Risk Management

Imperial College Business School

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  • from 5 days
  • online, in person

Imperial College Business School


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Who should attend

This programme is appropriate for mid to senior-level finance managers looking to expand their knowledge of risk regulation and practice. Solid quantitative skills are required.

About the course

Imperial Risk Management Programme is an intensive five-day course that challenges finance professionals to think critically and creatively about risk.

Based in London, the financial capital of the world, our experienced faculty will guide you and your international peers to predict future societal, financial, corporate and environmental risks.

Covering topics including the management of risk in finance, risk measurement, markets and financial instruments, you will learn practical ways to measure and hedge risk in your organisation. The programme blends quantitative research and intelligent risk strategies with practical case studies to broaden participants’ risk management understanding and ability.

Learning outcomes

  • Evaluate risk management frameworks and practices and apply them to industry settings
  • Critically assess risk management reports and research
  • Examine changes in risk management practices as a result of paradigm shifts in global banking, insurance and asset management
  • Analyse the mechanism of corporate governance and its critical relationship to and with risk

Programme content

Day 1

Introduction to Risk Management – The Big Picture

  • A brief history of risk management
  • Risk management – the big picture
  • Simulation of risk management under pressure – Carbon capture lab

This module will provide a big-picture overview of risk management and highlight key issues in bank and asset management risk management. It will introduce issues the key risks facing financial services companies and other corporates. The second part of the module will involve a risk management simulation in Imperial’s capture lab. The simulation will make risk management tangible as participants will need to make risk management decisions under pressure, communicate effectively within their team, their company and externally while solving the crisis at hand.

Module Outline - 1

  • Back to the Future: the only certainty is “risk” – a brief history
  • “Risk”- integral to Financial institutions’ DNA, but what does it really mean?
  • The main risks affecting financial companies and other corporates
  • People, processes, Operational risk

Module Outline - 2

  • Carbon Capture Lab simulation
  • Risk management communication and decision making under pressure
  • What finance can learn from risk management in the energy industry
  • Novel technologies, information asymmetries, and risk management

Foundations of Risk Measurement

  • Statistics for Risk: Mean, Variance, Correlation, Skewness
  • Basic rules of probability
  • Probability Distributions Useful for Risk and Financial Models.
  • Linear Regressions and Risk Modeling Fundamentals

This module offers an overview of the essential tools of statistical analysis used in the quantitative analysis of financial instruments and risk management. These tools are all used in downstream modules of the Risk Management course. The mathematical prerequisites are similar to those of a newly admitted MBA student, and prior knowledge of statistics and probability is not assumed.

Descriptive Statistics

  • Numerical descriptive measures (measures of central tendency and of dispersion)
  • The empirical rule (the central limit theorem)
  • How to relate two things (covariances and correlations)
  • Linearly related variables (mean and variance of portfolios)
  • Linear regression model
  • The p.d.f. and the c.d.f., The normal family of distributions
  • Quantiles and Value-at-risk

Day 2

Foundations of Risk Finance Theory

  • Risk and Risk Aversion
  • Portfolio Theory and Basic Portfolio Mathematics
  • Efficient Frontier
  • Introduction to CAPM
  • Multi-factor models
  • Basic Capital Structure

This module deals with two fundamental problems in finance and risk management:

  • How to allocate capital across multiple investments
  • How to evaluate and monitor portfolio risks
  • Portfolio Allocation across multiple assets: Risk/return tradeoffs
  • Optimal portfolio allocation: Expected utility maximization, efficient frontier
  • Asset liability management and liability driven investing (LDI)
  • Evaluating and monitoring risks
  • The capital asset pricing model (CAPM): A model of risks and expected returns. Performance measures and risk-adjustments. Multi-factor models.

Financial Markets and Instruments

  • Bond Pricing
  • Futures and Forwards
  • Options and Swaps
  • Recent developments in OTC and Exchange-traded Derivatives
  • How to manage interest rate risk

Bond pricing and interest rates

  • Markets and pricing methods
  • Start with the simplest securities: bonds
  • Default-free bonds: Spot rates, coupon bonds, zeros,
  • Yields and yield curves
  • Forward rates, No-arbitrage pricing
  • Motivation: bonds and interest rates are the simplest products and are the basis for all derivative pricing. Develop no-arbitrage methods for pricing, which will be extensively used to price more complicated products.

