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Unit of study_

QBUS6820: Business Risk Management

Prescriptive analytics is concerned with using quantitative tools to turn data into managerial and operational decisions, in both deterministic settings and under risk. This unit introduces mathematical optimisation modelling, with applications to problems in management, logistics, economics, science and engineering. Students will learn techniques for rigorously formulating complex decision-making problems as mathematical models, state-of-the-art computational tools to solve the models, how to incorporate measures of risk into models, and how to interpret outputs of models in the relevant decision-making context. It is expected that students have a good understanding of fundamental data analytics concepts such as vectors, matrices, probability, and the Python programming language.

Code QBUS6820
Academic unit Business Analytics
Credit points 6
ECMT5001 or QBUS5001
Assumed knowledge:
Vectors, matrices, probability, Python

At the completion of this unit, you should be able to:

  • LO1. classify different types of risk and discuss how they may be addressed in practice
  • LO2. calculate value at risk and expected shortfall, and analyse risk with different types of tail behaviour
  • LO3. build models of decision choices, including the use of prospect theory to describe decisions made in practice in risky environments
  • LO4. use the tools needed for stochastic optimisation, including Monte Carlo simulation, and carry out calculations based on robust optimisation and real options
  • LO5. construct and analyse a credit scorecard.

Unit outlines

Unit outlines will be available 1 week before the first day of teaching for the relevant session.