LFU:online

The objective of this course is to teach students quantitative methods in portfolio management focussing on (i) the statistics of asset allocation, (ii) classical asset allocation and advanced topics including (iii) accounting for estimation risk.

After completing this course, students shall be able to

• understand the holistic quantitative approach for portfolio management,

• apply and solve portfolio optimization problems in Matlab,

• get an idea of ‘state of the art’ methods in practice and

• critically assess the strengths and weaknesses as well as pitfalls in practical applications.

i Introduction

– Review of basic concepts, introduction to Matlab, P versus Q, 10 step checklist (Meucci, 2011);

ii Univariate and multivariate statistics

– Distributions taxonomy, representation (pdf, cdf, cf, quantiles), location, dispersion, dependence, Copulas;

P1 Market invariants

– Finding invariants in markets, applications and tests, advanced dynamics: autocorrelation, long memory, volatility clustering;

P2 Estimation

– Estimating the distribution of market invariants: Nonparametric, parametric, shrinkage, robustness, practical tips, bias versus efficiency;

P3 Projection

– How to project invariants to the investment horizon, square root of time rule;

P4 Pricing

– From invariants to prices, linear factor models;

P5 Aggregation

– How to generate the P&L distribution for a portfolio with multiple securities;

P6 Attribution

– Decompose the projected portfolio P&L linearly into a set of relevant risk factors;

P7 Evaluation

– Satisfaction, utility based, VaR, CVaR, constraints, stress test;

P8 Optimization

– Classical Mean-Variance (Markowitz), pitfalls, Bayesian, Black-Litterman, Resampled, Robust, Robust Bayesian;

P9 Execution

P10 Ex-Post Analysis

Lecture, exercises in Matlab, short presentations, case study, discussions

Case study

Main reference:

Meucci (2010): Risk and Asset Allocation, Springer.

Articles posted on OLAT

Optional:

Campbell/Lo/McKinlay (1996): The Econometrics of Financial Markets, Princeton.

Fabozzi/Kolm/Pachamanova/Focardi (2007): Robust Portfolio Optimization and Management, Wiley.

McDonnell (2010): Optimal Portfolio Modeling, Wiley.

Chincarini/Kim (2006): Quantitative Equity Portfolio Management, McGraw-Hill.

Linear algebra, matrix notation/manipulation, multivariate calculus and basic statistics/econometrics.