BigDataandMachineLearninginQuantitativeInvestment 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 machinelearningandbigdata 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 machinelearningand finally finishing with innovative approaches using deep learning.
• Gain a solid reason to use machinelearning
• Frame your question using financial markets laws
• Know your data
• Understand how machinelearning is becoming ever more sophisticated
Machinelearningandbigdata are not a magical solution, but appropriately applied, they are extremely effective tools for quantitativeinvestment — and this book shows you how.