November 2020
Intermediate to advanced
378 pages
8h 47m
English
Content preview from Python for Algorithmic Trading
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Preface
Dataism says that the universe consists of data flows, and the value of any phenomenon or entity is determined by its contribution to data processing….Dataism thereby collapses the barrier between animals [humans] and machines, and expects electronic algorithms to eventually decipher and outperform biochemical algorithms.1
Yuval Noah Harari
Finding the right algorithm to automatically and successfully trade in financial markets is the holy grail in finance. Not too long ago, algorithmic trading was only available and possible for institutional players with deep pockets and lots of assets under management. Recent developments in the areas of open source, open data, cloud compute, and cloud storage, as well as online trading platforms, have leveled the playing field for smaller institutions and individual traders, making it possible to get started in this fascinating discipline while equipped only with a typical notebook or desktop computer and a reliable internet connection.
Nowadays, Python and its ecosystem of powerful packages is the technology platform of choice for algorithmic trading. Among other things, Python allows you to do
efficient data analytics (with pandas, for example), to apply machine learning to stock market prediction (with scikit-learn, for example), or even to make use of Google’s deep learning technology with TensorFlow.
This is a book about Python for algorithmic trading, primarily in the context of alpha generating strategies (see Chapter 1). ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.