Time Series Forecasting Model Based on Wavelet Denoising Application in Manufacturing PMI Prediction

DOI

10.2991/isss-15.2015.82How to use a DOI?

Keywords

wavelet denoising; ARIMA model; Manufacturing PMI; Prediction interval; Time series analysis.

Abstract

PMI is of great significance in terms of business analysis and economic forecasts. To accurately grasp the running of macroeconomic trend the right strategic decisions and auxiliary enterprises, this article takes our country manufacturing PMI as the research object, the wavelet noise reduction as the core, combined with the ARIMA model is established based on the wavelet noise reduction of ARIMA non-stationary time series forecasting model. Finally it used the model for the empirical analysis of China's manufacturing PMI. The results show that the prediction precision of the model, fitting and prediction intervals are improved obviously. Our country economy is in steady stage, our country macroeconomic policy has obvious effect

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dongdong Bai
AU  - Jinyu Wei
PY  - 2015/08
DA  - 2015/08
TI  - Time Series Forecasting Model Based on Wavelet Denoising Application in Manufacturing PMI Prediction
BT  - Proceedings of the 1st International Symposium on Social Science (isss-15)
PB  - Atlantis Press
SP  - 336
EP  - 339
SN  - 2352-5398
UR  - https://doi.org/10.2991/isss-15.2015.82
DO  - 10.2991/isss-15.2015.82
ID  - Bai2015/08
ER  -