Advanced Methods in Quantitative Finance

A course in statistical methods for financial risk and derivatives — from Value-at-Risk and dynamic volatility/correlation models to implied-volatility surfaces and option-implied state-price densities — with hands-on estimation on real market data.

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Advanced Methods in Quantitative Finance (XFG) is a course on the statistical methods used to measure financial risk and to extract information from derivative markets. It begins with Value-at-Risk and Expected Shortfall — their theory, regulatory background, and computation via variance–covariance, historical-simulation, and Monte-Carlo methods — then turns to high-dimensional volatility and correlation modelling (multivariate GARCH, dynamic conditional correlation). The second half is devoted to options: estimating and nonparametrically smoothing implied-volatility surfaces, and recovering risk-neutral state-price densities through nonparametric regression and implied binomial trees. Throughout, methods are implemented on real market data (DJIA, DAX, VDAX).