臺灣博碩士論文加值系統

本文以股價同步性作為公司股價反映公司特定資訊與市場公開資訊關聯之衡量指標，以檢驗並解釋股價同步性與移動平均線(MA)技術交易獲利性之關係。低股價同步性的公司，其股價具有較多資訊不確定性 (IU)，意即公司特定資訊較少反映在股價上，使其放大投資者反應不足之偏誤與股價動能效果取得溢酬。本文研究對象為台灣證券交易所與台北證券交易所之上市櫃公司股票，以1997年7月至2021年6月為研究期間，將股價同步性由低至高排序，分為5組投資組合進行測試，檢測是否與股價同步性相關資訊不確定性假設具有一致性。本文實證結果顯示，根據Fama-French 5 因子模型迴歸驗證，低股價同步性投資組合中，移動平均線策略相對於買入持有策略之年化異常報酬率高達18.05%，其高於高股價同步性投資組合策略之年化異常報酬率9.22%。考量不同加權方式投資組合、不同子樣本期間、替代移動平均線策略週期，以及控制市場狀態變數，如市場流動性、市場情緒、經濟政策不確定性以及經濟循環週期，低股價同步性投資組合中移動平均線策略仍維持有效性。

This study investigates how stock price synchronicity, as a measure of how stock prices reflect market-wide information relative to firm-specific information, explains the profitability of moving-average (MA) technical trading. The stocks of firms with less synchronicity have more information uncertainty (IU) (i.e., they reflect less firm-specific information), which amplifies investors’ underreaction bias and the price momentum effect, and are therefore more profitable. Testing a sample of stocks listed on the Taiwan and the Taipei stock exchanges over July 1997–June 2021, these provide evidence consistent with the synchronicity-related IU hypothesis. For a low-synchronicity stock price quintile portfolio, the abnormal returns of an MA strategy relative to a buy-and-hold strategy as estimated by the Fama–French 5-factor model are high at 18.05% per annum and even higher for a high-synchronicity stock price quintile portfolio (9.22% per annum). The MA strategy for low-synchronicity stock price portfolio remains more effective even when considering equally and value-weighted portfolios, testing various sub-periods, considering alternative MA lag lengths and controlling for market variables such as liquidity, sentiment, economic policy uncertainty, and economic cycle.

Table of Contents
中文摘要 ........................................................................................................................iii
ABSTRCT ...................................................................................................................... iv
誌謝 .............................................................................................................................. . v
Table of Contents ...........................................................................................................vii
List of Tables ................................................................................................................ viii
1. Introduction ............................................................................................................. 1
1.1. Research Motivation…………………………………………………….......1
1.2. Research Content……………………………………………………………2
2. Literature Review and Hypothesis Development ................................................. 7
3. Data and Methodologies ........................................................................................ 10
3.1. Sample Construction .................................................................................... 10
3.2. Summary Statistics: Synchronicity and IU .................................................. 11
3.3. Using a Moving-Average Timing Strategy on a Synchronicity- Based Portfolio ....................................................................................................... 13
3.4. Measuring the MA’s Returns on the Synchronicity-Based Portfolios ........ 14
4. MA Strategy’s Returns on the Synchronicity-Based Portfolios ............................ 16
4.1. MA Strategy’s Trading Information and Preliminary Results .................... 16
4.2. MA Strategy’s Risk-Adjusted Alphas ......................................................... 19
4.3. Robustness Checks ...................................................................................... 21
4.4. Controlling for Other Market States ............................................................ 25
5. Conclusions ........................................................................................................... 32
References ..................................................................................................................... 35


List of Tables
Table 1. Summary Statistics Sorted by Synch-based Quintiles ..................................... 12
Table 2. MA20’s Trading Information and Return Performance for Synch Quintile Portfolios ....................................................................................................................... 17
Table 3. MAP’s Risk-Adjusted Alphas for Synch Quintile Portfolios .......................... 20
Table 4. Robustness Analyses ....................................................................................... 22
Table 5. Controlling for a Variety of Market States ...................................................... 26

List of Figures
Figure 1. The Mind Map of This Study………………………...................................... 3

