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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.7 No.3 pp.44-50

Estimation of Smoothing Constant of Minimum Variance and its Application to Industrial Data

Kazuhiro Takeyasu, 1Kazuko Nagao
Osaka Prefecture University 1-1 Gakuenchou, Sakai, Osaka-fu 599-8531, JAPAN
1Osaka Prefecture University 1-1 Gakuenchou, Sakai, Osaka-fu 599-8531, JAPAN
Selected paper from APIEMS2005


Focusing on the exponential smoothing method equivalent to (1, 1) order ARMA model equation, a new method of estimating smoothing constant using exponential smoothing method is proposed. This study goes beyond the usual method of arbitrarily selecting a smoothing constant. First, an estimation of the ARMA model parameter was made and then, the smoothing constants. The empirical example shows that the theoretical solution satisfies minimum variance of forecasting error. The new method was also applied to the stock market price of electrical machinery industry (6 major companies in Japan) and forecasting was accomplished. Comparing the results of the two methods, the new method appears to be better than the ARIMA model. The result of the new method is apparently good in 4 company data and is nearly the same in 2 company data. The example provided shows that the new method is much simpler to handle than ARIMA model. Therefore, the proposed method would be better in these general cases. The effectiveness of this method should be examined in various cases.



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