This course introduces techniques for risk modelling, with an emphasis on application to insurance portfolios and financial risks.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Describe the properties of individual loss distributions, and estimate individual loss distributions, both with and without risk sharing arrangements.
2. Describe and utilise extreme value distributions to model severity of loss.
3. Describe and utilise a variety of copulas to model financial risks.
4. Explain the concepts underlying time series models, and apply the concepts to the modelling and forecasting of financial time series.
5. Explain and apply principles of machine learning.

Research-Led Teaching

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.

Required Resources

Course and lecture notes, lecture slides, R code examples, data and other material will be made available on Wattle. There are no prescribed texts.

Recommended Resources

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.

Staff Feedback

Students will be given feedback in the following forms:

• Feedback on marked assignments will be available to students on request.
• Students will have the opportunity to speak with the lecturer and seek feedback about their individual performance in all assessment pieces.

Student Feedback

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.

Other Information

Scaling

Your raw mark for the course will be based on the marks allocated for each of your assessment items. However, your final mark for the course might differ from your raw mark for the course, due to scaling. 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.

Co-Teaching

STAT6057 shares the same lecture content with STAT3057, however these cohorts may have separate tutorials and different assessments. The different cohorts of students will also be treated separately in grading and any scaling that is applied.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Loss distributions - Introduction to financial losses. Modelling loss severity: continuous skewed distributions; parameter estimation techniques (method of moments, method of percentiles, maximum likelihood estimation); estimator precision.
2	Loss distributions (cont.) - Pearson chi-square goodness of fit testing. Generating loss distributions: functions of random variables; finite and continuous mixture distributions.
3	Loss distributions (cont.) - Modelling loss frequency: common discrete distributions; modifying zeros; parameter estimation; goodness of fit testing.
4	Loss distributions with risk sharing - Reinsurance and policy excesses. Proportional and Excess-of-Loss reinsurance. Modelling individual losses and claims with reinsurance.
5	Extreme value theory - Modelling the tails of loss distributions: risk measures (value-at-risk and tail value-at-risk); types of EVT distributions (GEV and GPD); fitting EVT distributions.	Assignment 1 due: Friday 25 March
6	Copulas - Introduction to measuring and modelling joint risks, definitions of dependence and concordance, tail dependence. Copula theory, copula families, fitting copulas.
7	Time series - Introduction and objectives of time series analysis. Introduction to univariate time series. Properties of financial time series. Stationarity, random processes, unit roots, operators.
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.	Assignment 2 due: Friday 20 May
11	Machine learning (cont.) - Introduction to artificial neural networks (ANN). Software for applying machine learning techniques. Examples and applications to risk modelling.
12	Machine learning (cont.) - Examples and applications to risk modelling. Course summary

Tutorial Registration

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 on Wattle no later than week one of the semester.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Assignment 1	10 %	25/03/2022	01/04/2022	1
Assignment 2	20 %	20/05/2022	27/05/2022	2,3,4
Final Examination	70 %	02/06/2022	30/06/2022	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

Policies

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:

• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Policy and General Information 
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure

Assessment Requirements

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 Academic Integrity . 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.

Participation

Course content delivery will take the form of a weekly pre-recorded lecture, as well as weekly on-campus lectures (recorded and available via echo360 on Wattle), and weekly tutorials delivered in hybrid format (on campus, live through scheduled Zoom sessions and as pre-recorded videos).

Examination(s)

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

Assignment 1

The details of Assignment 1 including the questions and other requirements, will be made available on Monday 14 March (Week 4). It will be due at 5pm on Friday 25 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

Assignment 2

The details of Assignment 2 including the questions and other requirements, will be made available on Monday 2 May (Week 9). It will be due at 5pm on Friday 20 May (Week 11). Marked assignments will be returned by the end of Week 12. Assignment 2 will count for 20% of your final grade for the course.

Assessment Task 3

Final Examination

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

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.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignments. Please keep a copy of the assignments for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

There are no hardcopy submissions for this course.

Late Submission

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.

Referencing Requirements

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.

Returning Assignments

Assignments marks 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.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

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