Mutual funds, tunneling and firm performance:evidence from China

© 2019, The Author(s). In contrast to US companies, Chinese firms have concentrated ownership with the effect that the central agency problem emanates from controlling shareholders expropriating minority shareholders, a phenomenon referred to as ‘tunneling’. This study examines the monitoring effect of mutual funds on the tunneling behavior of controlling shareholders. Due to the distinctive institutional settings in China, including a high level of ownership concentration, underdeveloped legal system in the stock markets and weak governance mechanisms in the mutual fund industry, we find that an increase in mutual fund ownership effectively mitigates the tunneling behavior of controlling shareholders thus improving firm performance. Nonetheless, after the mutual fund ownership reaches a certain threshold, an increase in concentrated mutual fund ownership is associated with heavier tunneling and lower firm performance. This may suggest that concentrated mutual funds collude with controlling shareholders in order to preserve their private interests. Moreover, the above effects are found to be more pronounced for firms with heavier tunneling activities. Our finding of the non-monotonic monitoring role of mutual funds brings attention to the private interest theory for mutual funds, an aspect that has been largely ignored in previous studies on mutual funds

Multiscale Fluctuation Features of the Dynamic Correlation between Bivariate Time Series

The fluctuation of the dynamic correlation between bivariate time series has some special features on the time-frequency domain. In order to study these fluctuation features, this paper built the dynamic correlation network models using two kinds of time series as sample data. After studying the dynamic correlation networks at different time-scales, we found that the correlation between time series is a dynamic process. The correlation is strong and stable in the long term, but it is weak and unstable in the short and medium term. There are key correlation modes which can effectively indicate the trend of the correlation. The transmission characteristics of correlation modes show that it is easier to judge the trend of the fluctuation of the correlation between time series from the short term to long term. The evolution of media capability of the correlation modes shows that the transmission media in the long term have higher value to predict the trend of correlation. This work does not only propose a new perspective to analyze the correlation between time series but also provide important information for investors and decision makers