The aim of this course is to introduce students to the econometric models for financial markets and their application to modelling and forecasting data from financial time series. The course discusses the empirical analysis of financial models (CAPM, Fama-French) and the empirical assessment of portfolio efficiency. It also pays special attention to modelling and forecasting of returns and volatility.
At the end of the course the student is expected to (a) have solid knowledge of the basic topics in financial econometrics; (b) understand and use concepts and expressions commonly used in the econometric analysis of financial markets; (c) perform empirical applications using financial data and econometric techniques; (d) interpret results from empirical applications developed by others.
Dual teaching (in presence and remotely)
b. Statistics and algebra recap
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
b. Hypothesis testing: t and F tests; RESET test; White test
c. Britten-Jones portfolio test
4. Market equilibrium
a. Capital Asset Pricing Model and equilibrium returns
b. Empirical assessment and extensions (Fama-MacBeth and APT models)
5. Model selection
a. Fit of the model to the data
b. Variable selection (Stepwise selection; Ridge and LASSO regression)
6. Models for financial time series
a. AR, MA and ARMA models to estimate returns
b. Model selection, forecast, trend and Dickey-Fuller test
c. ARCH and GARCH models to estimate volatilities
|Elton, E.J., Gruber, M.J., Brown, S.J., Goetzmann, W.N.||Teorie di Portafoglio e Analisi degli Investimenti||Apogeo||2013|
The exam is written; no oral integration is planned.
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. Students can separately reject the essay grade and the homework grade. However, the homework grade can be rejected only once.
The written essay is taken remotely, lasts one hour and thirty minutes and covers the whole program of the course. Use of handheld calculators is allowed, but use of personal notes or other teaching material is not allowed.
The homework is developed individually, and can be of two types (Homework I or Homework II). Homework I aims to develop analytical skills through personal data analysis. Homework II aims to develop critical skills with respect to empirical applications. 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 has to be delivered before taking part in the written essay; its grade grade remains valid throughout the academic year.