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Live Forecasting


Short-term forecasting for:

1. Series without clear upward/downward trend and seasonality (About)
    -- Use this Method :   Enter Data Manually
or: Paste Data From File

2. Series with upward/downward trend but no seasonality (About)

    -- Use this Method :   Enter Data Manually
  or: Paste Data From File

3. Series with upward/downward trend and seasonality (About)

Please note: this forecasting method currently only forecasts Quarterly data

    -- Use this Method :   Enter Data Manually
or: Paste Data From File
Note: If you are uncertain about which forecasting tool to use, we recommend you use #2 as it is more general.

Three methods, which we use for forecasting, belong to the wide range of exponential smoothing algorithms producing reliable short-term forecasts. Exponential smoothing is based on the concept of moving average that smoothes out the irregular fluctuations. But in contrast to pure moving average approach it gives more weight to recent observations and exponentially smaller weight to more distant observations. This technique has been successfully employed in practice to predict the future values of many types of time series, such as production, sales, or inventory data. Exponential smoothing methods under some circumstances may be more feasible, accurate, cheaper, and easier to use than more complicated forecasting techniques.

Interactive program smoothes the data (smoothing constants are estimated automatically) and produces the forecast for a required number of periods.


 

Phone: 404-894-3542
Fax: 404-894-1890
Email: haizheng.li@econ.gatech.edu

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School of Economics
Georgia Institute of Technology
Atlanta, GA-30332