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

Area of Science:

• Financial Economics
• Econometrics
• Market Regulation

Background:

• Financial bubbles pose a persistent challenge for economists, necessitating real-time detection and dating for early warning and market stability.
• Existing research often uses stock price indices, but alternative metrics may offer a more nuanced view of market dynamics.

Purpose of the Study:

• To apply the right-tail recursive Augmented Dickey-Fuller (ADF) test to identify and date multiple financial bubbles in China's multi-level stock market.
• To utilize the ratios of the natural logarithm of real stock prices to the natural logarithm of real dividends as the primary testing metric.

Main Methods:

• Employed generalized sup ADF (GSADF) and backward sup ADF (BSADF) tests with flexible window widths for real-time bubble detection.
• Applied a right-tail recursive ADF test based on the financial present value model to China's stock market data.

Main Results:

• Identified 8 bubbles in the Main-Board Market, 6 in the Small and Medium Enterprises Board (SMEs), and 4 in the Growth Enterprise Market (GEM).
• Bubbles were predominantly liquidity-driven, linked to loose credit cycles, except for those in 2014-2015.
• Frequent bubble occurrences suggest China's stock market is still emerging, exhibiting herd behavior and lacking robust risk monitoring.

Conclusions:

• The study enhances real-time dynamic research on periodical bubbles in China's stock market.
• Findings provide an empirical reference for investor decisions, corporate financial strategies, and regulatory warning mechanisms.