We consider a direct control Virtual Power Plant, which is given the task of maximizing the profit of a portfolio of flexible consumers by trading flexibility in Energy Markets. Spot price optimization has been quite intensively researched in Smart Grid literature lately. In this work, however, we develop a three stage market model, which includes Day-Ahead (Spot), Intra-Day and Regulating Power Markets. This allows us to test the hypothesis that the Virtual Power Plant can generate additional profit by trading across several markets. We find that even though profits do increase as more markets are penetrated, the size of the profit is strongly dependent on the type of flexibility considered. We also find that penetrating several markets makes profits surprisingly robust to spot price prediction errors. ; We consider a direct control Virtual Power Plant, which is given the task of maximizing the profit of a portfolio of flexible consumers by trading flexibility in Energy Markets. Spot price optimization has been quite intensively researched in Smart Grid literature lately. In this work, however, we develop a three stage market model, which includes Day-Ahead (Spot), Intra-Day and Regulating Power Markets. This allows us to test the hypothesis that the Virtual Power Plant can generate additional profit by trading across several markets. We find that even though profits do increase as more markets are penetrated, the size of the profit is strongly dependent on the type of flexibility considered. We also find that penetrating several markets makes profits surprisingly robust to spot price prediction errors.