A recurrent theme in Underwriting Commercial Real Estate in a Dynamic Market is that good thinking and good underwriting go together. This stands in contrast with "getting an answer" or even worse "reverse engineering" - getting to a solution by assuming that current trends in market pricing is best. The cases in Underwriting Commercial Real Estate in a Dynamic Market will force readers to recognize that there is no single answer, but rather a range of answers that will depend on numerous perspectives. And, in order to make valuation decisions, they will have to undertake a rich conversation about what constitutes a good trade-off and what does not. Cases can be structured for use with introductory material as well as advanced topics.

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.