Messages from the Academic Literature on Risk Management for the Trading Book
After completing this reading, you should be able to: Explain the following lessons on VaR implementation: time horizon over which VaR is estimated, the recognition of time-varying volatility in VaR risk factors, and VaR backtesting. Describe exogenous and endogenous liquidity…
VaR Mapping
After completing this reading, you should be able to: Explain the principles underlying VaR mapping, and describe the mapping process. Explain how the mapping process captures general and specific risks. Differentiate among the three methods of mapping portfolios of fixed…
Tokenization and Financial Market Inefficiencies
After completing this reading, you should be able to: Explain the process of tokenization and describe the fundamental features of tokenized assets and digital ledgers. Describe frictions and inefficiencies that can arise during different phases of an asset’s lifecycle and…
Global Financial Stability Report
After completing this reading, you should be able to: Identify and explain the key channels through which geopolitical risk influences asset prices and financial stability and discuss policy measures to address potential consequences. Analyze how global geopolitical risk events affect…
Advances in Artificial Intelligence: Implications for Capital Markets Activities
After completing this reading, you should be able to: Describe current uses of artificial intelligence (AI) and machine learning (ML) in capital markets, and potential future uses of sophisticated AI models including GenAI. Explain the implications of further adoption of…
Backtesting VaR
After completing this reading, you should be able to: Describe backtesting and exceptions and explain the importance of backtesting VaR models. Explain the significant difficulties in backtesting a VaR model. Verify a model based on exceptions or failure rates. Identify…
Market Risk Measurement and Management
1. Estimating Market Risk Measures 2. Non-Parametric Approaches 3. Parametric Approaches (II): Extreme Value 4. Backtesting VaR 5. VaR Mapping 6. Messages from the Academic Literature on Risk Management for the Trading Book 7. Some Correlation Basics: Properties, Motivation, Terminology 8. Empirical Properties of Correlation: How Do Correlations…
The Vasicek and Gauss+ Models
After completing this reading, you should be able to: Describe the structure of the Gauss+ model and discuss the implications of this structure for the model’s ability to replicate empirically observed interest rate dynamics. Compare and contrast the dynamics, features,…
Regression Hedging and Principal Component Analysis
After completing this reading, you should be able to: Explain the drawbacks to using a DV01-neutral hedge for a bond position. Describe a regression hedge and explain how it can improve a standard DV01-neutral hedge. Calculate the regression hedge adjustment…
Beyond Exceedance – Based Backtesting of Value-at-Risk Models: Methods for Back-testing the Entire Forecasting Distribution Using Probability Integral Transform
After completing this reading, you should be able to: Identify the properties of an exceedance-based backtest that indicate a VaR model is accurate, and describe how these properties are reflected in a PIT-based backtest. Explain how to derive probability integral…
