Syllabus del corso
Obiettivi formativi
L’obiettivo del corso è quello di ripercorrere e analizzare i recenti sviluppi teorici ed empirici nell'ambito del portfolio management, focalizzando in particolare l’attenzione sul tema dell’asset allocation tattica, sui principali modelli quantitativi di stock selection, valutazione delle performance e strategie d’investimento.
Il corso si configura come un insegnamento intermedio/avanzato di asset management, orientato all'applicazione pratica delle strategie di investimento precedentemente approfondite da un punto di vista teorico. In tal senso, parte delle lezioni saranno di carattere applicativo/informatico, basate sull'utilizzo del software Matlab®.
Contenuti sintetici
Il corso si compone di tre macro aree di argomenti. Una prima parte che studia i modelli più avanzati di teoria di portafoglio, quindi modelli di Asset Allocation di tipo Strategico. Una seconda parte nella quale ci si focalizza su tematiche di Equity Portfolio Management, analizzando modelli fattoriali di tipo Economico, Fondamentale e di Screening. Una terza parte che si focalizza poi sui "Trend" in atto nell'industria del risparmio gestito e quindi di strategie di investimento più specifiche.
Programma esteso
Strategic Asset Allocation
Course Introduction. The framework for Asset Management
The framework for Asset Management, Strategic Asset Allocation (Markowitz, CAPM)
Improving Strategic Asset Allocation: constrained efficient frontier
Improving Strategic Asset Allocation: resampled efficient frontier
Improving Strategic Asset Allocation: the Black and Littermann (BL) model
Quantitative Equity Portfolio Management
Introduction to Quantitative Equity Portfolio Management (QEPM)
The link between Efficient market Hypothesis (EMH) and QEPM
The APT and Multifactoer models
Economic Models a la Fama French
Fundamental Models
A special case of fundamental models: Stock Screening Models
One-off topics in Portfolio Management
Dynamic allocation models, Buy and Hold, Constant Mix and CPPI
Exchange Rate Models Basics
Alternative asset classes: currency investring
Performance Measurement: stock selection ability, market timing and portfolio polarization
Performance Measurement: performance attribution, style analisys
Matlab programming basics and models/strategies implementations
introduction to Matlab programming
The GUI, import/export of data, matrix algebra, logical statements, loops, basic plotting
Implementing a CPPI strategy
Resampling the efficient frontier
The application of the BL model
Building a simultaneus screening model
Implementing a Risk Attribution Model
Prerequisiti
Non ci sono prerequisiti formalmente richiesti per il corso, saranno però dati per scontati i concetti di base della teoria finanziaria come il CAPM, o l’efficienza di mercato, così come i principi base di valutazione dei titoli azionari e obbligazionari.
Ci si attende inoltre che gli studenti conoscano i concetti fondamentali di statistica e in particolare quelli connessi ai modelli di regressione lineare multipla. Saranno anche dati per scontati i concetti base di algebra matriciale.
Metodi didattici
Il corso viene impartito prevalentemente basato quindi su didattica frontale tradizionale. Prevede anche lo svolgimento di applicazioni e sviluppo di modelli in modalità con l'ausilio del linguaggio di programmazione Matlab®. Lo sviluppo di modelli, di cui alcuni esempi sono il modello di Black and Littermann, il Ricampionamento della frontiera efficiente, la CPPI etc.. risulta prodromico all' Assignment che viene erogato a fine corso e che rappresenta un'opportunità concreta per gli studenti di mettere a frutto e consolidare le conoscenze sviluppate durante tutto il corso.
Nello specifico il corso prevede:
14 lezioni da 3 ore svolte in modalità erogativa in presenza;
5 esercitazioni/programmazione da 3 ore svolta in modalità erogativa in presenza;
Modalità di verifica dell'apprendimento
La valutazione della preparazione distingue fra studenti che sono considerati Frequentanti e quelli Non Frequentanti.
I Frequentanti sono gli studenti che decideranno di svolgere in gruppi di 3-4 studenti l'Assigment che sarà somministrato agli studenti al termine del corso. Coloro che sceglieranno di non svolgere il lavoro di gruppo saranno considerati Non Frequentanti. L'Assignment è composto da tre esercizi che prevedono di programmare e testare strategie di asset allocation o specifiche strategie di investimento, e che potrà essere svolto durante l'estate con consegna prevista entro settembre.
Per gli studenti frequentanti il voto finale sarà la media fra la valutazione che il loro gruppo otterrà con riferimento all'assignment svolto (il cui punteggio ha una scala da 0 a 35), e la valutazione ottenuta nell'esame.
