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Further Statistics for Actuarial Science - MAN00065H

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• Department: The York Management School
• Module co-ordinator: Dr. Sule Sahin
• Credit value: 20 credits
• Credit level: H
• Academic year of delivery: 2023-24

Module summary

The aim of the module is to expose students to a number of advanced statistical topics that are used in actuarial science and quantitative risk management, including Bayesian inferential procedures, credibility theory, extreme value theory, the modelling of dependent risks and machine learning

Module will run

Occurrence Teaching period
A Semester 1 2023-24

Module aims

The aim of the module is to expose students to a number of advanced statistical topics that are used in actuarial science and are part of the professional syllabus, including generalised linear models (GLMs), machine learning, extreme value theory, the modelling of dependent risks and mortality projection models.

Module learning outcomes

After successful completion the student is able to:

Subject content

• explain the main theory and concepts of generalised linear models (GLMs);

• apply GLMs to data and demonstrate knowledge of their importance in actuarial applications;

• demonstrate knowledge of the main concepts of machine learning and explain their relevance to actuarial science;

• demonstrate understanding of the main ideas of extreme value theory and apply these to actuarial loss modelling problems;

• explain how dependence may be modelled at a deeper level than correlation and apply copulas to dependence modelling problems;

• apply mortality projection models to data including the Lee-Carter model

• present statistical analyses in a logical, rigorous, and concise way.

• strict logical reasoning from assumptions to conclusion;

• critically assess assumptions necessary to draw certain conclusions.

Module content

Syllabus:

• Generalised linear models (GLMs)

• Introduction to machine learning

• Extreme value theory (EVT)

• Copulas and dependence

• Mortality projection

Assessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Closed exam : Closed Examination
2.5 hours 70
Essay/coursework
Coursework : Case study
N/A 30

None

Reassessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Closed exam : Closed Examination
2.5 hours 70
Essay/coursework
Essay: Case Study Essay : Case study Essay : Case study Essay : Case study
N/A 30

Module feedback

Students will receive feedback within three weeks of the hand-in problem sets. The feedback will be handed to students personally and takes the form of comments and suggestions for improvement written on the handed in work.