In the electricity market environment， a power supply company or a retail company needs to predict the electricity prices in various markets so as to develop an optimal purchasing strategy. Theoretically， the higher-order moments of the profit function associated with the retail company concerned， especially the third moment or the so-called skewness are not negligible in the decision-making process; or in other word， in building an optimal purchasing strategy for a retail company it is necessary to reasonably account for the skewness of its profit function， and hence it is demanding to study the expression form and application approach of the skewness. Moreover， the electricity purchasing procedure is dynamic in nature due to uncertain load demands. Given this background， a skewness-VaR（value at risk） based dynamic model is presented for developing the optimal electricity purchasing strategy in multiple markets by quantifying the risk with the VaR and skewness. An auto reverse model is utilized to estimate the load demand. By employing this model， a retail company can reasonably allocate the electricity amount to be purchased among various markets dynamically so as to make a compromise between maximizing the profit and minimizing the risk associated. The developed method provides retail companies a new tool for assisting decision-making and risk management in the dynamic electricity purchasing process. Finally， a sample example is served for demonstrating the essential features of the developed model and method.