Machine learning and big data with kdb+/q

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Bibliographic Information

Title
"Machine learning and big data with kdb+/q"
Statement of Responsibility
Jan Novotny, Paul A. Bilokon, Aris Galiotos, Frédéric Déléze
Publisher
  • Wiley
Publication Year
  • 2020
Book size
26 cm

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Notes

Includes bibliographical references (p. 601-605) and index

Summary: "The book will start with an examination of the foundations of kdb+/q and will proceed to consider the practicalities of dealing with real high-frequency data, and then demonstrate how kdb+/q can be used to solve econometric problems of practical importance. The exploratory journey of the language follows the path the high-frequency quants undertake every time they develop a working strategy: from data description and summary statistics to basic regression methods and cointegration, from volatility estimation and modelling to optimal execution, from market impact and microstructure analyses to advanced machine learning techniques including the neural networks"-- Provided by publisher

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