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Course 2023-2024 a.y.


Department of Finance

Course taught in English

Go to class group/s: 31

CLMG (6 credits - II sem. - OP  |  SECS-P/05)
Course Director:

Classes: 31 (II sem.)

Synchronous Blended: Lezioni erogate in modalità sincrona in aula (max 1 ora per credito online sincrona)

Suggested background knowledge

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 (both taught as compulsory courses within the MSc. Finance curriculum) are useful but the gap can be easily recovered with some individual study efforts.

Mission & Content Summary

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. Special emphasis is devoted to modern techniques in asset pricing and asset management and to their interaction.


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)
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

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.

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.)
  • Individual assignments

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
  • Written individual exam (traditional/online)
  •     x
  • Individual assignment (report, exercise, presentation, project work etc.)
  •     x

    Teaching materials

    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.

    Last change 12/12/2023 20:06