Multivariate Time Series Analysis in Corporate Decision-Making Application
Yatao Li, Fen Ying · 2011
In order to solve nonlinear, non-stationary and complex problem with the time series in practical production and life, a multiple regression model for time series analysis is used in this paper. By introducing the principle of multiple regression, the multivariate time series analysis model not only overcome random factors of the time series, but also consider the many factors affecting the development of things, so as to improve forecasting accuracy and increase the reliability of predictio. For illustration, an example of a business forecast is utilized to show the feasibility of the multivariate time series analysis model in solving nonlinear, non-stationary and complex problem with the time series in practical production and life. Empirical results show that using the model in the case of known factors, combined with experimental data, can effective forecast for corporate earnings. This multivariate time series analysis model effective solution to the nonlinear time series, non-stationary and complex issues, so as to provide decision-making basis with an accurate quantitative and intuitive for decision makers.