Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convener
Simon Guthrie
Contact via email
E4A616
Please refer to the i-Learn announcement.
Lecturer
Han Li
Contact via email
E4A724
Please refer to the i-Learn announcement.
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Credit points |
Credit points
3
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Prerequisites |
Prerequisites
ACST356 and STAT271
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit examines the use of statistical models in general insurance. The models include those used in time series analysis, generalised linear statistical modelling and runoff triangle models. Time series models are considered for both single and multiple time series. These models are often used for forecasting and inferring the behaviour of times series. Generalised linear models are used in the pricing of insurance such as automobile or homeowner insurance. Runoff triangle models are used to predict outstanding insurance liabilities. The use of no claim discount systems as a method of experience rating is also described. A good knowledge of the material covered in STAT271 is essential. Students should understand regression analysis, and the nature and use of a statistical model. Students gaining a grade of credit or higher in both ACST356 and ACST357 are eligible for exemption from subject CT6 of the professional exams of the Institute of Actuaries of Australia.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Name | Weighting | Hurdle | Due |
---|---|---|---|
Early Assessment Quiz | 5% | No | Week 3 |
Class Test | 20% | No | Week 7 |
Assignment | 15% | No | Week 10 |
Final Examination | 60% | No | In the university exam period |
Due: Week 3
Weighting: 5%
1. This will be an online quiz with five multiple choices questions.
2. It is envisaged that the online quiz will cover all materials in Weeks 1-2.
3. Please use the quiz as an indicator of whether you are progressing satisfactorily in the unit. If you are having difficulties, please see the Unit Convenor and consider withdrawing before the census date in week 4.
Due: Week 7
Weighting: 20%
1. It is envisaged that the class test will cover all materials from Week 1 to Week 5.
2. The class test will be held in the lecture.
Due: Week 10
Weighting: 15%
1. This will be a written assignment that will require use of the software package R.
2. The assignment must be done individually and must be your own work.
3. Further details will be provided on iLearn.
Due: In the university exam period
Weighting: 60%
It is envisaged that the final examination will cover all materials in the unit.
Classes
The timetable for classes can be found on the University web site at: https://timetables.mq.edu.au/2019/
Required texts
A set of lecture notes and study pack including tutorial exercises and R examples are available for downloading from the ACST357/862 teaching website.
Optional ActEd material
The ActEd CT6 are not set as required or recommended reading for this unit, since the lecture notes are comprehensive and detailed.
Other useful references:
Some additional references will be listed in the lecture notes.
Unit Web Page
To access the website, go to http://ilearn.mq.edu.au and login using your usual login and password.
Unit Guides, Lectures, Tutorials and Assessments Materials (Whenever Applicable)
Week Number |
Week Beginning Monday |
Topic and Notes | Tutorial |
1 |
29 July |
Introduction to GLMs | No tutorial |
2 |
5 August |
GLMs |
Tutorial Set 1 |
3 |
12 August |
GLMs |
Tutorial Set 2 |
4 |
19 August |
GLMs |
Tutorial Set 3 |
5 | 26 August |
1. GLMs 2. Introduction to Claim Reserving |
Tutorial Set 4 |
6 | 2 September | Outstanding Claims | Tutorial Set 5 |
7 |
9 September |
1. Class Test 2. Outstanding Claims |
No tutorial |
STUDY BREAK |
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No classes No classes |
STUDY BREAK |
8 | 30 September |
Outstanding Claims |
Tutorial Set 6 |
9 | 7 October |
Intro to Time Series |
Tutorial Set 7 |
10 | 14 October |
Time Series |
Tutorial Set 8 |
11 | 21 October | Time Series | Tutorial Set 9 |
12 | 28 October | Time Series | Tutorial Set 10 |
13 |
4 November |
Revision |
Tutorial Set 11 |
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Supplementary exams
Information regarding supplementary exams, including dates, is available at: http://www.businessandeconomics.mq.edu.au/current_students/undergraduate/how_do_i/disruption_to_studies
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Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.
This graduate capability is supported by:
We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.
This graduate capability is supported by:
Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.
This graduate capability is supported by:
The student will learn some basic theories and methodologies in time series analysis, generalized linear models and run-off triangles which are expected to be useful for researching and practising general insurance pricing and reserving.