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.

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.

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.

This self-contained volume brings together a collection of chapters by some of the most distinguished researchers and practitioners in the field of mathematical finance and financial engineering. Presenting state-of-the-art developments in theory and practice, the book has real-world applications to fixed income models, credit risk models, CDO pricing, tax rebates, tax arbitrage, and tax equilibrium. It is a valuable resource for graduate students, researchers, and practitioners in mathematical finance and financial engineering.

Modern financial markets offer the real world's best approximation to the idealized price auction market envisioned in economic theory. Nevertheless, as the increasingly exquisite and detailed financial data demonstrate, financial markets often fail to behave as they should if trading were truly dominated by the fully rational investors that populate financial theories. These markets anomalies have spawned a new approach to finance, one which as editor Richard Thaler puts it, "entertains the possibility that some agents in the economy behave less than fully rationally some of the time." Advances in Behavioral Finance collects together twenty-one recent articles that illustrate the power of this approach. These papers demonstrate how specific departures from fully rational decision making by individual market agents can provide explanations of otherwise puzzling market phenomena. To take several examples, Werner De Bondt and Thaler find an explanation for superior price performance of firms with poor recent earnings histories in the tendencies of investors to overreact to recent information. Richard Roll traces the negative effects of corporate takeovers on the stock prices of the acquiring firms to the overconfidence of managers, who fail to recognize the contributions of chance to their past successes. Andrei Shleifer and Robert Vishny show how the difficulty of establishing a reliable reputation for correctly assessing the value of long term capital projects can lead investment analysis, and hence corporate managers, to focus myopically on short term returns. As a testing ground for assessing the empirical accuracy of behavioral theories, the successful studies in this landmark collection reach beyond the world of finance to suggest, very powerfully, the importance of pursuing behavioral approaches to other areas of economic life. Advances in Behavioral Finance is a solid beachhead for behavioral work in the financial arena and a clear promise of wider application for behavioral economics in the future.

Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.