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ECONOMIC AND FINANCIAL STATISTICS Single discipline educational activity
Course Sheet Academic Year of enrolment:
Professor and Collaborators:
Hours of classroom activity:
Prerequisites:
Elementary notions of inferential and descriptive statistics.
Objectives
Contents The course relates to two modules. The first one contains a discussion of the stochastic behavior of financial markets. The second one deals with sampling methods from finite populations.
Extended Syllabus Module 1: Statistical analysis of financial markets
. Financial data feeds
. Mark to Market evaluations
. Return measures
. Gaussian and Log-Normal models
. Moments of linear transformations
. Volatility
. Value at Risk measures
.. Delta-Normal VaR
.. RiskMetrics VaR
.. Incremental and Component VaR
. Financial data analytics with R/C#
Module 2: Sampling Theory
. Sampling designs
.. First and second order inclusion probabilities
.. Simple random sampling
. Sampling statistics
.. Horvitz-Thompson estimators
. Sampling strategies
.. Total estimation in a given population
.. Mean estimation in a given population
Recommended Bibliography Lafratta G. (2004), Statistical Methods for the Analysis of Financial Markets, in Italian, Franco Angeli, Milano.
Lecture notes on sampling theory, in Italian.
Methods of Provision
Teaching Methods The lectures will be held by the teacher in the form of frontal classes, which will revolve around theoretical topics. Experts in financial analytics or survey methodology might occasionally participate.
Evaluation methods Verification of learning:
Learning verification is based on an examination consisting of two sets of questions: the first set, composed by 2/3 of the overall questions, regarding the statistical analysis of financial markets, and the second one focusing on sampling theory.
The final grade is based on a 30-point scale.
In the formulation of the final judgment, the following evaluation criteria will be applied: • Failure to pass the exam: the candidate does not achieve any of the results described in points A-E of the section dedicated to "Expected learning outcomes". • From 18 to 21: Sufficient level. The candidate achieves, in particular, the learning outcomes described in point A. • From 22 to 24: Fully sufficient level. The candidate achieves, in particular, the learning outcomes described in points A and B. • From 25 to 26: Good level. The candidate achieves the learning outcomes referred to in points A-C. • From 27 to 29: Very good level. The candidate achieves the learning outcomes referred to in points A-D. • From 30 to 30 laude: Excellent level. The candidate fully achieves all expected learning outcomes.
Contacts/More Information Students are strongly encouraged to attend the lessons.