博碩士論文 100225016 詳細資訊




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姓名 林幸怡(Hsing-yi Lin)  查詢紙本館藏   畢業系所 統計研究所
論文名稱 台灣指數上的股價報酬預測性
(The stock return predictability in TAIEX.)
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摘要(中) 本文主要研究台股加權指數(TAIEX) 分別對長期與短期的可預測性。探討股利收益
率與短期利率是否對超額報酬、股息增長與利率有預測能力。我們感興趣的目標為台
灣經濟新報(TEJ) 中的台灣加權指數, 研究時間為民國76 年1 月至民國102 年
1 月, 共313 個月。利用預測迴歸與Andrew 和Geert (2007) 所提出的預測方法,
針對所選擇的研究變數進行資料蒐集, 蒐集之對象包含每月台股加權指數之收盤價和股
利率的月資料。研究結果顯示, 股利收益率和短期利率只有在短期對超額報酬作預測有
預測性。
摘要(英) In this thesis, mainly researched data is the Taiwan capitalization weighted index (TAIEX),
the purpose of the study is to examine the predictive power of the dividend yields and short
rate for forecasting excess return, cash flows, and interest rates over long period and short
period. We use the monthly data of TAIEX in the Taiwan Economic Journal (TEJ) and
refer to Andrew and Geert ( 2007) that proposed prediction method. The data analysis in
this thesis is collected from January, 1987 to January, 2013, total of 313 months. To collect
data for the selected variables is the closing price of the monthly TAIEX and the monthly
dividend. The empirical results shows that, dividend yields predict excess returns only at
short horizon together with the short rate and do not have long-horizon predictive power.
At short horizon, the short rate predicts returns with strongly negative relationship.
關鍵字(中) ★ 預測迴歸
★ 報酬預測性
★ 台股加權指數
關鍵字(英)
論文目次 摘要i
Abstract ii
誌謝iii
目錄v
圖目次vii
表目次viii
第一章緒論1
第二章研究方法3
第三章模擬模型6
3.1 模型介紹. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.2 模擬單變數模型. . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.3 模擬雙變數模型. . . . . . . . . . . . . . . . . . . . . . . . . . . 8
第四章實證分析12
4.1 資料簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.2 資料說明. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.3 對未來超額報酬的預測性. . . . . . . . . . . . . . . . . . . . . . 13
4.4 以股利收益率預測股息增長與利率. . . . . . . . . . . . . . . . . . 14
4.4.1 股息增長的預測性. . . . . . . . . . . . . . . . . . . . . . 15
4.4.2 利率的預測性. . . . . . . . . . . . . . . . . . . . . . . . 15
第五章結論與展望20
參考文獻22
參考文獻 [1] Ang, A. and G. Bekaert (2007). “Stock Return Predictability: Is it
There?.” The Review of Financial Studies, 20, 651-707.
[2] Campbell, J.Y., and Yogo, M. (2006). “Efficient tests of stock return
predictability.” Journal of Financial Economics, 81, 27-60.
[3] Cochrane, J.H. (2008). “The dog that did not bark: A defense of return
predictability.” The Review of Financial Studies, 21, 1533-1575.
[4] Fama, E.F. and French, K.R. (1988). “Dividend yields and expected stock
returns.” Journal of Financial Economics, 22, 3-25.
[5] Hodrickl, R.J. (1992). “Dividend Yields and Expected Stock Returns:
Alternative Procedures for Inference and Measurement.” The Review of
Financial Studies, 5, 357-386.
[6] Kohei Aono and Tokuo Iwaisako (2010). “On the Predictability of
Japanese Stock Returns Using Dividend Yield.” Asia-Pacific Finan Mar-
kets, 17, 141-149.
[7] Lewllen, J. (2004). “Predictive returns with financial ratios.” Journal of
Financial Economics, 74, 209-235.
[8] Richardson, M. (1993). “Temporary Components of Stock Prices: A
Skeptic’s View.” Journal of Business and Economic Statistics, 11, 199-
207.
[9] Stambaugh, R.F. (1986). “Bias in trgressions with lagged stochastic regressors.”
Working paper series, University of Chicago, Chicago, , .
[10] Stambaugh, R.F. (1999). “Predictive Regressions.” Journal of Financial
Economics, 54, 375-421.
[11] Torous, W.,Valkanov, R. and Yan, S. (2004). “On predicting stock returns
with nearly integrated explanatory variables.” Journal of Busi-
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指導教授 傅承德 審核日期 2013-7-9
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