The goal of the course is to introduce students to the modern econometric and time series tools for analyzing and modeling financial returns and volatility. The course provides students with theoretical and practical knowledge of the statistical and computational skills needed for the identification, estimation and test of stochastic processes used by the financial operators to manage risk and develop investment strategies. At the end of the course, students will be able to critically compare the price dynamic of different assets and to estimate the parameters of the stochastic processes that captures the main stylized facts observed in the financial markets.
1. Financial prices and stock indexes
1.1 Price formation in financial markets
1.2 Stock indexes
- Computational methods
- Main Italian stock indexes
1.3 Correction factors for financial prices
2. Empirical Properties of Returns
2.1 Financial returns
2.2 Distributional properties of returns
2.3 Correlation properties of returns. The autocorrelation function.
3. Stochastic processes for returns
3.1 Moments: definitions and estimation
3.2 Stochastic processes for financial returns: white noise, random walk, autoregressive, moving average.
3.3 Box-Jenkins procedure: preliminary adjustments, identification, estimation and test.
4. Volatility of financial returns
4.1 Characteristics of Volatility.
4.2 Symmetric GARCH processes.
- G. M. Gallo, B. Pacini, Metodi quantitativi per i mercati finanziari, Carocci, Roma, 2013 (VII Ristampa).
- Bee M., Santi F., Finanza Quantitativa con R, Apogeo, 2013
The interaction with students will be encouraged by discussing real financial cases. Exercises will be held in the classroom by means of the freeware R statistical software and analyzing the prices of financial assets quoted in the Italian market. Face-to-face classes are possible following the general rules given by the University. During Covid-19 emergency, classes will be made available on streaming and recorded.
Attending and passing the exam "Econometria dei Mercati Finanziari" is a suggested pre-requisite.
|G. M. Gallo, B. Pacini,||Metodi quantitativi per i mercati finanziari (Edizione 7)||Carocci||2013|
Both the student's preparation will be evaluated as well as its ability to interpret and evaluate the results of the analyses based on the topics taught during the course.
The structure of the written test is as follows:
- one open question (up to 10 points, out of 30),
- two/three numerical exercises (up to 20 points, out of 30). Data will be provided for the solution of real case-studies using the basic tools learned during classes.
Exams will be in face-to-face mode. However, the remote mode is possible for all students upon request during the academic year 2020-21.
The oral test is optional and is aimed to assess the student's ability to use the R language.
Project work (optional activity)
It is carried out by groups of 3/4 students. The project will be carried out by sticking to anti-Covid rules and preference should be given to remote working. The first part of the project work must be completed and sent by e-mail to the teacher for evaluation by the deadline that will be announced by the lecturer. Students will have to demonstrate that they are able to implement all the techniques studied during course through the software R.
The final version of the project work must be sent by email to the teacher for approval at least one week before the exam.
Project work should NOT be presented in the classroom.
Project Work's evaluation will entitle you to a bonus of up to 3/30 that will be added to the grade you have earned in the written test, provided the written grade is equal to or greater than 18/30. The bonus will be valid until September 2021. The bonus can be added to the written exam evaluation only once.