Financial econometrics: program (Giovanni Millo) (see also the Syllabus)

Scope and purpose of Econometrics. Econometrics vs. Financial Econometrics. Types of data (cross-sections vs. time series, panel data).

Simple linear regression. Regression vs. correlation. Assumptions of the classical linear model. Properties of the errors. Derivation of the OLS estimator. Precision and standard errors.

Introduction to statistical inference. Testing in the context of the classical linear model. The t-ratio. Example: the CAPM model; testing hypotheses on beta, Jensen's Alpha.

Generalization to multiple regressors. The OLS estimator in matrix form: derivation of the estimator and of its covariance matrix. Examples: hedonic house pricing and the APT model.

Multiple hypothesis testing: the F-test. Goodness of fit statistics and their relation to the F-test. Specification analysis: encompassing models and tests of non-nested hypotheses. Omitted and redundant regressors.

Violations of the classical hypotheses: diagnostic testing for heteroskedasticity and for correlation; testing for normality and for the wrong functional form. Parameter stability: testing for breakpoints; dummy variables. Dynamic regression models and conditions for their consistency.


With reference to Brooks, Introductory Econometrics for Finance, III Ed. (Cambridge),

Ch 1 all but 1.7, 1.8

Ch 2 all but 2.3.6, 2.3.7

Ch 3 all but 3.5, 3.13

Ch 4 all but 4.11, A.4.2

Ch 5 all but 5.13