Forecasting the electricity spot market price (i.e., the price of electricity traded for the next day) is important in planning efficient power generation and demand schedules. This research aims to discuss the following two points in the forecasting task: an explicit scheme for estimating high and low-price situations and an effective weighted integration of given multiple forecast products depending on the estimated situations. The authors propose an adaptive method of combining market price forecasts (ADAPTIVE) to utilize several types of given forecast results efficiently and improve forecasting accuracy. The method aims to capture the features of the component models' results considering high- and low-prices situations. To evaluate the effectiveness of the proposed ADAPTIVE, numerical experiments were conducted on electricity spot market prices in the Japan Electric Power Exchange. The results indicate that the proposed method is a promising way to improve the accuracy of the conventional method of combining forecasts.