The Application of Grey Markov Forecasting Model Based on Entropy Method

摘要

Markov forecasting model is applicable for data fluctuation interval estimation and prediction. It is important to determine the weighting in model evaluation to avoid subjectivity. In order to close the gap, comparison studies are performed on prediction accuracy and weighting coefficient selection among Markov chain model, grey model and ARIMA model. Furthermore, a new grey Markov forecasting model based on entropy method is established to predict stock prices. Empirical analysis shows that it is an effective method, because it is more reliable and more accurate than the aforementioned models.