20836 - ADVANCED METHODS FOR PORTFOLIO AND RISK MANAGEMENT
Department of Finance
Course taught in English
Go to class group/s: 31
CLMG (6 credits - II sem. - OP | SECS-P/05) - M (6 credits - II sem. - OP | SECS-P/05) - IM (6 credits - II sem. - OP | SECS-P/05) - MM (6 credits - II sem. - OP | SECS-P/05) - AFC (6 credits - II sem. - OP | SECS-P/05) - CLELI (6 credits - II sem. - OP | SECS-P/05) - ACME (6 credits - II sem. - OP | SECS-P/05) - DES-ESS (6 credits - II sem. - OP | SECS-P/05) - EMIT (6 credits - II sem. - OP | SECS-P/05) - GIO (6 credits - II sem. - OP | SECS-P/05) - DSBA (6 credits - II sem. - OP | SECS-P/05) - PPA (6 credits - II sem. - OP | SECS-P/05) - FIN (6 credits - II sem. - OP | SECS-P/05)
Course Director:
MASSIMO GUIDOLIN
MASSIMO GUIDOLIN
Mission & Content Summary
MISSION
This course is designed to illustrate how quant techniques are applied to finance, with particular reference to the practice of asset management under nonlinear multivariate dependencies and the measurement and the pricing of multi-asset derivatives. Market crashes and the resulting contagion effects have emphasized the limitations of linear correlations in capturing the dependence structure among asset returns for the purposes of: (1) assessing the risk of a financial institution; (2) pricing derivatives whose value depends on the interaction in the performance of different underlying assets. Hence, it is essential to learn how to model dependence beyond the correlation structure implied by multivariate normal distributions. A portion of the course is devoted to tracing a link between empirical asset pricing and portfolio sorting methods and the practice of asset management. A few sessions are devoted to the practical implementation of models in MatLab.
Although these are not formal pre-requisites, a working knowledge of the key contents of the courses in the Quantitative Finance and Derivatives I and of Financial Econometrics II are useful but the gap can be easily recovered with some individual study efforts.
CONTENT SUMMARY
1. The Instability of Correlations: Multivariate GARCH, DCC Models, and Markov Switching Models (6 hours)
2. Copulas in Risk Management (4 hours)
3. Volatility Modeling and Forecasting (6 hours)
4. Introduction and review of key concepts: Loss functions and decision theory; forecast evaluation. (3 hours)
5. Forecasting stock returns; time-varying parameter models. (3 hours)
6. The Econometrics of Network Connectedness and its Applications to Risk Management (4 hours)
7. Introduction to structured financial instruments: equity protection structures; exotic options and barriers and their applications in structuring (4 hours)
8. An Introduction to Simulations and Monte Carlo Pricing (2 hours)
9. The role of structured products in dynamic asset management (5 hours)
10. A review of key notions in static asset pricing (2 hours)
11. The cross section of stock returns (2 hours)
12. The classical anomalies/priced factors: size, value, and momentum (2 hours)
13. The “new” anomalies (priced factors?): volatility, higher-order moments, and liquidity (3 hours)
14. Exotic anomalies (factors?): implied volatility, jumps, and network effects (2 hours)
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
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
Assess the risk of financial institutions under rich and non linear dependence structure among asset returns
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
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.)
- Group assignments
DETAILS
A few sessions are devoted to the practical implementation of models in MatLab.
One track allows students to work on one group 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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x |
ATTENDING STUDENTS
20 points out of 30 will derive from a 60-minute open book, open questions exam.
11 points out of 30 from one 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.
NOT ATTENDING STUDENTS
90-minute closed-book exam on entire program.
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 (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.
Last change 11/08/2022 11:38