This book collects high-quality papers on the latest fundamental advances in the state of Econophysics and Management Science, providing insights that address problems concerning the international economy, social development and economic security. This book applies the multi-fractal detrended class method, and improves the method with different filters. The authors apply those methods to a variety of areas: financial markets, energy markets, gold market and so on. This book is arguably a systematic research and summary of various kinds of multi-fractal detrended methods. Furthermore, it puts forward some investment suggestions on a healthy development of financial markets.
This book collects high-quality papers on the latest fundamental advances in the state of Econophysics and Management Science, providing insights that address problems concerning the international economy, social development and economic security. This book applies the multi-fractal detrended class method, and improves the method with different filters. The authors apply those methods to a variety of areas: financial markets, energy markets, gold market and so on. This book is arguably a systematic research and summary of various kinds of multi-fractal detrended methods. Furthermore, it puts forward some investment suggestions on a healthy development of financial markets.
In today's world, we are increasingly exposed to the words 'machine learning' (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it.An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.