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題名 以技術分析建構投資人情緒整合指標之可行性分析
Feasibility Analysis of Constructing an Integrated Investor Sentiment Indicator Using Technical Analysis
作者 王晨妍
Wang, Chen-Yan
貢獻者 郭維裕
王晨妍
Wang, Chen-Yan
關鍵詞 行為投資
投資人情緒
技術分析
Behavioral Finance
Investor Sentiment
Technical Analysis
日期 2024
上傳時間 5-Aug-2024 11:57:40 (UTC+8)
摘要 本研究旨在建立一個綜合指標，以捕捉投資人情緒與市場技術分析之間的關聯性，並探討其對股票報酬的影響。本文透過綜合多個技術指標的交易訊號，設計了一個能夠更全面地反映市場情緒和趨勢的指標。然而，實證結果顯示合併方法存在顯著的局限性，並且不如預期。這可能是由於合併過程中消除正負號交易訊號所致。儘管如此，透過修正股票報酬，本文發現綜合指標仍然呈現與股票報酬顯著正向的關聯。這表示了綜合指標在預測股票報酬方面的潛力，同時也提供了改進合併方法和進一步研究的方向。總的來說，本研究為投資者提供了一個更加全面和準確的市場分析工具，以幫助他們在複雜多變的金融市場中做出更明智的投資決策。
This study aims to establish a comprehensive index to capture the relationship between investor sentiment and market technical analysis, and to explore its impact on stock returns. By combining the trading signals of multiple technical indicators, this paper constructs an index that can more comprehensively reflect market sentiment and trends. However, empirical results show significant limitations in the combination method, falling short of expectations. This may be due to the cancellation of positive and negative trading signals during the combination process. Nevertheless, by adjusting stock returns, the study finds that the composite index still exhibits a significant positive correlation with stock returns. This indicates the potential of the composite index in predicting stock returns, while also suggesting directions for improving merging methods and further research. Overall, this study provides investors with a more comprehensive and accurate market analysis tool to assist them in making wiser investment decisions in the complex and volatile financial markets.
參考文獻 Baker, M., and Wurgler, J., 2006. Investor Sentiment in the Stock Market. Journal of Economic Perspectives 21, 129-151. Brock W., Lakonishok J., and Lebaron B., 1992. Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731-1764. Boyarchenko, N., Crump, R. K., Kovner, A., and Shachar, O. 2022. Measuring Corporate Bond Market Dislocations. FRB of New York Staff Report 957, Rev. December 2022, 69. Clewell, D., Faulkner-Macdonagh, C., Giroux, D., Page, S., and Shriver, C. 2018. Macroeconomic Dashboards for Tactical Asset Allocation. Journal of Portfolio Management, Multi-Asset Special Issue 2018, 44(2), 50-61. Eric, D., Andjelic, G., and Redzepagic, S. 2009. Application of MACD and RVI Indicators as Functions of Investment Strategy Optimization on the Financial Market. Proceedings of Rijeka Faculty of Economics, Journal of Economics and Business, 27(1), 171-196. Han, Y., Yang, K., and Zhou, G. 2010. A New Anomaly: The Cross-Sectional Profitability of Technical Analysis. Huang, D., Jiang, F., Tu, J., and Zhou, G. 2015. Investor Sentiment Aligned: A Powerful Predictor of Stock Returns. Review of Financial Studies, 28, 791-837. Liu, Y., Zhou, G., and Zhu, Y. 2021. Maximizing the Sharpe Ratio: A Genetic Programming Approach. Naved, M., and Srivastava, P. 2015. Profitability of Oscillators Used in Technical Analysis for Financial Market. Advances in Economics and Business Management （AEBM）, 2(9), 925-931. Park, C.-H., and Irwin, S. H. 2004. The Profitability of Technical Analysis: A Review. AgMAS Project Research Report, No. 2004-04. 106. Park, C.-H., and Irwin, S. H. 2007. What Do We Know About the Profitability of Technical Analysis? Journal of Economic Surveys, 21(4), 786–826. Shawn, L. K. J., Hisarli, T., and He, N. S. 2013. The Profitability of a Combined Signal Approach: Bollinger Bands and the ADX. International Federation of Technical Analysts' Journal, 2014 Edition. 7. Yen, M.-F., and Hsu, Y.-L. 2010. Profitability of Technical Analysis in Financial and Commodity Futures Markets — A Reality Check. Decision Support Systems, 50(1), 128-139. Zhou, G. 2018. Measuring Investor Sentiment. Annual Review of Financial Economics, Forthcoming, 37.
