b. Statistics recap and introduction to the software
2. Optimal portfolio allocation
a. Mean-Variance criterion; Sharpe index
b. Efficient frontiera with and without risk-free asset; Tangency portfolio; Two-fund separation theorem
3. Ordinary Least Squares (OLS) model
a. Univariate and multivariate regressions; Marginal effects and elasticities; Goodness of fit of the model
b. Hypothesis testing: t and F tests, diagnostics
4. Market equilibrium
a. Capital Asset Pricing Model and empirical assessment
b. Multi-factor models; Fama-MacBeth tests
5. Portfolio tests
a. Return estimates (historical, equilibirum, implicit); Black-Litterman approach
b. Efficient portfolios; Robustness to return estimates; Efficiency test of Jobson-Korkie; Britten-Jones approach
6. Models for financial time series
a. AR, MA and ARMA models to estimate returns
b. ARCH and GARCH models to estimate volatilities
|Verbeek, M.||A Guide to Modern Econometrics||Wiley||2000|
|Elton, E.J., Gruber, M.J., Brown, S.J., Goetzmann, W.N.||Teorie di Portafoglio e Analisi degli Investimenti||Apogeo||2013|
The exam is made of one written essay and one individual homework; the final grade is given by the average of the grades in the essay and the homework, with 75% and 25% weights respectively. In order to pass the exam, it is necessary to obtain a grade not below 16/30 in the written essay.
The written essay is taken in a teaching room, lasts two hours and covers the whole program of the course. Use of handheld calculator, personal notes or other teaching material is not allowed.
The homework is developed individually outside the teaching rooms, and can be of two types (Homework I or Homework II). Each student can choose which type of homework to deliver, but must deliver one of them. Once the deadline for delivery of Homework I has expired, it is possible to deliver Homework II only. The homework grade remains valid throughout the academic year.
Homework I aims to develop analytical skills through personal data analysis.
Homework II aims to develop critical skills with respect to empirical applications.
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