Learning objectives
SKILLS TO BE DEVELOPED AND LEARNING OUTCOMES EXPECTED
1) Knowledge and understanding .The course aims to provide the basic tools most suitable for the analysis of some fundamental aspects of monetary and financial market. Particular attention will be paid to time series of financial issues: exchange rates, interest rates, prices and equity returns, prices and yields of derivatives. Participation in teaching activities in conjunction with the exercises, increase the student's ability to develop, independently, that type of "statistical data" that characterizes the nature of the degree course in Economics and Finance.
2) Ability to apply knowledge and understanding . At the end of the course, the student will be able to implement in an autonomous way the statistical techniques described above. The student will have therefore developed specific skills, they are associated with critical skills for diagnostic, which are essential ingredients in building a good statistical model, with the possible assistance of the appropriate level of computer tools.
3) Making judgments .At the end of the course, the student will be able to perform independently all the considerations regarding the problems of analysis of financial time series. In addition, the student will be able to correctly interpret the results of such analyzes, even when made by other users or experts
4) Communication skills . At the end of the course, the student will be able to use appropriate technical language in communicating with the operators of financial markets. Also it should be able to summarize the statistical information of considerable size
5) Learning skills. We want to give the student the opportunity to assimilate the key results of the statistical theory and probability that form the basis of building a statistical model. At the end of the course, the student will have acquired the key concepts to be able to accurately use quantitative tools, if they become necessary in the solution of concrete problems of a financial nature
Prerequisites
- - -
Course unit content
/ Elementary theory of stochastic processes for stationary series
1. Recalls elements of probability 'for random vectors.
2. Transformation of univariate and multivariate random variables.
3. Gaussian and White Noise processes.
4. Brief introduction to non-stationary processes of type Random Walk
/ Empirical evidence of the observed time series
1. Empirical characteristics of the time series of financial returns. Formulas combinations of multi-period returns.
2. The shape of the distribution of returns. Test of symmetry, kurtosis, and normality .
3. The time dependence (linear and nonlinear) of returns. Autocorrelation function and tests of significance 'associates.
4. Autoregressive processes for stationary series of returns and transforms associated with them.
/ Overview of analysis of the trend of stock market prices and moving averages
Full programme
/ Elementary theory of stochastic processes for stationary series
1. Recalls elements of probability 'for random vectors.
2. Transformation of univariate and multivariate random variables.
3. Gaussian and White Noise processes.
4. Brief introduction to non-stationary processes of type Random Walk
/ Empirical evidence of the observed time series
1. Empirical characteristics of the time series of financial returns. Formulas combinations of multi-period returns.
2. The shape of the distribution of returns. Test of symmetry, kurtosis, and normality .
3. The time dependence (linear and nonlinear) of returns. Autocorrelation function and tests of significance 'associates.
4. Autoregressive processes for stationary series of returns and transforms associated with them.
/ Overview of analysis of the trend of stock market prices and moving averages
Bibliography
Slides on all topics of the course (available from the office of the Faculty photocopies) and supplementary teaching materials made available during the course.
Books for deepening
DE LUCA G., Metodi statistici per le decisioni finanziarie, A.A. 2011/2012, Università di Napoli Parthenope
(http://www.economia.uniparthenope.it/siti_docenti/SitoDocentiStandard/Visualizza_cartelle.asp)
GALLO G.M. e PACINI B. , Metodi quantitativi per i mercati finanziari, Carrocci Editore, Firenze, 2008.
LAURINI F., Elementi di analisi delle serie storiche finanziarie, Dipartimento di Economia, Università di Parma, 2012.
PELAGATTI M.M., Statistica dei Mercati Monetari e Finanziari , Milano ,2009. (http://www.statistica.unimib.it/utenti/p_matteo/lessons/SMMF/StatFin.pdf)
TSAY, R. , Analysis of financial time series, Wiley, New York, 2002
Teaching methods
Acquisition of knowledge: oral lessons. In the course of the lessons will be used to using Microsoft Excel and Gretl. Gretl is an acronym for Gnu Regression, Econometrics and Time-series Library. It is a software package for econometrics that is easy to use and powerful enough. Gretl is distributed as free software that can be downloaded from http://gretl.sourceforge.net and installed on your personal computer
Acquisition of the ability to apply knowledge: Tutorials
Acquisition of judgment: During the course students will be encouraged to identify strengths and weaknesses of the statistical tools.
Acquisition of learning skills: for each topic will be provided an illustration of the problem to solve and will analyze critically the solutions adopted.
Acquisition of technical language: while teaching you will learn the meaning of terms commonly used in the analysis of financial time series
Assessment methods and criteria
The exam is in written form.
Other information
- - -
