Checking date: 24/03/2018


Course: 2018/2019

Advanced risk management
(15926)
Study: Master in Finance (261)
EPE


Coordinating teacher: PEÑA SANCHEZ DE RIVERA, JUAN IGNACIO

Department assigned to the subject: Department of Business Administration

Type: Electives
ECTS Credits: 3.0 ECTS

Course:
Semester:




Students are expected to have completed
Target Audience: This course is useful for any student in the master (she could be an Economics, Engeniering, Math, Physics or from Business Administration bachelor). The courses of Computer Science for Finance(Matlab), Financial Markets, Financial Derivatives, Risk Management and Investment should have been completed previously. The empirical exercises will be done using Matlab and only in some cases in Excel.
Competences and skills that will be acquired and learning results.
This course is designed to train the participants in managing financial risks and specially credit and operational risks using advanced methods. First the main points related with why and how should firms hedge are addressed. Then the course then focuses on credit risks and its measure (CVaR) and how to deal with it using credit derivatives. The emphasis of the course is on modelling and measuring financial risk. The course deals with credit (corporate and sovereign) and operational risks. The course draws heavily on financial theory. In addition, the disciplines of econometrics and statistics are heavily used to formulate and solve the problems faced by risk managers. PROFESSOR: Beatriz Balbas (University of Alcala)
Description of contents: programme
Chapter 1: Credit Background and Traditional Credit Instruments -Credit Debt vs Risk-Free Debt -Default and Recovery Data -Transition Matrices: calibration with Matlab -Credit Portfolio and Portfolio Risk: VaR and counterparty VaR Chapter 2: Credit Derivatives Concepts -Introduction to Credit Derivatives -CDS Product Definition and Documentation -CDS Application and Elementary Strategies -The Fundamental Credit Arbitrage ¿ Repo Cost -Default and Recovery Model Claim Amount Chapter 3: Credit Derivatives: Valuation and Risk -Deterministics Default Rate Models -Stochastic Default Rate Models: Hazard and Pseudo-Hazard Rates -Calibration to Market Data with Matlab -CDS Deal Examples -CDS/Bond Basis Trading Chapter 4: Credit Derivatives: Portfolio Products -Nth-to-default Baskets: Synthetic CDOs, Cashflow CDOs and Alternative Leverd Credit Portfolio Products -The normal Copula and Correlation -Valuation and hedging (with Matlab). Chapter 5: Introduction to Operational Risk -Definition of operational risks: -Internal risks: system failures, theft, fraud, and mistakes -External risks: weather events, accidents, and terrorism -Measuring Operational VaR
Learning activities and methodology
Students will work in teams, learning to collaborate and organize the different roles in the team. In addition, the Professor will present the main theoretical concepts using Power Point presentations just before students do the cases or exercises. In every lesson or topic, students will work in a practical exercise (similar to the case but easier) during the lesson in order to learn the main concepts and apply them to a practical problem. Every case is based on real data coming from financial markets. Students must present a report for the case 1 and 2 what provides them the ability to write profesional reports (using the same structure as an Academic paper).
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40
Basic Bibliography
  • Crouhy, M. , D. Galai and R. Mark . The Essentials of Risk Management. Wiley. 2014
  • John Hull. Options, Futures, and Other Derivatives. Pearson Prentice Hall. 2011
  • Jorion, P. . Financial Risk Manager Handbook. Wiley. . (2011) . 6th Edition

The course syllabus and the academic weekly planning may change due academic events or other reasons.