基于互联网搜索信息的预测模型研究--以余额宝产品需求为例

基于百度指数，以余额宝资产规模为例，运用ARIMA模型构建引入互联网搜索量的市场需求预测模型，同时建立不含互联网搜索量的预测模型，并将二者进行对比研究，发现包含互联网搜索量数据的预测模型的预测准确度更高，说明互联网搜索量数据包含一些在传统模型中未能考虑到的因素，该变量的引入有利于提高模型的预测准确度，为产品或服务的市场决策提供更加精确的预测结果。

Prediction Model Based on Internet Search Information---Taking Yu’ e Bao Product Demand as an Example

Based on Baidu index and taking Yu’ E Bao asset volume as an example, market demand prediction models containing Internet search volume and excluding Internet search volume are constructed and compared by using ARIMA model.Comparative study shows that prediction model containing search volume has high preci-sion, which means the data contains some factors not considered in traditional model.The introduction of this variable is beneficial to improving the prediction precision of the model, providing more accurate results for the product or service market decision-making.