- Class Number 3290
- Term Code 3130
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Timothy Higgins
- Dr Timothy Higgins
- Class Dates
- Class Start Date 22/02/2021
- Class End Date 28/05/2021
- Census Date 31/03/2021
- Last Date to Enrol 01/03/2021
This course introduces techniques for risk modelling, with an emphasis on application to insurance portfolios and financial risks.
Upon successful completion, students will have the knowledge and skills to:Upon successful completion of the requirements for this course, students will be able to:
- Describe the properties of loss distributions in a variety of contexts, and estimate individual and compound loss distributions, both with and without risk sharing arrangements.
- Describe and utilise extreme value distributions to model severity of loss.
- Describe and apply a variety of copulas to model financial risks.
- Explain the concepts underlying time series models, and apply the concepts to the modelling and forecasting of financial time series.
- Explain and apply principles of machine learning.
The course convener has 25 years of professional practice and has undertaken research in statistical and actuarial topic areas. Lectures in the course will be informed by practical examples.
Lecture notes, lecture slides, R code examples, and other material will be made available on Wattle. There are no prescribed texts.
The R programming language will be used extensively throughout the course. Students will require access to a laptop or desktop computer with the R software language loaded. Information about loading and using R will be given in week 1 of lectures. R will be required for completing the assignments.
Students will be given feedback in the following forms:
- Feedback will be given to the class about the general performance on each of the assignments.
- Marked assignments will be returned to students.
- Students will have the opportunity to speak with the lecturer and seek feedback about their individual performance in all assessment pieces.
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
Your final mark for the course will be based on the raw marks allocated for each of your assessment items. However, your final mark may not be the same number as produced by
that formula, as marks may be scaled. Any scaling applied will preserve the rank order of raw marks (i.e. if your raw mark exceeds that of another student, then your scaled mark
will exceed the scaled mark of that student) and may be either up or down.
Exemption from Actuarial Professional examination
The Australian National University is accredited by the Actuaries Institute to provide students with exemptions from the Part I professional examinations of the Institute.
Exemptions are recommended subject to obtaining sufficiently high grades in designated courses. The standard required by the Actuaries Institute for an exemption will be upheld and thus no quota applies to the percentage of students receiving each grade in this course.
|Week/Session||Summary of Activities||Assessment|
|1||Loss distributions - Introduction to modelling individual losses. Exponential distribution; parameter estimation techniques: method of moments, method of percentiles, maximum likelihood estimation. Estimator precision. Pearson chi-square goodness of fit testing|
|2||Loss distributions (cont.) - Skewed distributions: Gamma, log-normal, Weibull. Mixture distributions and claim number/frequency distributions|
|3||Loss distributions with risk sharing - Reinsurance and policy excesses. Proportional and Excess-of-Loss reinsurance. Modelling individual claims with reinsurance.|
|4||Aggregate loss distributions - Collective Risk Model. Compound Poisson, Binomial and Negative Binomial distributions. Compound distributions and reinsurance.|
|5||Extreme value theory - Modelling the tails of loss distributions. Types of EVT distributions (GEV and GPD), fitting EVT distributions||Assignment 1 due: Friday 19 March|
|6||Copulas - Introduction to measuring and modelling joint risks, definitions of dependence and concordance, tail dependence. Copula theory, copula families, and fitting copulas to model risk dependency.|
|7||Time series - Introduction and objectives of time series analysis. Introduction to univariate time series. Properties of financial time series. Stationarity, random processes (including random walks), unit roots, operators.||Assignment 2 due: Monday 19 April|
|8||Time series (cont.) - AR, MA, ARMA and ARIMA processes. Model selection and diagnostics - identifying unit roots, correlograms, fitting models using software, residual tests. Application to financial returns and losses.|
|9||Time series (cont.) - Basic time series forecasting. Limitations with simple univariate models and introduction to extensions for heteroscedasticity (ARCH and GARCH), and multivariate series.|
|10||Machine learning - Introduction to elementary principles of machine learning. Unsupervised and supervised learning techniques. Introduction to artificial neural networks (ANN).||Assignment 3 due: Friday 14 May|
|11||Machine learning (cont.) - Software for applying ANN. Examples and applications to risk modelling.|
Tutorials will be available on campus, live through scheduled Zoom sessions and as pre-recorded videos. Information regarding enrolments for these options will be provided during O-week, prior to the start of the semester.
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Assignment 1||10 %||19/03/2021||26/03/2021||1|
|Assignment 2||10 %||19/04/2021||30/04/2021||2,3|
|Assignment 3||10 %||14/05/2021||21/05/2021||4|
|Final Examination||70 %||03/06/2021||01/07/2021||1,2,3,4,5|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Course content delivery will take form of pre-recorded weekly lectures (available via echo360 on Wattle), pre-recorded weekly workshops, and drop-in sessions (on campus, live through scheduled Zoom sessions).
Centrally scheduled examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information.
Assessment Task 1
Learning Outcomes: 1
The details of Assignment 1 including the questions and other requirements, will be made available on Monday 8 March (Week 4). It will be due at 5pm on Friday 19 March (Week 5). Marked assignments will be returned by the end of Week 6. Assignment 1 will count for 10% of your final grade for the course.
Assessment Task 2
Learning Outcomes: 2,3
The details of Assignment 2 including the questions and other requirements, will be made available on Friday 2 April (Week 6). It will be due at 5pm on Monday 19 April (Week 7). Marked assignments will be returned by the end of Week 8. Assignment 2 will count for 10% of your final grade for the course.
Assessment Task 3
Learning Outcomes: 4
The details of Assignment 3 including the questions and other requirements, will be made available on Monday 3 May (Week 9). It will be due at 5pm on Friday 14 May (Week 10). Marked assignments will be returned by the end of Week 12. Assignment 3 will count for 10% of your final grade for the course.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5
The final exam will count for 70% of your final grade and will be held in the exam period. It will cover material from all weeks of the course. Further information about the examination will be provided on Wattle no later than the end of week 10 of the semester.
Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.
The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.
The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.
You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.
There are no hardcopy submissions for this course.
No submission of assignments without an extension after the due date will be permitted. If an assignment is not submitted by the due date, a mark of 0 will be awarded.
Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
Assignments will be returned via Wattle.
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Resubmission of Assignments
Students will not be permitted to resubmit assignments.
Distribution of grades policy
Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.
Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
Support for students
The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Income contingent loans, superannuation and retirement income policy, microsimulation modelling
Dr Timothy Higgins