Deep Learning for Finance: Creating Machine and Deep Learning Models for Trading in Python

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning.

Sofien Kaabar—financial author, trading consultant, and institutional market strategist—introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization.

Understand and create machine learning and deep learning models
Explore the details behind reinforcement learning and see how it's used in time series
Understand how to interpret performance evaluation metrics
Examine technical analysis and learn how it works in financial markets
Create technical indicators in Python and combine them with ML models for optimization
Evaluate the models' profitability and predictability to understand their limitations and potential