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This lecture by the instructor covers the modeling of volatility in quantitative risk management, focusing on topics such as ARMA processes, ARCH and GARCH models, and volatility forecasting. The lecture delves into the properties and causal representation of ARMA processes, the estimation and stationarity of ARCH and GARCH models, and the fitting of these models to data. Additionally, it explores the simulation of ARCH processes, serial correlation, and the use of GARCH processes for risk-factor changes. The lecture concludes with discussions on conditional risk measurement, intraday volatility models like Garman-Klass and Garman-Klass-Yang-Zhang, and rough volatility modeling.