研究貢獻、限制與建議

本論文主要之貢獻是延續 Kamara, Lou, and Sadka (2008) 之論文研究，並 將研究時間拉長至 2018 年底，觀察過去流動性 beta 和報酬性 beta 這兩個變數是 否有延續過去的趨勢。此外，在本論文中加入周轉率這一新的變數來觀察其時間 趨勢、與其他變數之交互關係、與機構投資人持股比例之關係，讓讀者與後續研 究者更瞭解以周轉率這個變數為切入點來觀察整個市場，是否有不同的見解。最 後，本論文除了將市場上的公司以規模區分外，更利用了股票報酬波動性來分組 探討，為後續研究者開啟”公司的股票波動性是否影響投資人交易趨勢、習慣”

等議題。

在研究限制方面，本研究在探討機構投資人持有比例與周轉率 beta 之關係 時，我們的資料是從 1981 年開始計算，然而我們的周轉率 beta 是從 1963 年開始 計算，由於受限於資料庫的資料不足，因此少了快 20 年的樣本。另外，在 Kamara, Lou, and Sadka (2008) 之論文中，有將機構投資人分類成更細的類型(銀行、保 險業等等)，但礙於本論文研究資料庫之限制，因此並未能取得更詳細的研究資料。

未來若有相關研究，建議將機構投資人分類成更詳細的類型(銀行、保險業等 等)，並且能加入不同衡量流動性的指標來度測這些指標的 beta 時間趨勢，以及 這些指標的 beta 交互關係、以及這些指標的 beta 與機構投資人持有比例之關係 等。

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附錄

Appendix 1-1 流動性 beta 歷年變化 (以市值分組)

Small Large Large minus Small

Date mean t-stat mean t-stat mean t-stat p-value 1963Q1 0.509 0.224 0.553 0.530 0.043 0.222 0.133

1974Q1 0.543 0.231 0.535 0.854 -0.008 0.018 0.150

1986Q4 0.412 0.323 0.670 1.215 0.258 5.762 <0.001

1999Q3 0.312 0.231 0.528 0.322 0.216 4.480 <0.001

2012Q2 0.314 0.714 0.831 2.710 0.517 9.893 <0.001

Small Large Large minus Small

Date mean t-stat mean t-stat mean t-stat p-value

1966Q4 0.725 0.940 0.810 1.083 0.085 0.582 0.116

1979Q3 0.641 0.874 0.852 2.833 0.211 3.594 <0.001

1992Q2 0.521 0.857 0.905 3.176 0.384 9.515 <0.001

2005Q1 0.562 1.420 0.851 1.614 0.289 6.326 <0.001

2017Q4 0.556 1.050 0.847 2.634 0.291 6.617 <0.001

Small Large Large minus Small

Date mean t-stat mean t-stat mean t-stat p-value

1972Q2 0.519 0.533 0.727 1.088 0.208 6.276 <0.001

1985Q1 0.464 0.560 0.834 1.574 0.370 10.273 <0.001

1997Q4 0.540 1.117 0.714 1.442 0.173 10.313 <0.001

2010Q3 0.610 1.132 0.730 1.478 0.120 5.447 <0.001

Small Large Large minus Small

Date mean t-stat mean t-stat mean t-stat p-value 1963Q1 0.597 0.335 0.627 0.358 0.031 6.674 <0.001

1965Q1 0.604 0.295 0.621 0.324 0.017 7.966 <0.001

1977Q4 0.651 1.265 0.497 0.755 -0.154 2.941 0.003

1990Q3 0.639 1.316 0.617 1.002 -0.022 3.311 <0.001

2003Q2 0.657 0.810 0.606 0.756 -0.051 2.862 0.004

2016Q1 0.872 3.339 0.645 1.814 -0.228 2.473 0.014 2016Q2 0.895 3.794 0.684 2.312 -0.211 1.583 0.114 2016Q3 0.889 2.790 0.637 1.536 -0.252 1.727 0.084 2016Q4 0.909 4.611 0.727 2.845 -0.183 1.180 0.238 2017Q1 0.883 2.827 0.651 1.523 -0.232 1.489 0.137 2017Q2 0.889 3.089 0.701 1.772 -0.188 1.593 0.111 2017Q3 0.932 3.107 0.765 1.847 -0.167 2.203 0.028 2017Q4 0.914 4.524 0.664 2.447 -0.249 -0.507 0.612 2018Q1 0.849 3.169 0.591 1.518 -0.258 3.715 <0.001 2018Q2 0.849 2.918 0.611 1.556 -0.238 2.987 0.003 2018Q3 0.889 3.125 0.712 1.777 -0.177 2.613 0.009 2018Q4 0.907 4.483 0.806 2.988 -0.101 1.185 0.237 2019Q1 0.835 3.133 0.666 1.711 -0.169 1.011 0.313 2019Q2 0.876 3.604 0.604 1.717 -0.272 -0.318 0.751 2019Q3 0.827 3.909 0.648 2.113 -0.178 0.254 0.799 2019Q4 0.923 4.552 0.716 2.728 -0.208 -0.403 0.687