Machine Learning and Big Data with KDB+/Q

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Develop solid high-frequency strategies with q's unprecedented speed and efficiency In the world of high-frequency trading, the q programming language and kdb+ database have risen to the top of the ranks as tools for implementing quantitative analyses of all types. Until now, there has been a lack of accessible, implementation-focused books to assist in Data Science and Machine Learning using this technology. Machine Learning and Big Data with kdb+/q bridges this conspicuous gap, providing you with a practical introduction to the q language and a guide to using data science to enable data-driven decision making. You'll also learn the basic principles and techniques underpinning powerful trading mechanisms based upon machine learning. This book opens the world of q and kdb+ to a wide audience, as it emphasises solutions to problems of practical importance. Implementations covered include: * Data description and summary statistics * Basic regression methods and cointegration * Volatility estimation and time series modelling * Advanced machine learning techniques, including neural networks, random forests, and principal component analysis * Techniques useful beyond finance related to text analysis, game engines and agent based models Written by four top figures in global quantitative finance and technology, Machine Learning and Big Data with kdb+/q is a valuable resource in high-frequency trading.