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ACST356 – Mathematical Theory of Risk

2017 – S1 Day

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit convenor and lecturer
Jackie Li
Contact via Email
E4A 610
Mondays 11am-1pm during teaching weeks or by appointment
Lecturer
David Pitt
Contact via Email or phone 9850 8455
E4A 611
Wednesdays 3pm-4pm during teaching weeks
Angela Chow
Credit points Credit points
3
Prerequisites Prerequisites
(39cp at 100 level or above) including STAT272
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description
This unit examines the use of statistical models in the insurance context. Statistical models of the number of claims and the sizes of the claims are studied. These models are used as a basis for the study of risk theory, ruin theory and the effect of reinsurance. Decision theory and simulation are also studied. 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.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at http://students.mq.edu.au/student_admin/enrolmentguide/academicdates/

Learning Outcomes

  1. Model insurance claims using loss distributions and Bayesian analysis
  2. Perform Monte Carlo simulation for insurance models
  3. Apply premium principles to price insurance products
  4. Construct risk models with frequency and severity distributions and apply ruin theory to insurance problems
  5. Apply credibility theory and decision theory to insurance problems

General Assessment Information

It is the responsibility of students to view their marks for each within session assessment on iLearn within 20 working days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment marks (not including the final exam mark) will not be addressed.

 

Assessment criteria for all assessment tasks will be provided on the unit iLearn site.

 

Assessment Tasks

Name Weighting Due
Assignment 15% Week 3 and Week 12
Final exam 70% Exam period
Class Test 15% Week 7

Assignment

Due: Week 3 and Week 12
Weighting: 15%

There are two written assignments due in Week 3 (5%) and Week 12 (10%). Marks will be granted for accuracy and clarity of the work submitted.

 

No extensions will be granted. Students who have not submitted the task prior to the deadline will be awarded a mark of zero (0) for the task, except for cases in which an application for disruption to studies is made and approved.

 

It is the responsibility of students to view their marks for each within session assessment on iLearn within 20 working days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment marks (not including the final exam mark) will not be addressed.

 

Assessment criteria and submission method will be provided on the unit iLearn site. 

 

 


This Assessment Task relates to the following Learning Outcomes:
  • Model insurance claims using loss distributions and Bayesian analysis
  • Perform Monte Carlo simulation for insurance models
  • Apply premium principles to price insurance products
  • Construct risk models with frequency and severity distributions and apply ruin theory to insurance problems
  • Apply credibility theory and decision theory to insurance problems

Final exam

Due: Exam period
Weighting: 70%

A three-hour (3) written exam will be held during the normal university exam period. Questions will cover the entire unit. Marks will be granted for accuracy and clarity of the work shown.

 

You are permitted one (1) A4 page of paper containing reference material printed on both sides. The material may be handwritten or typed. The page will not be returned to you at the end of the final exam. Non-programmable calculators with no text-retrieval capacity are permitted.

Students who do not attend the final exam will be awarded a mark of zero (0) for the exam, except for cases in which an application for disruption to studies is made and approved.

 

 

 


This Assessment Task relates to the following Learning Outcomes:
  • Model insurance claims using loss distributions and Bayesian analysis
  • Perform Monte Carlo simulation for insurance models
  • Apply premium principles to price insurance products
  • Construct risk models with frequency and severity distributions and apply ruin theory to insurance problems
  • Apply credibility theory and decision theory to insurance problems

Class Test

Due: Week 7
Weighting: 15%

The class test covers the lecture content in Week 1 to Week 5. Students will have 75 minutes to complete the test. Marks will be granted for accuracy and clarity of the work submitted. It will be conducted in the lecture on Monday 10 April at 8:30am.

 

You are permitted one (1) A4 page of paper containing reference material printed on both sides. The material may be handwritten or typed. The page will not be returned to you at the end of the class test.

 

Students who do not attend the class test will be awarded a mark of zero (0) for the test, except for cases in which an application for disruption to studies is made and approved.

