Wealthy individual investors and stock markets' tail risk.

This paper employs a unique data set to analyze the trading behavior of wealthy individual investors across Mainland China and their impact on Chinese stock markets' tail risk. Results show that the wealthy individual investors' trading behavior can explain Chinese stock markets' tail risk, and the daily investment portfolios based on the network density of wealthy individual investors have significant excess returns. This paper also investigates the determinants of wealthy individual investors' trading behavior with the social network method and the spatial econometric model, and reveals that wealthy individuals benefit from the spillover effect of their trading behavior through the investor networks. The results of this paper not only reveal micro evidence for the formation mechanism of asset prices, but also provide insight into the behavior of wealthy individual investors.

Piercing the corporate veil system and creditors protection: Based on the investigation of debt paying ability--Empirical evidence from the 2005 Company Law amendment.

This paper uses the difference-in-differences model to research how the "piercing the corporate veil" system marked by the 2005 Company Law amendment affects the level of corporate creditor protection. The research results show that private enterprises and local state-owned enterprises are sensitive and significant to this legal amendment. In contrast, local state-owned enterprises are more sensitive and have a stronger motivation to protect the interests of creditors. The motivation of companies with weaker profitability for creditor protection lasts not only for the year of law revision but also extends to the year of implementation. With the law's implementation, the growth effect of creditor protection for local state-owned enterprises has become more significant. Further analysis shows that the main findings of this article are more significant in companies with larger debt scales, companies with a higher year-on-year growth rate of operating income, companies with controlling shareholders, and companies with higher stock market capitalization. From an empirical research view, this paper explains the economic effect and mechanism of the whole corporate personality under the complete system and adds economic evidence for how the law acts on the capital market.

Driving force of value reversal in Chinese overleveraged firms: The mechanism and path of private placement.

To stimulate economic growth, China has launched multiple economic stimulus plans in recent years, intensifying corporate debt financing and subsequently elevating the leverage levels. Addressing and effectively reducing the leverage levels of our country's enterprises has emerged as a pressing issue in the trajectory of our economic development. This paper primarily investigates the drivers, pathways, and mechanisms for reversing the over-leveraged values of enterprises. Key findings include: (1) Excessive indebtedness exerts a negative impact on corporate value, with the suppressing effect intensifying as the degree of over-leverage increases; (2) Over-leveraged enterprises can effectively decrease their debt levels and enhance their value through private placement. Further research suggests that this mechanism operates by amplifying the operational leverage of over-leveraged enterprises post private placement and alleviating financing constraints, thereby elevating corporate value. (3) Compared to non-state-owned enterprises, state-owned enterprises exhibit higher levels of indebtedness. Among over-leveraged firms, enhancements in corporate governance and increased investment efficiency can positively transform corporate value. This study offers valuable insights for the ongoing supply-side structural reforms and governance guidance from the regulatory bodies.

Guaranteed minimum withdrawal benefits with high-water mark fee structure.

The Guaranteed Minimum Withdrawal Benefit (GMWB), an adjunct incorporated within variable annuities, commits to reimbursing the entire initial investment regardless of the performance of the underlying funds. While extensive research exists in financial and actuarial literature regarding the modeling and valuation techniques of GMWBs, much of it is founded on a static fee structure. Our study introduces an innovative fee structure based on the high-water mark (HWM) principle and a regime-switch jump-diffusion model for the pricing of GMWBs, employing numerical solutions through the Monte Carlo method for solving the stochastic differential equation (SDE). Furthermore, a companion piece of research addresses the risk management of GMWBs within the same analytical framework as the pricing component, an aspect that has received limited attention in the existing literature. In assessing the necessary capital reserves for unforeseen losses, our methodology involves the computation of two risk metrics associated with the tail distribution of net liability from the insurer's perspective, Value-at-Risk (VaR) and Conditional-Tail-Expectation (CTE). Comprehensive numerical results and sensitivity analyses are also provided.

Application of the DEMATEL method for quantitative analysis of risk factors for railway investments in Poland.

