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

  • 10h 14m 55s
  • Sofien Kaabar
  • Gildan Media
  • 2024

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.

This book will help you to 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; and evaluate the models' profitability and predictability to understand their limitations and potential.

About the Author

Sofien Kaabar is a financial author, trading consultant, and institutional market strategist specializing in the currencies market with a focus on Technical & Quantitative topics. Sofien's goal is to make Technical Analysis objective by incorporating clear conditions that can be analyzed and created with the use of technical indicators that rival existing ones. Having elaborated many successful trading algorithms, Sofien is now sharing back the knowledge he has acquired over the years to make it accessible to everyone.

In this Audiobook

  • Chapter 1 - Introducing Data Science and Trading
  • Chapter 2 - Essential Probabilistic Methods for Deep Learning
  • Chapter 3 - Descriptive Statistics and Data Analysis
  • Chapter 4 - Linear Algebra and Calculus for Deep Learning
  • Chapter 5 - Introducing Technical Analysis
  • Chapter 6 - Introductory Python for Data Science
  • Chapter 7 - Machine Learning Models for Time Series Prediction
  • Chapter 8 - Deep Learning for Time Series Prediction I
  • Chapter 9 - Deep Learning for Time Series Prediction II
  • Chapter 10 - Deep Reinforcement Learning for Time Series Prediction
  • Chapter 11 - Advanced Techniques and Strategies
  • Chapter 12 - Market Drivers and Risk Management