This paper investigates the high-frequency dynamics of macroeconomic expectations and disagreement among professional forecasters. We propose a novel mixed-frequency estimation approach that integrates daily asset returns with quarterly expectation data from the Survey of Professional Forecasters. Our findings indicate that consensus forecasts are updated efficiently according to Bayes' rule, independent of prior forecasts. By employing "representative forecasters" as proxies for real-world agents, we derive a simple yet intuitive evolution equation for disagreement, revealing that changes in disagreement are primarily driven by different interpretations of new information. Furthermore, we reconstruct daily series of expectations and disagreement concerning macroeconomic growth, achieving impressive R2 values of 93.3% and 84.5% against the true quarterly series.

Despite nearly twenty years of privatization, mixed-ownership reform has been the mainstay of SOE reform in China in recent years. This raises the question of whether the financial performance of mixed-ownership firms (Mixed firms) is better than private-owned enterprises (POEs). Although Mixed firms suffer more from government intervention, unclear property rights, and interest conflicts between state shareholders and private shareholders, they can also benefit from the external resources controlled by the state. Therefore, the performance of Mixed firms is still unclear. Collecting data from the Chinese A-share listed market, we divide the firms into POEs, Mixed firms controlled by the state (MixedSOEs), and Mixed firms controlled by the private sectors (MixedPOEs). Measuring profitability using ROA and ROE, we find that on average, POEs perform better than Mixed firms, and MixedPOEs have a higher profitability than MixedSOEs. Within Mixed firms, more state shares are related to lower profitability, and more private shares are related to higher profitability. Using the NBS survey data, we further find that on average, SOEs exhibit the lowest profitability, with MixedSOEs and MixedPOEs in the middle, and POEs have the highest profitability. We try to address the endogeneity challenge in several ways and get similar results. Overall, our analysis provides new evidence on the financial performance of mixed-ownership firms.

There is mixed evidence of a positive relationship between the stock market risk and return. We reexamine this critical implication of asset pricing theory using fresh data from China's stock market, which is largely segmented from the rest of the global financial market. Using formal variable selection methods and a comprehensive set of predictor variables, we identify conditional market variance, scaled market prices, and inflation as crucial determinants of equity premiums. The estimated simple risk-return relationship exhibits downward omitted variable bias, which underlines the importance of considering multiple factors to explain the variation in equity premiums. We cannot wholly attribute the three-factor conditional equity premium model to data mining, as Guo, Sanni, and Yu (2022) select the same model for the U.S. stock market. These findings challenge existing asset pricing models and provide valuable guidance for future theoretical research.

In the era of digital economy, although the production (labor) tools of enterprises are digitalized, intelligent, and networked, and new characteristics and scenarios have emerged in enterprise operation and labor methods, the human capital possessed by workers has become the driving force for the sustainable development of entrepreneurial enterprises. Workers who master digital technology play a decisive role in the sustainable and healthy development of entrepreneurial enterprises. The article points out that in the era of digital economy, human capital is a key factor for economic growth and development. In the fields of mixed ownership and private economy, the employment system will gradually "retire", and modern partnership systems will prevail; The modern partnership system can motivate partners to collaborate and innovate, which is an upgrade of the manager system; The article briefly introduces the advantages and disadvantages of the dual ownership structure and the dynamic equity distribution mechanism of start-up companies; And the achievements made by Xiaomi Group, Huawei Company, and Midea Group in implementing a business partnership system.

China’s emissions trading system applies a two-stage emissions intensity-based compliance quota allocation scheme different from the cap-and-trade systems prevalent in developed economies. It was designed to accommodate the country’s socioeconomic complexities and implemented following a learning-by-doing approach. Compliance firms significantly expanded green investment and production workforce. Their climate decisions are influenced by state ownership and regional heterogeneity. State-owned enterprises (SOEs) and less liberal market firms increased hiring, but not investment; non-SOEs and more liberal market firms grew investment. There are mixed welfare effects: compliance firms maintained productivity and efficiency; however, ordinary workers’ real wages were reduced, more prominent in SOEs.

This paper selects Chinese A-share listed manufacturing companies from 2011 to 2020 as a research sample and analyzes the impact of economic policy uncertainty on business performance. We find that economic policy uncertainty is detrimental to the improvement of business performance; service transformation can significantly offset the adverse effect of economic policy uncertainty on business performance, and this positive effect will increase with the depth of service transformation, Furthermore, embedded service transformation is more effective than mixed service transformation in weaking the adverse effects of economic policy uncertainty on business performance. The results of the heterogeneity test show that the negative relationship between economic policy uncertainty and firm business performance, as well as the positive effect of servitization transformation, is more noticeable in non-state-owned enterprises and low sale growth firms. The results are robust after various specifications of variables, possible endogeneity issues, and more control variables are considered.

