In recent times, the problem of portfolio optimization has become increasingly complex due to the myriad objectives and constraints induced by the market norms, investor preferences and investment strategies which define the underlying portfolios. With the required mathematical models finding little help from traditional methods, there has been a growing need to look for non-traditional algorithms from the emerging field of Metaheuristics, a sub-discipline of Computational Intelligence, to arrive at the optimal portfolios.

This book therefore elucidates a collection of strategic portfolio optimization models, such as risk budgeting, market neutral investing and portfolio rebalancing, which employ metaheuristics for their effective solutions. The results are demonstrated using MATLAB® implementations on live portfolios invested across global stock universes. The MATLAB® programs and functions can be accessed at the MATLAB Central File Server.

This book, belonging to the cross-disciplinary field of Computational Intelligence in Finance, is structured to appeal to readers who are novices in finance or metaheuristics.