‧
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
不比有台灣經濟泡沫樣本之迴歸結果顯著。控制景氣循環亦改善兩個代理變數的 解釋能力，歷價比與週價比的預測能力顯著的被提升，甚至週價比在一個月的預 測期間達顯著水準。
由此可見，在月資料迴歸模型中，去除台灣經濟泡沫的確改善了兩個代理變 數的預測能力，使其能發揮身為代理變數的能力。然而，其預測能力卻仍然不具 顯著性，推測除了因為月迴歸的樣本數相對較少以外，台灣股市相對其他大國規 模小，為淺碟型市場，市場較不活絡，即使沒有了台灣泡沫經濟的影響，亦容易 受到其他因素的影響，例如：證所稅議題等。觀察圖 2 可知過去三十年台股並無 創出較多新的歷史高位，過去 52 週高位的產生也相對不如活絡的國際市場多，
故可能造成歷價比與週價比在月迴歸模型中無法成為良好的過度反應與反應不 足代理變數的情形。此顯示以月資料作為樣本的月迴歸模型並不適用在本迴歸模 型。
在最後階段本研究比較台股加權指數、TW50 指數與摩根台股指數的能見度作 比較，此三個指數之間的關聯性非常高。結果發現在控制景氣循環後，摩根台股 指數的兩個代理變數實證結果最為顯著，台股加權指數次之，而 TW50 指數居末。
顯然摩根台股指數具最高能見度，推測是因為摩根台股指數相較下在國際市場的 知名度較高，故較容易被投資人鎖定為投資定錨。此外，TW50 指數的代理變數 則以長期預測期間（3 個月以上）的預測能力較為顯著。
簡而言之，使用不同的指數作為樣本會對兩個代理變數的預測能力產生影響，
因為指數具不同程度的能見度，且不同指數捕捉到的投資人注意力程度不同，與 前述探討之投資人有限注意力與定錨假設相符。即假說二「選用能見度高的指數 作為樣本，應使週價比與歷價比更具顯著的預期未來市場報酬能力」成立。
‧
Abdullah, D. A. and S. C. Hayworth. 1993. “Macroeconometrics of Stock Price Fluctuations.” Quarterly Journal of Business and Economics 32:50–67.
Barber, B. M., and T. Odean. 2001. “Boys will Be Boys: Gender, Overconfidence, and Common Stock Investment.” Quarterly Journal of Economics 116:261-92.
Chan, L., Jegadeesh, N., Lakonishok, J. 1997. Momentum strategies. Journal of
Finance 51:1681-1713.
Chen, Roll and Ross. 1986. “Economic Forces and Stock Market”. Journal of
Business.
Cutler, D., Poterba, J., Summers, L. 1991. “Speculative dynamics.” Review of
Economic Studies 58:529-546.
De Bondt, W., Thaler, R. 1985. “Does the stock market overreact?” Journal of
Finance 40:793-805.
Edwards, W. 1968. “Conservatism in human information processing.” In: Kleinmutz, B. （Ed.）. Formal Representation of Human Judgment, John Wiley and Sons, New York, pp. 17-52.
Fama, E., French, K. 1988. “Dividend yields and expected stock returns.” Journal of
Financial Economics 22:3-25.
George, T., Hwang, C., 2004. “The 52-week high and momentum investing.” Journal
of Finance 59:2145-2176.
Griffin, D., Tversky, A. 1992. “The weighing of evidence and the determinants of confidence.” Cognitive Psychology 24:411-435.
Grinblatt, M., Keloharju, M. 2001. “What makes investors trade?” Journal of Finance 56:589-616.
‧
Jegadeesh, N., Titman, S. 1993. “Returns to buying winners and selling losers:
implications for market efficiency.” Journal of Finance 48:65-91.
Kahneman. D. 1973. Attention und effilrt. Englewood Cliffs, NJ: Prentice-Hall.
Kahneman, D., Slovic, P., Tversky, A. 1982. In: Judgment Under Uncertainty:
Heuristics and Biases Cambridge University Press, New York.
K. Geert Rouwenhorst. 1998. "International Momentum Strategies," Journal of
Finance, American Finance Association, vol. 53（1）, pages 267-284, 02.
Kleinmutz, B. （Ed.）, “Formal Representation of Human Judgment” John Wiley and
Sons, New York, pp. 17–52.
Li, J., & Yu, J. 2012. “Investor attention, psychological anchors, and stock return predictability”. Journal of Financial Economics, 104（2）, 401-419.
Ljungqvist, A., & Wilhelm, W. J. 2005. “Does prospect theory explain IPO market behavior?” the Journal of Finance, 60（4）, 1759-1790.
Moskowitz, T. J., & Grinblatt, M. 1999. “Do industries explain momentum?” The
Journal of Finance, 54（4）, 1249-1290.
Odean, T. 1998. “Are investors reluctant to realize their losses?” Journal of Finance 53:1775–1798.
Park, 1997, “Rationality of Negative Stock-Price Responses to Strong Economic Activity” Financial Analysis Journal, P53, 52-57.
Pashler, H., and J. C. Johnston. 1998. “Attentional limitations in dual-task performance”, Attention, 155-189.
Peng, L., Xiong, W. 2006. “Investor attention, over confidence, and category learning.” Journal of Financial Economics 80:563–602.
Poterba, J.M., Summers, L.H. 1988. “Mean reversion in stock returns: evidence and implications.” Journal of Financial Economics 22:27–59.
Tversky, A., Kahneman, D. 1974. “Judgment under uncertainty: heuristics and biases.” Science 185:1124–1131.
Wickens, Christopher D. 1992. Engineering psychology and human performance.
HarperCollins Publishers