SAS/ETS software provides extensive facilities for analyzing time series and performing financial analysis.
SAS/ETS 12.1 is the latest release and introduces many new estimation features, including Bayesian options, new variable selection methods, a new data access engine, and many enhancements to existing procedures. SAS/ETS has also developed p-values based on accurate high-performance simulation methods for many popular test statistics in the AUTOREG and PANEL procedures.
Systems modeling for econometric data is done in three parts: econometric modeling, simulation, and forecasting. Often, these tasks are performed sequentially. A model is fitted to the data, then simulated with historical data, and finally used for forecasting. Models for estimation can consist of a single equation or a system of equations; they can be linear, nonlinear, or ordinary differential equations; they can require restrictions on parameters. SAS/ETS software enables you to estimate and test hypotheses for all these types of models.Time Series Analysis
Time series are any univariate or multivariate data collected over time. SAS/ETS software includes a wide range of tools for analyzing time series data. You can estimate relationships and produce forecasts that make use of information in past values, independent or explanatory variables, and indicator or dummy variables. In addition, you can model and predict the autoregressive conditional heteroscedastic (ARCH) model or its generalizations (GARCH). Additional tools provide regression analysis for linear models with distributed lags and time series cross-sectional regression analysis for panel data.
You can perform multiple regression in the presence of serially correlated error terms, fit models that allow for an error term generated by an autoregressive integrated moving-average (ARIMA) process, or use spectral analysis to decompose a series into cyclical components or to perform frequency domain tests.Automatic Forecasting
Forecasting is the combining of knowledge from the past and future expectations with an estimated model to produce likely outcomes for the future. It enables more accurate predictions of the future to be made, reducing the uncertainty inherent in the decision-making process.
Many of the SAS/ETS procedures have options that facilitate the forecasting of time series variables.The Time Series Forecasting System
SAS/ETS software includes a point-and-click application for exploring and analyzing univariate time series data. You can use the automatic model selection facility to select the best-fitting model for each time series, or you can use the system's diagnostic features and time series modeling tools interactively to develop forecasting models customized to best predict your time series. The system provides both graphical and statistical features to help you choose the best forecasting method for each series.Data Manipulation
SAS/ETS software contains tools that can be used to convert irregularly spaced data to equally spaced data, interpolate missing values, or convert time series data from one frequency to another (such as from weekly to monthly or vice versa).
Seasonal time series can be adjusted using the U.S. Bureau of the Census X11 or X12 Seasonal Adjustment algorithms, and the X11-ARIMA or X12-ARIMA methods developed by Statistics Canada.Access to Economic and Financial Databases
SAS/ETS software makes it easy to access directly many of the most popular commercially available economic and financial time series databases. Data can be extracted from files supplied by government and commercial data vendors and then converted into SAS data sets.Financial Analysis and Reporting
Widely varying credit market conditions in the past few decades have given rise to many new types of financing arrangements. SAS/ETS software provides the means to compare quickly and easily different loans, to analyze fixed and variable rate loans, to analyze buydown and balloon loans, to perform calculations, and to generate financial reports.