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題名 基本面選股策略運用於儀表板之投資組合績效評估—以台灣半導體產業為例
Dashboard on Fundamental Stock Selection Strategy for Assets Allocation in Taiwan Semiconductor Industry
作者 莊語宸
Chuang, Yu-Chen
貢獻者 郭維裕
Kuo, Wei-Yu
莊語宸
Chuang, Yu-Chen
關鍵詞 基本面分析
會計資訊
動能策略
選股策略
儀表板
投資組合配置
超額報酬率
多空策略
半導體產業
Fundamental
Accounting information
Momentum
Stock selection
Dashboard
Excess return
Long-short strategy
Semiconductor
日期 2021
上傳時間 1-Jul-2021 16:01:09 (UTC+8)
摘要 本研究以基本面的角度切入股市,運用多項常見之22項財務指標以及動能策略,建立一個新的選股方法,以儀表板(dashboard)視覺化的方式呈現買進及賣出訊號,並將此資產配置方法運用於台股之半導體產業中,最後依據所組成之投資組合績效來評估本研究採用之基本面選股方法,以檢視上述基本面指標是否有預測未來股價走向之能力。本研究以2005年第二季至2020年第三季台股半導體產業之72家標的公司作為研究樣本,並設定50%、60%與70%三種命中率(hit rate),以及持有投資組合一個月、兩個月與三個月,共九種情形做為不同狀況之分析。採用全樣本做為研究對象時,持有兩個月以及三個月之投資組合績效明顯優於大盤,其中,又以持有三個月投資組合之績效最佳,報酬率大幅優於同期大盤之報酬率;採用五年期滾動(rolling)預測時,在所有情況下,本研究之投資組合績效優於大盤的比率皆大於50%,又以命中率為70%的情況下表現最佳。上述結果於命中率設定為50%下並持有一個月及兩個月,以及命中率設定為70%下並持有兩個月之投資組合績效在90%信心水準下顯著。此外,將本實驗結果於套用本資產定價模型(CAPM)時,在命中率設定為60%下,其超額報酬最為顯著,超額報酬分別為1.85%、4.41%以及8.23%。其中,持有兩個月及三個月之投資組合之超額報酬於99%信心水準下仍為顯著,而顯著性在命中率設定為50%時次之。因此,依據本研究之基本面選股策略,可增強對於個股標的股價未來走勢的預測能力。
This research uses 22 financial indicators and momentum strategies to establish a new stock selection method, and visualizes whether to long or short in a dashboard. Applying this asset allocation method to the Taiwanese semiconductor industry, and at the end of this study we examine whether these fundamental indicators have the ability to predict price. This study uses 72 companies in the Taiwanese semiconductor industry from the 2005 Q2 to 2020 Q3 as sample, and sets three hit rates:50%, 60%, and 70%, as well as holding portfolios 1 month, 2 months and 3 months.When using full sample, the return of the two and three-month portfolios is largely better than that of the market. When using the five-year rolling forecast, in all cases, the rate of the portfolio return outperforming the market is greater than 50%, and the best return is when the hit rate is 70%. From the above results, when the hit rate is set to 50% and held for one and two months, also the hit rate is set to 70% and held for two months, their return are significant under the 90% confidence level. In addition, when the results are applied to CAPM, the excess returns are most significant when the hit rate is set to 60% which are 1.85%, 4.41%, and 8.23%, respectively. The excess return of the portfolio held for two and three months is significant under the 99% confidence level, and the significance takes second place when the hit rate is set to 50%. Therefore, based on the stock selection strategy of this research, the ability to predict the future prices of stocks can be enhanced.
參考文獻 1. Clewell, D., Faulkner-Macdonagh, C., Giroux, D., Page, S., & Shriver, C. (2017). Macroeconomic Dashboards for Tactical Asset Allocation. The Journal of Portfolio Management, 44(2), 50-61.

2. Piotroski, J. D. (2000). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, 1-41.

3. Abarbanell, J. S., & Bushee, B. J. (1997). Fundamental analysis, future earnings, and stock prices. Journal of Accounting Research, 35(1), 1-24.

4. Kok, U. W., Ribando, J., & Sloan, R. (2017). Facts about formulaic value investing. Financial Analysts Journal, 73(2), 81-99.

5. Asness, C., Frazzini, A., Israel, R., & Moskowitz, T. (2015). Fact, fiction, and value investing. The Journal of Portfolio Management, 42(1), 34-52.

6. Haghani, V., & Dewey, R. (2016). A case study for using value and momentum at the asset class level. The Journal of Portfolio Management, 42(3), 101-113.

