
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown ...
DETAILS
Machine Learning in Finance
From Theory to Practice
Dixon, Matthew F., Halperin, Igor, Bilokon, Paul
Kartoniert, xxv, 548 S.
XXV, 548 p. 97 illus., 83 illus. in color.
Sprache: Englisch
235 mm
ISBN-13: 978-3-030-41070-4
Titelnr.: 94405926
Gewicht: 872 g
Springer, Berlin (2021)
Herstelleradresse
Springer Heidelberg
Tiergartenstr. 17
69121 - DE Heidelberg
E-Mail: buchhandel-buch@springer.com