#Bubble worlds game level 138 series#

Traditional unit roots and cointegration tests have also been widely used for bubble testing. However, there are certain theoretical properties that can be clearly used for bubbles detection.

#Bubble worlds game level 138 series#

In addition, if there is a relatively short-term bubble in a long time series of data, the existence of this bubble may not be correctly recognized. Dezbakhsh and Demirguc-Kunt criticized West’s approach for size distortion in small samples, rejecting null hypotheses frequently, and being inconsistent under bubble alternative hypothesis. This method tested for the presence of a bubble on the basis of comparing asset price model with and without bubbles. West’s two-step tests were a milestone in asset price bubble test, the existence of bubbles was explicitly considered as alternative hypotheses for the first time. Marsh and Merton suggested that variance bound tests would fail when dividends and stock prices were non-stationary, and along with the small sample distortions. In fact, this method was a test of the validity of standard present value model, the rejection of null hypothesis may be due to any assumption of the model failure. Once actual price volatility exceeded the bound, there might be a bubble. Variance bound tests imposed an upper bound on stock price volatility. Early rational bubble test based on the assumption that the bubble was linear, which meant that the bubble would always exist and would not burst or start again. Rational bubble theory assumes that the actual price of an asset is equal to the sum of the present value of relevant fundamentals and the bubble component which is expected to grow at the real interest rate, meanwhile the investors have rational expectations. Irrational bubble have been studied from the perspective of behavioral finance and game theory by combining investor psychology with environmental factors, including fashion trend model, positive feedback investment strategy model, noise trader model, investor sentiment model and herd behavior model. Asset price bubble can be divided into two categories: rational bubble and irrational bubble.

The Internet stock bubble at the turn of the century, the real estate bubble, and the Bitcoin bubble are all the recognized bubble in the world. Skyrocketing price of Dutch tulip bulbs in the 1630s is regarded as the first bubble recorded in economic history. Empirical tests need to provide early warning diagnosis for bubbles to help central banks, regulators and policy makers maintain economic and financial stability. The 2008–2009 global financial turmoil triggered by US subprime mortgage crisis and its subsequent impact on commodity markets, exchange rates and real economic activity has rekindled economists’ interest in researching financial bubbles and its potential global consequences. 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.Ī large number of studies have shown that asset price bubbles and their subsequent collapse can lead to misallocation of resources and may have a serious impact on the country’s actual economic activities. In addition, frequent fluctuations imply there is a serious “herd effect” and a lack of monitoring mechanism for bubble risk. The frequent emergence of bubbles in a short time indicates that China’s stock market is still emerging market. These bubbles are liquidity-driven and presuppose a loose credit cycle, with the exception of bubbles in 2014–2015. 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). 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. 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. 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. 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. Financial bubbles have always been a topic of long-term concern for economists.