Détail de l'auteur
Auteur Michael ISICHENKO |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Faire une suggestion Affiner la recherche
Quantitative Portfolio Management : The Art and Science of Statistical Arbitrage Ed. 1 / Michael ISICHENKO / John Wiley & Sons (2021)
Titre : Quantitative Portfolio Management : The Art and Science of Statistical Arbitrage Ed. 1 Type de document : e-book Auteurs : Michael ISICHENKO Editeur : John Wiley & Sons Année de publication : 2021 ISBN/ISSN/EAN : 9781119821328 Note générale : copyrighted Langues : Anglais (eng) Résumé : Discover foundational and advanced techniques in quantitative equity trading from a veteran insider In Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage, distinguished physicist-turned-quant Dr. Michael Isichenko delivers a systematic review of the quantitative trading of equities, or statistical arbitrage. The book teaches you how to source financial data, learn patterns of asset returns from historical data, generate and combine multiple forecasts, manage risk, build a stock portfolio optimized for risk and trading costs, and execute trades. In this important book, you'll discover: Machine learning methods of forecasting stock returns in efficient financial markets How to combine multiple forecasts into a single model by using secondary machine learning, dimensionality reduction, and other methods Ways of avoiding the pitfalls of overfitting and the curse of dimensionality, including topics of active research such as ?benign overfitting? in machine learning The theoretical and practical aspects of portfolio construction, including multi-factor risk models, multi-period trading costs, and optimal leverage Perfect for investment professionals, like quantitative traders and portfolio managers, Quantitative Portfolio Management will also earn a place in the libraries of data scientists and students in a variety of statistical and quantitative disciplines. It is an indispensable guide for anyone who hopes to improve their understanding of how to apply data science, machine learning, and optimization to the stock market. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88945592 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=579114
LIBRARY - Campus Rouen
NEOMA Business School
pmb
-
59 Rue Taittinger, 51100 Reims
-
00 33 (0)3 26 77 46 15
Library Campus Reims
-
1 Rue du Maréchal Juin, BP 215
76825 Mont Saint Aignan cedex -
00 33 (0)2 32 82 58 26