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. Financial returns (simple price difference, simple gross returns and continuously compounded returns). 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.
/ Overview of analysis of the trend of stock market prices and approaches for their identification. Moving averages (Simple, Linear Weighted and Exponential).
How to use and Interpret the Moving Averages on a Trading Chart
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.
/ Overview of analysis of the trend of stock market prices and approaches for their identification. Moving averages: Simple (SMA), Linear Weighted (LWMA) and exponential moving averages (EMA).
Bibliography
Textbook for all topics of the course: GOZZI G., Metodi Statistici per l’Analisi dei Mercati Finanziari, Libreria Medico Scientifica , Parma, Edizione 2019 (available on UNINOVA.it) 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, Chichester, England.
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
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
Classes will take place online through the use of the Teams and Elly platforms. They will be both synchronous (via Teams) and asynchronous (uploaded on the Elly page of the course). Asynchronous lessons will be dedicated to a rigorous exposition of the theory, for the acquisition of knowledge.
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.
Synchrounous classes will be mainly dedicated to the presentation of examples and exercises. Students will be encouraged to actively participate to the discussion, to develop the ability to apply knowledge and the acquisition of judgements and learning skills.
For the acquisition of technical language, the meaning of the specific terms used in the course will be illustrated.
At the beginning of the course, exercises and exam topics assigned in previous years will be uploaded to the Elly platform.
Acquisition of knowledge: oral lessons. 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
In the winter session, the summative evaluation of learning will be done through a written test evaluated on a 0-33 scale: the test will be a quiz on Elly, with the use of the Respondus software (alternativley, Teams will be used. The test, assessed on a scale of 0-33, will consists of 11 multiple choice questions of 3 points each divided as follows:
- (1) 5 questions related to all the theoretical topics learned during the course - (2) 6 questions each related to the result of solving a numerical exercise on the topics addressed during the course.
In case of return to activity in presence (face-to-face activity), the exam will consist of a written test evaluated on a 0-33 scale. During the test, the student is asked to:
1) explain the theoretical topics learned during the course, by answering three open questions (6pt each) to ascertain the ability to communicate with technical language. 2) solve exercises structured in several questions (15pt), in order to test learning ability, the capacity of applying knowledge to real problems and the judgment.
A scientific calculator may be used during the test. In addition, the student can also use a copy of the TOOLBOX FOR THE WRITTEN EXAM, divided into: 1) FORM: A summary of the main formulas; 2) TABLES of random variables: Standard normal, Student's T and Chi square. This TOOLBOX will be uploaded to Elly.
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 test. 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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2030 agenda goals for sustainable development
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