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Decision Theory - MAN00050H

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  • Department: The York Management School
  • Module co-ordinator: Prof. Jacco Thijssen
  • Credit value: 10 credits
  • Credit level: H
  • Academic year of delivery: 2022-23
    • See module specification for other years: 2021-22

Module summary

The aim is to introduce students to decision theory and its applications in economics, OR, finance and actuarial science.

Module will run

Occurrence Teaching period
A Autumn Term 2022-23

Module aims

The aim is to introduce students to decision theory and its applications in economics, OR, finance and actuarial science. Students are introduced to axiomatic approaches to utility, expected utility, and subjective expected utility. The module also introduces behavioural critiques to expected utility theory and modern developments, such as prospect theory and multiple-prior maxmin utility. 

Module learning outcomes

After successful completion the student is able to:

Subject content

  • demonstrate how preferences over lotteries can be represented by expected utility functions;
  • calculate measures of risk aversion and certainty equivalents of lotteries;
  • describe and assess Savage’s construction of subjective expected utility (SEU);
  • describe behavioural critiques of SEU and consequent theoretical developments;

 

Academic and graduate skills

  • present decision theoretic analyses in a logical, rigorous, and concise way.
  • strict logical reasoning from assumptions to conclusion;
  • critically assess assumptions necessary to draw certain conclusions.

Assessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Closed examination		 1.5 hours 80
Essay/coursework
Presentation		 N/A 20

Special assessment rules

None

Reassessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Closed examination		 2 hours 100

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.

Indicative reading

Gilboa, I. (2009), “Theory of Decision under Uncertainty”, Cambridge University Press.

Berger, J.O. (1985), “Statistical Decision Theory and Bayesian Analysis” (2nd ed), Springer Verlag


The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.