Datascience for Finance
- Enseignant(s):
- Titre en français: Datascience pour la finance
- Cours donné en: anglais
- Crédits ECTS:
- Horaire: Semestre d'automne 2021-2022, 4.0h. de cours + 1.0h. d'exercices (moyenne hebdomadaire)
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séances
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site web du cours
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Formations concernées:
Maîtrise universitaire ès Sciences en finance : Entrepreneuriat financier et science des données
Maîtrise universitaire ès Sciences en finance, Orientation gestion des actifs et des risques
Maîtrise universitaire ès Sciences en finance, Orientation finance d'entreprise -
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ObjectifsThe objective of the class is to provide students with:
This class should be a "hands-on" class on dealing with data. It will be composed of two parts, in the first part of each session, we will go over econometric models; in the second part, we will use software such as STATA, python, etc to analyze related examples. Contenus1. Introduction Introduction to Econometrics Tools used for economic analysis 2. The Linear Regression Model The Linear Regression Model Least Squares Regression Hypothesis Tests and Model Selection 3. Estimation Methodology 4. Cross Sections, Time Series and Panel Data * Important: I might adjust the pace of the class and this syllabus according to our progress throughout the semester. Please pay close attention to the Moodle system. RéférencesRequired Textbook: W. Greene (2018), "Econometric Analysis" (8th edition, Prentice Hall). Other (read if interested): J. Hamilton (1994), "Time Series Analysis" (Princeton University Press). W. McKinney (2013), "Python for Data Analysis" (O'Reilly Media Inc) Evaluation1ère tentative
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