基于TEI@I的银行间质押式回购利率预测研究

针对银行间质押式回购利率受到多种外部因素影响较难预测的问题，本研究提出基于TEI@I思想的EEMD-XGBoost-ARIMA的银行间质押式回购利率预测算法，构建基于宏观经济、货币政策、流动性因素、相关利率指标等多维度的预测指标体系，引入百度搜索指数作为文本指标进一步提升预测精度。结果表明，基于TEI@I的组合预测模型表现优于传统时间序列预测模型ARIMA，对银行间质押式回购利率的有效预测可为金融机构、投资者和相关监管部门进行流动性管理提供有效依据。

A Study on Prediction of Interbank Repo Rates Based on TEI@I

In view of the difficulty in predicting the interbank pledged repo rate due to the influence of multiple external factors, a TEI@I-based EEMD-XGBoost-ARIMA prediction algorithm is proposed for interbank pledged repo rates. This algorithm constructs a multi-dimensional forecasting index system based on macroeconomic, monetary policy, liquidity factors, relevant interest rate indicators, etc. The prediction accuracy is further enhanced by the introduction of Baidu search index as a textual indicator. The results show that the combined forecasting model based on TEI@I outperforms the traditional time series forecasting model ARIMA, and the effective forecasting of inter-bank pledged repo rates can provide an effective reference for financial institutions, investors and relevant regulators in liquidity management.