Introduction to Option and Swap Markets

  • Options contracts and markets, – Option pricing models
  • Swaps: Interest Rate Swaps
  • Case: Expand on ALM in context on Bank One Corp case study and interest rate risk management
  • How to manage currency risk (forwards, futures, currency and fx swaps)

Day 3

Market Risk Management

  • Overview of Market Risk Management
  • Risk measures for different asset classes
  • Portfolio Risk Measures
  • Value at Risk (VaR) and Expected Shortfall
  • Analytical VaR Models
  • Decision criteria and preferences for risk
  • Stylized features of asset returns
  • Risk measures: Value at Risk and Expected Shortfall examples

Analytical VaR case studies

  • Modeling the conditional distribution
  • Portfolio VaR limits
  • Risk limits in the carbon capture lab
  • Re-set provisions in agricultural insurance programs

Portfolio VaR case studies

  • Modelling dynamic correlations
  • Market and credit risk co-movement
  • Capital requirements in insurance

Market Risk Management

  • Nonparametric VaR Models
  • Monte Carlo VaR Models
  • Modeling complex portfolios
  • Backtesting and stress testing
  • Risk measures beyond market risk

Other approaches to the computation of risk measures

  • Standard, weighted, and filtered Historical Simulation
  • Monte Carlo simulation
  • Scenario analysis and stress testing
  • Modeling a “perfect storm” in asset management

Practical insights from a Chief Risk Officer in the non-financial sector

  • Managing and measuring key risks in the corporate sector
  • Quantitative risk management tools for daily decision making
  • The CRO explains how to manage and measure the key risks in the corporate sector
  • Managing reputation risk
  • How to use quantitative risk management tools for daily decision making
  • Explanation of how the risk management function informs board level decision making

Day 4

Credit Risk Management

  • Single name Credit products: Bonds, CDS
  • Market implied default probabilities and correlations
  • Firm Value Models: Merton, Black Cox and AT1P models.
  • Case study of Calibration on Lehman Brothers CDS with firm value models
  • Intensity Models: Constant, time inhomogeneous and stochastic spreads
  • Case study of Calibration of Lehman with intensity models
  • Multi-name credit products: Default Baskets and CDOs
  • Correlation and Dynamic loss models
  • CDOs and the credit crisis of 2007-2008
  • Defaultable Bonds and Credit Default Swaps (CDS)
  • Market implied default probabilities and recovery rates.

Firm Value Models

  • Merton Model and Black Cox Model.
  • AT1P model and Bond/CDS Calibration
  • Case study with Lehman Brothers CDS in 2007-2008
  • Extension to random default barrier and fraud risk

Intensity Models

  • Intensity as local default probability or credit spread
  • Analogies between survival probabilities and bonds
  • Constant, time-varying or stochastic credit spreads
  • The JCIR++ model and CDS calibration
  • Case study with Lehman Brothers CDS in 2007-2008

Multi-name Products and Models

  • Default Baskets, Credit Indices and CDOs. iTraxx and CDX pools.
  • Hints at Copula models, implied correlation and dynamic loss models
  • CDOs and the credit crisis 2007-2008. Where now?

Counterparty and Funding Risk

Introduce CVA, DVA, FVA, KVA, and XVA

  • A consistent and comprehensive framework for counterparty credit and funding risk
  • Credit valuation adjustments (CVA), Incorporating CVA into Pricing
  • Debit Valuation Adjustment (DVA) and regulatory conflict. DVA as funding benefit?
  • Closeout. First to default risk. Payout risk for CVA/DVA.
  • Value at Risk of CVA?
  • CVA for interest rate swaps, commodities, credit and equity products
  • Hints at Funding valuation Adjustments and global valuation problems
  • Funding as aggregation dependent and nonlinear. No “law of one price”
  • Capital valuation adjustment (KVA)
  • Toward XVA
  • Lessons from Historical Case Studies: Lehman Brothers and other examples
  • Implementation of counter-party and funding risk: Hedging counterparty Risk

Day 5

Practical insights from a Chief Risk Officer (CRO) in the Financial Sector

  • The CRO of a $20 billion asset management firm shares is insights about risk management
  • How to build a risk department
  • How to measure and manage operational and investment risks as well as investment compliance for a broad range of investment strategies across multiple asset classes
  • Overview of how risk management supports the growth of an asset management firm

Risk management of complex portfolios

  • Risk Factors and VaR Approximations
  • Managing risk in derivative portfolios
  • Measuring Concentration and Liquidity Risks

Risk measures beyond market risk case studies

  • Measuring the economic costs of space weather
  • Reputational risk in micro-finance/insurance programs

Operational Risk Management and Enterprise Risk Management (ERM)

  • Operational Risk Management
  • Enterprise Risk Management
  • Cybersecurity
  • ERM & Stress testing/Scenario modelling
  • Case study
  • Visualizing, forecasting and predicting risk

Risk Management and Insurance Markets

  • Insurance markets
  • Key risks
  • Risk management
  • Relevance for corporates, banks and asset managers
  • Risk premia in insurance markets
  • Principles of risk management in insurance markets
  • Lloyd’s and the London Insurance market
  • The relevance of insurance risk premia for banks, asset managers and insurance sectors.
  • Trends in insurance markets and risk management

Programmes content – Online

Week 1

Introduction to Risk and Decision Making Under Uncertainty

Understand how foresight and imagination influence risk as future uncertainty. Recognise the importance of good judgement, perception, and appreciation of risk. Understand the importance of risk appetite and of the importance of role and responsibility.

