Training and Research
PhD Programme Courses/classes - 2022/2023
Advice to Young Economists
Credits: 4
Language: English
Teacher: Marco Piovesan
Behavioral and Experimental Economics
Credits: 5
Language: Italian
Teacher: Simone Quercia, Maria Vittoria Levati, Marco Piovesan
Development Economics
Credits: 5
Language: English
Teacher: Federico Perali
Finance
Credits: 5
Language: English
Teacher: Cecilia Mancini
Game Theory
Credits: 5
Language: Inglese
Teacher: Francesco De Sinopoli
Inequality
Credits: 5
Language: English
Teacher: Francesco Andreoli, Claudio Zoli
Introduction to Probability – Module II (attività formativa per la Scuola di Dottorato)
Credits: 2
Language: Italian
Teacher: Claudia Di Caterina
Introduction to Probability – Module I
Credits: 2
Language: English
Introduction to Statistical Inference
Credits: 2
Language: English
Teacher: Marco Minozzo
Macroeconomics I
Credits: 7,5
Language: English
Teacher: Tamara Fioroni, Alessia Campolmi
Mathematics
Credits: 7,5
Language: English
Teacher: Letizia Pellegrini, Alberto Peretti
Microeconomics 1
Credits: 10,5
Language: English
Teacher: Simona Fiore, Claudio Zoli, Martina Menon
Political economy
Credits: 5
Language: English
Teacher: Emanuele Bracco, Roberto Ricciuti
Probability
Credits: 7,5
Language: English
Teacher: Marco Minozzo
Finance (2022/2023)
Teacher
Referent
Credits
5
Language
English
Class attendance
Free Choice
Location
VERONA
Learning objectives
The course deals with the problem of how to evaluate financial derivative securities, showing how stochastic modeling of the dynamics of the underlying securities is operationally useful.
The basic principles of the risk neutrality approach are illustrated and practical results particularly used in quantitative finance are recalled.
It is then shown how the same concepts have been extended and analogous results have been obtained for more realistic models.
Prerequisites and basic notions
Important knowledge for a profitable learning: linear systems, real functions of one or more real variables (in particular: continuous functions, composition of functions, derivatives, plots), basic concepts of financial mathematics (interest rate, return on an investment, difference between bonds and stocks, discount factor), fundamental concepts of probability theory (sigma algebra, random variables, probability and expected values, independence, conditional expected values, equivalent probability measures, probability density, Gaussian law)
Preparatory courses: Mathematics, Financial Mathematics, Statistics, Probability
Skills necessary for profitable learning: willingness and ability to conduct logical reasoning rigorously, to always justify passages and conclusions
Program
1. Preliminaries
Bonds, stocks
The problem of pricing derivatives
2. Equity prices
Pricing under uncertainty: stochastic models
Risk neutral pricing, risk aversion
3. Pricing derivatives
Risk hedging
Options prices and forward contracts
On the basis of the audience the following models will be treated: discrete single/multi-period models or models in continuous time and with continuous trajectories with constant or stochastic volatility or models in continuous time and with jumps.
4. The problem of selecting/estimating a model.
Bibliography
Didactic methods
reading course
Learning assessment procedures
The exam consists of a series of presentations of assigned material to be studied and understood, and a written report containing the commented proof of a theoretical result.
For the exam to be passed it is necessary that the grade obtained is at least D.
Assessment
The student is required to demonstrate a critical and in-depth knowledge of the topics covered in the course. The concepts must not be exposed in a mechanical but reasoned way, connections may be required.
The synthetic but exhaustive, rigorous and direct exposition immediately at the heart of the matter will be particularly appreciated. Vague, imprecise, poorly detailed or incorrect statements will be penalized
Criteria for the composition of the final grade
50% for the presentations, 50% for the written proof
PhD school courses/classes - 2022/2023
PhD students
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Guidelines for PhD students
Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2024/2025.
Documents
Title | Info File |
---|---|
Guidelines PhD students | pdf, en, 137 KB, 11/12/24 |
Linee guida dottorandi | pdf, it, 137 KB, 11/12/24 |
Percorso formativo | pdf, it, 125 KB, 11/12/24 |
Training program | pdf, en, 124 KB, 11/12/24 |