This paper examines whether subjective macroeconomic expectations predict equity risk premia in China. Using professional macro forecasts from the Wind database over 2011- 2023, we construct a composite macroeconomic expectation index via PLS. We find that the index significantly and positively predicts future equity premia both in-sample and out-ofsample, implying a countercyclical equity premium. The predictive power is robust to a wide range of macro-financial controls and delivers economically meaningful gains in portfolio allocation. Further analysis shows that controlling for forecast errors does not attenuate predictability, and the subjective index largely subsumes the information in realized macro variables, suggesting that it captures forward-looking macroeconomic conditions rather than belief bias. Cross-sectional and long-horizon results reinforce this interpretation.

Under China’s transition toward high-quality financial development, this study investigates the tail dependence among media sentiment, investor attention, and stock market returns using the M-Clayton Copula. Comparative model fitting tests demonstrate that the M-Clayton Copula outperforms both single Copula models and M-Copula models in characterizing asymmetric negative dependence structures. It is particularly effective in capturing both upper-lower and lower-upper tail dependencies, thereby providing a more comprehensive analysis of their interdependencies. The empirical results reveal three key findings. First, a significant positive tail dependence exists between media sentiment and stock market returns, suggesting that they tend to move together under extreme conditions, with notable asymmetry in the strength of co-movements. Second, media sentiment and investor attention exhibit negative tail dependence, with the lower-upper tail dependence coefficient exceeding its upper-lower counterpart, suggesting higher probability of rising investor attention following media sentiment decline than vice versa. Third, a pronounced negative tail dependence emerges between stock market returns and investor attention, particularly showing strong lower-upper tail correlation, implying substantial likelihood of increased investor attention subsequent to market downturns.

The global financial system is currently navigating a profound transformation driven by digitalization and the rise of decentralized financial innovations. In response, central banks are increasingly exploring or implementing Central Bank Digital Currencies (CBDCs) as a sovereign digital evolution of fiat money. This study investigates the dual nature of CBDCs, evaluating whether they represent a strategic opportunity to modernize the economy or a systemic threat to existing financial stability. Employing a qualitative methodology, the research analyzes official policy frameworks from the IMF and BIS alongside diverse real-world case studies, including China’s e-CNY, the Bahamas’ Sand Dollar, Nigeria’s eNaira, and the European Central Bank’s Digital Euro. The findings suggest that while CBDCs offer significant benefits—such as enhanced payment efficiency, reduced transaction costs, and improved financial inclusion—they also introduce critical risks. These include the potential disintermediation of commercial banks, heightened cybersecurity vulnerabilities, and concerns regarding individual data privacy and government surveillance. The study concludes that the successful integration of CBDCs is not merely a technical challenge but a social and strategic one. Adoption is heavily dependent on infrastructure, digital literacy, and public trust. Ultimately, the research highlights that there is no "one-size-fits-all" model; the future of money will be shaped by how effectively individual nations balance technological innovation with the preservation of financial architecture.

On October 10, 2025, Bitcoin fell 9.1% in thirty minutes on Binance following a geopolitical shock, contributing to a 16.0% peak-to-trough drawdown over 33 hours. Using minute-level Binance and Bybit data across spot, perpetual futures, and mark price feeds for BTC, ETH, and SOL, this paper situates the event within an empirical distribution of 62 BTC drawdowns exceeding 3% over 30 minutes during 2024–2026. October 10 ranks first of 62 on every microstructure metric simultaneously: a SOL futures-spot drawdown gap of 11.0 percentage points (z = +7.65), a BTC basis swing of $1,367 (z = +6.18), and a mark to-spot undershoot of $2,507 (z = −4.21). It also ranks first on multivariate anomaly measures (Mahalanobis distance 7.70; sum of absolute z-scores 45.9, 2.4 times the runner-up). A parsimonious conceptual cascade model identifies the mark price oracle as the crypto-specific amplifier.

