TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 86

SAS/Ets User's Guide 86. 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 | 842 F Chapter 15 The FORECAST Procedure EXPO Method Exponential smoothing is used when the METHOD EXPO option is specified. The term exponential smoothing is derived from the computational scheme developed by Brown and others Brown and Meyers 1961 Brown 1962 . Estimates are computed with updating formulas that are developed across time series in a manner similar to smoothing. The EXPO method fits a trend model such that the most recent data are weighted more heavily than data in the early part of the series. The weight of an observation is a geometric exponential function of the number of periods that the observation extends into the past relative to the current period. The weight function is wT m 1 - t T where r is the observation number of the past observation t is the current observation number and is the weighting constant specified with the WEIGHT option. You specify the model with the TREND option as follows TREND 1 specifies single exponential smoothing a constant model TREND 2 specifies double exponential smoothing a linear trend model TREND 3 specifies triple exponential smoothing a quadratic trend model Updating Equations The single exponential smoothing operation is expressed by the formula St Xt 1 - M St-1 where St is the smoothed value at the current period t is the time index of the current period and xt is the current actual value of the series. The smoothed value St is the forecast of xt 1 and is calculated as the smoothing constant times the value of the series xt in the current period plus 1 times the previous smoothed value St _1 which is the forecast of xt computed at time t 1. Double and triple exponential smoothing are derived by applying exponential smoothing to the smoothed series obtaining smoothed values as follows st2 St 1 - m S st3 St2 1 - S3_ 1 Missing values after the start of the series are replaced with one-step-ahead predicted values and the predicted value is then applied to the smoothing equations. The polynomial time trend .

• 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