Soft Computing Techniques And Applications In Financial Engineering

Soft Computing is an emerging approach which parallels the remarkable ability of the human brain to reason and learn in an environment of uncertainty and imprecision. It is one of the most emerging consortiums of methodologies including artificial neural networks (ANNs), fuzzy logic (FL) etc. They provide tractable, robust and lower cost solutions to the complex and gigantic real world-problems with the help of functional approximations and learning paradigms. It can also handle linguistic uncertainties, vagueness and imprecision involved in real life problems with reduced mathematical complexities. Soft computing techniques have outperformed the conventional approaches with lesser complexity, vagueness, tuning requirements and higher level of robustness, and tractability. On the other hand, most of the actuarial problems are stochastic in nature with soaring noises and variable volatilities, resulting in signals that are complicated to handle with conventional modeling and forecasting techniques.

Autorentext

Dr. Jilani received his PhD with specialization soft computing and data mining in 2007. Currently, he is working as assistant professor at the Department of Computer Science, University of Karachi. His research interests include machine learning, data mining, natural language processing, statistics and health informatics.