F71QR Quantitative Risk Analysis

Dr Giovanni Rabitti

Course co-ordinator(s): Dr Giovanni Rabitti (Edinburgh).


The aims of this course are:

  • To provide a thorough grounding in the wide range of risks that a financial institution or other enterprise might be exposed to
  • To provide an introduction to the statistical methods underpinning financial risk management
  • To teach students the different methods of assessing financial risk
  • To equip students with a variety of tools to tackle problems involving financial data

Detailed Information

Course Description: Link to Official Course Descriptor.

Pre-requisites: none.

Location: Edinburgh.

Semester: 1.



  • The concept of Enterprise Risk Management, the drivers behind it and the resulting value to organisations
  • Risk and uncertainty, different definitions
  • Direct and indirect stakeholders in an enterprise: Relevance of risk measurement and management to all stakeholders
  • Risk taxonomy and overlaps

Quantitative analysis of financial data

  • Quantifiable and non-quantifiable risks
  • Common univariate distributions, model fitting and diagnostic tests
  • Extreme value theory
  • Common multivariate distributions
  • Modelling multivariate risks using copulas
  • Different measures of correlation including tail correlation
  • Risk measures; coherent risk measures
  • Model and parameter risk
  • Backtesting

Contagion and credit risk

  • Sources of credit risk; contagion
  • Theoretical and commercial approaches to modelling credit risk

Risk management

  • Securitisation and alternative risk transfer
  • The risk management control cycle

Learning Outcomes: Subject Mastery

Understanding, Knowledge and Cognitive Skills


On completion of this course the student should be able to:

  • Demonstrate an understanding of the different reasons for measuring financial risk.
  • Describe and apply the different measures of financial risk
  • Define what is meant by a coherent measure of risk;
  • Use appropriate statistical and computational methods to determine the fatness of the tails of returns data
  • Describe and apply the main univariate and multivariate distributions to financial data
  • Describe and apply the fundamental concepts and theorems in Extreme Value Theory (EVT)
  • Describe how analysis of financial data using EVT differs from traditional statistical methods
  • Describe and apply the main statistical methods in EVT to financial data
  • Demonstrate how multivariate returns can be described using marginal distributions and copulas
  • Describe and apply the main copulas
  • Explain how the use of different copulas can affect the returns distribution on a portfolio containing two assets
  • Demonstrate a good understanding of the different sources of credit risk and credit spreads
  • Understand how ratings agencies assess risk
  • Explain the risk management control cycle
  • Describe the feedback loop in risk management
  • Define what is meant by securitization and alternative risk transfer
  • Describe different forms of risk transfer and their advantages


Scholarship, Enquiry and Research (Research-Informed Learning)

  • Use appropriate statistical software to analyse problems involving financial risk
  • Show an awareness of the different approaches to modelling and managing credit risk
  • Use an appropriate computer package to analyse financial data and solve complex problems

Learning Outcomes: Personal Abilities

Industrial, Commercial & Professional Practice

  • Show an appreciation of the interface between academic theory and industrial practice
  • Show an appreciation of the societal role of risk management in protecting the consumer and other stakeholders


Autonomy, Accountability & Working with Others

  • Demonstrate the ability to learn independently and as part of a group
  • Manage time, work to deadlines and prioritise workloads


Communication, Numeracy & ICT

  • Use an appropriate computer package to analyse financial data and solve complex problems
  • Present results in a way that demonstrates that they have understood the technical and broader issues of financial risk management

SCQF Level: 11.

Credits: 15.

Other Information

Help: If you have any problems or questions regarding the course, you are encouraged to contact the course leader.

Canvas: further information and course materials are available on Canvas