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Please use this identifier to cite or link to this item: http://ir.lib.stu.edu.tw:80/ir/handle/310903100/3075

Title: 以灰色理論探討台灣加權股價指數與有關經濟因素之研究
Apply of Grey System Theory to the TAIEX Prediction and Relation of the Relevant Economic Element
Authors: 黃筱淇
Hsiao-Chi Huang
Contributors: 經營管理研究所
許寶東
Keywords: 灰關聯分析;灰預測;GM(1,1);GM(1,N);台灣加權股價指數
Gray relational analysis;Grey prediction;GM(1,1);GM(1,N);TAIEX
Date: 2012
Issue Date: 2012-12-11 15:35:53 (UTC+8)
Publisher: 高雄市:[樹德科技大學經營管理研究所]
Abstract:   自證券商設立申請後,證券市場迅速成長,股票發展和經濟景氣關係緊密,可以發現股價不僅反應過去、現在亦或是未來的經濟活動,因此由證券交易所編製之台灣加權股價指數(TAIEX)的變動,常被視為未來景氣變化的先行指標。且近年來提倡國際金融全球化、自由化,國際股市間連動性日漸密切,掌握國際股市動態也成投資者關注的重點。
  本研究主要以灰色理論進行探討,資料數據來自於台灣經濟新報TEJ資料庫,研究以灰關聯分析進行我國股市與國際股市間連動性,以及股價指數與有關經濟因素的關聯性分析,再由分析出資料建構灰預測理論GM(1,1)模型與GM(1,N)模型,進行台灣加權股價指數未來趨勢的預測,且加入殘差檢驗及滾動檢驗以檢測此預測模型是否達到準確的效果。希望透過現實規律且簡單的灰預測模型,幫助投資者在投資時有更多的參考依據。
  灰關聯分析結果顯示,與股市關聯性較高的國際股價指數為香港恆生指數、美國NASDAQ指數、德國法蘭克福DX指數;與股市關聯性較高的有關經濟因素為WPI躉售物價指數、CPI消費者物價指數、歐元兌美元匯率。另外,實證建構出之GM(1,1)模型精確度高達98.31%;代入灰關聯性較高因子建構之二項GM(1,4)模型,其精確度高達99.58%及98.94%,以上皆預測得知股市未來發展趨勢為漸漲。且發現GM(1,N)模型比GM(1,1)模型精準度更高,可以判定加入影響股市之因子,更可表現股市變化的真實性數據。
  Since the establishment of the Securities Dealers, the securities market grew rapidly. Stock development and economic prosperity is closely related. Found stock price can reflect the past, present and future economic activity. So the TWSE compiled TAIEX change, often on behalf of the prosperity changes. In recent years to promote international financial globalization, liberalization, international stock markets are linked increasingly closely. Master the international stock market dynamic has also become a focus of investor attention.
  In this research, the gray relational analysis was applied to explore the relationship between the Taiwan stock market and the international stock markets, as well as between the stock market and relevant economic factors. Then after the analysis of data, gray prediction based on GM(1,1)model and GM(1,N)model was constructed to predict future trends in the Taiwan stock market. In addition, residual test and the rolling test were added to inspect whether this prediction model can achieve accurate results. The research fiudings should help investors to invest with more accurate decisions.
  Grey relational analysis results indicated that, the international stock index es with higher relevance to the Taiwan stock market are Hang Seng Index, NASDAQ index and DAX index. Relevance of economic factors and the Taiwan stock market relevance is higher for the WPI and CPI, Euro exchange rates USD. In addition, the empirical construct GM (1,1) has an model accuracy of 98.31%. It was substituted into the high relevance factor construct of two GM (1,4) model, with an accuracy of 99.58% and 98.94%. Research results show that the stock market future trends are predicted to rise. It was also found that the GM (1, N) model accuracy was higher than GM (1,1) model, which can be determined by adding the impact of stock market factors. The authenticity of the data can be expressed in the stock market changes.
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