Descriptif
Financial Decisions under Risk 2. The main objective of this course is to present the application of machine learning in industries of asset management. This course contains three parts. The first part is devoted to the presentation of financial instruments (stock, bond, forward, future, option, etc.) in different asset classes such as equity, fixed-income, commodity, foreign exchange, and credit. The second part concerns the mathematical modeling of different assets and option pricing. The third part is devoted to the presentation of major machine learning algorithms (regularized linear regression, LASSO, RIDGE, logistic regression, Support Vector Machine, random forest, neural network) and their applications in asset management. Moreover, we introduce the portfolio optimization under risk and transaction constraints and present some alternative methods in portfolio construction. Also, the implementation in R is proposed to students to practice with real market datas.
Syllabus attached.
Cours dispensé en Anglais
Langue du cours : Anglais
Credits ECTS : 4
Diplôme(s) concerné(s)
- Echanges PEI
- Diplôme d'ingénieur de l'Ecole polytechnique
- Economics, Data Analytics and Corporate Finance
Parcours de rattachement
Format des notes
Numérique sur 20Littérale/grade réduitPour les étudiants du diplôme Economics, Data Analytics and Corporate Finance
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Diplôme d'ingénieur de l'Ecole polytechnique
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Echanges PEI
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 5 ECTS