This lesson provides an in-depth examination of market risk measurement and management. It covers the core concepts of Value at Risk (VaR), historical simulation, variance-covariance approaches, and the limitations of VaR, as taught in leading programs at NYU Stern and UC Irvine .

• Definition of Market Risk: Market risk is the risk of losses resulting from adverse movements in market prices, including equity prices, interest rates, foreign exchange rates, and commodity prices . The course covers measurement techniques for different types of financial risks (equity, fixed income, currency, commodity) and instruments .

• Value at Risk (VaR): Value-at-Risk is a key tool for measuring market risk, providing a quantitative estimate of the maximum potential loss over a specified time horizon at a given confidence level . Tools covered include duration, portfolio beta, factor sensitivities, and portfolio distribution analysis . The VaR methodology examines different approaches: historical simulation, variance-covariance, and Monte Carlo simulation .

• Risk Analytics and Portfolio Management: Beyond VaR, the course covers risk analytics and their practical use in the fund management industry. After a review of theoretical and statistical concepts underlying portfolio management, the focus is on risk analytics, tracking error (ex-ante and ex-post), and tracking error decomposition, along with its usefulness in active portfolio management .

• Volatility and Correlation Modeling: Volatility is one of the most fascinating aspects of financial market prices. Tools covered include how to measure and forecast financial volatility using ARCH/GARCH models, exponential smoothing, and historical volatilities. These tools are then used to analyze alternative approaches to calculating Value at Risk . The multi-asset problem is also addressed, discussing traditional and new approaches to measuring and forecasting correlations .