In the current scope of economics, the management of client portfolios has become a considerable problem within financial institutions due to the amount of risk that goes into assigning assets. Various algorithmic models exist for solving these portfolio challenges; however, considerable research is lacking that further explains these design problems and provides applicable solutions to these imperative issues. Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities is a pivotal reference source that provides vital research on the application of various programming models within the financial engineering field. While highlighting topics such as landscape analysis, breaking symmetries, and linear programming, this publication analyzes the quadratic constraints of current portfolios and provides algorithmic solutions to maximizing the full value of these financial sets. This book is ideally designed for financial strategists, engineers, programmers, mathematicians, banking professionals, researchers, academicians, and students seeking current research on recent mathematical advances within financial engineering.

Measuring Economic Growth and Productivity: Foundations, KLEMS Production Models, and Extensions presents new insights into the causes, mechanisms and results of growth in national and regional accounts. It demonstrates the versatility and usefulness of the KLEMS databases, which generate internationally comparable industry-level data on outputs, inputs and productivity. By rethinking economic development beyond existing measurements, the book's contributors align the measurement of growth and productivity to contemporary global challenges, addressing the need for measurements as well as the Gross Domestic Product. All contributors in this foundational volume are recognized experts in their fields, all inspired by the path-breaking research of Dale W. Jorgenson.