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Testing bubbles based on modified PWY method

  • Department of statistics and Finance,School of management, University of Science and Technology of China, Hefei 230026, China

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https://doi.org/10.52396/JUST-2020-1138
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  • Author Bio:

    Liu Weibo is a Master degree of University of Science and Technology of China (USTC), studying at department of statistics and Finance, School of management. Hegraduatedfromthe school of the gifted young at USTC. His research field is financial risk and financial bubbles.

  • Corresponding author: Ye Wuyi is an associate professor of school of management at University of Science and Technology of China (USTC). He received the PhD degree of Management Science and Engineering at USTC in 2016. Hisresearchfocuseson financial engineering and financial risk management. E-mail: wyye@ustc.edu.cn
  • Publish Date: 31 January 2021
    Abstract

  • Abstract

    In recent years, the identification and inspection of bubbles has appeared as an important research topic in the financial field. ADF testing method and the PWY alternative method are commonly used, with serial correlation in high-frequency financial time series. In order to remove the influence of serial correlation and be able to test the situation of multiple bubbles at the same sample period, we have made a correction to the PWY alternative method with serial correlation. The BSADF method is used to obtain the statistical sequence, and the corresponding modified critical value sequence is given based on the simulation one. According to the Shanghai Stock Index from 2000 to 2019, an empirical study was conducted based on the GSADF and the revised PWY method to identify and test the bubble phenomenon. The empirical results show that three bubbles appeared between 2000 and 2019, which is in line with the actual financial market conditions, and the traditional PWY method cannot detect all bubbles. Therefore, the GSADF and the modified PWY method given in this article can find bubbles in time and provide some guidance to identify market risks and prevent financial crises.

    Abstract

    In recent years, the identification and inspection of bubbles has appeared as an important research topic in the financial field. ADF testing method and the PWY alternative method are commonly used, with serial correlation in high-frequency financial time series. In order to remove the influence of serial correlation and be able to test the situation of multiple bubbles at the same sample period, we have made a correction to the PWY alternative method with serial correlation. The BSADF method is used to obtain the statistical sequence, and the corresponding modified critical value sequence is given based on the simulation one. According to the Shanghai Stock Index from 2000 to 2019, an empirical study was conducted based on the GSADF and the revised PWY method to identify and test the bubble phenomenon. The empirical results show that three bubbles appeared between 2000 and 2019, which is in line with the actual financial market conditions, and the traditional PWY method cannot detect all bubbles. Therefore, the GSADF and the modified PWY method given in this article can find bubbles in time and provide some guidance to identify market risks and prevent financial crises.
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    • References(13)
  • [1]
    Mao Youbi, Zhou Jun. Measurement of Stock Market Bubbles and Differentiation of Nature. Financial Research, 2007, 000(012):186-197.
    [2]
    Pan Guoling. Research on Stock Market Bubbles. Financial Research, 2000, 000(007):71-79.
    [3]
    Ferguson N . The Ascent of Money: A Financial History of the World. Journal of Global History, 2009, 4(3):509-510.
    [4]
    Robert J . SHILLER. Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?, The American Economic Review. . Bull Fed Soc Gynecol Obstet Lang Fr, 1981.
    [5]
    Engle R F , Granger C . Cointegration And Error-Correction: Representation, Estimation And Testing. Econometrica, 1987, 55(2):251-276.
    [6]
    VanNorden S, Schaller H. The predictability of stock market regime: evidence from the Toronto Stock Exchange. The Review of Economics and Statistics, 1993: 505-510.
    [7]
    Ahmed E, Rosser Jr J B,Uppal J Y. Evidence of nonlinear speculative bubbles in pacific-rim stock markets. The quarterly review of economics and finance, 1999, 39(1): 21-36.
    [8]
    Zheng Xiaoya. The long-term trend and short-term characteristics of China's equity risk premium: an empirical study combining threshold autoregressive model and BP multiple structural breakpoint test. Journal of Shandong University of Finance and Economics, 2014, 6: 24-36.
    [9]
    Cui Chang, Liu Jinquan. Analysis of Speculative Bubbles in my country's Stock Market Based on Nonlinear Coordination and Integration Relations. Finance and Economics, 2006, 2006(11): 24-30.
    [10]
    Phillips P C B, Wu Y, Yu J. Explosive behavior in the 1990s Nasdaq: When did exuberance escalate asset values?. International economic review, 2011, 52(1): 201-226.
    [11]
    Homm U , Breitung J . Testing for Speculative Bubbles in Stock Markets: A Comparison of Alternative Methods. Journal of Financial Econometrics, 2010, 10.
    [12]
    Phillips P C B, Shi S, Yu J. Testing for multiple bubbles: Historical episodes of exuberance and collapse in the S&P 500. International economic review, 2015, 56(4): 1043-1078.
    [13]
    Evans G W. Pitfalls in testing for explosive bubbles in assetprices. The American Economic Review, 1991, 81(4): 922-930.
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    [1]
    Mao Youbi, Zhou Jun. Measurement of Stock Market Bubbles and Differentiation of Nature. Financial Research, 2007, 000(012):186-197.
    [2]
    Pan Guoling. Research on Stock Market Bubbles. Financial Research, 2000, 000(007):71-79.
    [3]
    Ferguson N . The Ascent of Money: A Financial History of the World. Journal of Global History, 2009, 4(3):509-510.
    [4]
    Robert J . SHILLER. Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?, The American Economic Review. . Bull Fed Soc Gynecol Obstet Lang Fr, 1981.
    [5]
    Engle R F , Granger C . Cointegration And Error-Correction: Representation, Estimation And Testing. Econometrica, 1987, 55(2):251-276.
    [6]
    VanNorden S, Schaller H. The predictability of stock market regime: evidence from the Toronto Stock Exchange. The Review of Economics and Statistics, 1993: 505-510.
    [7]
    Ahmed E, Rosser Jr J B,Uppal J Y. Evidence of nonlinear speculative bubbles in pacific-rim stock markets. The quarterly review of economics and finance, 1999, 39(1): 21-36.
    [8]
    Zheng Xiaoya. The long-term trend and short-term characteristics of China's equity risk premium: an empirical study combining threshold autoregressive model and BP multiple structural breakpoint test. Journal of Shandong University of Finance and Economics, 2014, 6: 24-36.
    [9]
    Cui Chang, Liu Jinquan. Analysis of Speculative Bubbles in my country's Stock Market Based on Nonlinear Coordination and Integration Relations. Finance and Economics, 2006, 2006(11): 24-30.
    [10]
    Phillips P C B, Wu Y, Yu J. Explosive behavior in the 1990s Nasdaq: When did exuberance escalate asset values?. International economic review, 2011, 52(1): 201-226.
    [11]
    Homm U , Breitung J . Testing for Speculative Bubbles in Stock Markets: A Comparison of Alternative Methods. Journal of Financial Econometrics, 2010, 10.
    [12]
    Phillips P C B, Shi S, Yu J. Testing for multiple bubbles: Historical episodes of exuberance and collapse in the S&P 500. International economic review, 2015, 56(4): 1043-1078.
    [13]
    Evans G W. Pitfalls in testing for explosive bubbles in assetprices. The American Economic Review, 1991, 81(4): 922-930.
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