The course covers all aspects of quantitative risk and portfolio management from the foundations to the newest developments.

Statistics: multivariate distributions, copulas, location-dispersion ellipsoid, correlation and other measures of co-dependence;

Multivariate estimation: non-parametric, maximum-likelihood under thick tails, shrinkage, robust, Bayesian, extreme value theory;

Market modeling: quest for invariance in different markets, advanced dynamics, factor models, principal component analysis;

Pricing: FFT projection to horizon, delta-gamma approximation, full Monte Carlo;

Portfolio evaluation: stoch. dominance, satisfaction, utility/certainty equivalent;

Risk management: value at risk, expected shortfall, coherent measures, risk decomposition in elliptical and generic markets;

Classical portfolio management: trading/prospect theory, total return management, benchmark allocation, mean-variance and pitfalls;

Advanced portfolio management: mean-CVaR, mean-VaR, Black-Litterman and beyond, copula opinion pooling, Bayesian, robust cone programming;

Liquidity: transaction costs, optimal execution, algorithmic trading

The most advanced statistical and optimization techniques are introduced and thoroughly discussed by means of live MATLAB® simulations, intuitive geometrical representations, figures and plenty of examples.

Audience

Buy-side practitioners (portfolio managers and risk managers with solid quantitative background) will deepen and broaden their understanding of the recipes they implement everyday and will learn the most cutting-edge techniques.

Academics and sell-side practitioners (traders, financial engineers, quantitative analysts, research teams) will understand the big-picture and the details of buy-side finance in a quantitative language to them familiar.