In this paper, the wind power aggregator is cooperating with a commercial compressed air energy storage (CCAES) to participate in three markets, including day-ahead (DA), intraday (IN), and balancing (BL) markets. A three-stage stochastic programming problem is formulated to model the optimal operation of the proposed system. In the proposed model, the uncertainties of wind power, as well as DA, IN, and BL markets price is modeled by the implementation of scenario generation and reduction methods. Financial risks imposed from the uncertain parameters are investigated in the proposed stochastic optimization framework. For this purpose, the downside risk constraints approach (DRCA) is modeled in the stochastic formulation to manage the financial risks. In the proposed DRCA, a risk-based strategy can be proposed for the aggregation of CCAES and wind as a power aggregator (PA) that has a controlled risk in the risk-averse strategy. According to obtained results, the expected profit of PA without DRCA is (sic) 4176.3, while the proposed strategy by the DRCA leads to a (sic) 4094.0 profit. Therefore the proposed strategy by DRCA has a lower profit (1.97%) while leads to a guaranteed risk-controlled strategy for PA with the reduced risk by 100%. (C) 2020 Elsevier Ltd. All rights reserved.