In the era of big data, asset pricing is influenced by various factors, which are extracted from multi-source heterogeneous information, such as high frequency market and sentiment information, low frequency firm characteristic and macroeconomic information. Especially, low frequency policy information plays a significant role in the long-term pricing in China but it is barely investigated due to its textual form. To this end, we first extract policy variables from major national development plans (“Five-Year Plans”, “Government Work Reports”, and “Monetary Policy Reports”) using Natural Language Processing (NLP) technique and Dynamic Topic Model (DTM). However, traditional models are inadequate for mixed frequency data modeling and feature extraction. Then, we propose a mixed frequency deep factor asset pricing model (MIDAS-DF) that solves the asset pricing problems under the mixed frequency data environment through mixed data sampling (MIDAS) technique and deep learning architecture. Time-varying latent factors and factor loadings can be modeled from mixed frequency data directly in a nonlinear and data-driven way. Thus, the MIDAS-DF model is able to learn the nonlinear joint-patterns hidden in multi-source heterogeneous information. Our empirical studies of 4939 stocks on the Chinese A-share market from January 2003 to July 2022 demonstrate that low frequency policy information has profound impacts on asset pricing, which anchors the long-term pricing direction, and high frequency market and sentiment information have significant influences on stock prices, which optimize the short-term pricing accuracy, they together enhance the pricing effects. Consequently, pricing effects the MIDAS-DF model outperform the five competing models on individual stocks, various test portfolios, and investment portfolios. Our research about heterogeneous information provides implications to the government and regulators for decision-support in policy-making and our investment portfolio is of great importance for investors’ financial decisions.

We examine an important yet understudied form of reputational sanction in China, namely public criticisms imposed on culpable firms by the Chinese stock exchanges from 2013 to 2018. We find significantly negative cumulative abnormal returns around the announcement date, and they were affected by several factors, including financing propensity, governance mechanism, and equity nature. However, the market reaction is significantly negative only for firms relying on external financing and non-state enterprises, and importantly, becomes insignificant in cases where the firm had self-exposed misconduct before the official announcement of public criticism. Further, we examine other effects of public criticism, finding that public criticism does not improve firms’ long-term values, nor produce strong deterrence to change their behaviour. Overall, the evidence of the effects of public criticism on culpable firms is mixed, suggesting that reputational sanction is a weak, if not ineffective, instrument of market regulation in China.

We examine the impact of mixed ownership on the performance of venture capital (VC) firms in China. We use successful/unsuccessful exits from VC-financed entrepreneurial companies and number of patent applications by VC-financed companies as proxies for VC firms’ performance. Consistent with existing research on the inferior performance of SOEs relative to non-SOEs, we find that on average government-controlled VC firms (GVCs) underperform domestic private investors-controlled VC firms (PVCs). More importantly, we find that introducing minority private investors (i.e., mixed ownership) helps improve the performance of GVCs. However, we find no evidence that introducing minority government investors (i.e., mixed ownership) helps improve the performance of PVCs. Our results provide relevant information to the ongoing debate on the role of the government investors and private investors in developing the VC industry in emerging markets.

We provide a model of hedge fund securing financing from a prime broker where deterioration in collateral value exacerbates counterparty risk and liquidity risk for the prime broker due to strategic actions of hedge funds. Costs of liquidity insurance and enforcing contracts determine hedge fund leverage. The model provides several new insights. First, it uncovers a new channel for funding liquidity that can explain why illiquid funds fare worse in times of stress and why better governed funds fared better during the financial crisis. Second, the model provides a new testable hypothesis that systematic or idiosyncratic shocks to fundamentals of bank holding companies may spillover to connected hedge funds through internal capital markets. It also offers an identification strategy to distinguish between possible competing hypotheses. Third, strong governance at hedge funds may reduce incentives to invest in profitable opportunities. Fourth, banking reforms such as Supplementary Leverage Ratio, Liquidity Coverage Ratio and Standing Repo Facility intended to improve resilience of banks may also make hedge funds less vulnerable to shocks in the banking sector. Fifth, the model offers a possible reconciliation for the mixed evidence on the impact of leverage on hedge fund survival documented in the literature.