• Preface; 1. Introduction; Part I. Foundations: 2. Fundamentals of Financial Time-Series; 3. Supervised Learning and Canonical Networks; 4. The Model Training Workflow; Part II. Applications: 5. Enhancing Classical Quantitative Trading Strategies with Deep Learning; 6. Deep Learning for Risk Management and Portfolio Optimization; 7. Applications to Market Microstructure and High-Frequency Data; 8. Conclusions; List of Acronyms; Appendix A: Different Asset Classes; Appendix B: Access to Market Data; Appendix C: Investment Performance Metrics; Appendix D: Code Scripts.

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• Preface; 1. Introduction; Part I. Foundations: 2. Fundamentals of Financial Time-Series; 3. Supervised Learning and Canonical Networks; 4. The Model Training Workflow; Part II. Applications: 5. Enhancing Classical Quantitative Trading Strategies with Deep Learning; 6. Deep Learning for Risk Management and Portfolio Optimization; 7. Applications to Market Microstructure and High-Frequency Data; 8. Conclusions; List of Acronyms; Appendix A: Different Asset Classes; Appendix B: Access to Market Data; Appendix C: Investment Performance Metrics; Appendix D: Code Scripts.

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• Preface; 1. Introduction; Part I. Foundations: 2. Fundamentals of Financial Time-Series; 3. Supervised Learning and Canonical Networks; 4. The Model Training Workflow; Part II. Applications: 5. Enhancing Classical Quantitative Trading Strategies with Deep Learning; 6. Deep Learning for Risk Management and Portfolio Optimization; 7. Applications to Market Microstructure and High-Frequency Data; 8. Conclusions; List of Acronyms; Appendix A: Different Asset Classes; Appendix B: Access to Market Data; Appendix C: Investment Performance Metrics; Appendix D: Code Scripts.

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