Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in...

Readers learn to solve large scale bi-level optimization problems by efficiently combining metaheuristics with complementary...

Haskell Financial Data Modeling and Predictive Analytics is a hands-on guide that...

Emerging over twenty years ago, Market Profile analysis continues to realize a strong following among active traders. The approach explains the underlying dynamics and structure of markets, identifies value areas, price rejection points, and...

To be financially literate in today’s market, one must have a solid understanding of derivatives concepts and instruments and the uses of those instruments in corporations.  The Third Edition has an accessible mathematical presentation, and more importantly, helps readers gain intuition by linking theories and concepts...

It is the purpose of this book to provide the meteorological knowledge and tools to improve the risk management of energy industry decisions, ranging from the long term finance and engineering planning assessments to the short term operational measures for scheduling and maintenance. Most of the chapters in this book are based on...

​Among the symmetrical distributions with an infinite domain, the most popular alternative to the normal variant is the logistic distribution as well as the Laplace or the double exponential distribution, which was first introduced in 1774. Occasionally, the Cauchy distribution is also used. Surprisingly, the hyperbolic secant...

Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have...

Investment and risk management problems are fundamental problems for  financial institutions and involve both speculative and hedging decisions. A structured approach to these problems naturally leads one to the field of applied mathematics in order to translate subjective probability beliefs and attitudes towards risk and reward into...