Module: Actuarial Modelling

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-ordinator	Semester 1: Michael Marsh Semester 2: Michael Marsh Autumn: Michael Marsh
Module Teachers	Michael Marsh Mary Hall Kwok Chuen Wong
NFQ level	8	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

None

Description

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.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	28	Presentation of course material.
Laboratory	8	Practical computer labs– mixture of presentations and students working from supplied lab sheets. Four 2 hour labs.
Tutorial	10	Working from supplied tutorial sheets.
Independent Study	79	Revising 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 Assessment	25%	Examination Weight	75%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Digital Project	R lab exam	25%	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

None

Programme or List of Programmes

ACM	BSc in Actuarial Mathematics

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