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This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.

Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.

This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.

This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.

In this paper, a new grey Cosine New Structured Grey Model (CNSGM(1,N)) prediction power model is constructed for the small-sample modeling and prediction problem with complex nonlinearity and insignificant volatility.

Firstly, the weight of some relevant factors is determined by the grey comprehensive correlation degree, and the data are preprocessed. Secondly, according to the principle of “new information priority” and the volatility characteristics of the sequence growth rate, the ideas of damping accumulation power index and trigonometric function are integrated into the New Structured Grey Model (NSGM(1,N)) model. Finally, the non-structural parameters are optimized by the genetic algorithm, and the structural parameters are calculated by the least squares method, so a new CNSGM(1,N) predictive power model is constructed.

Under the principle of “new information priority,” through the combination with the genetic algorithm, the traditional first-order accumulation generation is transformed into damping accumulation generation, and the trigonometric function with the idea of integer is introduced to further simulate the phenomenon that the volatility is not obvious in the real system. It is applied to the simulation and prediction of China’s carbon dioxide emissions, and compared with other comparison models; it is found that the model has a better simulation effect and excellent performance.

The main contribution of this paper is to propose a new grey CNSGM(1,N) prediction power model, which can not only be applied to complex nonlinear cases but also reflect the differences between the old and new data and can reflect the volatility characteristics of the characteristic behavior sequence of the system.

This paper aims to systematically review, discuss and synthesize the current state of research in the realm of hedge fund activism (HFA). By exploring HFA-related literature through a transparent and rigorous method, this study identifies unexplored areas for future research to develop a comprehensive understanding of the subject.

The authors perform a systematic database survey procedure as recommended in the prior literature. The review includes 74 articles published in high-impact journals from 2008 to January 2024, sourced from the Web of Science and Scopus databases and filtered using several exclusion/inclusion criteria.

This review offers a detailed analysis of the selected papers, highlighting trends in HFA research, the most influential journals and authors and additional insights into current studies. By systematically presenting the state-of-the-art, this paper categorizes the current research into three main streams and provides a critical evaluation of existing knowledge, identifying gaps and potential directions for future research.

This study makes two significant contributions to the literature. First, this study systematically reviews HFA-related research and provides a comprehensive examination of our existing scientific understanding of the factors shaping activism and its implications. Especially, this paper adopts a rigorous methodological protocol to ensure transparency and replicability in the review process, while earlier reviews focus on specific areas and are primarily narrative. Second, this study identifies research gaps and questions across all three streams of literature, offering valuable insights for future scholars aiming to expand our knowledge of the dynamic and evolving nature of HFA.