Il corso si propone di illustrare alcuni modelli matematici che vengono utilizzati nella gestione dei portafogli finanziari.
An introduction to mathematical methods focusing on portfolio optimization. Starting from the model of asset allocation of Markowitz, the student will be introduced to classical portfolio theory, to move to allocation methods based on Value at Risk, Expected Shortfall, as well as to techniques relying on bootstrap.
Modalità didattiche
Lessons held by the referee teacher as well as cases study. The course will utilize R data analysis and statistical modeling.
Presente su Aulaweb
Yes X No ☐
Part I: Portfolio selection à la Markowitz
Returns calculation. Stylized facts: lack of correlation; Quadratic Positive Correlation; Absence of Normality. Mean-Variance Model: the case of two assets and the general case. Graphical analysis,. Implications. The separation theorem and its financial interpretation. Efficient portfolios by way of matrix algebra. The efficient frontier. The model with a risk-free asset. An outline on CAPM and market line.
Part II: Risk Measures.
A quantile-based approach. Coherent risk measures. Value-at-Risk: definition and statistical implications. Expected Shortfall: definition and statistical implications. Some tests on VaR.
Part III: Advanced Asset Allocation.
Outline of bootstrap techniques. The resampling approach by Michaud. The Black-Litterman model. Mean-variance-skewness models of asset allocation. Portfolio optimization based on risk measures.
The classes material will be set in the classroom at the beginning of the lessons, as well as published on Aulaweb.
Ricevimento: http://www.economia.unige.it/index.php/il-dipartimento/personale/docenti-ad-economia/163-marina-resta
MARINA RESTA (Presidente)
LUCA PERSICO
Sem: I
19 settembre - 15 dicembre 2016
MODERN PORTFOLIO THEORY
Scritto
Modalità di accertamento
Esame X scritto ☐ orale ☐ altro: The students will present and discuss a report according to the indications provided by the teacher during the lessons.
Ripetizione dell’esame
Three times in the first session. It is mandatory to sign for the examination through the web portal.
Eventuali propedeuticità e/o pre requisiti consigliati
Risultati di apprendimento previsti
Informazioni aggiuntive per gli studenti non frequentanti
The course will utilize R data analysis and statistical modeling.
Obblighi
Testi di studio