Abstract
General Context: Forecasting in the market trading world has been recognized as the core decision-making imperative. Archimedes remarked: Give Me a Fulcrum, and I Shall Move the World; the simile in the market trading world is; Give Me an Effective Forecasting Model and I can make Bill Gates and Sam Walton look like Paupers. An essential aspect of creating forecasts that can inform decision-makers are confidence intervals on forecasting projections.Research Focus: The Bloomberg™ terminals [BBT] provide a treasure-trove of historical data and also, on a selected basis, single-valued forecasting projections. However, these forecasts are single-value estimates, usually one or two periods-ahead only for the Income Statement variables. The focus of this research report is to produce an interval that can be: (1) simply oriented from reported BBT-information, and (2) used to better develop a decision-context for the information accessible through the FA-link of the BBT.Results: Using forecasting models in the OLS regression-class for: Time-Series, Y = f(X) versions, and a Moving Average Model, seven forecasting capture intervals were developed from randomly selected firms offered by the BBT. These capture intervals were used to produce standardized-capture-scalar-coefficients that were applied to the reported values offered by the BBT to create one-period-ahead capture intervals. This modeling protocol is referred to as the Empirical Interval Capture Model [EICM]. The EICM produces a capture interval with precision of about 30% where the capture rate was on the order of 90%.
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