7. Dimson, E., Marsh, P., & Staunton, M. (2017). Factor-based investing: The long-term evidence. The Journal of Portfolio Management, 43(5), 15-37.

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

9. Arnott, R. D., Hsu, J., & Moore, P. (2005). Fundamental indexation. Financial Analysts Journal, 61(2), 83-99.

10. Hou, K., Xue, C., & Zhang, L. (2020). Replicating anomalies. The Review of Financial Studies, 33(5), 2019-2133.

11. Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.

12. Asness, C., Frazzini, A., Israel, R., & Moskowitz, T. (2014). Fact, fiction, and momentum investing. The Journal of Portfolio Management, 40(5), 75-92.

13. Ko, K. C., Lin, S. J., Su, H. J., & Chang, H. H. (2014). Value investing and technical analysis in Taiwan stock market. Pacific-Basin Finance Journal, 26, 14-36.

14. Sloan, R. G. (1996). Do stock prices fully reflect information in accruals and cash flows about future earnings?. Accounting Review, 289-315.

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

16. 朱詩桓(2014)。「價值投資:選股策略之投資績效」,國立政治大學商學院金融學系碩士班碩士論文。
描述 碩士
國立政治大學
國際經營與貿易學系
108351011
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108351011
資料類型 thesis
dc.contributor.advisor 郭維裕zh_TW
dc.contributor.advisor Kuo, Wei-Yuen_US
dc.contributor.author (Authors) 莊語宸zh_TW
dc.contributor.author (Authors) Chuang, Yu-Chenen_US
dc.creator (作者) 莊語宸zh_TW
dc.creator (作者) Chuang, Yu-Chenen_US
dc.date (日期) 2021en_US
dc.date.accessioned 1-Jul-2021 16:01:09 (UTC+8)-
dc.date.available 1-Jul-2021 16:01:09 (UTC+8)-
dc.date.issued (上傳時間) 1-Jul-2021 16:01:09 (UTC+8)-
dc.identifier (Other Identifiers) G0108351011en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/135896-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 國際經營與貿易學系zh_TW
dc.description (描述) 108351011zh_TW
dc.description.abstract (摘要) 本研究以基本面的角度切入股市,運用多項常見之22項財務指標以及動能策略,建立一個新的選股方法,以儀表板(dashboard)視覺化的方式呈現買進及賣出訊號,並將此資產配置方法運用於台股之半導體產業中,最後依據所組成之投資組合績效來評估本研究採用之基本面選股方法,以檢視上述基本面指標是否有預測未來股價走向之能力。本研究以2005年第二季至2020年第三季台股半導體產業之72家標的公司作為研究樣本,並設定50%、60%與70%三種命中率(hit rate),以及持有投資組合一個月、兩個月與三個月,共九種情形做為不同狀況之分析。採用全樣本做為研究對象時,持有兩個月以及三個月之投資組合績效明顯優於大盤,其中,又以持有三個月投資組合之績效最佳,報酬率大幅優於同期大盤之報酬率;採用五年期滾動(rolling)預測時,在所有情況下,本研究之投資組合績效優於大盤的比率皆大於50%,又以命中率為70%的情況下表現最佳。上述結果於命中率設定為50%下並持有一個月及兩個月,以及命中率設定為70%下並持有兩個月之投資組合績效在90%信心水準下顯著。此外,將本實驗結果於套用本資產定價模型(CAPM)時,在命中率設定為60%下,其超額報酬最為顯著,超額報酬分別為1.85%、4.41%以及8.23%。其中,持有兩個月及三個月之投資組合之超額報酬於99%信心水準下仍為顯著,而顯著性在命中率設定為50%時次之。因此,依據本研究之基本面選股策略,可增強對於個股標的股價未來走勢的預測能力。zh_TW
dc.description.abstract (摘要) This research uses 22 financial indicators and momentum strategies to establish a new stock selection method, and visualizes whether to long or short in a dashboard. Applying this asset allocation method to the Taiwanese semiconductor industry, and at the end of this study we examine whether these fundamental indicators have the ability to predict price. This study uses 72 companies in the Taiwanese semiconductor industry from the 2005 Q2 to 2020 Q3 as sample, and sets three hit rates:50%, 60%, and 70%, as well as holding portfolios 1 month, 2 months and 3 months.When using full sample, the return of the two and three-month portfolios is largely better than that of the market. When using the five-year rolling forecast, in all cases, the rate of the portfolio return outperforming the market is greater than 50%, and the best return is when the hit rate is 70%. From the above results, when the hit rate is set to 50% and held for one and two months, also the hit rate is set to 70% and held for two months, their return are significant under the 90% confidence level. In addition, when the results are applied to CAPM, the excess returns are most significant when the hit rate is set to 60% which are 1.85%, 4.41%, and 8.23%, respectively. The excess return of the portfolio held for two and three months is significant under the 99% confidence level, and the significance takes second place when the hit rate is set to 50%. Therefore, based on the stock selection strategy of this research, the ability to predict the future prices of stocks can be enhanced.en_US
dc.description.tableofcontents 第一章 緒論 1
第二章 文獻回顧 3
第三章 研究方法 9
第一節 樣本頻率與期間 9
第二節 樣本資料選定 11
第三節 資料處理 13
第四章 研究結果 21
第一節 樣本敘述統計量 21
第二節 全樣本測試 23
第三節 五年滾動式樣本測試 43
第五章 結論與建議 51
第一節 研究結論 51
第二節 研究貢獻 52
第三節 研究限制與建議 53
一、樣本限制 53
二、模型限制 53
參考文獻 54
附錄 56
zh_TW
dc.format.extent 4626194 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108351011en_US
dc.subject (關鍵詞) 基本面分析zh_TW
dc.subject (關鍵詞) 會計資訊zh_TW
dc.subject (關鍵詞) 動能策略zh_TW
dc.subject (關鍵詞) 選股策略zh_TW
dc.subject (關鍵詞) 儀表板zh_TW
dc.subject (關鍵詞) 投資組合配置zh_TW
dc.subject (關鍵詞) 超額報酬率zh_TW
dc.subject (關鍵詞) 多空策略zh_TW
dc.subject (關鍵詞) 半導體產業zh_TW
dc.subject (關鍵詞) Fundamentalen_US
dc.subject (關鍵詞) Accounting informationen_US
dc.subject (關鍵詞) Momentumen_US
dc.subject (關鍵詞) Stock selectionen_US
dc.subject (關鍵詞) Dashboarden_US
dc.subject (關鍵詞) Excess returnen_US
dc.subject (關鍵詞) Long-short strategyen_US
dc.subject (關鍵詞) Semiconductoren_US
dc.title (題名) 基本面選股策略運用於儀表板之投資組合績效評估—以台灣半導體產業為例zh_TW
dc.title (題名) Dashboard on Fundamental Stock Selection Strategy for Assets Allocation in Taiwan Semiconductor Industryen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 1. Clewell, D., Faulkner-Macdonagh, C., Giroux, D., Page, S., & Shriver, C. (2017). Macroeconomic Dashboards for Tactical Asset Allocation. The Journal of Portfolio Management, 44(2), 50-61.