Firms frequently overstate digital transformation in public disclosures while committing less in observable investment, a phenomenon known as digital catering. We examine whether digital public financial infrastructure can discipline such symbolic behavior. Using a staggered difference-in-differences design on Chinese A-share listed firms over 2014--2024, we find that exposure to China's e-CNY pilot reduces digital catering by roughly 14% relative to the sample mean. The decline is driven almost entirely by reduced rhetorical digital transformation, while balance-sheet-based digital commitment rises only marginally: the e-CNY pilot is associated with substantially less digital talk, but not with a commensurate increase in digital walk in the short run. The effect operates through lower agency costs and reduced information asymmetry, and follows an amplification--substitution pattern---stronger among digital-sector and accounting-opaque firms, weaker where internal controls and institutional ownership are already strong. The evidence identifies financial-transaction verifiability as a novel source of discipline over corporate cheap talk: CBDC-related infrastructure constrains unsupported symbolic claims without immediately accelerating substantive digital investment.

暂无

Against the backdrop of systemic financial risk prevention and the pursuit of a virtuous cycle in the real economy, whether Local Government Financing Vehicles (LGFVs) shareholding alleviates maturity mismatch of corporate investment and financing activities is a question of critical importance, not only for the development of individual firms but also for high-quality macroeconomic growth. Using a sample of A-share listed firms in China’s Shanghai and Shenzhen stock exchanges from 2009 to 2021, this paper theoretically analyzes and empirically tests the impact of LGFVs shareholding on corporate maturity mismatch. The empirical results indicate that LGFVs shareholding can significantly alleviate corporate maturity mismatch and the finding is still robust across a series of empirical checks. Mechanism analyses show that LGFVs shareholding improves firms’ long-term financing capacity through a resource provision channel and restrains overinvestment through a governance optimization channel, thereby collectively mitigating corporate maturity mismatch. Further analysis indicates that the mitigating effect of LGFVs shareholding is more pronounced in firms with concentrated LGFVs shareholding, firms controlled by non-state-owned capital and firms under higher economic policy uncertainty. Our findings provide valuable theoretical insights for policy design aimed at optimizing corporate financial behavior and curbing corporate financial risks.

We examine the relationship between government data opening and corporate leverage manipulation. Leveraging the staggered establishment of province-level open government data platforms in China as a quasi-natural experiment, we find that government data opening significantly reduces corporate leverage manipulation. This policy effect is more pronounced among firms with low capital intensity, firms with limited analyst coverage, and those located in regions with low banking competition. Mechanism analysis suggests that government data opening affects the cost-benefit tradeoff of corporate leverage manipulation by alleviating financing constraints and enhancing corporate governance, thereby mitigating leverage manipulation practices. Our research contributes to the literature on government data opening, highlighting its role in reducing leverage manipulation and offering valuable implications for mitigating significant financial risks.

This paper studies whether and how policies that promote a currency’s use in trade invoicing can also strengthen its role as an anchor currency in other economies’ exchange rate baskets. We exploit the establishment of RMB swap lines by the People’s Bank of China as a natural setting to examine this mechanism. We first estimate countries’ implicit currency baskets and the weights assigned to the RMB, and then use a staggered difference-in-differences design to assess the effect of initiating swap line agreements on the RMB’s weights in these baskets. Our results indicate that RMB weights increase by approximately 5% about nine months after a swap line is introduced and remain persistently higher thereafter. Finally, we develop a three-country DSGE model to interpret these findings, showing that by promoting RMB invoicing, swap lines reinforce the RMB’s role as an anchor currency for exchange rate stabilization.

The robustness of the securities market is a necessary condition for ensuring the stable operation of the financial market, and stock price fluctuations have always been a major concern for academia and investors. One of the main influencing factors of stock price fluctuations is macroeconomic monetary policy. As one of the important control tools of macroeconomic monetary policy, the impact of benchmark interest rates on stock price fluctuations cannot be ignored. This paper takes Chinese A-shares as the research object, analyzes the impact of benchmark interest rate changes on stock price fluctuations, and further introduces investor sentiment as a mediating variable to analyze its role in the transmission process of monetary policy. This paper selects monthly data of Chinese A-share listed companies from 2018 to 2024 and conducts empirical tests by constructing direct effect models and mediating effect models. The research results show that: First, benchmark interest rates have a significant negative impact on stock price fluctuations; second, benchmark interest rates can indirectly affect stock price fluctuations by influencing investor sentiment, with investor sentiment playing a partial mediating role. The research conclusions of this paper help to deepen the understanding of the transmission mechanism of monetary policy's impact on securities prices, and provide micro-evidence for monetary policymakers to assess the impact of policy adjustments on capital market stability, while also providing a reference for investors to understand the risk characteristics of the securities market under changes in the interest rate environment.