In this value at risk course we demonstrate how to calculate and interpret market and credit value at risk (VaR) measures. We will discuss how these measures should be incorporated into a broader risk management process. The value at risk course is conducted as a workshop in which small groups of participants acquire information and develop new skills by working together to complete a series of exercises. Many of the exercises involve ‘hands-on’ construction of value at risk measures for real market data, using Excel spreadsheets.
Value at Risk Course Objectives:
By the end of the value at risk course, participants will be able to:
- Construct and interpret value at risk measures for linear portfolios using parametric covariance (delta-normal) methods
- Show how parametric value at risk methods can be adapted to accommodate non-normal distributions for risk factors
- Construct and interpret value at risk measures for linear portfolios using historical simulation
- Discuss methods for extending daily value at risk measures to longer horizons
- Construct and interpret value at risk measures for linear portfolios using Monte Carlo simulation
- Explain why non-linear effects may cause value at risk methods to give misleading results for market risk in option portfolios and describe methods for adapting historical and Monte Carlo methods to capture this non-linearity
- Calculate and interpret conditional value at risk or estimated tail loss (ETL) measures and explain how these are related to ordinary value at risk
- Identify issues that arise in measuring value at risk for credit portfolios and discuss methods for implementing value at risk that are specific to credit portfolios
- Explain why different value at risk methods give different results and discuss strategies for identifying and limiting model risk
- Discuss the use of scenario analysis and stress testing in implementing value at risk models and show how this analysis is conducted
- Identify limitations of value at risk as a risk measure and discuss how value at risk measures should be incorporated into a broader risk management process
- Explain regulatory developments in regard to value at risk
- Analyze how value at risk is used in relation to risk capital
Prerequisites: Participants should understand simple financial concepts such as present value and the calculation of returns and have some familiarity with financial markets and instruments. They should also be comfortable with the use of basic statistical concepts such as probability distribution, mean and variance to describe possible gains or losses on portfolios. No advanced knowledge of mathematics or statistics is required.
Program Level: Foundation
Advance Preparation: None
Recommended CPE Credits: 7
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