THEORY AND PORTFOLIO MANAGEMENT
Instructional goals
The course illustrates the topics and techniques underlying the management of portfolios for intermediaries and investors operating in the stock and bond markets. The theoretical portfolio models reported in the finance books are only the starting point of the course focused, instead, on the management practice. At the end of the course the student will be able to correctly perform the different phases of the decision-making process of portfolio construction: definition of objectives, formulation of forecasts, development of investment strategies and performance measurement.
Intended learning outcomes
Students will develop knowledge of the main portfolio construction models.
Students will be able to choose amoung different asset allocation and product selection models when they will be called to apply them in activities such as property portfolio management and investment advice.
Students will be able to judge which portfolio construction model is best suited in different financial institutions.
Students will learn the asset management glossary, thus being able to discuss investment models and solutions in the broadest financial fields.
Students will be able to evaluate which portfolio construction models have the necessary characteristics in order to be used for the creation of rational and reasonable investment solutions.
Course Contents
1. The stages of Portfolio Construction:
- Strategic Asset allocation
- Tactical Asset Allocation
- Stock/Bond Selection
2. Benchmark
3. Strategic Asset allocation:
- Naive Portfolio Formation Rule
- Markowitz Model
- Modello di Markowitz: Limits
- Estimation Error
- Heuristic Techniques: Additional Constraints e Resampling(TM)
- Bayesian Techniques: Black-Litterman Model
4. Tactical Asset Allocation
5. Fund Valuation and Selection:
- Risk Measures
- Fund Management: passive versus active
- Risk Adjusted Performance Measure
-The Return Based Style Analysis
Reference Books
Pomante, U., “Asset Allocation Razionale”, Bancaria Editrice, Roma, 2008.
Teaching Methods
Lessons will take place in the computer lab
Lessons using a whiteboard, Excel files for simulations, other software, slides and online surveys.
Assessment Method
The exam is oral and is structured as follows:
- the candidate will be asked three questions;
- the questions can be both theoretical and practical (exercises aimed at verifying the ability to know how to apply theoretical concepts);
- each question will be given a score of thirty and the final grade will be given by the arithmetic average of the scores, rounded to the nearest integer;
- in case the student can aspire to laude, a further question will be formulated.
The student can repeat the exam in every single exam session.
A written exam is also provided for students attending classes.
Criteria for formulating the judgment expressed out of thirty:
- Fail (<18/30): significant deficiencies and/or inaccuracies in knowledge and understanding
of the topics; limited analysis and synthesis skills, frequent generalizations.
- 18-20: just minimun knowledge and understanding of the topics with significant
imperfections; Sufficient analytical, synthesis and independent judgment skills.
- 21-23: Knowledge and understanding of routine topics; Correct analysis and synthesis
skills with coherent logical argumentation.
- 24-26: Fair knowledge and understanding of the topics; good analytical and synthesis
skills with rigorously expressed arguments.
- 27-29: Complete knowledge and understanding of the topics; remarkable analytical and
synthesis skills. Good independent judgement.
- 30-30L: Excellent level of knowledge and understanding of the topics. Remarkable
analytical and synthesis skills and independent judgement. Arguments expressed in an
original way.
Thesis assignment criteria
No criteria
Week 1
Introduction to portfolio construction
Benchmark / Market Index
Week 2
Risk-Return indicators
Week 3
Introduction to Strategic Asset Allocation
Näive portfolios
Week 4
Limits of the Mean-Variance Model
Week 5
Adding new constraints to the Mean-Variance Model
Infra-Group Constraints
Week 6
Resampling®
Week 7
The Black-Litterman Model
Week 8
(Follows) The Black-Litterman Model
Week 9
Combining heuristic and bayesian techiniques
Optimization end VaR
Week 10
Tactical Asset Allocation
Week 11
Active versus Passive
Fund Analysis and Valuation
Week 12
(Follows) Fund Analysis and Valuation