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
Knowledge of basic descriptive and inferential statistics
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
esteso / 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: simple (SMA), linear weighted moving average(LWMA), exponential moving average (EMA).
Bibliography
Textbook for all topics of the course: GOZZI G., Strumenti Statistici per l’Analisi dei Mercati Finanziari, Libreria Medico Scientifica , Parma, Edizione 2018 and integrative teaching materials uploaded to the Elly site (http://sea.unipr.it/it).
Book for deepening:
Alexander, C. (2008), Quantitative Methods in Finance, John Wiley & Sons Ltd,
C h i c h e s t e r , E n g l a n d . h t t p : / / n p u . e d u . u a / ! e -
book/book/djvu/A/iif_kgpm_Carol_Quantitative_Methods_in_Finance.pdf.pdf
De Luca , G. (2013), Metodi statistici per le decisioni nanziarie, Università
Parthenope a.a. , 2011-2012, Napoli
http://www.economia.uniparthenope.it/modifica_docente/deluca/msdf.pdf
Gallo G.M. e Pacini B. (2002), Metodi quantitativi per i mercati finanziari, Carocci
Editore, Roma.
Di Fonzo T. e Lisi F. (2005), Serie storiche economiche. Analisi statistiche e
applicazioni, Carocci editore, Roma
Laurini F. (2012) Elementi di analisi delle serie storiche finanziarie, Libreria Medico
Scientifica , Parma
Pelagatti M.M. (2009), Statistica dei Mercati Monetari e Finanziari , Università
Milano - Bicocca.
http://www.statistica.unimib.it/utenti/p_matteo/lessons/SMMF/StatFin.pdf
Proietti T. , Econometria Applicata, Dipartimento di Scienze Statistiche, Università
d i U d i n e .
http://www.statistica.unimib.it/utenti/p_matteo/lessons/SSE/EcAppl_Dispense.pdf
Ruppert D. (2003), Statistics and Finance . An introduction, Springer, New York
Tsay, R.S. (2010), Analysis of Financial Time Series, Third Edition,Wiley, New York
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 themeaning of terms commonly used in the analysis of financial time series.
On the Elly platform will be uploaded at the
beginning of the course exercises and tests assigned in
previous years. To download the material, registration to the online
course is required.
Assessment methods and criteria
The exam is in written form.
The summative evaluation of the learning will be done through a written test evaluated on a 0-30 scale. During the test, the student is asked to: 1) present the theoretical arguments learned during the course, by answering three open questions (5pt each) to ascertain the capacity of communicate with an appropriate technical language. 2) solve exercises, structured in severel questions (15pt), in order to test learning ability, the capacty of applying knowledge to real problems, and the independence of judgment. A scientific calculator may be used during the test. The text of the test with its solution will be uploaded to Elly within a week after the test.
The result of the test will be published on Elly within 10 days after the exam.
Information about the evaluation of the global exam and the awarding of the "lode" can be found in the syllabus of the whole course
Please note that online registration for the appeal is mandatory.
Other information
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