- Class Number 3279
- Term Code 3330
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Timothy Higgins
- Dr Timothy Higgins
- Class Dates
- Class Start Date 20/02/2023
- Class End Date 26/05/2023
- Census Date 31/03/2023
- Last Date to Enrol 27/02/2023
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:
- Describe the properties of loss models, and estimate loss models for individual risks, both with and without risk sharing arrangements and coverage modifications.
- Describe the properties of risk measures and calculate risk measures.
- Apply extreme value distributions to model severity of loss.
- Apply basic copulas to model financial risks.
- Explain the concepts underlying time series models, and apply the main concepts to the modelling and forecasting of financial time series.
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.
Course and lecture notes, lecture slides, R code examples, data 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, but will not be required for the final exam.
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.
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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.
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 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.
STAT3057 shares the same lecture content with STAT6057, 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.
|Week/Session||Summary of Activities||Assessment|
|1||Loss distributions - Introduction to financial losses. Modelling loss severity: continuous skewed distributions; parameter estimation techniques; 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 and coverage modifications - Coverage modifications, proportional and Excess-of-Loss reinsurance, policy excesses. Modelling individual claims with reinsurance. Parameter estimation with truncated or censored data.|
|5||Risk measures - Properties of coherent risk measures. Value at Risk (VaR) and Tail value at risk (TVaR).||Assignment 1 due: Friday 24 March|
|6||Extreme value theory - Modelling the tails of loss distributions; types of EVT distributions (GEV and GPD); fitting EVT distributions.|
|7||Copulas - Introduction to measuring and modelling joint risks, definitions of dependence and concordance, tail dependence. Copula theory, copula families, fitting copulas.|
|8||Time series - Introduction and objectives of time series analysis. Introduction to univariate time series. Properties of financial time series. Stationarity, random processes, unit roots.|
|9||Time series (cont.) - AR, MA, ARMA and ARIMA processes. Model selection and diagnostics - identifying unit roots, correlograms, fitting models using software, residual tests.|
|10||Time series (cont.) - Application to financial returns and losses. Time series forecasting.|
|11||Time series (cont.) - Limitations with simple univariate models and introduction to extensions for heteroscedasticity (ARCH and GARCH models) and multivariate time series.||Assignment 2 due: Friday 19 May|
Tutorials will be held weekly (starting from week 2). Tutorials will be available on campus, live through scheduled Zoom sessions and as pre-recorded videos. ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. https://www.anu.edu.au/students/program-administration/timetabling].
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Assignment 1||10 %||24/03/2023||31/03/2023||1|
|Assignment 2||20 %||19/05/2023||26/05/2023||2,3,4,5|
|Final Examination||70 %||01/06/2023||29/06/2023||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 Integrity Rule before the commencement of their course. Other key policies and guidelines include:
- Academic Integrity Policy and Procedure
- Student Assessment (Coursework) Policy and Procedure
- Special Assessment Consideration Guideline and General Information
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
- Code of practice for teaching and learning
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 Skills 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 the form of weekly on-campus lectures (recorded and available via echo360 on Wattle) as well as occasional pre-recorded lectures, and weekly tutorials delivered in hybrid format (face-to-face on campus, live through scheduled Zoom sessions and as pre-recorded videos). Attendance at lectures and tutorials, while not compulsory, is expected in line with “Code of Practice for Teaching and Learning”, clause 2 paragraph (b).
Students will be able to engage with staff via weekly zoom or face-to-face consultation with the lecturer, email consultation, tutorials, and through the Wattle discussion board which will be monitored by staff.
It is expected that there will not be any invigilation for the exam, however, further information about the examination will be provided on Wattle no later than the end of week 10 of the semester. 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 13 March (Week 4). The assignment will require written answers and calculations, and will involve the use of the R programming language for some questions. The assignment will be due at 5pm on Friday 24 March (Week 5) and submission will be via Wattle. Feedback will be provided in the form of individual marks that will be available on Wattle by the end of Week 6, along with complete solutions provided to all students. Assignment 1 will count for 10% of your final mark for the course. Assignment 1 is NOT redeemable.
Assessment Task 2
Learning Outcomes: 2,3,4,5
The details of Assignment 2 including the questions and other requirements will be made available on Monday 1 May (Week 9). The assignment will require written answers and calculations, and will involve the use of the R programming language for some questions. The assignment will be due at 5pm on Friday 19 May (Week 11) and submission will be via Wattle. Feedback will be provided in the form of individual marks that will be available on Wattle by the end of Week 12, along with complete solutions provided to all students. Assignment 2 will count for 20% of your final mark for the course. Assignment 2 is NOT redeemable.
Assessment Task 3
Learning Outcomes: 1,2,3,4,5
The final exam will count for 70% of your final mark and will be held in the exam period. It will cover material from all weeks of the course. The exam will involve short answer questions that require mathematical calculations. The exam will be open book and is expected to be approximately 3.5 hours long. It is expected that there will not be any invigilation for the exam, however, 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. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.
The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.
The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.
The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.
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.
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.
The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.
Assignment 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.
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 Access 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
Dr Timothy Higgins