Abstract
Trading with futures is complex and abounds with risks, to mitigate which a multi-pronged approach such as diversification in different asset classes across dissimilar markets or imposing risk budgets on individual assets and/or asset classes or enforcing capital budgets and other investor preferential constraints modeling their risk appetites and allocation limits, can be adopted. However, the enforcement of such constraints turns the problem model complex rendering it difficult for direct solving using traditional methods engendering the need to look for metaheuristic solutions.In this work, we discuss the metaheuristic construction of a long-only futures portfolio with the objective of maximizing its diversification index, in the face of risk budgeting and other investor specific constraints. Adopting Diversification Ratio for its diversification index and enforcing risk budgets on the individual assets as well as on asset classes turns the transformed problem model into a Multi-objective Non-linear Non Convex Constrained Fractional Programming problem, to solve which a metaheuristic strategy, viz., Multi-objective Differential Evolution, has been evolved to obtain the Pareto Optimal solution set. Experimental simulations have been undertaken over a futures portfolio of equity indices and bonds spread across global markets, making use of a historical data set for the period March 2004-June 2013.
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