Foundations of Risk Measurement 1

Review and create a level playing field in terms of knowledge of statistics that are important for risk management. Learn essential statistical tools used in quantitative analysis of financial instruments. Understand summary statistics such as mean, variance, correlation.

Week 2

Foundations of Risk Measurement 2

Understand the basic rules of probability and measures of tail risk. Learn to apply linear regression models and risk modelling fundamentals.

Foundations of Risk Finance Theory 1

Learn from the Head of Quantitative Research of a multibillion-dollar asset management firm on how to view risk management decisions, projects or investments as a portfolio of risks with different return, risk and correlation properties. Understand portfolio theory and basic portfolio mathematics in the context of the Harvard Management Company case study. Learn how to allocate capital across multiple investments.

Week 3

Foundations of Risk Finance Theory 2

Understand the distinction between risk that can and cannot be diversified. Learn how to risk-adjust performance measures. Understand how to form return expectations and forecast returns using multi-factor models.

Financial Markets and Instruments 1

Understand the basic financial tools available for risk management. Learn to use futures, forwards, swaps and options to hedge equity, interest rate, commodity and currency risk.

Week 4

Financial Markets and Instruments 2

Understand asset-liability management (ALM) for banks, asset managers, and corporates and how to use derivatives in ALM. Learn how to use interest rate swaps for ALM via the Banc One Corporation case study. Learn financial foresight by understanding asset class dynamics and how history repeats itself through the use of case studies.

Insights from the Chief Risk Officer of an Asset Management Company

Learn from the Chief Risk Officer of a $20 billion asset management firm how to build a risk department from scratch and how to manage operational and investment risks. Understand how to manage investment compliance for a broad range of investment strategies across multiple asset classes. Understand how risk management supports the growth of an asset management firm.

Week 5

Market Risk Management 1

Understand principles of market risk management, including risk measures such as expected short-fall and Value at Risk (VaR) and how to apply them. Learn how to set risk limits via an analytical VaR study.

Market Risk Management 2

Learn nonparametric and Monte Carlo VaR models. Understand and apply scenario analysis and stress testing. Learn how to model a ‘perfect storm' in asset management.

Week 6

Risk Management of Complex Portfolios

Learn how to manage risk in complex portfolios. Understand how to manage risk in derivative portfolios, including concentration and liquidity risk. Learn how to manage 'exotic risks' such as space weather and climate change risks.

AI and Exotic Risk Management

Explore the use of some AI tools in risk management and discuss exotic risk case studies.

Week 7

Credit Risk Management

Understand how to measure and manage credit risk. Learn what credit default swaps are and how to use them. Understand default probabilities, intensity models, and multi-name products and models.

Counter-Party and Funding Risk

Understand how to manage counter-party risk. Understand how to calculate CVA, DVA, KVA and XVA. Learn practical counter-party risk lessons from the Lehman Brothers Case study.

Week 8

Risk Management and Insurance Markets

Learn from an experienced insurance executive, the principles of risk management in insurance markets. Understand risk premia in insurance markets and the functioning of the Lloyd's and London insurance market. Appreciate the importance of insurance risk premia for banks, asset managers, and insurance.

Communicating Risk

Learn how financial foresight can help inform senior board level decision-making. Understand how to manage risk through improved mapping techniques. Understand how scenario planning can contribute to better foresight and how to communicate risk effectively to different audiences.


Enrico Biffis

Summary Enrico Biffis is Associate Professor of Actuarial Finance at Imperial College Business School, a fellow of the Pensions Institute in London, and a member of the Munich Risk and Insurance Centre at LMU Munich. His areas of expertise are risk analysis and asset-liability management, with a ...

Paolo Zaffaroni

Summary   Paolo is Professor in Financial Econometrics at Imperial College Business School. He has a summa cum laude degree in economic statistics from Roma and holds a PhD  in Econometrics  from the London School of Economics. He is also  teaching at the University of Rome La Sapienza  and  has...

Robert Kosowksi

Summary Robert Kosowski is Associate Professor in the Finance Group of Imperial College Business School, Imperial College London. He is also a resea rch fellow at the Centre for Economic Policy Research (CEPR) and an associate member of the Oxford-Man Institute of Quantitative Finance at Oxford U...

Damiano Brigo

Summary Professor Damiano Brigo holds the Chair in Mathematical Finance at Imperial College, London, where he co-heads the Mathematical Finance research group and is part of the Stochastic Analysis research group.  Previous roles of Professor Brigo include: 2012-2014, Prof. Brigo held the role ...

Markus Krebsz

Seasoned Risk Specialist, Research Director, Chief Risk Officer, Board member, NED and Government advisor with 25 years experience in global financial markets, thereof 19 years in Risk. Creator/Author of the 'New Global Conduct Risk Paradigm' (GCRP, for bank/FIs - released into the public domain...

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Risk Management at Imperial College Business School

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