EMPIRICAL FINANCE

After following this course, students should be able to: - Evaluate and reflect upon empirical studies using financial markets data. - Apply econometric methods in analysing prices, returns and volatilities from financial markets. - Generalise the results from empirical analyses to financial market theories. - Adopt a computational tool (MATLAB) for the implementation of econometric methods for the analysis of financial time series.

The prerequisites are: - Applied Statistics and Econometrics - Econometric Theory - MATLAB

Knowledge and understanding: The course will offer theoretical and empirical tools to analyze financial data. This course provides advanced knowledge and analytical resources that will enable students to understand and test autonomously the implications of the main financial theories and to construct efficient and robust prections of key financial variables, such as volatility. Applying knowledge and understanding: The students will be able to: • Carry out univariate and multivariate time series analysis of financial variables • Determine the fair price of various financial instruments such as derivatives • Establish the effect of macroeconmic announcements (or of other specific events) on financial prices (event studies analysis) Making judgements: We expect students to be able to analyze financial models to demonstrate a critical understanding of the scope and empirical challenges of financial theories, through their empirical assessment with the application of econometric methods to real data. Students are asked to use the software MATLAB to gain insights on the econometric methodologies and their implementation Learning skills: This course will contribute to empower learners giving them the theoretical, econometric and programming tools to autonomously study financial data and verify financial theories.

1) The econometrics of univariate and multivariate time series models 2) Volatility modeling: a) Univariate GARCH models b) Multivariate GARCH models 3) The predictability of asset returns 4) Market Microstructure and ex-post volatility modeling 5) Event Study Analysis 6) Asset pricing models: theory and empirical validation (CAPM, APT, multifactor models, CCAPM) 7) Present value relations 8) Option Pricing

Main references: - John Y. Campbell, Andrew W. Lo, Archie Craig Mackinlay, The Econometrics of Financial Markets, Princeton University Press 1996 - Christian Gourieroux and Joann Jasiak, Financial Econometrics: Problems, Models, and Methods, Princeton University Press, 2001 - Oliver Linton, Financial Econometrics: Models and Methods, Cambridge, 2019 - Specific material for the first part of the course on the econometrics of time series will be provided by the teacher

Lectures on relevant empirical issues. Students’ participation during lectures is strongly encouraged and will be considered in the final assessment. Weekly assignments require the use of MATLAB to solve empirical exercises based on real data.

Oral exam + weekly problem sets + take home assignment

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