Data-Driven Intelligent Financial Portfolio Selection
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Beschreibung
This book synthesizes the development and advanced methods in the financial investment decision making in the big data environment, and explores systematic solutions for quantitative portfolio selection problems by integrating theoretical elaboration with practical applications, while also summarizing the future development directions and trends of the field. It aims to provide a valuable reference for researchers in quantitative finance, and investment practitioners, as well as graduate students specializing in related disciplines.
This book synthesizes the development and advanced methods in the financial investment decision making in the big data environment, and explores systematic solutions for quantitative portfolio selection problems by integrating theoretical elaboration with practical applications, while also summarizing the future development directions and trends of the field. It aims to provide a valuable reference for researchers in quantitative finance, and investment practitioners, as well as graduate students specializing in related disciplines.
Data-driven, multi-dimensional portfolio optimization grounded in rigorous quantitative investment theory Precise modeling of transaction costs and taxes enables realistic, high-frequency online trading strategies Advanced market and asset state modeling with flexible cash-flow control to enhance long-term returns
Autor*in
Sini Guo
Themen in »Data-Driven Intelligent Financial Portfolio Selection«
Quantitative Finance Online portfolio selection Adaptive return prediction Transaction cost Capital gain tax Risk parity Market states Robust optimization Cash flows Markov process