Phép lọc tuyến tính và vấn đề khử xu hướng của chuỗi thời gian: Nghiên cứu thực nghiệm tại Việt Nam - Bui Thi Thien , My; Nguyen Thi , Yen (JOURNAL OF ASIAN BUSINESS AND ECONOMIC STUDIES, 2022)
Filters are the popular tools for analyzing a time series into trend and cyclical components. The common property of the filters is retaining some components of the original time series as well as affecting the amplitude and the phase of the series received after filtering. The article analyzes the characteristic properties of popular linear filters: Differences, moving averages, high-pass, low-pass, band-pass, Hodrick-Prescott and Baxter-King filters through analysis of the transfer functions and the gain functions. For the purpose of extracting the trend component, only high-pass (HF), Hodrick-Prescott (HPF) and Baxter-King (BKF) filters can be used. Besides, these three types of filters do not change the phase and the amplitude of the cyclical component compared to the original data series. With the experimental study of HF, HPF, BKF filters on the weekly frequency VN-Index, the authors find out the reasonable parameters for HF, HPF, and BKF.