Abstract: Reasonable forecasting and prejudging of contract prices in the bilateral contract electricity market can provide important support for market operation and regulation.Traditional electricity price forecasting methods are mainly used for nodal,regional,or system electricity prices that can form a stable time series.But these methods are not directly applicable to bilateral contract markets as they have highly heterogeneous characteristics,i.e.,each participant has many contracts,and each contract includes a specific price.The current status of China’s bilateral contract market with single data type and small data size further increases the difficulty of forecasting.A solution idea that maps micro-behavior to macro-price is proposed.And a price forecasting approach that is driven by the hybrid of an electricity economics model and empirical data is subsequently given.Firstly,considering the characteristics of electricity markets,an axiomatic economics model is proposed which can interpret the two-player negotiation mechanism and link estimation value of electricity valuations of market participants to the equilibrium price.Secondly,a multiparticipant joint optimization model is established based on data regression ideas to estimate the valuation of each participant by inverse optimization.Finally,the contract prices are forecasted by combining the optimal estimation value of the valuations of market participants and the proposed economics model.Case studies indicate that the proposed approach can adapt to the data limitations in the current context,and it is highly accurate,fast,and robust.Meanwhile,it can also reveal the microeconomic laws of bilateral contract markets,i.e.,it owns a strong interpretation.