Grey Markov Model Forecast in Economic System under Incomplete Information and its Application on Foreign Direct Investment

Foreign direct investment (FDI) plays an extraordinary role in developing countries and its fluctuations reflect the changes of influencing factors during time, and therefore the models to simulate and forecast the trends are of great significance. Model GM (1, 1) is used in this paper to overcome the problems of small sample size and poor data. In the pre-procession of the raw data, two sequences are generated from weakening operator and from logarithm process respectively, and the simulation results show that the model constructed from the logarithm sequence has better simulation accuracy. Then Markov Chain is introduced to original model to get more accurate forecast results, which indicate the growing trend of FDI inflows in the following three years. The grey system models applied in economic areas are proved to have accurate simulation and convincing results.