Description
Quantitative Investing, 1st ed. 2020
From Theory to Industry
Author: Ma Lingjie
Language: EnglishSubjects for Quantitative Investing:
Publication date: 09-2021
455 p. · 15.5x23.5 cm · Paperback
Publication date: 09-2020
455 p. · 15.5x23.5 cm · Hardback
Description
/li>Contents
/li>Biography
/li>Comment
/li>
This book provides readers with a systematic approach to quantitative investments and bridges the gap between theory and practice, equipping students to more seamlessly enter the world of industry. A successful quantitative investment strategy requires an individual to possess a deep understanding of the financial markets, investment theories and econometric modelings, as well as the ability to program and analyze real-world data sets.
In order to connect finance theories and practical industry experience, each chapter begins with a real-world finance case study. The rest of the chapter introduces fundamental insights and theories, and teaches readers to use statistical models and R programming to analyze real-world data, therefore grounding the learning process in application. Additionally, each chapter profiles significant figures in investment and quantitative studies, so that readers can more fully understand the history of the discipline.This volume will be particularly useful to advanced students and practitioners in finance and investments.
Dr. Lingjie Ma has 15 years of experience developing global multi-asset investment strategies. He has worked as both a head of research and as a portfolio manager in the investment industry, overseeing full-spectrum investment process and business management. He joined the University of Illinois at Chicago in 2016 as a clinical associate professor in finance. Dr. Ma is a frequent public speaker on quantitative investing and quantamental strategies.
Provides real-world case studies and data sets that connect quantitative finance theory to industry practice
Profiles notable figures in investment and quantitative studies, illustrating the contextual history of the discipline
Incorporates dirty data and statistical models using R programming, preparing readers to seamlessly enter the industry
Includes supplementary material: sn.pub/extras
These books may interest you
Impact Investment, + WebsiteA Practical Guide to Investment Process and Social Impact Analysis 91.83 €
Big Data Science in Finance 115.82 €