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Upgrade your programming language to more effectively handle
high-frequency data Machine Learning and Big Data with KDB+/Q
offers quants, programmers and algorithmic traders a practical
entry into the powerful but non-intuitive kdb+ database and q
programming language. Ideally designed to handle the speed and
volume of high-frequency financial data at sell- and buy-side
institutions, these tools have become the de facto standard; this
book provides the foundational knowledge practitioners need to work
effectively with this rapidly-evolving approach to analytical
trading. The discussion follows the natural progression of working
strategy development to allow hands-on learning in a familiar
sphere, illustrating the contrast of efficiency and capability
between the q language and other programming approaches. Rather
than an all-encompassing "bible"-type reference, this book is
designed with a focus on real-world practicality -to help you
quickly get up to speed and become productive with the language.
Understand why kdb+/q is the ideal solution for high-frequency data
Delve into "meat" of q programming to solve practical economic
problems Perform everyday operations including basic regressions,
cointegration, volatility estimation, modelling and more Learn
advanced techniques from market impact and microstructure analyses
to machine learning techniques including neural networks The kdb+
database and its underlying programming language q offer
unprecedented speed and capability. As trading algorithms and
financial models grow ever more complex against the markets they
seek to predict, they encompass an ever-larger swath of data --
more variables, more metrics, more responsiveness and altogether
more "moving parts." Traditional programming languages are
increasingly failing to accommodate the growing speed and volume of
data, and lack the necessary flexibility that cutting-edge
financial modelling demands. Machine Learning and Big Data with
KDB+/Q opens up the technology and flattens the learning curve to
help you quickly adopt a more effective set of tools.
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