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題名 | 以灰色理論與遺傳演化類神經網路建構航空股收盤價預測模型之研究=Grey Theory and GABPN Based Grey Prediction Model for Predicting Closing Stock Prices for Major Airline Companies in Taiwan |
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作者 | 潘文超; Pan, Wen-tsao; |
期刊 | 蘭陽學報 |
出版日期 | 20060500 |
卷期 | 5 民95.05 |
頁次 | 頁130-139 |
分類號 | 563.54 |
語文 | chi |
關鍵詞 | 灰色理論; 灰色預測; 遺傳演化類神經網路; Grey theory; Grey prediction; GABPN; |
中文摘要 | 目前國內航空公司經歷了多次浩劫,例如SARS風暴,南亞大海嘯和近日的能源危機,使得海內外觀光人數迅速減少、不但影響到觀光業的發展,而且亦使得航空公司經營業績大打折扣。雖然,各家航空公司陸續推出優惠票價並與觀光飯店合作,企圖提振觀光產業的景氣,但效益如何仍值得進一步探討。 本文以國內三家知名航空公司為例,探討如何運用灰色理論、遺傳演化類神經網路與多元迴歸模型預測其短期、長期股票收盤價,並且比較此三種預測模型之優劣,最後觀察收盤價之趨勢,以提供投資人作投資分析時參考。 由研究結果顯示不論是在長期或是短期資料的情況下,灰色預測皆有很好的預測能力。 |
英文摘要 | Major catastrophes such as the SRAS epidemic, the great tsunami in South East Asia in 2004, and the recent energy crisis have not only dampened the development of the tourism industry but also greatly reduced airline companies’ sales figures. Hoping to reinvigorate the drooping industry, many airline companies have launched discount tickets and cooperated with major vacation resorts and hotels. The outcome, nonetheless, deserves more in-depth discussions. Basing the study on three well-known domestic airline companies, this paper apples the Grey Theory, the GAPBN method, and the multiple regression method to predict short- and long-term closing stock prices. It then evaluates the predictions of these three models, and lastly, tracks the trend of closing prices, which is a good source of refence for investment analysis for investors. Research result indicates that, for longer-term data and short –term data, the predictions derived from the Grey Prediction are excellent. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。