Advances In Financial Economics

Advances in Financial Economics Vol. 16 contains a set of empirical papers by a set of global scholars who examine corporate governance and market regulation from a variety of perspectives.

Advances in Pacific Basin Business, Economics, and Finance is an annual publication designed to focus on interdisciplinary research in finance, economics, and management. It particularly emphasizes the economic, financial, and management relationships among Pacific Rim countries.

​Discussing a wide range of topics of contemporary relevance from the domain of finance and economics, this book presents a collection of twenty-four research papers, which were selected on the basis of their topicality, the novelty of their methods, and the importance of their subject matter. All papers pursue an empirical approach to address key research issues, and are categorized into three major parts. Part one includes papers related to development economics and environmental economics. The second part focuses on monetary economics, public economics, and behavioral economics, while the third tackles issues concerning corporate finance and financial risk management. Bringing together works of scholars from around the world, the book presents a truly global perspective, and not only serves as an essential guide on the topic for researchers, but also has a distinctive role to play in policymaking.

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

This volume, in the series Advances in Financial Economics, discusses a variety of topics in the field.