描述 碩士
國立政治大學
國際經營與貿易學系
111351033
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111351033
資料類型 thesis
dc.contributor.advisor 郭維裕zh_TW
dc.contributor.author (Authors) 王晨妍zh_TW
dc.contributor.author (Authors) Wang, Chen-Yanen_US
dc.creator (作者) 王晨妍zh_TW
dc.creator (作者) Wang, Chen-Yanen_US
dc.date (日期) 2024en_US
dc.date.accessioned 5-Aug-2024 11:57:40 (UTC+8)-
dc.date.available 5-Aug-2024 11:57:40 (UTC+8)-
dc.date.issued (上傳時間) 5-Aug-2024 11:57:40 (UTC+8)-
dc.identifier (Other Identifiers) G0111351033en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/152401-
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) 111351033zh_TW
dc.description.abstract (摘要) 本研究旨在建立一個綜合指標，以捕捉投資人情緒與市場技術分析之間的關聯性，並探討其對股票報酬的影響。本文透過綜合多個技術指標的交易訊號，設計了一個能夠更全面地反映市場情緒和趨勢的指標。然而，實證結果顯示合併方法存在顯著的局限性，並且不如預期。這可能是由於合併過程中消除正負號交易訊號所致。儘管如此，透過修正股票報酬，本文發現綜合指標仍然呈現與股票報酬顯著正向的關聯。這表示了綜合指標在預測股票報酬方面的潛力，同時也提供了改進合併方法和進一步研究的方向。總的來說，本研究為投資者提供了一個更加全面和準確的市場分析工具，以幫助他們在複雜多變的金融市場中做出更明智的投資決策。zh_TW
dc.description.abstract (摘要) This study aims to establish a comprehensive index to capture the relationship between investor sentiment and market technical analysis, and to explore its impact on stock returns. By combining the trading signals of multiple technical indicators, this paper constructs an index that can more comprehensively reflect market sentiment and trends. However, empirical results show significant limitations in the combination method, falling short of expectations. This may be due to the cancellation of positive and negative trading signals during the combination process. Nevertheless, by adjusting stock returns, the study finds that the composite index still exhibits a significant positive correlation with stock returns. This indicates the potential of the composite index in predicting stock returns, while also suggesting directions for improving merging methods and further research. Overall, this study provides investors with a more comprehensive and accurate market analysis tool to assist them in making wiser investment decisions in the complex and volatile financial markets.en_US
dc.description.tableofcontents 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 2 第三節 研究架構與流程 3 第二章 文獻回顧 5 第一節 投資人情緒指標相關研究 5 第二節 技術分析指標相關理論 6 第三節 綜合指標模型相關研究 12 第三章 研究方法 18 第一節 研究期間與資料來源 18 第二節 研究變數定義與衡量 19 第三節 研究模型設定 21 第四章 實證結果 34 第一節 技術分析指標與報酬之迴歸 34 第二節 綜合指標分析與報酬之迴歸 40 第五章 結論與未來建議 46 第一節 研究結論 46 第二節 研究建議 47 參考文獻 49zh_TW
dc.format.extent 2634447 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111351033en_US
dc.subject (關鍵詞) 行為投資zh_TW
dc.subject (關鍵詞) 投資人情緒zh_TW
dc.subject (關鍵詞) 技術分析zh_TW
dc.subject (關鍵詞) Behavioral Financeen_US
dc.subject (關鍵詞) Investor Sentimenten_US
dc.subject (關鍵詞) Technical Analysisen_US
dc.title (題名) 以技術分析建構投資人情緒整合指標之可行性分析zh_TW
dc.title (題名) Feasibility Analysis of Constructing an Integrated Investor Sentiment Indicator Using Technical Analysisen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Baker, M., and Wurgler, J., 2006. Investor Sentiment in the Stock Market. Journal of Economic Perspectives 21, 129-151. Brock W., Lakonishok J., and Lebaron B., 1992. Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731-1764. Boyarchenko, N., Crump, R. K., Kovner, A., and Shachar, O. 2022. Measuring Corporate Bond Market Dislocations. FRB of New York Staff Report 957, Rev. December 2022, 69. Clewell, D., Faulkner-Macdonagh, C., Giroux, D., Page, S., and Shriver, C. 2018. Macroeconomic Dashboards for Tactical Asset Allocation. Journal of Portfolio Management, Multi-Asset Special Issue 2018, 44(2), 50-61. Eric, D., Andjelic, G., and Redzepagic, S. 2009. Application of MACD and RVI Indicators as Functions of Investment Strategy Optimization on the Financial Market. Proceedings of Rijeka Faculty of Economics, Journal of Economics and Business, 27(1), 171-196. Han, Y., Yang, K., and Zhou, G. 2010. A New Anomaly: The Cross-Sectional Profitability of Technical Analysis. Huang, D., Jiang, F., Tu, J., and Zhou, G. 2015. Investor Sentiment Aligned: A Powerful Predictor of Stock Returns. Review of Financial Studies, 28, 791-837. Liu, Y., Zhou, G., and Zhu, Y. 2021. Maximizing the Sharpe Ratio: A Genetic Programming Approach. Naved, M., and Srivastava, P. 2015. Profitability of Oscillators Used in Technical Analysis for Financial Market. Advances in Economics and Business Management （AEBM）, 2(9), 925-931. Park, C.-H., and Irwin, S. H. 2004. The Profitability of Technical Analysis: A Review. AgMAS Project Research Report, No. 2004-04. 106. Park, C.-H., and Irwin, S. H. 2007. What Do We Know About the Profitability of Technical Analysis? Journal of Economic Surveys, 21(4), 786–826. Shawn, L. K. J., Hisarli, T., and He, N. S. 2013. The Profitability of a Combined Signal Approach: Bollinger Bands and the ADX. International Federation of Technical Analysts' Journal, 2014 Edition. 7. Yen, M.-F., and Hsu, Y.-L. 2010. Profitability of Technical Analysis in Financial and Commodity Futures Markets — A Reality Check. Decision Support Systems, 50(1), 128-139. Zhou, G. 2018. Measuring Investor Sentiment. Annual Review of Financial Economics, Forthcoming, 37.zh_TW