This paper aims to clarify the relationship between key audit matters (KAMs) disclosure and corporate financialization. The findings reveal that key audit matters (KAMs) disclosure can provide incremental information value, thereby impeding corporate financialization in China. Moreover, this effect is more pronounced in the samples with low media attention, low shareholding of institutional investors, and non-state-owned enterprises. Further research indicates that reducing managerial myopia and easing financing constraints serve as key channels through which key audit matters (KAMs) disclosure affects corporate financialization. This study provides empirical evidence on efficiently preventing excessive financialization of enterprises, as well as some insights for mitigating systemic financial risks from the key audit matters (KAMs) disclosure perspective.

The corporate maturity mismatch is highly likely to trigger systemic financial risks, which is a realistic issue commonly faced by businesses. In the context of the intelligent era, the impact of artificial intelligence on maturity mismatch has emerged as a focal point of academic inquiry. Leveraging data from Chinese A-share companies over the 2011–2023 timeframe, this research employs a double machine learning approach to systematically examine the influence and underlying mechanisms of artificial intelligence on maturity mismatch. The findings reveal that artificial intelligence significantly exacerbates maturity mismatch. However, this effect is notably mitigated by government subsidies, media attention, and collectivist cultural. Further analysis indicates that in high-climate-risk scenarios, collectivist culture exerts a notably strong moderating influence. By contrast, government subsidies and media attention exhibit stronger moderating influences in low-climate-risk environments. This study constructs a multi-stakeholder collaborative governance framework, which helps to reveal the 'black box' between artificial intelligence and maturity mismatch, thereby offering a theoretical basis for monitoring maturity mismatch.

Based on the expected utility under uncertain probability distribution, we explore whether the ambiguity of individual stocks is priced in China’s A-share market and the mechanism behind the ambiguity premium phenomenon. Theoretically, when the asset price is in a specific price range, investors with ambiguity aversion do not participate in the transaction of the asset. As the ambiguity of assets increases, investors with high ambiguity aversion withdraw from the market, and investors with low ambiguity aversion remain in the market (the limited market participation phenomenon); investors who remain in the market due to lower ambiguity aversion are also willing to accept a low ambiguity premium. Empirically, we use "the volatility of the distributions of daily stock returns within a month" to measure monthly ambiguity; and find that (1) the equal-weighted average returns of the most ambiguous portfolios (top 20%) are significantly lower 1.38% than those of the least ambiguous portfolios (bottom 20%); (2) ambiguity still significantly negatively affects the cross-sectional stock return after controlling for common firm characteristics; (3) the higher the ambiguity, the lower the future trading activity, the empirical results are consistent to the theoretical predictions. Those findings reveal the mechanism of the negative ambiguity premium in the A-share market, provide new ideas for further building a factor pricing model suitable for the A-share market, and provide a fresh perspective for preventing systemic financial risk.

Based on the expected utility under uncertain probability distribution, we explore whether the ambiguity of individual stocks is priced in China’s A-share market and the mechanism behind the ambiguity premium phenomenon. Theoretically, when the asset price is in a specific price range, investors with ambiguity aversion do not participate in the transaction of the asset. As the ambiguity of assets increases, investors with high ambiguity aversion withdraw from the market, and investors with low ambiguity aversion remain in the market (the limited market participation phenomenon); investors who remain in the market due to lower ambiguity aversion are also willing to accept a low ambiguity premium. Empirically, we use "the volatility of the distributions of daily stock returns within a month" to measure monthly ambiguity; and find that (1) the equal-weighted average returns of the most ambiguous portfolios (top 20%) are significantly lower 1.38% than those of the least ambiguous portfolios (bottom 20%); (2) ambiguity still significantly negatively affects the cross-sectional stock return after controlling for common firm characteristics; (3) the higher the ambiguity, the lower the future trading activity, the empirical results are consistent to the theoretical predictions. Those findings reveal the mechanism of the negative ambiguity premium in the A-share market, provide new ideas for further building a factor pricing model suitable for the A-share market, and provide a fresh perspective for preventing systemic financial risk.

Based on the connectedness time-frequency domain decomposition method are adopted in this paper. With the help of network topology for visualization, the characteristics and transmission path of financial risks in the time-frequency domain under major emergencies are studied. The results show that after the occurrence of MPEs, the level of risk spillover in China's financial market usually decreases in the short term, medium term and long term. When the policy has a long time lag or the market reaction is not timely, the medium term risk spillover will be higher than the short term risk spillover.