Future distribution systems will accommodate an increasing share of distributed energy resources (DERs). Facing with this new reality, virtual power plants (VPPs) play a key role to aggregate DERs with the aim of facilitating their involvement in wholesale electricity markets. In this paper, the trading strategies of a VPP in cooperation with its neighboring VPPs are addressed. Toward this aim, a portfolio of inter-regional contracts is considered to model this cooperation and maximize the energy trade opportunities of the VPP within a medium-term horizon. To hedge against profit variability caused by market price uncertainties, two efficient risk management approaches are also implemented in the VPP decision-making problem based on the concepts of conditional value at risk (CVaR) and second-order stochastic dominance constraints (SSD). The resulting models are formulated as mixed-integer linear programming (MILP) problems that can be solved using off-the-shelf software packages. The efficiency of the proposed risk-hedging models is analyzed through a detailed case study, and thereby relevant conclusions are drawn. (C) 2017 Elsevier Ltd. All rights reserved.