Big Data and Machine Learning in Quantitative Investment
Big Data and Machine Learning in Quantitative Investment by Tony Guida, published by John Wiley & Sons on March 25, 2019, offers an insightful exploration into the integration of machine learning and big data within the realm of quantitative finance. This 304-page book is designed for practitioners, focusing on the practical applications and underlying principles rather than just the technical aspects. It addresses the essential questions of why and how these technologies can be effectively utilized in investment strategies.
Readers will find a structured approach across 13 chapters, each authored by different experts, which progressively covers topics from foundational concepts to advanced applications, including deep learning techniques. The book emphasizes the importance of understanding data and framing financial questions appropriately, while also clarifying that machine learning and big data are tools that, when applied correctly, can enhance quantitative investment practices. This edition serves as a comprehensive resource for those looking to deepen their knowledge in finance, data science, and analytics.
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Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment
Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance.
The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning.
• Gain a solid reason to use machine learning
• Frame your question using financial markets laws
• Know your data
• Understand how machine learning is becoming ever more sophisticated
Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment — and this book shows you how.
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