Per gli studenti non frequentanti il voto finale sarà basato solo sulla valutazione ottenuta nell'esame.
L'esame prevede una prima parte svolta sulla piattaforma EsamiOnline, basata su 15 Multiple Choice (MC) in 20 minuti e con penalità per le risposte errate, e un successivo orale, la cui valutazione parte come riferimento dal punteggio ottenuto nelle MC. Al termine delle MC gli studenti possono decidere di ritirarsi, ma non potranno farlo dopo la valutazione orale. Sebbene il programma sia il medesimo per gli studenti frequentanti e non, l'orale sarà differente, nel caso di studenti non frequentanti la valutazione orale sarà più approfondita e dattagliata.
Testi di riferimento
Il materiale del corso si basa in parte sul testo:
- Ludwig B Chincarini, Daehwan Kim, 2006, Quantitative Equity Portfolio Management, McGraw-Hill Library of Investment and Finance. I capitoli del testo rilevanti vanno dal cap.1 al 7.
Il manuale copre all’incirca il 30% degli argomenti trattati durante il corso. I restanti argomenti saranno attraverso set di slides utilizzate durante il corso e messe a disposizione degli studenti e articoli da riviste scientifiche di seguito elencati:
Deutsche bank (2006), Currency: pensions saviors? Global Market Rersearch.
Drobetz, W., 2001, How to Avoid the Pitfalls in Portfolio Optimization? Putting the Black-Litterman Approach at Work, Swiss Society for Financial Market Research, 15(1), pp. 59-75.
Harvey C., D. Achour, G. Hopkins and C. Lang, 1999, Stock Selection in Mexico, Emerging Markets Quarterly 3, Fall, pp. 38-75.
Ibbotson, R. and P. Chen, 2003, Long-Run Stock Returns: Participating in the Real Economy, Financial Analysts Journal, 59(1), pp. 89-98.
Idzorek, T., 2006, Strategic Asset Allocation and Commodities, PIMCO Research Paper.
Lazzari, V. and M. Navone, 2004, The Selection Ability of Italian Mutual Fund Managers, SDA WP N° 100.
McKinsey & Co. 2006, The Asset Management Industry in 2010, mimeo.
Miller, K., 2005a, S&P 500 Industry Group Rotation Model, Citigroup Smith Barney Quantitative Research.
Miller, K., 2005b, The Smith Barney U.S. Equity Risk Attribute Model (RAM), Citigroup Smith Barney Quantitative Research.
Pain, D. and J. Rand, 2008, Recent Developments in Portfolio Insurance, Bank of England Quarterly Bulletin.
Scherer, B., 2002, Portfolio Resampling: Review and Critique, Financial Analysts Journal, 58(6), pp. 98-109
Periodo di erogazione dell'insegnamento
Secondo semestre
Lingua di insegnamento
Italiano
Learning objectives
The objective of the course is to review and analyze recent theoretical and empirical developments in portfolio management, focusing in particular on the issue of tactical asset allocation, the main quantitative models of stock selection, performance evaluation and investment strategies.
The course is an intermediate/advanced asset management course, oriented towards the practical application of investment strategies previously investigated from a theoretical point of view. In this perspective, part of the lessons will be applicative/informatic, based on the use of Matlab® software.
Contents
The course has three main subject areas. A first part that studies the most advanced models of portfolio theory, then Strategic Asset Allocation models. The second part focuses on Equity Portfolio Management, analyzing economic, fundamental and screening models. A third part that then focuses on the current "Trends" in the asset management industry and therefore on more specific investment strategies.
Detailed program
Strategic Asset Allocation
Course Introduction. The framework for Asset Management
The framework for Asset Management, Strategic Asset Allocation (Markowitz, CAPM)
Improving Strategic Asset Allocation: constrained efficient frontier
Improving Strategic Asset Allocation: resampled efficient frontier
Improving Strategic Asset Allocation: the Black and Littermann (BL) model
Quantitative Equity Portfolio Management
Introduction to Quantitative Equity Portfolio Management (QEPM)
The link between Efficient market Hypothesis (EMH) and QEPM
The APT and Multifactoer models
Economic Models a la Fama French
Fundamental Models
A special case of fundamental models: Stock Screening Models
One-off topics in Portfolio Management
Dynamic allocation models, Buy and Hold, Constant Mix and CPPI
Exchange Rate Models Basics
Alternative asset classes: currency investring
Performance Measurement: stock selection ability, market timing and portfolio polarization
Performance Measurement: performance attribution, style analisys
Matlab programming basics and models/strategies implementations
introduction to Matlab programming
The GUI, import/export of data, matrix algebra, logical statements, loops, basic plotting
Implementing a CPPI strategy
Resampling the efficient frontier
The application of the BL model
Building a simultaneus screening model
Implementing a Risk Attribution Model
Prerequisites
There are no formal prerequisites to be met for the course, but basic concepts of financial theory such as CAPM, or market efficiency, as well as basic principles of valuation of equities and bonds will be taken for granted.
