Robust Asset Allocation Based on Forecasts of Econometric Methods (ARMA & GARCH) and Uncertainty for Return & Covariance

Document Type : Research Paper


1 . Prof. in Financial Management, Faculty of Management, University of Tehran, Tehran, Iran

2 MSc. Student in Financial Engineering, Faculty of Management, University of Tehran, Tehran, Iran


In this paper we use robust optimization to solve asset allocation problem under uncertainty for return and covariance-variance parameters. Not taking uncertainty into account about input parameters in optimization problems can take optimal solutions away from optimum region or make them infeasible. For designing and defining the set of uncertainty for return and covariance-variance, we use the concept of estimated distance and bootstrap for predictions, respectively. Calculations of the sets of uncertainty are based on predications of ARMA and GARCH methods. In order to ensure that robust approach’s results outperform the nonrobust approch’results we use robust sharpe index with the help of pair comparison test during eight consecutive quarter periods. Finally, some numerical examples are given to illustrate the effectiveness of the proposed approach.


Main Subjects

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