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Big Data and Machine Learning in Quantitative Investment
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.
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.
- GenresFinance
296 pages, Kindle Edition
Published December 12, 2018
24 people are currently reading
95 people want to read
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Displaying 1 - 2 of 2 reviews
November 12, 2019
I bought this book because I need a specific chapter from it. There are a lot of high quality case studies that explain results that you can replicate in here.
August 30, 2020
Overall, a great compilation of reader-friendly introductory research pieces by many authors related to Machine Learning applied to investments .
As stated in the description, the book doesn't intend to delve into the mathematical or coding side of things and focuses on providing hands-on investment applications. The book reads very well for with good charts and explanations, yet sometimes there are articles that lack a little bit more of detail upon the weaknesses of the models utilized, especially when the lack of alternative data forces the authors to train models with less than four years or even one year of data.
That said, I fully recommend this book to those investment professionals motivated to start learning Machine Learning as the very first chapters are very introductory in nature. Another audience I think could be benefitted of reading this book are COOs (Chief Operations Officers) and CIOs (Chief Investment Officers) of asset managers that are trying to understand how Machine Learning can enhance their investment operations in the coming decade.
As stated in the description, the book doesn't intend to delve into the mathematical or coding side of things and focuses on providing hands-on investment applications. The book reads very well for with good charts and explanations, yet sometimes there are articles that lack a little bit more of detail upon the weaknesses of the models utilized, especially when the lack of alternative data forces the authors to train models with less than four years or even one year of data.
That said, I fully recommend this book to those investment professionals motivated to start learning Machine Learning as the very first chapters are very introductory in nature. Another audience I think could be benefitted of reading this book are COOs (Chief Operations Officers) and CIOs (Chief Investment Officers) of asset managers that are trying to understand how Machine Learning can enhance their investment operations in the coming decade.
Displaying 1 - 2 of 2 reviews