Students are also expected to know the basic concepts of statistics and in particular those related to models of multiple linear regression. The basic concepts of matrix algebra will also be taken for granted.
Teaching methods
The course is taught maynly in a traditional way, based on frontal teaching. In addition it entails the development of applications and models interactively with the aid of the Matlab® programming language. The development of models, of which some examples are the Black and Littermann model, efficient frontier Resampling, CPPI, etc., is prodromic to the Assignment that is given at the end of the course and that represents a concrete opportunity for the students to make use of and consolidate the knowledge developed throughout the course.
Specifically, the course includes:
14 lectures of 3 hours delivered in face-to-face mode;
5 exercises/programming of 3 hours delivered in face-to-face mode;
Assessment methods
The proficiency assessment distinguishes between students who are considered Attending and Non-Attending.
Attending Students are those students who will choose to complete the Assigment that will be given to students at the end of the course, working in groups of 3-4 students. Those who choose not to do the group work will be considered Non-Attending students. The Assignment consists of three exercises that require students to write matlab programs testing asset allocation strategies or specific investment strategies, and can be completed during the summer with delivery due by September.
For attending students, the final grade will be the simple average between the grade their group will earn in the assignment (the score of which has a scale from 0 to 35), and the grade obtained in the exam.
For Non-Attending students, the final grade depends only on the grade obtained in the exam.
The exam includes a first part on the Online platform, based on 15 Multiple Choice (MCs) in 20 minutes, with penalties for wrong answers, and a subsequent oral examination, the assessment of which will start, as a reference, from the score obtained in the MCs. At the end of the MCs, students may decide to withdraw, but will not be allowed to do so after the oral assessment. Although the syllabus is the same for Attending and Non-Attending students, the oral assessment will be different; in the case of Non-Attending students, the oral assessment will be more in-depth and detailed.
Textbooks and Reading Materials
The course material is based in part on the text:
- Ludwig B Chincarini, Daehwan Kim, 2006, Quantitative Equity Portfolio Management, McGraw-Hill Library of Investment and Finance.
The relevant chapters of the text range from chapter 1 to chapter 7.
The manual will cover approximately 30% of the topics discussed during the course. The remaining topics will be through sets of slides used during the course and made available to students and articles from scientific journals as listed below:
Deutsche bank (2006), Currency: pensions saviors? Global Market Rersearch.
Drobetz, W., 2001, How to Avoid the Pitfalls in Portfolio Optimization? Putting the Black-Litterman Approach at Work, Swiss Society for Financial Market Research, 15(1), pp. 59-75.
Harvey C., D. Achour, G. Hopkins and C. Lang, 1999, Stock Selection in Mexico, Emerging Markets Quarterly 3, Fall, pp. 38-75.
Ibbotson, R. and P. Chen, 2003, Long-Run Stock Returns: Participating in the Real Economy, Financial Analysts Journal, 59(1), pp. 89-98.
Idzorek, T., 2006, Strategic Asset Allocation and Commodities, PIMCO Research Paper.
Lazzari, V. and M. Navone, 2004, The Selection Ability of Italian Mutual Fund Managers, SDA WP N° 100.
McKinsey & Co. 2006, The Asset Management Industry in 2010, mimeo.
Miller, K., 2005a, S&P 500 Industry Group Rotation Model, Citigroup Smith Barney Quantitative Research.
Miller, K., 2005b, The Smith Barney U.S. Equity Risk Attribute Model (RAM), Citigroup Smith Barney Quantitative Research.
Pain, D. and J. Rand, 2008, Recent Developments in Portfolio Insurance, Bank of England Quarterly Bulletin.
Scherer, B., 2002, Portfolio Resampling: Review and Critique, Financial Analysts Journal, 58(6), pp. 98-109
Semester
Second semester
Teaching language
Italian
Scheda del corso
Staff
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Gianfranco Forte