A method for forecasting a value of a dependent variable, such as product demand, in a future time period later than the next, upcoming future time period. The method includes selecting a dependent variable for which a value is to be forecast, gathering historical data on values of the dependent variable and explanatory variables in prior time periods, and determining a forecasting equation based on the gathered historical data. The method includes selecting a future time period that is a number of time periods beyond the next, upcoming time period. The forecasting method continues with calculating a forecasted value of the dependent variable for the selected future time period, then determining an error value by comparing the forecasted value with the historical data and based on the error value, modifying the forecasting equation to reduce the error value. The forecasting equation may be a time series forecasting equation and the determining of the forecasting equation includes initial setting values for included time series forecasting parameters. The modifying of forecast equation then includes adjusting these forecasting parameters to lower or otherwise optimize the error value. Particularly, the method includes selecting an error metric for optimization for the forecasting equation and the adjusting of the parameters is performed as a function of the selected error metric to move it toward an optimal value.