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淺談巨量資料之分析與應用-以臺灣市場為例

A Brief Discussion on Big Data Analyses and Applications: Evidence from Taiwan Market

摘要


近年來,巨量資料(Big Data)成功的應用在各行各業上。資料之所以成為新的價值來源,就是因為其選項價值,可以作為新的用途。臺灣證券交易所擁有之資料量規模已達巨量,而臺灣證券交易市場在巨量資料上的應用也相對領先其他行業。舉例而言,兩稅合一之抵稅額從期初每年約新台幣400至500億的水準快速成長,近年已達千餘億元。我們想瞭解政策的實施是否會影響投資人的持股或交易行為、甚至國家整體的稅收?藉由分析歷史資料,發現高股利殖利率和高稅額扣抵比率的股票在除息日前五天有顯著正的累積異常報酬率,但是除息日當天則有顯著負的異常報酬率。因而推論,綜合所得稅率低的投資人,有強烈的傾向於除息前買進高股利殖利率和高稅額扣抵比率的股票,賺取高扣抵稅額,除息後再賣出股票,此舉一來,更加造成稅收的損失。當然,若要進一步探究不同投資者之交易行為和稅額扣抵比率的相關性,就必須運用資料探勘技術進一步萃取資料,而其中也許牽涉到個人資料和隱私權的問題。

並列摘要


Big Data has been extensively used in many fields. Data has become a new value origin because of its option value which can be utilized for new purposes. Taiwan Stock Exchange has built massive amount of data and held the leading position in applications of Big Data than other industries. Taiwan has established the imputation tax system since 1998. The refundable tax credit has rapidly grown from NT$40-50 billion per year in the beginning to nearly a hundred billion in the recent year. It is interesting to understand whether an implementation of a policy affects investors' behavior of holding stocks and transactions, and the overall tax revenue of Taiwan. By analyzing historical data, for the stocks with high dividend yield and high tax credit ratio, we find that there are significantly and positively cumulative abnormal returns for the five-day period before ex-dividend days. However, there are significant and negative abnormal returns on ex-dividend days. We conclude that for getting high tax credit, investors with low tax bracket strongly prefer to buy stocks with high dividend yield and high tax credit ratio cum-dividend and sell them ex-dividend. This causes a great loss to tax revenue of the country. For further exploring the relevance between trading behavior and tax credit ratio, we need to use data mining techniques to extract information.

參考文獻


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邱怡瑄(2017)。以大數據的資料分析應用在電子商務之市場區隔〔碩士論文,朝陽科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0078-2712201714440587

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