 

 

 

It is the responsibility of students to view their marks for each within session assessment on iLearn within 20 working days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment marks (not including the final exam mark) will not be addressed.

 

Assessment criteria will be provided on the unit iLearn site. 

 


This Assessment Task relates to the following Learning Outcomes:
  • Model insurance claims using loss distributions and Bayesian analysis

Delivery and Resources

The timetable for classes can be found on the University website at: 

https://timetables.mq.edu.au/2017/

 

Lecture notes are available for download from iLearn. You will need to print the lecture notes and bring them to classes to complete.

 

From Week 8 onward, the required textbook is:

Dickson, D. (2005). Insurance Risk and Ruin. Cambridge University Press.

 

Other references include:

Hossack, I.B., Pollard, J.H. and Zehnwirth, B. (1999). Introductory Statistics with Applications in General Insurance. 2nd Edition. Cambridge University Press.

Klugman, S.A., Panjer, H.H. and Willmot, G.E. (2004). Loss Models: From Data to Decisions. 2nd Edition. Wiley: New York.

Casualty Actuarial Society (2001). Foundations of Casualty Actuarial Science. 4th Edition. 

 

Students will be required to use iLearn, Excel, PDF, Word, and a non-programmable calculator.

 

Unit Schedule

Week 1     Loss Models I

Week 2     Loss Models II

Week 3     Loss Models III

Week 4     Loss Models IV

Week 5     Reinsurance and Deductibles

Week 6     Simulation

Week 7     Class Test

Week 8     Premium Principles

Week 9     Risk Models

Week 10    Ruin Theory

Week 11    Ruin Theory with Reinsurance

Week 12    Credibility Theory

Week 13    Decision Theory

 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:

Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html

Assessment Policy http://mq.edu.au/policy/docs/assessment/policy_2016.html

Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html

Complaint Management Procedure for Students and Members of the Public http://www.mq.edu.au/policy/docs/complaint_management/procedure.html​

Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.

In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/

Results

Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.

Supplementary exams

Information regarding supplementary exams, including dates, is available at:

http://www.businessandeconomics.mq.edu.au/current_students/undergraduate/how_do_i/special_consideration

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.

Student Enquiry Service

For all student enquiries, visit Student Connect at ask.mq.edu.au

Equity Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Graduate Capabilities

Problem Solving and Research Capability

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:

Learning outcomes

  • Model insurance claims using loss distributions and Bayesian analysis
  • Perform Monte Carlo simulation for insurance models
  • Apply premium principles to price insurance products
  • Construct risk models with frequency and severity distributions and apply ruin theory to insurance problems
  • Apply credibility theory and decision theory to insurance problems

Assessment tasks

  • Assignment
  • Final exam
  • Class Test

Discipline Specific Knowledge and Skills

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:

Learning outcomes

  • Model insurance claims using loss distributions and Bayesian analysis
  • Perform Monte Carlo simulation for insurance models
  • Apply premium principles to price insurance products
  • Construct risk models with frequency and severity distributions and apply ruin theory to insurance problems
  • Apply credibility theory and decision theory to insurance problems

Assessment tasks

  • Assignment
  • Final exam
  • Class Test

Critical, Analytical and Integrative Thinking

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:

Learning outcomes

  • Model insurance claims using loss distributions and Bayesian analysis
  • Perform Monte Carlo simulation for insurance models
  • Apply premium principles to price insurance products
  • Construct risk models with frequency and severity distributions and apply ruin theory to insurance problems
  • Apply credibility theory and decision theory to insurance problems

Assessment tasks

  • Assignment
  • Final exam
  • Class Test

Changes since First Published

Date Description
02/03/2017 The class test will be conducted in the lecture on Monday 10 April at 8:30am.
23/02/2017 Professor David Pitt's consultation hours are Wednesdays 3pm-4pm during teaching weeks.
07/02/2017 The class test covers the lecture content in Week 1 to Week 5. Students will have 75 minutes to complete the test.