Description
Objectives
1. Reach robust knowledge of probabilistic theory and decision analysis. 2. Achieve solid knowledge of qualitative and quantitative risk modeling; 3. Identify structured risk management methodologies for organizations and know the competitive advantages derived from risk management; 4. Apprehend the concepts of risk and uncertainty, subjective probabilities and Bayesian revision of probabilities; 5. Understand the specific formulations of the groups of risk, namely operational, financial, market, political and regulatory risks; 6. Perceive the risk-return duality in financial risks, understand risk measures and risk mitigation instruments; Know the methods of analysis of security and reliability risks; 7. Develop autonomous work with cases of study, use specific software and develop cross-cutting competences.
Syllabus
1. Risk management frameworks, ISO 31000 and COSO; Treatment and mitigation of risks. 2. Risk matrices, axioms, potentialities and limitations; event registration; Risk measures, extreme events, VaR and CVar; Financial risk, including Credit, Market Risk and Portfolio analysis; derivatives; 3. Notable cases of risk management; Monte Carlo simulation models with @Risk software, including correlation methods between variables; 4. Concept of subjective probability and biases; the value of the information; Assessment of risk measures of investment projects: Cash-Flow at Risk, NPV at Risk, IRR at Risk; 5. Utility functions, risk profiles; Bayesian networks with Netica software; 6. Influence diagrams and decision trees with Precision Tree software; 7. Security and reliability analysis, Fault tree, Event tree, FMEA.
Prerequisites
Knowledge of probabilities and university-level statistics.
Cross Competence Component
Cross-cutting Competencies will be developed through individual presentation analysing a scientific publication and a group work project. It is expected that this approach will develop cross-cutting competences of Critical and Innovative Thinking (e.g. creativity, strategic thinking, problem solving), Interpersonal Skills (e.g. oral presentations, communication and organizational skills, teamwork, etc.) and Information Literacy (research and information analysis). The weight of this evaluation will be 10% of the total evaluation, distributed between the group work and the presentation.
Laboratorial Component
Building risk models in @Risk software, influence diagrams and decision trees with Precision Tree software, building Bayesian networks with Netica software, introduction to ITEM ToolKit reliability and security software (Fault Tree, Event Tree, FMEA).
Programming And Computing Component
Use of @Risk, Precision Tree, Netica and ITEM ToolKit software in lecturing and in some groupwork.
Ethical Principles
All members of a group are responsible for the group's work. In any assessment, every student shall honestly disclose any help received and sources used. In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.