Advanced Course in Asset Management (Presentation Slides)

These presentation slides have been written for the Advanced Course in Asset Management (theory and applications) given at the University of Paris-Saclay. They contain 5 lectures (Part 1. Portfolio Optimization Part 2. Risk Budgeting Part 3. Smart Beta, Factor Investing and Alternative Risk Premia Part 4. Green and Sustainable Finance, ESG Investing and Climate Risk Part 5. Machine Learning in Asset Management) and 15 tutorial exercises. The Table of contents is the following: Part 1. Portfolio Optimization 1. Theory of portfolio optimization 1.a. The Markowitz framework 1.b. Capital asset pricing model (CAPM) 1.c. Portfolio optimization in the presence of a benchmark 1.d. Black-Litterman model 2. Practice of portfolio optimization 2.a. Covariance matrix 2.b. Expected returns 2.c. Regularization of optimized portfolios 2.d. Adding constraints 3. Tutorial exercises 3.a. Variations on the efficient frontier 3.b. Beta coefficient 3.c. Black-Litterman model Part 2. Risk Budgeting 1. The ERC portfolio 1.a. Definition 1.b. Special cases 1.c. Properties 1.d. Numerical solution 2. Extensions to risk budgeting portfolios 2.a. Definition of RB portfolios 2.b. Properties of RB portfolios 2.c. Diversification measures 2.d. Using risk factors instead of assets 3. Risk budgeting, risk premia and the risk parity strategy 3.a. Diversified funds 3.b. Risk premium 3.c. Risk parity strategies 3.d. Performance budgeting portfolios 4. Tutorial exercises 4.a. Variation on the ERC portfolio 4.b. Weight concentration of a portfolio 4.c. The optimization problem of the ERC portfolio 4.d. Risk parity funds Part 3. Smart Beta, Factor Investing and Alternative Risk Premia 1. Risk-based indexation 1.a. Capitalization-weighted indexation 1.b. Risk-based portfolios 1.c. Comparison of the four risk-based portfolios 1.d. The case of bonds 2. Factor investing 2.a. Factor investing in equities 2.b. How many risk factors? 2.c. Construction of risk factors 2.d. Risk factors in other asset classes 3. Alternative risk premia 3.a. Definition 3.b. Carry, value, momentum and liquidity 3.c. Portfolio allocation with ARP 4. Tutorial exercises 4.a. Equally-weighted portfolio 4.b. Most diversified portfolio 4.c. Computation of risk-based portfolios 4.d. Building a carry trade exposure Part 4. Green and Sustainable Finance, ESG Investing and Climate Risk 1. ESG investing 1.a. Introduction to sustainable finance 1.b. ESG scoring 1.c. Performance in the stock market 1.d. Performance in the corporate bond market 2. Climate risk 2.a. Introduction to climate risk 2.b. Climate risk modeling 2.c. Regulation of climate risk 2.d. Portfolio management with climate risk 3. Sustainable financing products 3.a. SRI Investment funds 3.b. Green bonds 3.c. Social bonds 3.d. Other sustainability-linked strategies 4. Impact investing 4.a. Definition 4.b. Sustainable development goals (SDG) 4.c. Voting policy, shareholder activism and engagement 4.d. The challenge of reporting 5. Tutorial exercises 5.a. Probability distribution of an ESG score 5.b. Enhanced ESG score & tracking error control Part 5. Machine Learning in Asset Management 1. Portfolio optimization 1.a. Standard optimization algorithms 1.b. Machine learning optimization algorithms 1.c. Application to portfolio allocation 2. Pattern learning and self-automated strategies 3. Market generators 4. Tutorial exercises 4.a. Portfolio optimization with CCD and ADMM algorithms 4.b. Regularized portfolio optimization