We propose a novel dual-screening classification framework for fund selection designed to align statistical objectives with investor goals. Testing on the Chinese mutual funds market, a Gradient Boosting model implementing our framework generates a statistically and economically significant 14.65% annual risk-adjusted alpha, substantially outperforming identical models trained under a standard regression framework. Feature importance analysis confirms that fund-level momentum and flows are the most significant predictors of performance in this market. Our findings provide a robust and practical framework for active management, demonstrating that modelling both upside potential and downside risk is critical for superior performance.

With the accelerating global aging population, the prevalence of cognitive impairments, particularly Alzheimer’s disease and related dementias, is rising steadily, giving rise to a substantial and rapidly expanding market for memory services. This review aims to systematically examine the core development trends, driving factors, innovative service models, and challenges within the memory services market in the context of the aging economy. It provides a comprehensive analysis of the entire industry chain, spanning early screening, diagnosis, non-pharmacological interventions, long-term care, and technological support. By integrating the latest business models, policy directions, and evolving consumer demands, this article explores future development trajectories and investment potential in the memory services sector. The insights offered herein are intended to support practitioners, policymakers, and researchers engaged in this critical field by delivering an in-depth understanding of current market dynamics and emerging opportunities.

The impact of corporate environment, society, and governance (ESG) disclosure on the online market remains uncertain. To address this ambiguity, this study utilizes text analysis to thematically classify research samples to examine the positive influence of corporate ESG disclosure on stock liquidity from a reputational perspective. Interestingly, the reputational effect of ESG disclosure shows asymmetry within the online market, particularly in its highly information-sensitive environment. Notably, negative media reputation insignificantly diminishes the positive impact of ESG disclosure on stock liquidity. A series of robustness tests confirm the reliability of the sample screening method and findings.

In China's labor market, there is a phenomenon that enterprises choose whether to provide "social insurance and housing fund" to laborers autonomously. This paper use micro-data from two leading Internet recruitment platforms and empirically finds that in a labor market with double-side information asymmetry, "social insurance and housing fund" is not only a cost but also a signal. Providing workers with "social insurance and housing fund" can both send a signal of stable operation to the labor market and identify high-quality workers for enterprises. With an instrument variable of local average social security payment rate, this paper excludes the endogenous effect of labor supply on wages while the signaling effect above is still significant. In addition, "housing fund" has a stronger signaling effect than "social insurance", and the strength of the two signaling effects is affected by the scale of the enterprises and the level of local payment rates. This paper also introduces a theoretical framework of two micro-mechanisms — signaling and screening — into the analysis. In terms of policies, this paper proposes to strengthen the information disclosure and the propagation of social security payment, and further reduce the financial burden of enterprises.

Using proprietary individual level loan data, this paper explores the economic consequences of the 2009 bank entry deregulation in China. Such deregulation leads to higher screening standards, lower interest rates, and lower delinquency rates for corporate loans from entrant banks. Consequently, in deregulated cities, private firms with bank credit access increase asset investments, employment, net income, and ROA. In contrast, the performance of state-owned enterprises (SOEs) does not improve following deregulation. Deregulation also amplifies bank credit from productive private firms to inefficient SOEs due mainly to SOEs’ soft budget constraints. This adverse effect accounts for 0.31% annual GDP losses.

Open banking facilitates data sharing consented by customers who generate the data, with a regulatory goal of promoting competition between traditional banks and challenger fintech entrants. We study lending market competition when sharing banks’ customer data enables better borrower screening or targeting by fintech lenders. Open banking could make the entire financial industry better off yet leave all borrowers worse off, even if borrowers could choose whether to share their data. We highlight the importance of equilibrium credit quality inference from borrowers’ endogenous sign-up decisions. When data sharing triggers privacy concerns by facilitating exploitative targeted loans, the equilibrium sign-up population can grow with the degree of privacy concerns.

This paper uses a dataset of more than 100,000 firms over the period of 2000-07 to assess whether and why Chinese firms overinvest. We find that corporate investment in China has become increasingly efficient over time, suggesting that overinvestment has been declining. However, within all ownership categories, we find evidence indicating a degree of overinvestment by firms that invest more than the industry median. The free cash flow hypothesis provides a good explanation for China’s overinvestment in the collective and private sectors, whereas in the state sector, overinvestment is attributable to the poor screening and monitoring of enterprises by banks.