Expanded BSADF test in the presence of breaks in time trend – a further analysis on the recent bubble phenomenon in China’s stock market

Yu, Jiyu; Ma, Zixiang

doi:10.1080/13504851.2018.1438578

Cited by 3 publications

(2 citation statements)

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“…Nonlinear methods are also widely used to detect bubbles in China’s stock market. For example, Deng et al [ 30 ], Zhang, Xu and Zhai [ 31 ] and Yu and Ma [ 32 ] adopted SADF test to conduct bubble testing and dating on China’s stock market. Most of the researchers only adopt price series to detect China’s capital market bubble without considering dividends when they use the right-tail recursive unit root test proposed by PWY [ 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Deng et al [ 30 ], Zhang, Xu and Zhai [ 31 ] and Yu and Ma [ 32 ] adopted SADF test to conduct bubble testing and dating on China’s stock market. Most of the researchers only adopt price series to detect China’s capital market bubble without considering dividends when they use the right-tail recursive unit root test proposed by PWY [ 31 , 32 ]. It does not conform to the specification of test model and cannot be theoretically supported.…”

Section: Introductionmentioning

confidence: 99%

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Research on multiple bubbles in China’s multi-level stock market

Xiao

Yang

et al. 2021

PLoS ONE

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Financial bubbles have always been a topic of long-term concern for economists. Understanding bubble phenomenon and dating the period of bubbles in real time can provide an early warning diagnosis for financial bubbles and help regulatory authorities to control it and maintain market order. The generalized sup ADF (GSADF) and backward sup ADF (BSADF) tests with flexible window width can effectively detect and date periodically collapsing bubbles in real time. Based on the financial present value model, this paper applies right-tail recursive ADF test to test multiple bubbles in China’s multi-level stock market. Unlike the other researches in China, the ratios of the real stock prices’ natural logarithm to the real dividends’ natural logarithm are used for our testing instead of stock price index. Empirical results show that there are 8 bubbles in the Main-Board Market, 6 bubbles in the Small and Medium Enterprises Board (SMEs), and 4 bubbles in the Growth Enterprise Market (GEM). These bubbles are liquidity-driven and presuppose a loose credit cycle, with the exception of bubbles in 2014–2015. The frequent emergence of bubbles in a short time indicates that China’s stock market is still emerging market. In addition, frequent fluctuations imply there is a serious “herd effect” and a lack of monitoring mechanism for bubble risk. This study not only enrich the real-time dynamic research on periodical bubbles of China’s stock market, but also provide an empirical reference for investors’ investment choices, financial decisions of listed companies and warning mechanism of regulatory authorities.

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