The paper presents the results of research on the influence of risk factors on the implementation of railway investments in Poland (build stage) and deals with a detailed diagnosis of relation between factors. The application of DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method for the analyses allowed to develop a cause-and-effect model of key factors and analyse the importance of the factors. Eleven factors identified in eariel studies as the most important risk factors were examined. It was found that the factors: errors in the preparation of tender documents (10.38%), errors in project documentation (10.02%), improperly estimated time of completion of the investment by the Employer (9.82%), internal regulations of PKP Polskie Koleje Panstwowe S.A. (Polish State Railways) not coordinated with the provisions of contracts (9.51%) have the highest degree of importance. Factors: too many external institutions involved in the investment process and internal regulations of PKP Polskie Koleje Panstwowe S.A. (Polish State Railways) not coordinated with the provisions of contracts, have the greatest net impact on the other factors. The relations between the factors and factors importance are valuable knowledge for engineers, enabling the project to be implemented according to the planned schedule and investment cost.

High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions.

In the field of financial risk management, the accuracy of portfolio Value-at-Risk (VaR) forecasts is of critical importance to both practitioners and academics. This study pioneers a comprehensive evaluation of a univariate model that leverages high-frequency intraday data to improve portfolio VaR forecasts, providing a novel contrast to both univariate and multivariate models based on daily data. Existing research has used such high-frequency-based univariate models for index portfolios, it has not adequately studied their robustness for portfolios with diverse risk profiles, particularly under changing market conditions, such as during crises. Our research fills this gap by proposing a refined univariate long-memory realized volatility model that incorporates realized variance and covariance metrics, eliminating the necessity for a parametric covariance matrix. This model captures the long-run dependencies inherent in the volatility process and provides a flexible alternative that can be paired with appropriate return innovation distributions for VaR estimation. Empirical analyses show that our methodology significantly outperforms traditional univariate and multivariate Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models in terms of forecasting accuracy while maintaining computational simplicity and ease of implementation. In particular, the inclusion of high-frequency data in univariate volatility models not only improves forecasting accuracy but also streamlines the complexity of portfolio risk assessment. This research extends the discourse between academic research and financial practice, highlighting the transformative impact of high-frequency data on risk management strategies within the financial sector.

Does corporate governance and balance sheet feature influence the financial policy of cooperatives? PLS-SEM approach.

Effective financial policy minimizes business risk, increases the net present value of the Company's investment programs and increases value for shareholders. However, the impact hasn't yet been examined in the research area. The purpose of this study is to empirically investigate, how corporate governance and balance sheet aspects affect the financial policy of cooperatives in south-western Ethiopia using the PLS-SEM model. Information covering three years from 2020 to 2022 was gathered from 145 cooperatives. The study used corporate governance and balance sheet features as the latent factors that affect the dependent variable cooperative financial policy measured by both short-term debt and long-term debt. Managerial characteristics were used as the control variables. The study discovered that corporate governance has negative and significant effect on the financial policy of cooperatives in southwest Ethiopia. The study also revealed that balance sheet features have significant and positive effect the financial policy of cooperatives in southwest Ethiopia. Additionally, managerial characteristics' have a significant impact on the financial policy and balance sheet features but have no impact on the corporate governance of cooperatives. The study concludes that the financial policy of cooperatives in southwest Ethiopia is significantly influenced by all aspects of corporate governance, balance sheet features, and management characteristics'. The study advises cooperatives to consider managerial characteristics', corporate governance, and balance sheet characteristics while establishing their financial policy.

Government infrastructure investment stimulation through booming natural resources: Evidence from a lower-middle-income country.

