Marcos López de Prado - Advances in Financial Machine Learning-John Wiley & Sons, Inc. (2018)

• Author: Marcos López de Prado
• Publisher: John Wiley & Sons, Inc.
• Year of Publication: 2018
• Format: PDF
• Difficulty: ⭐⭐⭐⭐
• Recommendation Index: ⭐⭐⭐⭐⭐
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Introduction

This book, "Advances in Machine Learning for Finance," written by Marcos López de Prado, is a groundbreaking comprehensive guide that provides an in-depth exploration of the application of machine learning technology in the financial field. The book emphasizes the importance of handling financial data correctly and addresses common pitfalls in the field, such as financial data snooping (FDS) and the potential bias of traditional cross-validation methods.

This book details how to build a big data structure suitable for machine learning algorithms and how to use machine learning algorithms for research. It covers a variety of mathematical techniques and practical methods, including financial data sampling, cross-validation (such as Purged Cross-Validation and Combinatorial Purged Cross-Validation), financial feature engineering (such as Fractionally Differentiated Features), advanced ensemble methods, hyperparameter tuning, and how to conduct robust backtesting to avoid false positives. In addition, the book also explores machine learning applications of market influences and microstructural effects, as well as the use of high-performance computing in financial data analysis. This book is designed to provide quantitative analysts, algorithmic traders, financial engineers, and data scientists with practical guidance and solutions to help them succeed in modern finance.

Main features

• Solid theoretical foundation
• Rich practical cases
• Clear operating instructions
• Suitable for practical applications

Suitable for the crowd

• Quantitative Analyst
• Algorithmic Trader
• Financial Engineer
• Data Scientist