TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 205

SAS/Ets User's Guide 205. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 2032 F Chapter 31 The UCM Procedure Output Smoothed Trend for the GNP Series as per the Hodrick-Prescott Filter Example Using Splines to Incorporate Nonlinear Effects F 2033 Output Detrended GNP Series Example Using Splines to Incorporate Nonlinear Effects The data in this example are created to mirror the electricity demand and temperature data recorded at a utility company in the midwest region of the United States. The data set not shown utility has three variables load temp and date. The load column contains the daily electricity demand the temp column has the average daily temperature readings and the date column records the observation date. The following statements produce a plot shown in Output of electricity load versus temperature. Clearly the relationship is smooth but nonlinear the load generally increases when the temperatures are away from the comfortable sixties. ods graphics on proc sgplot data utility loess x temp y load smooth run 2034 F Chapter 31 The UCM Procedure Output Load versus Temperature Plot The time series plot of the load not shown also shows that apart from a day-of-the-week seasonal effect there are no additional easily identifiable patterns in the series. The series has no apparent upward or downward trend. The following statements fit a UCM to the series that takes into account these observations. The particular choice of the model is a result of a little modeling exercise that compared a small number of competing models. The chosen model is adequate but by no means the best possible. The temperature effect is modeled by a deterministic three-degree spline with knots at 30 40 50 60 and 75. The knot locations and the degree were chosen by visual inspection of the plot Output . An autoreg component is used in place of the simple irregular component which improved the residual analysis. The last 60 days of data are withheld for out-of-sample forecast evaluation note the BACK option in .

• Tài chính doanh nghiệp
• Hướng dẫn sử dụng SAS ETS
• các mô hình phân tích tài chính
• báo cáo tài chính
• phân tích đầu tư
• phân tích tính khả dụng các khoản đầu tư