The dynamics of central government funding to regions depend on local investments. In regional autonomy, local governments are encouraged to be more self-reliant from the central government. For regions with high natural resource yields, they will not encounter difficulties in meeting their fiscal needs. Community welfare can be realized through fulfilling basic needs, one of which is infrastructure development. High-quality infrastructure will be able to contribute to further progress in trade, thus enhancing production efficiency. The objective of this research is to analyze the extent of the influence of central government transfer funds, especially the Natural Resource Revenue Sharing Funds (DBH SDA), on local government investments in infrastructure across 508 districts/cities in Indonesia. The method used is dynamic panel regression using the Generalized Method of Moment (GMM) Arellano-Bond approach. This study finds that the role of DBH SDA is still low in infrastructure spending. The role of the central government remains significant in determining infrastructure spending at the district/city level in Indonesia. This indicates that local governments rely more on other sectors in infrastructure investment. By enhancing the role of DBH SDA through technological advancements, it is hoped that the market value of natural resources can be higher through resource downstreaming. This strategy will have broader impacts, as labor needs can be absorbed not only in raw material production activities but also in the processing technology sector. Furthermore, the utilization of natural resources with modern technology can increase extraction efficiency, support sustainable development, and minimize environmental impacts.

Exploring the nexus between FDI inflows and economic growth: A sectoral level analysis.

This study investigates the relationship between Foreign Direct Investment (FDI) inflows and economic growth at sectoral levels in Bangladesh, employing a panel study framework. Utilizing sectoral-level panel data spanning six sectors from 2007-08 to 2018-19, the analysis is conducted using Panel Vector Error Correction Model (Panel VECM). Results from panel unit root tests confirm that all variables are integrated of order one I (1), indicating stationarity. The Pedroni panel co-integration test further supports the presence of co-integration among the variables. Notably, the Panel VECM reveals evidence of a unidirectional causal relationship from Real Gross Domestic Product (RGDP) to Real Foreign Direct Investment (RFDI) across all six sectors of Bangladesh. The findings underscore the significance of formulating pragmatic policies and implementing them effectively to attract FDI across sectors, thereby contributing to the overall economic growth of Bangladesh.

Causality-driven multivariate stock movement forecasting.

Our study aims to investigate the interdependence between international stock markets and sentiments from financial news in stock forecasting. We adopt the Temporal Fusion Transformers (TFT) to incorporate intra and inter-market correlations and the interaction between the information flow, i.e. causality, of financial news sentiment and the dynamics of the stock market. The current study distinguishes itself from existing research by adopting Dynamic Transfer Entropy (DTE) to establish an accurate information flow propagation between stock and sentiments. DTE has the advantage of providing time series that mine information flow propagation paths between certain parts of the time series, highlighting marginal events such as spikes or sudden jumps, which are crucial in financial time series. The proposed methodological approach involves the following elements: a FinBERT-based textual analysis of financial news articles to extract sentiment time series, the use of the Transfer Entropy and corresponding heat maps to analyze the net information flows, the calculation of the DTE time series, which are considered as co-occurring covariates of stock Price, and TFT-based stock forecasting. The Dow Jones Industrial Average index of 13 countries, along with daily financial news data obtained through the New York Times API, are used to demonstrate the validity and superiority of the proposed DTE-based causality method along with TFT for accurate stock Price and Return forecasting compared to state-of-the-art time series forecasting methods.

WTI, Brent or implied volatility index: Perspective of volatility spillover from oil market to Chinese stock market.

This study investigates the impact of oil market uncertainty on the volatility of Chinese sector indexes. We utilize commonly used realized volatility of WTI and Brent oil price along with the CBOE crude oil volatility index (OVX) to embody the oil market uncertainty. Based on the sample span from Mar 16, 2011 to Dec 31, 2019, this study utilizes vector autoregression (VAR) model to derive the impacts of the three different uncertainty indicators on Chinese stock volatilities. The empirical results show, for all sectors, the impact of OVX on sectors volatilities are more economically and statistically significant than that of realized volatility of both WTI and Brent oil prices, especially after the Chinese refined oil pricing reform of March 27, 2013. That implies OVX is more informative than traditional WTI and Brent oil prices with respect to volatility spillover from oil market to Chinese stock market. This study could provide some important implications for the participants in Chinese stock market.

The influence of cultural friction on foreign divestment of multinational enterprises--the moderating role of formal institutional distance and political connections.

