This is the Linux app named ML for Trading whose latest release can be downloaded as 2ndEdition.zip. It can be run online in the free hosting provider OnWorks for workstations.
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ML for Trading
On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms, how to extract tradeable signals from financial text data like SEC filings, earnings call transcripts or financial news. Using deep learning models like CNN and RNN with financial and alternative data, and how to generate synthetic data with Generative Adversarial Networks, as well as training a trading agent using deep reinforcement learning.
- The 2nd edition of this book introduces the end-to-end machine learning for trading workflow
- Data sourcing, feature engineering, and model optimization
- Strategy design and backtesting
- It illustrates the workflow using examples
- The first part provides a framework for developing trading strategies driven by machine learning (ML)
- Outlines how to engineer and evaluate features suitable for ML models
This is an application that can also be fetched from https://sourceforge.net/projects/ml-for-trading.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.