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題名 建構技術分析危機預警條件預測股市泡沫與均數復歸研究
Using Technical Analysis Indicators as Crisisi Conditions to Identify Stock Market Bubbles and Mean Reversion作者 董鍾祥
Tung, Chung-Hsiang貢獻者 廖四郎
Liao, Szu-Lang
董鍾祥
Tung, Chung-Hsiang關鍵詞 泡沫
技術指標
乖離
移動平均線
均數復歸
Bubble
Technical Indicators
Bias
Moving Average
Mean Reversion日期 2020 上傳時間 1-Jul-2020 13:40:20 (UTC+8) 摘要 回顧383年金融泡沫史，每次泡沫破裂都造成金融風暴和嚴重的經濟衰退，本文試圖運用技術分析的指標過熱且正乖離過大，建構股市泡沫的危機預警條件：隨機指標(KD)的K值和相對強弱勢指標(RSI)的6RSI值>90且乖離率位於5%～15%，作為股市泡沫之預測工具，來預測股市泡沫，期望在泡沫破裂前提早發現，降低金融風暴的衝擊。現以已開發市場中的美國、日本和德國股市，以及新興市場中的中國、巴西和南韓股市(1995-2019年)為實證對象，用技術指標的危機預警條件預測泡沫和均數復歸的時間分布。從實證結果發現，已開發市場的波動性較小，調降預警條件可提高泡沫預測準確率，其泡沫破裂時間較長約6個月而新興市場的波動性較大，調升預警條件可提高其泡沫預測準確率，其泡沫破裂的時間較短約3個月內；不論基準泡沫預警條件或調整後較佳的泡沫預警條件，都能發揮泡沫的預警作用。2020年初美股引發全球股市泡沫，在泡沫破裂前，那斯達克和標普500指數皆符合本研究的泡沫預警條件，即時且準確地發揮了預警功能，成功避開股市泡沫。另外，我們從全球主要股市驗證結果得知，泡沫破裂的時間幾乎等於均數復歸的時間，全球41個主要股市中有高達31個股市的均數復歸時間為0週，比例高達75.61%。由驗證結果推論得知，均數復歸的時間有兩種：泡沫破裂點到均數復歸的時間約為0～1週。泡沫預警點到均數復歸的時間約5週至10週之內。
Looking back on the history of the financial bubbles in 383 years, each bubble burst caused a financial turmoil and severe economic recession. This paper attempts to use technical analysis indicators to construct a crisis warning condition of the stock market bubble: The K value of the Stochastics Oscillator (KD) and the 6RSI value of the Relative Strength Index (RSI) are both greater than 90, and the Bias is between 5% and 15%. It is hoped that it can be used as a tool for predicting financial bubbles in the stock market to reduce the impact of financial turmoil. The U.S., Japan and Germany stock markets in the developed markets, and China, Brazil and South Korea stock markets in the emerging markets (1995-2019) are the empirical objects. The crisis warning conditions of the technical indicators are applied to predict the financial bubbles, and the time distribution of the mean reversion. From the empirical results, it is found that the volatilities of the developed markets are smaller, and thus lowering the warning conditions can improve the accuracy of bubble prediction, and the bubble burst time is about 6 months. The emerging markets are more volatile, and raising the warning conditions can improve the accuracy of bubble prediction, and the bubble burst time is shorter in about 3 months. Regardless of the baseline bubble warning conditions or the adjusted bubble warning conditions, the bubble warning function can be useful. At the beginning of 2020, US stocks triggered a global stock market bubble. Before the bubble burst, the Nasdaq and S&P 500 index both met the bubble warning conditions of this study. Therefore, the warning conditions immediately and accurately predicted this financial bubble. In addition, we know from the empirical results of the world`s major stock markets that the bubble burst time is almost equal to the mean reversion time. Among the 41 major stock markets in the world, the average reversion time of up to 31 stock markets is 0 weeks, with a proportion as high as 75.61%. It is inferred from the empirical results that there are two kinds of the mean reversion:The time from the bubble burst point to the mean return is approximately 0 to 1 week.The time from the bubble warning point to the mean return is about 5 weeks to 10 weeks.參考文獻 石大剛（2013）。技術分析在台港中股市之應用-全球金融危機為例。未出版之碩士論文，雲林科技大學，台灣。米楠（2015）。證券市場技術分析有效性的行為金融學論證。現代商業，14，235-237。李春安、類惠貞 (2009)。正向回饋交易與股市崩盤，中華管理評論，12，2，1-28。宋玉臣、李楠博 (2013)。 股票收益率均值回歸理論及數量方法研究[J]，商業研究，11，129-137祁紅光 (2007)。基於均值回歸理論和數量分析方法的研究。科技信息， 9。吳世農（2004）。股市泡沫的生成機理和度量。財經科學，4，6-11。林黎、任若恩（2012）。泡沫隨機臨界時點超指數膨脹模型：中國股市泡沫的檢驗與識別。系統工程理論與實踐，32，4。周愛民（1998）。股市泡沫及其檢驗方法。經濟科學，5，44-49。楊崇齡、劉錫標（2010）。技術分析有效基礎的行為金融分析。時代金融，3，24-26。潘國陵（2000）。股市泡沫研究。金融研究，7，71-79。Shiller, R.J.,（2001）。非理性繁榮。北京：中國人民大學出版社。Balvers, R., Wu, Y., & Gilliland, E. (2000). Mean reversion across national stock markets and parametric contrarian investment strategies. The Journal of Finance, 55(2), 745-772.Journal of Finance, 55, 745-772.Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of financial economics, 49(3), 307-343.Baytas, A., & Cakici, N. (1999). Do markets overreact: international evidence. Journal of Banking & Finance, 23(7), 1121-1144.Blanchard, O. J., & Watson, M. W. (1982). Bubbles, rational expectations and financial markets (No. w0945). National Bureau of economic research.Campbell, J. Y. Shiller, Robert J.(1998),“Valuation Ratios and the Long-Run Stock Market Outlook”. Journal of Portfolio Management, 24(2), 11-17.Campbell, J. Y., & Shiller, R. J. (2001). Valuation ratios and the long-run stock market outlook: An update (No. w8221). National bureau of economic research.Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under‐and overreactions. the Journal of Finance, 53(6), 1839-1885.De Bondt, W. F., & Thaler, R. (1985). Does the stock market overreact?. The Journal of finance, 40(3), 793-805.De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of political Economy, 98(4), 703-738.Diba, B. T., & Grossman, H. I. (1988). Explosive rational bubbles in stock prices?. The American Economic Review, 78(3), 520-530.Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.Evans, G. W. (1991). Pitfalls in testing for explosive bubbles in asset prices. The American Economic Review, 81(4), 922-930.Granville, J. E. (1976). Granville`s New Strategy of Daily Stock Market Timing for Maximum Profit. Prentice-Hall.Hansen, L. P., & Singleton, K. J. (1982). Generalized instrumental variables estimation of nonlinear rational expectations models. Econometrica: Journal of the Econometric Society, 1269-1286.Hong, H., & Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. The Journal of finance, 54(6), 2143-2184.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.Sornette, D., Johansen, A., & Bouchaud, J. P. (1996). Stock market crashes, precursors and replicas. Journal de Physique I, 6(1), 167-175.Johansen, A., & Sornette, D. (2000). The Nasdaq crash of April 2000: Yet another example of log-periodicity in a speculative bubble ending in a crash. The European Physical Journal B-Condensed Matter and Complex Systems, 17(2), 319-328.Johansen, A., & Sornette, D. (2001). Bubbles and anti-bubbles in Latin-American, Asian and Western stock markets: An empirical study. International Journal of Theoretical and Applied Finance, 4(06), 853-920.LeRoy, S. F., & Porter, R. D. (1981). The present-value relation: Tests based on implied variance bounds. Econometrica: Journal of the Econometric Society, 555-574.Liew, J., & Vassalou, M. (2000). Can book-to-market, size and momentum be risk factors that predict economic growth?. Journal of Financial Economics, 57(2), 221-245.Lin, L., & R.E. REN, (2012). Super-exponential bubble model with stochastic mean-reverting critical times: Application in Chinese stock market. Systems Engineering——Theory & Practice, 32(4): 673-683.Lo, A. W., & MacKinlay, A. C. (1988). Stock market prices do not follow random walks: Evidence from a simple specification test. The review of financial studies, 1(1), 41-66.Malliaropulos, D., & Priestley, R. (1999). Mean reversion in Southeast Asian stock markets. Journal of Empirical Finance, 6(4), 355-384.Mankiw, N. G., Romer, D., & Shapiro, M. D. (1985). An unbiased reexamination of stock market volatility. The Journal of Finance, 40(3), 677-687.Poterba, J. M., & Summers, L. H. (1988). Mean reversion in stock prices: Evidence and implications. Journal of financial economics, 22(1), 27-59.Santos, M. S., & Woodford, M. (1997). Rational asset pricing bubbles. Econometrica: Journal of the Econometric Society, 19-57.Shiller, R.J., (1981) Do stock prices move too much to be justified by subsequent changes in dividends. American Economic Review, 71(3), 421-436Shiller, R. J. (1990). Speculative prices and popular models. Journal