- Docente: Massimiliano Marzo
- Credits: 6
- SSD: ECON-01/A
- Language: English
- Teaching Mode: In-person learning (entirely or partially)
- Campus: Bologna
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Corso:
Second cycle degree programme (LM) in
Greening Energy Market and Finance (cod. 6693)
Also valid for Second cycle degree programme (LM) in Quantitative Finance (cod. 6692)
Second cycle degree programme (LM) in Applied Economics and Markets (cod. 6756)
Learning outcomes
Objective of the course is to identify, describe and classify climate‑related financial and non‑financial risks, and the impacts of these on the economy, society and the financial services sector; explain the role of different actors in climate change, including central banks, financial supervisory authorities, national and multilateral development banks, corporate banks, and institutional investors.
Course contents
1. Expected utility, Risk aversion measures. The Canonical portfolio model and related theorems. Risk measures and Stochastic Dominance (First and Second Order).
2.The Mean Variance Model and the Capital Asset Pricing Model (CAPM).
3.The mathematics of portfolio theory. Separation theorem. The case with and without risk free asset. The non-unicity of market portfolio. A four-moments CAPM. Extensions.
4. Factor Models and Arbitrage Pricing Theory (APT).
5. The Bayesian approach to Portfolio Theory: Priors, Posteriors. Flat, conjugates priors. Shrinkage estimator. The Jorion's portfolio model. The role of views: Theil's model. The Black and Littermann model and its variants.
6. Pitfalls of the CAPM: the role of estimation bias in portfolio theory. Accurate portfolio allocation emerging as combination of complex portfolio rules. On the equivalence between Ambiguity and Bayesian approach in portfolio theory.
7. Measuring performance of investments: the structure of an investment fund (costs, fees, Net Asset Value definition). The role of index as benchmarks. Performance attribution measures: Sharpe, Sortino, Modigliani and Modigliani, Treynor-Mazuy, Henriksson-Merton, Treynor. Pain indexes.
8.Intertemporal portfolio theory. The recursive investment problem. The pricing kernel. Three puzzles: equity premium puzzle, volatility puzzle, risk-free puzzle. Solutions to Equity premium: Epstein-Zin utility function, Habit Formation model.
9. Heteroskedastic disturbances and equity premium. The model of Bansal and Yaron (2004). Investment in the long run: intertemporal vs. myopic portfolio theory.
10. The Term Structure of Interest rates and fixed income pricing. The link between financial and real variables. The role of macroeconomic shocks in financial markets.
10. (Tentative) A continuous time approach to portfolio theory. The Hamilton-Jacobi-Bellmann equation. Cox-Ingersoll-Ross model.
The prerequisites are represented by basic knowledge of algebra and probability theory, multivariate calculus and linear algebra. All necessary analytical tools will be provided in lectures.
Readings/Bibliography
Danthine, J.P., and J. Donaldson, Intermediate financial theory, third edition, Elsevier, N.Y., 2014.
Campbell, J., Financial Decisions and Markets, Princeton University Press, 2018.
M.Marzo, Asset Management, Il Mulino, 2022 (in italian).
Additional material (slides, problem sets, past exam) will be provided during lectures and it will be published on Virtuale
Teaching methods
In presence lectures
Assessment methods
In class written exam. An optional oral exam is possible, after the written exam. It is possible to access oral exam only after passing the written exam. The oral exam can improve the grade of the written exam by no more than 4 points. In case of a bad oral exam the final grade can go further down the grade obtained in the written exam.
The evaluation grid goes as follows:
<18: failed.
18-23: sufficient.
24-27: good.
28-30: very good.
30 with laude: excellent.
The in class written exam will be two-hour long.
Teaching tools
Slides. Papers from the literature. There will be an extensive use of specific software, like Matlab. Other software, like R and Python are possible. However, Matlab is more efficient and reliable.
Office hours
See the website of Massimiliano Marzo
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.