Multinational enterprises frequently divest their foreign assets in the current economic environment. Existing research, based on friction theory, has mainly focused on the impacts of political and economic disparities on foreign divestment while neglecting the nuanced influence of cultural factors. To address this gap, this paper draws on the cultural friction perspective to capture the diverse cultural resistance faced by each enterprise and explore the relationship between cultural friction and foreign divestment. Data from Chinese publicly listed enterprises engaged in foreign investment are leveraged, and a dual-level analysis is conducted using Logit panel regression and Cox survival analysis to examine the relationship between cultural friction and foreign divestment from both the viewpoints of the parent company and the overseas subsidiary. Additionally, the paper examines the marginal factors that affect the relationship between them from an institutional perspective. The findings reveal that cultural friction has a positive influence on the propensity of multinational enterprises to divest from foreign markets. Interestingly, a "formal institutional distance paradox" is demonstrated in our study, and politically connected enterprises are found to be more vulnerable to foreign divestment due to the "curse of political affiliations".

Foreign shareholder, overseas sale and corporate profit margin.

China is actively promoting the development of a robust trading nation. In this context, utilizing data from China's A-share listed companies spanning from 2003 to 2021, this study investigates the impact of foreign shareholders on enterprises in a scenario where overseas sales reduce the profit margin of Chinese firms. The findings reveal that overseas sales do indeed decrease the profit margin of Chinese enterprises; however, foreign shareholders mitigate this negative effect and various robustness tests support this conclusion. Mechanism analysis confirms that foreign shareholders primarily enhance enterprise productivity through improved production technology spillover effects, thereby alleviating the adverse impact of overseas sales on Chinese firms' profit margins. Heterogeneity analysis demonstrates that both longer holding periods for foreign shareholders and multiple foreign shareholders significantly alleviate the negative influence of overseas sales on Chinese firms' profit margins. Moreover, there is significant heterogeneity in how foreign shareholders alleviate these detrimental consequences based on property rights nature, institutional environment, overseas related party transactions and subsidiaries, as well as industry attributes. These findings have important reference value for China's efforts towards becoming a strong trading nation and can contribute to enhancing trade capacity in other countries.

"Investor attention fluctuation and stock market volatility: Evidence from China".

This paper examines the linkage between Chinese stock market volatility and investor attention fluctuation. In Heterogeneous autoregressive (HAR) model, first, we analyzed the linkage between both decomposed and undecomposed stock market realized volatility and investor attention fluctuations across full-sample and two-year moving window sub-samples. Second, we compare the predictive power of four models in short-, medium-, and long-term volatility forecasting. Empirical results show large positive attention fluctuation amplified Chinese stock market volatility after the outbreak of COVID-19, and negative small attention fluctuation significantly stabilized stock market volatility before COVID-19, and the impact dwindled in after COVID-19. The model incorporating decomposed realized volatility and decomposed attention fluctuation performs better in volatility Forecasting. This research underscores a shift in the dynamics between stock market volatility and investor attention fluctuations, and investor attention fluctuation improves the volatility forecasting accuracy of the Chinese stock market.

Common institutional investors and the quality of management earnings forecasts-Empirical and machine learning evidences.

Based on the data of the Chinese A-share listed firms in China Shanghai and Shenzhen Stock Exchange from 2014 to 2021, this article explores the relationship between common institutional investors and the quality of management earnings forecasts. The study used the multiple linear regression model and empirically found that common institutional investors positively impact the precision of earnings forecasts. This article also uses graph neural networks to predict the precision of earnings forecasts. Our findings have shown that common institutional investors form external supervision over restricting management to release a wide width of earnings forecasts, which helps to improve the risk warning function of earnings forecasts and promote the sustainable development of information disclosure from management in the Chinese capital market. One of the marginal contributions of this paper is that it enriches the literature related to the economic consequences of common institutional shareholding. Then, the neural network method used to predict the quality of management forecasts enhances the research method of institutional investors and the behavior of management earnings forecasts. Thirdly, this paper calls for strengthening information sharing and circulation among institutional investors to reduce information asymmetry between investors and management.