of Economic perspectives, 4(2), 55-65.Shiller, R.J., (2000). Irrational Exuberance. Princeton University, NJ.Sornette, D., & Andersen, J. V. (2002). A nonlinear super-exponential rational model of speculative financial bubbles. International Journal of Modern Physics C, 13(02), 171-187.Sornette, D. (2003). Critical market crashes. Physics Reports, 378(1), 1-98.Tirole, J. (1982). On the possibility of speculation under rational expectations. Econometrica: Journal of the Econometric Society, 1163-1181.Topol, R. (1991). Bubbles and volatility of stock prices: effect of mimetic contagion. The Economic Journal, 101(407), 786-800.West, K. D. (1987). A specification test for speculative bubbles. The Quarterly Journal of Economics, 102(3), 553-580.West, K. D. (1988). Bubbles, fads and stock price volatility tests: a partial evaluation. The Journal of Finance, 43(3), 639-656.White, C. B. (2000). What P/E will the US stock market support?. Financial Analysts Journal, 56(6), 30-38. 描述 博士
國立政治大學
金融學系
103352507資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103352507 資料類型 thesis dc.contributor.advisor 廖四郎 zh_TW dc.contributor.advisor Liao, Szu-Lang en_US dc.contributor.author (Authors) 董鍾祥 zh_TW dc.contributor.author (Authors) Tung, Chung-Hsiang en_US dc.creator (作者) 董鍾祥 zh_TW dc.creator (作者) Tung, Chung-Hsiang en_US dc.date (日期) 2020 en_US dc.date.accessioned 1-Jul-2020 13:40:20 (UTC+8) - dc.date.available 1-Jul-2020 13:40:20 (UTC+8) - dc.date.issued (上傳時間) 1-Jul-2020 13:40:20 (UTC+8) - dc.identifier (Other Identifiers) G0103352507 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/130538 - dc.description (描述) 博士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 金融學系 zh_TW dc.description (描述) 103352507 zh_TW dc.description.abstract (摘要) 回顧383年金融泡沫史，每次泡沫破裂都造成金融風暴和嚴重的經濟衰退，本文試圖運用技術分析的指標過熱且正乖離過大，建構股市泡沫的危機預警條件：隨機指標(KD)的K值和相對強弱勢指標(RSI)的6RSI值>90且乖離率位於5%～15%，作為股市泡沫之預測工具，來預測股市泡沫，期望在泡沫破裂前提早發現，降低金融風暴的衝擊。現以已開發市場中的美國、日本和德國股市，以及新興市場中的中國、巴西和南韓股市(1995-2019年)為實證對象，用技術指標的危機預警條件預測泡沫和均數復歸的時間分布。從實證結果發現，已開發市場的波動性較小，調降預警條件可提高泡沫預測準確率，其泡沫破裂時間較長約6個月而新興市場的波動性較大，調升預警條件可提高其泡沫預測準確率，其泡沫破裂的時間較短約3個月內；不論基準泡沫預警條件或調整後較佳的泡沫預警條件，都能發揮泡沫的預警作用。2020年初美股引發全球股市泡沫，在泡沫破裂前，那斯達克和標普500指數皆符合本研究的泡沫預警條件，即時且準確地發揮了預警功能，成功避開股市泡沫。另外，我們從全球主要股市驗證結果得知，泡沫破裂的時間幾乎等於均數復歸的時間，全球41個主要股市中有高達31個股市的均數復歸時間為0週，比例高達75.61%。由驗證結果推論得知，均數復歸的時間有兩種：泡沫破裂點到均數復歸的時間約為0～1週。泡沫預警點到均數復歸的時間約5週至10週之內。 zh_TW dc.description.abstract (摘要) Looking back on the history of the financial bubbles in 383 years, each bubble burst caused a financial turmoil and severe economic recession. This paper attempts to use technical analysis indicators to construct a crisis warning condition of the stock market bubble: The K value of the Stochastics Oscillator (KD) and the 6RSI value of the Relative Strength Index (RSI) are both greater than 90, and the Bias is between 5% and 15%. It is hoped that it can be used as a tool for predicting financial bubbles in the stock market to reduce the impact of financial turmoil. The U.S., Japan and Germany stock markets in the developed markets, and China, Brazil and South Korea stock markets in the emerging markets (1995-2019) are the empirical objects. The crisis warning conditions of the technical indicators are applied to predict the financial bubbles, and the time distribution of the mean reversion. From the empirical results, it is found that the volatilities of the developed markets are smaller, and thus lowering the warning conditions can improve the accuracy of bubble prediction, and the bubble burst time is about 6 months. The emerging markets are more volatile, and raising the warning conditions can improve the accuracy of bubble prediction, and the bubble burst time is shorter in about 3 months. Regardless of the baseline bubble warning conditions or the adjusted bubble warning conditions, the bubble warning function can be useful. At the beginning of 2020, US stocks