First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
STATISTICAL SCIENCES
Course unit
COMPUTATIONAL FINANCE
SCP4063078, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
STATISTICAL SCIENCES
SS1736, Degree course structure A.Y. 2014/15, A.Y. 2017/18
N0
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination COMPUTATIONAL FINANCE
Website of the academic structure http://scienzestatistiche.scienze.unipd.it/2017/laurea_magistrale
Department of reference Department of Statistical Sciences
Mandatory attendance No
Language of instruction English
Branch PADOVA

Lecturers
Teacher in charge MASSIMILIANO CAPORIN SECS-P/05

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
ECO2045306 COMPUTATIONAL FINANCE MASSIMILIANO CAPORIN EC1935

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines SECS-P/05 Econometrics 9.0

Mode of delivery (when and how)
Period First semester
Year 1st Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Laboratory 6.5 46 116.5 No turn
Lecture 2.5 18 44.5 No turn

Calendar
Start of activities 02/10/2017
End of activities 19/01/2018

Syllabus
Prerequisites: Elements of Economics and Mathematics of Financial Markets, elements of Statistics and Econometrics.
Target skills and knowledge: The course, based on two modules, aims at providing to the students the ability to address computational problems and issues in the broad area of finance. Emphasis will be given to the asset allocation framework. A the end of the course students will become advanced users of a statistical software enabling them to formalize and solve the computational problem related to an empirical finance question. The main module of the course will cover the formalization of computational problems into a statistical package.

The minor introductory module (first 10-12 lectures) will focus on an introduction to the financial economic theories and models needed to understand the main quantitative module.
Examination methods: The exam will be given in the form of a group homework. Each group (a team), will receive, at a beginning of the course (groups will be formed within the first two weeks of lectures), a list of tasks pointing at computational finance questions. Each team will have to coordinate activities, inducing team members to interact. During the exam session, each team will show results in the form of a presentation (PowerPoint-like). Each team member must have full knowledge of the presentation and of the analyses performed by the team and of the main findings.
Assessment criteria: The evaluation of the group homework will be based on the following criterias:
- presence of appropriate answers to the various tasks assigned to the team;
- appropriateness of the quantitative tools adopted by the team;
- interpretation/economic intuition of the results obtained;
- interaction across team members.
Course unit contents: Introduction (minor module)
- Introduction to financial instruments and markets;
- Investment choices under uncertainty and the approach of Markowitz;
- Market equilibrium, CAPM and APT, and market efficiency.

Main module:
1. The formalization of computational problems into a statistical package
2. Asset Allocation: from the approach of Markowitz to Risk Budgeting
3. Backtesting and performance evaluation
4. Introduction to Market Risk Management

The program might be subject to changes depending on a number of elements including: the interest of the students and their ability to solve computational problems with the statistical sowftare; the occurrence of particular events in the financial markets. Changes to the program content will affect the list of tasks included in the team work.
Planned learning activities and teaching methods: Theoretical lectures and empirical computer sessions.
Additional notes about suggested reading: Lecture notes will be distributed to students
Computer sessions and example codes will also be made available as well as the data sets used.
Textbooks (and optional supplementary readings)
  • Hull, J.C., Options, Futures and other derivatives. --: Prentice Hall, --. E' disponibile anche una versione in Italiano Cerca nel catalogo
  • Roncalli, T., Introduction to risk parity and budgeting. --: Chapman & Hall, --. Cerca nel catalogo
  • Bodie, Z., Kane, A. and Marcus, A.J., Investments. --: McGraw Hill, --. Cerca nel catalogo
  • Hull, J.C., Risk management and financial institutions. --: Wiley Finance, --. E' disponibile anche una versione in Italiano Cerca nel catalogo
  • Barucci, E., Marsala, C., Nencini, M., and Sgarra, C., Ingegneria finanziaria. --: Egea, --.
  • Elton, E.J., Gruber, M.J., Brown, S.J., and Goetzmann, W.N., Modern Portfolio Theory and Investment Analysis. --: Wiley, --. E' disponibile anche una versione in Italiano