Machine learning in asset pricing
La jaquette indique : "Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-s...
שמור ב:
| מחבר ראשי: | |
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| פורמט: | Livre numérique |
| שפה: | Anglais |
| יצא לאור: |
Princetons ; Oxford :
Princeton University Press
2021.
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| נושאים: | |
| גישה מקוונת: | Accès Université Orléans et IFPM |
| הערה: |
Couverture. https://static2.cyberlibris.com/books_upload/136pix/9780691218717.jpg Titre provenant de la page de titre du document numérique La pagination de l'édition imprimée correspondante est de 157 p. Cyberlibris (ScholarVox) corpus sciences économiques et gestion |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Machine learning in asset pricing, Stefan Nagel, 2021, Princetons, Princeton University Press, 1 vol. (X-144 p.), Princeton lectures in finance, 978-0-691-21870-0 |
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| 001 | 981591 | ||
| 008 | 221020s2021 xxg ||| |||| 00| 0 eng d | ||
| 009 | PPN265129990 | ||
| 020 | |a 9780691218717 | ||
| 041 | 0 | |a eng | |
| 082 | |a 332.6 | ||
| 082 | |a 332.63/2220285631 | ||
| 100 | 1 | |a Nagel, Stefan, |d 19..-...., |c Professeur de finance. | |
| 245 | 1 | 0 | |a Machine learning in asset pricing |c Stefan Nagel. |
| 260 | |a Princetons ; |a Oxford : |b Princeton University Press, |c 2021. | ||
| 500 | |a Couverture. https://static2.cyberlibris.com/books_upload/136pix/9780691218717.jpg | ||
| 500 | |a Titre provenant de la page de titre du document numérique | ||
| 500 | |a La pagination de l'édition imprimée correspondante est de 157 p. | ||
| 500 | |a Cyberlibris (ScholarVox) corpus sciences économiques et gestion | ||
| 504 | |a Bibliogr. p. [135]-139. Index | ||
| 506 | |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris | ||
| 520 | |a La jaquette indique : "Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. "Machine learning in asset pricing" presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation." | ||
| 538 | |a Configuration requise : navigateur internet | ||
| 650 | |a Intelligence artificielle | ||
| 650 | |a Investissements |x Modèles mathématiques | ||
| 650 | |a Prix |x Modèles mathématiques | ||
| 650 | |a Apprentissage automatique |x Aspect économique | ||
| 650 | |a Marché financier |x Modèles mathématiques | ||
| 650 | |a Modèle de fixation du prix des actifs | ||
| 776 | 0 | |0 258388838 |t Machine learning in asset pricing |f Stefan Nagel |d 2021 |c Princetons |n Princeton University Press |p 1 vol. (X-144 p.) |s Princeton lectures in finance |z 978-0-691-21870-0 | |
| 856 | 4 | |5 452349901:761294384 |u https://ezproxy.univ-orleans.fr/login?qurl=https://univ.scholarvox.com/book/88935231 |z Accès Université Orléans et IFPM | |
| 997 | |0 981591 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/ScholarVox (ebooks)/ | ||