MATH6158 Managing Uncertainty and Risk
The module introduces some widely used quantitative approaches for characterizing uncertainty and risks in finance and management problems. The aim of the module is to introduce a number of widely used techniques for uncertainty and risk management and provide an understanding of how they can be used in practice.
Aims and Objectives
To introduce a number of widely used techniques for uncertainty and risk management and provide an understanding of how they can be used in practice.
1. Structure of uncertainty and risk: probability of a risky event, intersection risk, union risk, using sampling to reduce uncertainty – Bayesian method, portfolio risk 2. Measuring risk: Value at risk and conditional value at risk, generic risk measures, coherent risk measures, application of the risk measures to simple problems in financial investment. 3. Decision analysis: utility theory, stochastic dominance models, St. Petersburg paradox, Allais paradox 4. Stochastic modelling and analysis: Markowitz portfolio optimization model, newsvendor problem, two stage stochastic programming model for network capacity expansion, two stage stochastic programming recourse models for production planning, two stage Stakelberg leader follower model, sample average approximation, robust approaches for stochastic optimization
Learning and Teaching
Teaching and learning methods
The module will be delivered through lectures
|Total study time||150|
Resources & Reading list
Anderson EJ (2014). Business Risk Management: Models and Analysis.
Feedbacks on exam will be generic and posed on the Blackboard
|Exam (2 hours)||100%|
Repeat type: Internal & External