2. Piotroski, J. D. (2000). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, 1-41.

3. Abarbanell, J. S., & Bushee, B. J. (1997). Fundamental analysis, future earnings, and stock prices. Journal of Accounting Research, 35(1), 1-24.

4. Kok, U. W., Ribando, J., & Sloan, R. (2017). Facts about formulaic value investing. Financial Analysts Journal, 73(2), 81-99.

5. Asness, C., Frazzini, A., Israel, R., & Moskowitz, T. (2015). Fact, fiction, and value investing. The Journal of Portfolio Management, 42(1), 34-52.

6. Haghani, V., & Dewey, R. (2016). A case study for using value and momentum at the asset class level. The Journal of Portfolio Management, 42(3), 101-113.

7. Dimson, E., Marsh, P., & Staunton, M. (2017). Factor-based investing: The long-term evidence. The Journal of Portfolio Management, 43(5), 15-37.

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

9. Arnott, R. D., Hsu, J., & Moore, P. (2005). Fundamental indexation. Financial Analysts Journal, 61(2), 83-99.

10. Hou, K., Xue, C., & Zhang, L. (2020). Replicating anomalies. The Review of Financial Studies, 33(5), 2019-2133.

11. Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.

12. Asness, C., Frazzini, A., Israel, R., & Moskowitz, T. (2014). Fact, fiction, and momentum investing. The Journal of Portfolio Management, 40(5), 75-92.

13. Ko, K. C., Lin, S. J., Su, H. J., & Chang, H. H. (2014). Value investing and technical analysis in Taiwan stock market. Pacific-Basin Finance Journal, 26, 14-36.

14. Sloan, R. G. (1996). Do stock prices fully reflect information in accruals and cash flows about future earnings?. Accounting Review, 289-315.

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

16. 朱詩桓(2014)。「價值投資:選股策略之投資績效」,國立政治大學商學院金融學系碩士班碩士論文。
zh_TW
dc.identifier.doi (DOI) 10.6814/NCCU202100556en_US