triggered a global stock market bubble. Before the bubble burst, the Nasdaq and S&P 500 index both met the bubble warning conditions of this study. Therefore, the warning conditions immediately and accurately predicted this financial bubble. In addition, we know from the empirical results of the world`s major stock markets that the bubble burst time is almost equal to the mean reversion time. Among the 41 major stock markets in the world, the average reversion time of up to 31 stock markets is 0 weeks, with a proportion as high as 75.61%. It is inferred from the empirical results that there are two kinds of the mean reversion:The time from the bubble burst point to the mean return is approximately 0 to 1 week.The time from the bubble warning point to the mean return is about 5 weeks to 10 weeks. 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 3第二章 文獻回顧 5第一節 金融泡沫理論與發展歷程 5第二節 檢驗股市泡沫的研究方法 9第三節 均數復歸現象 11第三章 研究方法 13第一節 泡沫預警機制 17第二節 均數復歸時間 24第四章 實證結果 25第一節 數據介紹 25第二節 調整後泡沫預警條件 27第三節 泡沫破裂時間與均數復歸時間 36第四節 延伸驗證目前(2020年)全球股市的泡沫現況 49第五章 結論與建議 103參考文獻 105 zh_TW dc.format.extent 8983615 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103352507 en_US dc.subject (關鍵詞) 泡沫 zh_TW dc.subject (關鍵詞) 技術指標 zh_TW dc.subject (關鍵詞) 乖離 zh_TW dc.subject (關鍵詞) 移動平均線 zh_TW dc.subject (關鍵詞) 均數復歸 zh_TW dc.subject (關鍵詞) Bubble en_US dc.subject (關鍵詞) Technical Indicators en_US dc.subject (關鍵詞) Bias en_US dc.subject (關鍵詞) Moving Average en_US dc.subject (關鍵詞) Mean Reversion en_US dc.title (題名) 建構技術分析危機預警條件預測股市泡沫與均數復歸研究 zh_TW dc.title (題名) Using Technical Analysis Indicators as Crisisi Conditions to Identify Stock Market Bubbles and Mean Reversion en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 石大剛（2013）。技術分析在台港中股市之應用-全球金融危機為例。未出版之碩士論文，雲林科技大學，台灣。米楠（2015）。證券市場技術分析有效性的行為金融學論證。現代商業，14，235-237。李春安、類惠貞 (2009)。正向回饋交易與股市崩盤，中華管理評論，12，2，1-28。宋玉臣、李楠博 (2013)。 股票收益率均值回歸理論及數量方法研究[J]，商業研究，11，129-137祁紅光 (2007)。基於均值回歸理論和數量分析方法的研究。科技信息， 9。吳世農（2004）。股市泡沫的生成機理和度量。財經科學，4，6-11。林黎、任若恩（2012）。泡沫隨機臨界時點超指數膨脹模型：中國股市泡沫的檢驗與識別。系統工程理論與實踐，32，4。周愛民（1998）。股市泡沫及其檢驗方法。經濟科學，5，44-49。楊崇齡、劉錫標（2010）。技術分析有效基礎的行為金融分析。時代金融，3，24-26。潘國陵（2000）。股市泡沫研究。金融研究，7，71-79。Shiller, R.J.,（2001）。非理性繁榮。北京：中國人民大學出版社。Balvers, R., Wu, Y., & Gilliland, E. (2000). Mean reversion across national stock markets and parametric contrarian investment strategies. The Journal of Finance, 55(2), 745-772.Journal of Finance, 55, 745-772.Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of financial economics, 49(3), 307-343.Baytas, A., & Cakici, N. (1999). Do markets overreact: international evidence. Journal of Banking & Finance, 23(7), 1121-1144.Blanchard, O. J., & Watson, M. W. (1982). Bubbles, rational expectations and financial markets (No. w0945). National Bureau of economic research.Campbell, J. Y. Shiller, Robert J.(1998),“Valuation Ratios and the Long-Run Stock Market Outlook”. Journal of Portfolio Management, 24(2), 11-17.Campbell, J. Y., & Shiller, R. J. (2001). Valuation ratios and the long-run stock market outlook: An update (No. w8221). National bureau of economic research.Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under‐and overreactions. the Journal of Finance, 53(6), 1839-1885.De Bondt, W. F., & Thaler, R. (1985). Does the stock market overreact?. The Journal of finance, 40(3), 793-805.De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of political Economy, 98(4), 703-738.Diba, B. T., & Grossman, H. I. (1988). Explosive rational bubbles in stock prices?. The American Economic Review, 78(3), 520-530.Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.Evans, G. W. (1991). Pitfalls in testing for explosive bubbles in asset prices. The American Economic Review, 81(4), 922-930.Granville, J. E. (1976). Granville`s New Strategy of Daily Stock Market Timing for Maximum Profit. Prentice-Hall.Hansen, L. P., & Singleton, K. J. (1982). 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