References
1.Abedifar, P., Bouslah, K., & Zheng, Y. (2021). Stock price synchronicity and price informativeness: Evidence from a regulatory change in the U.S. banking industry. Finance Research Letters, 40, 101678.
2.Amihud, Y. (2002). Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets, 5(1), 31-56.
3.Boubaker, S., Mansali, H., & Rjiba, H. (2014). Large controlling shareholders and stock price synchronicity. Journal of Banking and Finance, 40, 80-96.
4.Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance, 47(5), 1731-1764.
5.Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82.
6.Chan, K., & Hameed, A. (2006). Stock price synchronicity and analyst coverage in emerging markets. Journal of Financial Economics, 80(1), 115-147.
7.Chan, K., Hameed, A., & Kang, W. (2013). Stock price synchronicity and liquidity. Journal of Financial Markets, 16(3), 414-438.
8.Chen, C., Liu, L., & Zhao, N. (2020). Fear sentiment, uncertainty, and bitcoin price dynamics: The case of COVID-19. Emerging Markets Finance and Trade, 56(10), 2298-2309.
9.Chen, Y., & Zhao, H. (2012). Informed trading, information uncertainty, and price momentum. Journal of Banking and Finance, 36(7), 2095-2109.
10.Chen, C. H., Su, X. Q., & Lin, J. B. (2016). The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan. Finance Research Letters, 18, 263-272.
11.Chen, K. H., Su, X. Q., Lin, L. F., & Shih, Y. C. (2021). Profitability of moving-average technical analysis over the firm life cycle: Evidence from Taiwan. Pacific-Basin Finance Journal, 69, 101633.
12.Chue, T. K., Gul, F. A., & Mian, G. M. (2019). Aggregate investor sentiment and stock return synchronicity. Journal of Banking and Finance, 108, 105628.
13.Dang, T. L., Dang, M., Hoang, L., Nguyen, L., & Phan, H. L. (2020). Media coverage and stock price synchronicity. International Review of Financial Analysis, 67, 101430.
14.Dasgupta, S., Gan, J., & Gao, N. (2010). Transparency, Price Informativeness, and Stock Return Synchronicity: Theory and Evidence. Journal of Financial and Quantitative Analysis, 45(5), 1189-1220.
15.Durnev, A., Morck, R., Yeung, B., & Zarowin, P. (2003). Does greater firm‐specific return variation mean more or less informed stock pricing? Journal of Accounting Research, 41(5), 797-836.
16.Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22.
17.French, K. R., & Roll, R. (1986). Stock return variances: The arrival of information and the reaction of traders. Journal of Financial Economics, 17(1), 5-26.
18.Gul, F. A., Kim, J. B., & Qiu, A. A. (2010). Ownership concentration, foreign shareholding, audit quality, and stock price synchronicity: Evidence from China. Journal of Financial Economics, 95(3), 425-442.
19.Han, Y., Yang, K., & Zhou, G. (2013). A new anomaly: The cross-sectional profitability of technical analysis. Journal of Financial and Quantitative Analysis, 48(5), 1433-1461.
20.Hong, H., & Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. Journal of Finance, 54(6), 2143-2184.
21.Hong, H., Lim, T., & Stein, J. C. (2000). Bad news travels slowly: Size, analyst coverage, and the profitability of momentum strategies. Journal of Finance, 55(1), 265-295.
22.Hutton, A. P., Marcus, A. J., & Tehranian, H. (2009). Opaque financial reports, R2, and crash risk. Journal of Financial Economics, 94(1), 67-86.
23.Jiang, G., Lee, C. M. C., & Zhang, Y. (2005). Information uncertainty and expected returns. Review of Accounting Studies, 10(2-3), 185-221.
24.Jin, L., & Myers, S. C. (2006). R2 around the world: New theory and new tests. Journal of Financial Economics, 79(2), 257-292.
25.Lin, C., Yang, N. T., Chou, R. K., & Ko, K. C. (2022). A timing momentum strategy. Accounting and Finance, 62(S1), 1339-1379.
26.Mbanga, C., Darrat, A. F., & Park, J. C. (2019). Investor sentiment and aggregate stock returns: The role of investor attention. Review of Quantitative Finance and Accounting, 53(2), 397-428.
27.Morck, R., Yeung, B., & Yu, W. (2000). The information content of stock markets: Why do emerging markets have synchronous stock price movements? Journal of Financial Economics, 58(1-2), 215-260.
28.Olson, D. (2004). Have trading rule profits in the currency markets declined over time? Journal of Banking and Finance, 28(1), 85-105.
29.Park, C. H., & Irwin, S. H. (2007). What do we know about the profitability of technical analysis? Journal of Economic Surveys, 21(4), 786-826.
30.Petkova, R., & Zhang, L. (2005). Is value riskier than growth? Journal of Financial Economics, 78(1), 187-202.
31.Piotroski, J. D., & Roulstone, D. T. (2004). The influence of analysts, institutional investors, and insiders on the incorporation of market, industry, and firm‐specific information into stock prices. The Accounting Review, 79(4), 1119-1151.
32.Roll, R. (1988). R2. Journal of Finance, 43(3), 541-566.
33.Shen, H., Liu, R., Xiong, H., Hou, F., & Tang, X. (2021). Economic policy uncertainty and stock price synchronicity: Evidence from China. Pacific-Basin Finance Journal, 65, 101485.
34.Smith, D. M., Wang, N., Wang, Y., & Zychowicz, E. J. (2016). Sentiment and the effectiveness of technical analysis: Evidence from the hedge fund industry. Journal of Financial and Quantitative Analysis, 51(6), 1991-2013.
35.Wurgler, J. (2000). Financial markets and the allocation of capital. Journal of Financial Economics, 58(1-2), 187-214.
36.Xing, X., & Anderson, R. (2011). Stock price synchronicity and public firm-specific information. Journal of Financial Markets, 14(2), 259-276.
37.Zhang, X. F. (2006). Information uncertainty and stock returns. Journal of Finance, 61(1), 105-137.
38.Zhu, Y., & Zhou, G. (2009). Technical analysis: An asset allocation perspective on the use of moving averages. Journal of Financial Economics, 92(3), 519-544.