Modelling Financial Risk

Course Outline

In current market conditions a rigorous approach to risk management is essential. This programme applies some of the latest econometric and data handling techniques to practical problems faced daily by organisations operating in the capital markets. The course is highly relevant to anyone analysing or interpreting financial market data.

Who The Course is For

• Traders
• Risk Managers
• Strategists
• Consultants

• Middle and Senior Managers

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Prior Knowledge

Basic knowledge of Data Analysis for Risk Management.

This program is eligible for 24 Continuing Education credit hours from the CFA Institute. If you are a CFA Institute member, CE credit for your participation in this program will be automatically recorded in your CE Diary.

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Day One

Basic Building Blocks: Volatility Modelling and Random Number Generation

• Characteristics of financial data
• QQ Plots
• Simple volatility models
• Limitations of simple volatility models
• Introduction to GARCH models
• Complex distributions
• Acceptance-Rejection approach to random number generation

Workshop: Generating numbers from complex distributions

GARCH Modelling

• Alternative GARCH models
• Interpretation of GARCH models
• Forecasting using GARCH models
• Maximum likelihood estimation under normal distribution
• Maximum likelihood estimation under t-distribution
• Simulating GARCH models

Workshop: Estimating GARCH parameters using Maximum likelihood estimation

Day Two

Correlation modelling

• Variance-covariance and correlation
• Different interpretation of correlation
• Difficulties with interpreting correlation
• Modelling time varying covariance
• Modelling time varying correlation
• Estimating parameters in covariance and correlation models

Workshop: Measures of association and correlation modelling

Risk Management for Non-Linear Products

• Non-linear VaR
• Risk neutral valuation
• Option Delta
• Option Gamma
• Delta Gamma approach
• Pitfall in the Delta Gamma approach

Workshop: Value at Risk for options using Delta Gamma Approach

Day Three

Limitations of VaR - Alternative ways to measure risk

• Limitations of VaR approach to modelling risk
• Desirable properties of ideal risk measures
• Expected Shortfall
• Risk Aversion functions
• Spectral Risk Measures
• Estimating Spectral Risk Measures

Workshop: Comparison of Expected Shortfall with VaR

Testing the Results - VaR Simulation, Backtesting & Stress Testing

• Historical simulation
• Weighted historical simulation
• Monte Carlo simulation and filtered historical simulation
• Backtesting VaR

Workshop: VaR simulation and backtesting