The article chooses 453 non-financia l listed companies for the regression analysis to study the the ma in factors affecting China listed companies’ cash hold ings, using net increase in cash and cash equiva lents assets ratio(NCAR) as the change index of listed companies ’ cash hold ings, reflects both the change direction and degree of cash hold ings. According to the comprehensive analysis we find: the avera ge cash and equiva lents was increase from 2000 to 2007, and the avera ge NCAR was increasing since 2004; the avera ge NCAR of the non-sta te-controlled listed companies is higher tha n that of state-controlled ones, and the ma ximum and minimum of NCAR are all occurred in state-controlled listed companies; there exists a much significa nt correla tion between cash flow assets ratio and NCAR, the investment opportunities and the nature of domina nt stockholder have significa nt positive effects on NCAR ; and the enterprise size, profitability, the first majority shareholder sharehold ing ratio, executives sharehold ing ratio, concentration ration all have nonsignifica nt effects on NCAR.

By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imitation and herding of investors and traders and (iii) the mathematical and statistical physics of bifurcations and phase transitions, the logperiodic power law (LPPL) model has been developed as a flexible tool to detect bubbles. The LPPL model considers the faster-than-exponential (power law with finite-time singularity) increase in asset prices decorated by accelerating oscillations as the main diagnostic of bubbles. It embodies a positive feedback loop of higher return anticipations competing with negative feedback spirals of crash expectations. We use the LPPL model in one of its incarnations to analyze two bubbles and subsequent market crashes in two important indexes in the Chinese stock markets between May 2005 and July 2009. Both the Shanghai Stock Exchange Composite index (US ticker symbol SSEC) and Shenzhen Stock Exchange Component index (SZSC) exhibited such behavior in two distinct time periods: 1) from mid-2005, bursting in October 2007 and 2) from November 2008, bursting in the beginning of August 2009. We successfully predicted time windows for both crashes in advance [24, 1] with the same methods used to successfully predict the peak in mid-2006 of the US housing bubble [37] and the peak in July 2008 of the global oil bubble [26]. The more recent bubble in the Chinese indexes was detected and its end or change of regime was predicted independently by two groups with similar results, showing that the model has been well-documented and can be replicated by industrial practitioners. Here we present more detailed analysis of the individual Chinese index predictions and of the methods used to make and test them. We complement the detection of log-periodic behavior with Lomb spectral analysis of detrended residuals and (H, q)-derivative of logarithmic indexes for both bubbles. We perform unit-root tests on the residuals from the log-periodic power law model to confirm the Ornstein-Uhlenbeck property of bounded residuals, in agreement with the consistent model of ‘explosive’ financial bubbles [16].