Trading of wind energy in day-ahead electricity markets entails significant risks. Wind traders are, therefore, interested in mitigating their trading risks in a number of ways. This work suggests addressing this issue in a comprehensive manner by coordinating the trading of wind resources with thermal resources and a pumped-hydro storage system (PHS) and co-optimizing the trading in energy and regulation markets. The trading strategy is modeled as a mixed integer linear stochastic program that takes into account several uncertain parameters, including wind power outputs, prices for energy, balancing, and regulation, and regulation deployments. In this optimization, the trader's attitude toward risks is controlled by using the metric of conditional value at risk (CVaR). Simulation results show that coordinated and co-optimized trading of the generation resources and PHS significantly improve the total expected profits and mitigates trader's risks. (C) 2017 Elsevier Ltd. All rights reserved.