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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Actuarial Modelling
Module Code MS338
School School of Mathematical Sciences
Module Co-ordinatorSemester 1: Michael Marsh
Semester 2: Michael Marsh
Autumn: Michael Marsh
Module TeachersMichael Marsh
Mary Hall
Kwok Chuen Wong
NFQ level 8 Credit Rating 5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None

MS338 aims to provide students with a grounding in survival models and their application in modelling mortality and morbidity for actuarial applications. The module covers the theory of survival models and estimation methods for mortality and morbidity rates. Mortality graduation and projection methods are introduced with practical application of the methods implemented using R.

Learning Outcomes

1. Define models of mortality and life expectancy.
2. Estimate survival models using non parametric and semi-parametric methods.
3. Estimate transition intensities for Markov mortality and morbidity models.
4. Graduate mortality data for actuarial applications.
5. Understand and implement simple mortality projection methods.

Workload Full-time hours per semester
Type Hours Description
Lecture28Presentation of course material.
Laboratory8Practical computer labs– mixture of presentations and students working from supplied lab sheets. Four 2 hour labs.
Tutorial10Working from supplied tutorial sheets.
Independent Study79Revising coursework, solving tutorial and lab sheets.
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Concept of survival modelling
Lifetime and failure time; distributions and density functions of lifetime, survival function and the force of mortality and probabilities; laws of mortality; curtate and complete future lifetimes [CS2 – 4.1]

Non-parametric estimation procedures for lifetime distributions
Estimation methodologies - Kaplan-Meier estimate; Nelson-Aalen estimate; Cox PH model. [CS2 – 4.2]

Maximum likelihood estimators for and estimation of the transition intensities in models of transfers between states
Derive the Kolmogorov equations for a Markov Jump Processes / General Markov Model and solve Kolmogorov equations to obtain explicit expressions for the key probabilities associated with the process. [CS2 – 4.3, 4.4]

Methods of Actuarial Graduation
Statistical tests for comparison with a standard table; reasons for graduation and desirable properties; test for smoothness; the process of graduation using different method e.g., spline functions; comparison of crude and graduated estimates; allowance for duplicate policies; and comparison of crude estimates with a standard table or with graduated rates. [CS2 – 4.5]

Mortality Projections
Mortality improvement trends; simple mortality projections methods – Lee-Carter, APC and P-spline methods; implementation of projection models using R. [CS2 – 4.6]

Assessment Breakdown
Continuous Assessment25% Examination Weight75%
Course Work Breakdown
TypeDescription% of totalAssessment Date
Digital ProjectR lab exam25%n/a
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
This module is category 1
Indicative Reading List

  • Acted: 0, CS2 Combined Materials Pack,
Other Resources

Programme or List of Programmes
ACMBSc in Actuarial Mathematics

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