基于灰色马尔科夫的外汇预测模型

随着经济的发展和居民收入水平的提高，兑换外汇逐渐成为人们的日常需求。但国家对外汇有着严格的管理并限制了个人的兑换额度，所以当个人外汇支出超过规定额度时，就认为涉嫌分拆外汇。为了更好掌握未来涉嫌的外汇分拆量，则需要较为准确的预测。本文利用灰色预测模型对历史数据进行建模，结合马尔科夫预测模型，得到组合预测模型的预测值。本文的研究与应用表明灰色马尔科夫组合预测模型比单一预测模型精度更高，可以对未来数据进行更加准确的预测。

Predict Model for Foreign Exchange Based on Grey-Markov

With the development of the economy and the improvement of the income level of residents, exchange of foreign exchange has gradually become a daily demand for people. However, the state has strict management for foreign exchange and limits for personal exchange quotas. When the personal foreign exchange expenditure exceeds the prescribed amount, it is considered to be suspected of splitting foreign exchange.In order to better grasp the suspected foreign exchange split in the future, we need more accurate forecasts.The historical data is used by the grey prediction model, and the predicted value of the combined prediction model is obtained by combining the Markov prediction model. The research and application of this paper show that the grey Markov combination forecasting model has higher precision than the single forecasting model and can predict the future data more accurately.