modelling I

Credit Points: 12.5
Level: 3 (Undergraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2017:

Semester 1, Parkville - Taught on campus.Show/hide details
Pre-teaching Period Start not applicable
Teaching Period 27-Feb-2017 to 28-May-2017
Assessment Period End 23-Jun-2017
Last date to Self-Enrol 10-Mar-2017
Census Date 31-Mar-2017
Last date to Withdraw without fail 05-May-2017

Timetable can be viewed here.
For information about these dates, click here.
Time Commitment: Contact Hours: Contact hours: One x 1-hour online lecture per week, one x 1-hour workshop per week, and one x 1-hour tutorial per week, commencing in the second week of semester.
Total Time Commitment:

170 hours


For students who started their degree in 2007 or earlier: 300-204 Financial Mathematics II, 620-202 Statisticsand one of 620-113 Applied Mathematics (Advanced Plus) and 620-123 Applied Mathematics (Advanced). For students who started their degree in 2008 or later: ACTL20002 Financial Mathematics II and MAST20005 Statistics.

Corequisites: None
Recommended Background Knowledge:

Please refer to Prerequisites and Corequisites.

Non Allowed Subjects:

Students may not gain credit for both ACTL30001 Actuarial Modelling I and 300-330 Survival Models: Theory and Applications.

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability


Prof David Dickson



Subject Overview:

Topics include survival models concepts; estimation procedures for lifetime distributions; multiple state models; binomial model of mortality; actuarial applications of Markov processes.

Learning Outcomes:
  • Explain the concept of survival model;
  • Describe estimation procedures for lifetime distributions;
  • Define a Markov process, and apply Markov models in actuarial problems;
  • Describe models of transfer between multiple states, including processes with single or multiple decrements, and derive relationships between probabilities of transfer and transition intensities;
  • Derive maximum likelihood estimators for the transition intensities in models of transfers between states with piecewise constant transition intensities;
  • Describe the binomial model of mortality, a maximum likelihood estimator for the probability of death and compare the binomial model with the multiple state models;
  • Apply pre-requisite mathematical and statistical concepts to the solution of problems on the above topics.
  • 50-minute mid-semester test, middle of semester (10%)
  • One 1000-word assignment, due in the second half of semester (10%)
  • 2-hour end-of-semester examination, end of semester (80%)
  • To pass this subject students must pass the end of semester examination.
Prescribed Texts:

You will be advised of prescribed texts by your lecturer.

Recommended Texts:

Information Not Available

Breadth Options:

This subject potentially can be taken as a breadth subject component for the following courses:

You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:
  • High level of development: written communication; problem solving; statistical reasoning; application of theory to practice; synthesis of data and other information.

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