本文針對臺灣股票市場建構五個具有報酬預測力的因子，包括未預期盈餘、未預期月營收、本益比差距、三大法人持股率變化與外資持股率變化，探討其在資產定價模型中的解釋能力與資訊貢獻程度。研究建構五種因子的市值加權多空投組與多頭投組，依序引入Fama and French 三因子模型（Mkt、SMB、HML）、五因子模型（另納入RMW與CMA）及六因子模型（再納入UMD）三種嵌套式模型（Nested models）進行跨度迴歸檢驗（Spanning regression）和GRS聯合檢定。

實證結果顯示，SUE、MSURGE、PEDeviation、IHP與FHP的多空投資組合及多頭投資組合皆可產生顯著的平均報酬率，且在三因子、五因子及六因子模型跨度迴歸檢測中，亦存在顯著異常報酬，表示皆具備增量資訊貢獻能力（Incremental explanatory power）。此外，為驗證何項自建因子的效果最佳，本研究在六因子模型的基礎下，每次僅增列一項自建因子並將另一項自建因子設為被解釋變數，發現僅剩未預期月營收因子於所有迴歸模型皆無法被六因子及另外四種自建因子所解釋，證實其獨立資訊含量最高。據此，本文以GRS聯合檢定將表現最佳之MSURGE納入五因子與六因子兩種嵌套式模型，以檢視模型的定價能力是否顯著提升；惟結果顯示MSURGE仍未能有效消除模型的定價誤差，暗示尚有其他風險因子未被納入。最後，本文進一步檢驗MSURGE的超額報酬係源於系統性風險補償或投資人心理偏誤；然未能獲得明確結論，有待後續研究進行更加詳盡的驗證。

This study constructs five predictive factors for the Taiwan equity market—Standardized Unexpected Earnings (SUE), Monthly Standardized Unexpected Revenue Growth Estimator (MSURGE), Price-Earnings Deviation (PEDeviation), Institutional Investors’ Stock‐Holding Percentage Change (IHP), and Foreign Institutional Investors’ Stock‐Holding Percentage Change (FHP). To examine their explanatory power and incremental informational contributions in asset-pricing models, value-weighted long–short and long-side portfolios are formed on each factor, followed by the sequential introduction of the Fama-French three-factor model (Mkt, SMB, HML), the five-factor model (adding RMW and CMA), and the six-factor model (further incorporating UMD) as three nested models for spanning-regression analysis and the GRS joint test.

The empirical results show that value-weighted long–short and long-only portfolios for SUE, MSURGE, PEDeviation, IHP, and FHP deliver significant average returns and retain significant abnormal returns in spanning tests, indicating incremental explanatory power. When each factor is added in turn to the six-factor model (with the other four as controls), only MSURGE remains unexplained, confirming its unique informational content. Using the GRS joint test, this paper then incorporates MSURGE into the five-factor and six-factor nested models to assess whether pricing improves; pricing errors persist in both cases, suggesting additional risk factors remain omitted. Given MSURGE’s strong performance, this study further tests whether its excess returns reflect compensation for systematic risk or investor behavioral biases, but the evidence is inconclusive and warrants further inquiry.

王芯儀、徐政義、陳姿伶、賴弘能，2024。因子訂價模型有效性之比較：臺灣股市實證。證券市場發展季刊，第三十六卷第二期：1-64。

林哲鵬、黃昭祥、李春安，2006。機構投資人行為與台灣股市報酬的關聯性。財務金融學刊，第十四卷第二期：111-150。

陳立文、余歆儀、紀怡禎，2016。公司本益比和產業平均本益比之間的偏離程度與橫斷面股票報酬：風險或行為？證券市場發展季刋，第二十八卷第一期：1-38。

陳柔君、劉晏睿、蕭朝興，2022。台灣股市的未預期月營收：綜合分析。管理學報，第三十九卷第四期：503-545。

顧廣平，2010。營收動能策略。管理學報，第二十七卷第三期：267-289。

顧廣平，2011。盈餘與營收動能。管理學報，第二十八卷第六期：521-544。

Bernard, V. L., & Thomas, J. K. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research, 27(1), 1–48.

Chiao, C., & Lin, K.l. (2004). The informative content of the net-buy information of institutional investors: Evidence from the Taiwan stock market. Review of Pacific Basin Financial Markets and Policies, 7(2), 259–288.
Cochrane, John, H. (2005). Asset Pricing. Revised ed., Princeton University Press.

Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. The Journal of Political Economy, 81(3), 607–636.

Fama, E. F., & French, K. R. (1992). The cross‐section of expected stock returns. Journal of Finance, 47(2), 427–465.

Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3–56.

Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1–22.

Fama, E. F., & French, K. R. (2018). Choosing factors. Journal of Financial Economics, 128, 234–252.

Gibbons, M. R., Ross, S. A., & Shanken, J. (1989). A test of the efficiency of a given portfolio. Econometrica, 57(5), 1121–1152.

Gompers, P., & Metrick, A. (2001). Institutional investors and equity prices. The Quarterly Journal of Economics, 116(1), 229–259.

Griffin, J., Ji, X., & Martin, S. (2005). Global momentum strategies. Journal of Portfolio Management, 31(1), 23–39.

Harvey, C. R., Liu, Y., & Zhu, H. (2016). …and the cross-section of expected returns. Review of Financial Studies, 29(1), 5–68.

Jegadeesh, N., & Livnat, J. (2006a). Revenue surprises and stock returns. Journal of Accounting and Economics, 41(1–2), 147–171.

Jegadeesh, N., & Livnat, J. (2006b). Post-earnings-announcement drift: The role of revenue surprises. Financial Analysts Journal, 62(2), 22–34.

Lu, Y.C., Fang, H., & Nieh, C.C. (2012). The price impact of foreign institutional herding on large stocks in Taiwan. Review of Quantitative Finance and Accounting, 39, 189–208.

Nagel, S. (2005). Short sales, institutional investors and the cross-section of stock returns. Journal of Financial Economics, 78(2), 277–309.

Shu, T. (2007). Trader composition, price efficiency, and the cross-section of stock returns. Journal of Financial Economics, 86(2), 442–475.

Pasquariello, P. (1999). The Fama MacBeth Approach Revisited. Working Paper, Stern School of Business, New York University.

Yu, H.Y., Lee, K.H., & Yun, M.S. (2019). Deviation between individual unexpected earnings and industry unexpected earnings and equity pricing: Psychological biases or risk premium? Journal of Financial Studies, 27(2), 1–42.