- Class Number 3618
- Term Code 3030
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Timothy Higgins
- Dr Timothy Higgins
- Class Dates
- Class Start Date 24/02/2020
- Class End Date 05/06/2020
- Census Date 08/05/2020
- Last Date to Enrol 02/03/2020
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.
Examination Material or equipment
Both the mid-semester and final examinations will be closed book exams. Students will be permitted to bring in a non-programmable calculator and an unmarked paper based english language dictionary. A formula sheet will be provided for both exams.
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. It is recommended that students bring a laptop with them to class, with the R software language loaded on to their laptop. Information about loading and using R will be given in week 1 of lectures. R will be required for completing the assignment.
Students will be given feedback in the following forms:
- Following the quizzes, assignments and mid-semester examination, feedback will be given to the class about the general performance on the assessment pieces.
- Marked assignments will be handed back to students, and students will have an opportunity to look over their mid-semester examination script-books.
- 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.
|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||Quiz 1|
|3||Loss distributions with risk sharing - Reinsurance and policy excesses. Proportional and Excess-of-Loss reinsurance. Modelling individual claims with reinsurance.||Quiz 2|
|4||Aggregate loss distributions - Collective Risk Model. Compound Poisson, Binomial and Negative Binomial distributions. Compound distributions and reinsurance.||Quiz 3|
|5||Extreme value theory - Modelling the tails of loss distributions. Types of EVT distributions (GEV and GPD), fitting EVT distributions||Quiz 4|
|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.||Assignment available; Quiz 5|
|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.||Mid Semester Exam (Week 6 or 7); Quiz 6|
|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.||Quiz 7|
|9||Time series (cont.) - Basic time series forecasting - deterministic and stochastic. Limitations with simple univariate models and introduction to extensions for heteroscedasticity (ARCH and GARCH), and multivariate series.||Quiz 8|
|10||Machine learning - Introduction to elementary principles of machine learning. Unsupervised and supervised learning techniques.||Assignment due; Quiz 9|
|11||Machine learning (cont.) - Software for applying machine learning techniques. Examples and applications to risk modelling||Quiz 10|
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Weekly Online Quizzes||5 %||*||*||1,2,3,4,5|
|Mid Semester Exam||20 %||30/03/2020||*||1,2,3|
|Final Examination||55 %||04/06/2020||02/07/2020||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:
- 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
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.
Both the mid-semester and final examinations will be closed book exams. A formula sheet will be handed out at the start of the exams. Copies of the formula sheets for the mid-semester and final examinations will be made available through Wattle prior to the exams.
Assessment Task 1
Learning Outcomes: 1,2,3,4,5
Weekly Online Quizzes
Each week (starting week 2), online quizzes will be available covering material from the previous week. There will be 10 such quizzes. You will be required to answer a random selection of 5 questions in each quiz. Your mark on the quizzes will count for 5% of your final grade. The quizzes will open on 00:00 hrs Monday of the corresponding week and close on Sunday 23:59 of that week. Each quiz needs to be completed within 2 hours of starting it. Feedback will be available in the week following the quiz.
Assessment Task 2
Learning Outcomes: 1,2,3,4
This assessment will count for 20% of your final grade. The assignment will be made available in Week 6 and is due at 4pm on Monday, 11 May (Week 10). Data files will be provided to students, and the assignment will require answering questions based on the data. This will require use of the R programming language. More details will be provided in class when the assignment is released in Week 6. Marked assignments will be returned in Week 12.
Assessment Task 3
Learning Outcomes: 1,2,3
Mid Semester Exam
15 minute reading time; 90 minutes writing time. The mid-semester examination will count for 20% of your grade. The exam will cover material from Weeks 1 to 5 of the course. The exam will be closed book, but a formula sheet will be provided for use during the exam. Copies of the formula sheet will be made available through Wattle in the weeks prior to the examination.
The mid-semester exam will be held either in Week 6 or 7. Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Further information about the examination will be provided in class and on Wattle closer to the date of the examination, and no later than Week 5. You will be able to look through your marked mid-semester exam papers following completion of exam marking.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5
15 minute reading time; 3 hour writing time. The final exam will count for a minimum of 55% of your grade. It will cover material from all weeks of the course. The exam will be closed book, but a formula sheet will be provided for use during the exam. Copies of the formula sheet will be made available through Wattle in the weeks prior to the examination.
Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Further information about the examination will be provided in class and on Wattle closer to the date of the examination, and no later than Week 12.
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.
For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
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 in class.
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.
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
Dr Timothy Higgins