We examine the pricing ofsystematic information asymmetry, induced by Chinese gov-ernment intervention, in the cross-section of stock returns. Using market-wide order im-balance as a proxy for systematic information, we observe a strong correlation betweenthe standard deviation of market-wide order imbalance and economic policy uncertainty.Furthermore, we find a significant positive relationship between the sensitivity of stocks tosystematic information asymmetry (OIBeta) and their future returns. The average monthlyreturn spread between high- and low-OIBeta portfolios ranges from 1.30% to 1.77%, andthis result remains robust after controlling for traditional risk factors. Our results providesubstantial evidence that the pricing of OIBeta is driven by systematic information asym-metry rather than alternative explanatory channels.

This study highlights asymmetries in liquidity risk pricing from the perspective of heterogeneously informed traders facing changing levels of preference uncertainty. We hypothesize that higher illiquidity premium and liquidity risk betas may arise simultaneously in circumstances where investors are asymmetrically informed about their trading counterparts’ preferences and their financial firms’ timely valuations of assets . We first test the time-varying state transition patterns of IML, a traded liquidity factor of the return premium on illiquid-minus-liquid stocks, using a Markov regime-switching framework. We then investigate how the conditional price of the systematic risk of the IML fluctuate over time subject to changing levels of preference uncertainty. Empirical results from the Chinese stock market support our hypotheses that investors’ sensitivity to the IML systematic risk conditionally increase in times of higher preference uncertainty as proxied by the stock turnover and order imbalance. Further policy impact analyses suggest that China’s market liberalization efforts, contingent upon its recent stock connect and margin trading programs, reduce the conditional price of liquidity risk for affected stocks by helping the incorporation of information into stock prices more efficiently. Tighter macroeconomic funding conditions, on the contrary, conditionally increase the price of liquidity that investors require.

We develop an information choice model where information costs are sticky and co-move with firm-level intrinsic uncertainty as opposed to temporal variations in uncertainty. Incorporating analysts' forecasts, we predict a negative relationship between information costs and information acquisition, as proxied by the predictability of analysts' forecast biases. Finally, the model shows a contrasting pattern between information acquisition and intrinsic and temporal uncertainty, where intrinsic uncertainty strengthens return predictability of analysts' biases through the information cost channel, while temporal uncertainty weakens it through the information benefit channel. We empirically confirm these opposing relationships that existing theories struggle to explain.

Based on the sample data of Chinese listed companies, this paper finds that the increase in customer concentration significantly reduces the level of enterprise employment. The research results are robust to a series of tests. Further analysis shows that the increase of financing constraints, the increase of enterprise risk and the decrease of profitability are the mechanism of customer concentration affecting enterprise employment. In addition, the negative correlation between customer concentration and enterprise employment is stronger for enterprises with small size, fierce industry competition, and increasing economic policy uncertainty.

This paper utilizes the COVID-19 pandemic as an exogenous shock to investor uncertainty and examines the effect of uncertainty on stock liquidity. Analyzing data from Chinese listed firms, we find that stock liquidity dries up significantly in response to an increase in uncertainty resulting from regional pandemic exposure. The underlying reason for the decline in stock liquidity during the pandemic is a combination of earnings and information uncertainty. Funding constraints, market panic, risk aversion, inattention rationales, and macroeconomics factors are considered in our study. Our findings corroborate the substantial impact of uncertainty on market efficiency, and also add to the discussions on the pandemic effect on financial markets.

Compared to previous literature on external FinTech, this paper is more interested in the role played by bank FinTech. Based on panel data from Chinese commercial banks spanning 2010 to 2021, this paper investigates the impact of digital transformation on bank soundness and its potential mechanisms. The empirical findings demonstrate a positive association between digital transformation and bank soundness, driven primarily by strategic and management digitization. Mechanistic analysis indicates that digital transformation improves bank soundness by mitigating risk-taking behavior and promoting diversification. The positive effect of digital transformation is more pronounced in state-owned and joint-stock banks, banks with higher liquidity mismatch as well as in sub-samples with greater levels in external FinTech development and economic policies uncertainty. Additional analysis suggests that digital transformation can still enhance bank soundness even in the presence of relatively easy monetary and macroprudential policies, highlighting the harmonization and complementarity between internal innovation from digital transformation and external regulatory policies in maintaining banking stability. Overall, this paper contributes to the literature on bank FinTech, factors influencing bank stability. And it also provides a novel explanation for the relationship between financial innovation and financial stability.

The enforcement of peer-to-peer (P2P) registration requirements in mid-2018 triggered a P2P market meltdown, highlighting the inherent challenge faced by Chinese market participants in distinguishing between genuine and fraudulent fintech firms. The difference-in-difference results suggest that the too-big-to-fail (TBTF) perception can effectively halve investor outflows and borrower outflows during periods of uncertainty. Dynamic analysis further validates the parallel-trend assumption and underscores the persistent influence of TBTF perception. Moreover, the empirical findings suggest that, in the face of a market downturn, fintech market participants become unresponsive to all other certification mechanisms, including venture capital participation, custodian banks, and third-party guarantees.

In recent decades, over 40% of dollar-denominated corporate bonds have been issued by non-US firms. Strikingly, these foreign issuers face an extra discount of 20 bps than their US counterparts. While standard risks fail to account for the discount, the Economic Policy Uncertainty index from Baker, Bloom, and Davis (2016) can explain a substantial portion of this discrepancy, consistent with uncertainty-based model calibrations. Moreover, such foreign discount (USA effect) dominates the dollar safety premium (USD effect). My findings highlight the foreign discount effect in interna- tional corporate bonds, particularly amidst escalating global economic instability and uncertainty.

This study empirically investigates the impact of dialect diversity on corporate investment efficiency under different levels of economic policy uncertainty. Our findings reveal that local dialect diversity enhances investment efficiency during stable periods, but this advantage significantly diminishes under high economic policy uncertainty. This reduction primarily arises from underinvestment and overly cautious decision-making by fragmented management during periods of turmoil. Further analysis reveals that this reduction is exacerbated by stronger internal governance, which emphasizes checks and balances, and mitigated by stronger external governance, which focuses on supervisory power. Our results remain robust when using alternative measures of main variables and employing topography as an instrumental variable.

This study investigates whether and how corporate social responsibility (CSR) affects stock liquidity. Utilizing panel data from 3,366 Chinese enterprises spanning 2010 to 2021, empirical findings suggest that CSR endeavors facilitate an uplift in stock liquidity. Specifically, a 1% increase in CSR score will improve stock liquidity by 0.128%. The research further reveals that media coverage and corporate operations are crucial channels for CSR to affect stock liquidity, with the former playing a more dominant role. Notably, the bolstering effect of CSR on stock liquidity is amplified during periods of increasing economic policy uncertainty. Heterogeneity analysis reveals that the influence of CSR on stock liquidity is particularly salient in state-owned enterprises. Additionally, different CSR subcategories (shareholder responsibility, employee responsibility, and social responsibility) vary in their effect on stock liquidity. Shareholder and employee responsibilities both enhance stock liquidity, with the impact of shareholder liability being particularly pronounced.