Application of Stein Rules to Combination Forecasting
The authors propose some Stein-rule combination forecasting methods that are designed to ameliorate the estimation of risk inherent in making operational the variance-covariance method for constructing combination weights. By Monte Carlo simulation, it is shown that this amelioration can be substantial in many cases. Moreover, generalized Stein-rule combinations are proposed that offer the user the opportunity to enhance combination forecasting performance when shrinking the feasible variance-covariance weights toward a fortuitous shrinkage point. In an empirical exercise, the proposed Stein-rule combinations performed well relative to competing combination methods.
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Volume (Year): 9 (1991)
Issue (Month): 4 (October)
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