@article{oai:oiu.repo.nii.ac.jp:00000055,
 author = {石井, 康夫 and 永田, 恵子 and 竹安, 数博 and イシイ, ヤスオ and ナガタ, ケイコ and タケヤス, カズヒロ and Ishii, Yasuo and Nagata, Keiko and Takeyasu, Kazuhiro},
 issue = {2},
 journal = {国際研究論叢 : 大阪国際大学紀要, OIU journal of international studies},
 month = {Jan},
 note = {P(論文), Given that the equation of the exponential smoothing method (ESM) is equivalent to the (1,1) order ARMA model equation, a new method of estimation of the smoothing constant in the exponential smoothing method was proposed before by us which satisfied the minimum variance of forecasting
error. Generally, the smoothing constant is selected arbitrarily, but in this paper we utilize the above theoretical solution. Firstly, we estimate the ARMA model parameter and then estimate the smoothing constants. Thus the theoretical solution is derived in a simple way and may be utilized in various fields.
Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. This new method is applied to the stock market price data of Japan Real Estate Investment Trust (J-REIT), obtaining some interesting results.},
 pages = {13--32},
 title = {A Hybrid Method to Improve Forecasting Accuracy : Application to J-REIT（commerce, hotel, and logistics type）stock market  ｐrices},
 volume = {25},
 year = {2012}
}