Quantitative Genetic

After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools.

The purpose of this book is to show recent advances in the field of Genetic programming (GP), both the development of new theoretical approaches and the emergence of applications that have successfully solved different real world problems. The volume is primarily aimed at postgraduates, researchers and academics, although it is hoped that it may be useful to undergraduates who wish to learn about the leading techniques in GP.

This book covers the dynamic process of genetic diversity in living organisms. It comprises chapters that address various topics, including genetic diversity in crop production, the relationship between viruses and their hosts, patterns of genetic variability in silver carp populations in Pakistan, molecular markers used for wildlife conservation, and more.