20836 - ADVANCED METHODS FOR PORTFOLIO AND RISK MANAGEMENT
Department of Finance
MASSIMO GUIDOLIN
Suggested background knowledge
Mission & Content Summary
MISSION
CONTENT SUMMARY
1. Introduction and review of key concepts: Loss functions and decision theory; forecast evaluation (3 hours)
2. Forecasting stock returns; time-varying parameter models (4 hours)
3. Volatility modeling and forecasting (6 hours)
4. The instability of correlations: Multivariate GARCH, DCC models, and Markov Switching models (6 hours)
5. A review of key notions in static asset pricing (2 hours)
6. The cross section of stock returns (2 hours)
7. The classical anomalies/priced factors: size, value, and momentum (2 hours)
8. The “new” anomalies (priced factors?): volatility, higher-order moments, and liquidity (3 hours)
9. Exotic anomalies (factors?): implied volatility, jumps, and network effects (2 hours)
10. Are the old portfolio construction methods still working? The limitations of the mean-variance framework (3 hours)
11. “Smart Beta” factor investing: mapping factor exposures into asset allocations (3 hours)
12. Climate risk in asset management (3 hours)
13. The role of ESG criteria and constraints in the asset management industry (3 hours)
14. The role of structured products in dynamic asset management (6 hours)
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
Define quant techniques as applied to finance
Identify insights on the practice of asset and risk management under nonlinear multivariate dependencies
Learn how to price multi-asset derivatives
Appreciate the interaction between modern asset pricing models and asset management.
Understand the role played by climate risk and ESG considerations in applied portfolio management.
APPLYING KNOWLEDGE AND UNDERSTANDING
Connect and related quant techniques as applied to finance
Develop insights on the practice of asset and risk management under nonlinear multivariate dependencies
Analyze how to price multi-asset derivatives
Assess the risk of financial institutions under rich and non linear dependence structure among asset returns
Teaching methods
- Face-to-face lectures
- Exercises (exercises, database, software etc.)
- Individual assignments
DETAILS
A few sessions are devoted to the practical implementation of models in MatLab.
One track allows students to work on one individual assignment consisting of either the replica of an empirical paper to be agreed upon with the instructor or of an in-depth analysis of a portion of the literature related to the topics covered in the course. Precise guidelines will be made available during the course.
Assessment methods
Continuous assessment | Partial exams | General exam | |
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Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
Bali, T. G., Engle, R. F., & S., Murray (2016). Empirical Asset pricing: The Cross Section of Stock Returns. John Wiley & Sons.
Guidolin, M., and M., Pedio (2016), Essentials of Applied Portfolio Management, EGEA and Bocconi University Press (EAPM).
Guidolin, M. and M., Pedio (2018) Essentials of Time Series for Financial Applications, Academic Press.
The following textbooks may also be of some use:
Campbell, J. Y. (2017). Financial Decisions and Markets. Princeton University Press.
Wilmott P. (2007), Paul Wilmott Introduces Quantitative Finance. John Wiley & Sons.