Research on U-shaped relationship between short-term debt for long-term use and supply chain enterprise default risk: Evidence from Chinese listed firms.

This paper empirically investigates the impact mechanism of short-term debt for long-term use and the default risk of supply chain firms with the data of Chinese A-share listed firms from 2007 to 2021. The study shows that there is a significant U-curve relationship between short-term debt for long-term use and supply chain firms' default risk, and too high or too low a level of short-term loans and long-term investments will worsen firms' default risk. In addition, firm performance plays an mediating effect in the process of short-term debt for long-term investment affecting the default risk of supply chain firms. Finally, customer effect and firm heterogeneity play a moderating role in the impact of short-term loans and long-term investments on the default risk of supply chain firms, and the U-shaped relationship will be strengthened under the high-intensity customer effect. This study has important theoretical and practical significance for analyzing the impact of default risk contagion in supply chain enterprises.

The impact of green financial development on stock price crash risk from the perspective of information asymmetry in Chinese listed companies.

Solving the crash risk problem of corporate stock price caused by information asymmetry can mitigate the negative externality of its carbon emission to become green, low-carbon, and high-quality development. Green finance generally profoundly impacts micro-corporate economics and macro-financial systems but remains a giant puzzle of whether they can effectively resolve the crash risk. This paper examined the impact of green financial development on the stock price crash risk using the sample data of non-financial listed companies in Shanghai and Shenzhen A stock market in China from 2009 to 2020. We found that green financial development significantly inhibits the stock price crash risk; this is more obvious in listed companies with a high level of asymmetric information. And companies in high-level regions of green financial development attracted more attention from institutional investors and analysts. As a result, they disclosed more information about their operational status, thus reducing the crash risk of corporate stock price from the torrential public pressure of lousy environmental details. Therefore, this study will help continuously discuss the costs, benefits, and value promotion of green finance for synergy between corporate performance and environmental performance to improve ESG capabilities.

Fintech and investment risk of digital finance: mediating role of clean energy and green bonds through the dynamics of spill over.

This study examines how financial technology (FinTech) and green bonds have affected the ability of firms to finance energy efficiency measures by using data obtained from a subset of Chinese companies listed on the A-share market between 2011 and 2021. We apply the quantile-on-quantile method, which allows us to examine the interdependence of time series in each economy separately and yields data on the global and national levels indicating the relationship between the variables. The results show that an increase in both direct and indirect financing for businesses, as well as inter-bank competition, can greatly mitigate the financial limitations that firms suffer as a result of FinTech expansion. Our estimates show that the energy efficiency of the countries we chose improves when they are financed with green bonds across all quantiles of the data. Organizations not owned by the state, SMBs, and the more rapidly developing eastern half of China promise to benefit the most from the moderating effect of FinTech because of the faster pace of development there. The immediate ameliorating effect that financial technology has on reduced lending criteria mostly benefits businesses with either a strong innovation rate or a poor social responsibility performance rate. This is because businesses sharing either of these features are more likely to experiment and develop new products. Both theoretical and practical repercussions of this finding are explored.

Digital finance and regional green innovation: the perspective of environmental regulation.

The relationship between digital finance and regional green innovation has been partially confirmed, yet the role of environmental regulation in it remains unexplored. Therefore, this paper examines the impact of digital finance on regional green innovation and tests the moderating role of environmental regulation using Chinese city-level data from 2011 to 2019 as a research sample. The results show that digital finance can significantly promote regional green innovation by alleviating regional financing constraints and increasing regional R&D investment. Besides, digital finance has apparent regional difference effects (the contribution of digital finance to regional green innovation is greater in eastern China than in western China, and the development of digital finance in neighbouring regions has a negative transmission effect on local green innovation). Finally, environmental regulation positively moderates the relationship between digital finance and regional green innovation. This paper explores the relationship between digital finance and regional green innovation from the perspective of environmental regulation, providing empirical evidence to promote regional green innovation.

Absence of ultimate controller and investment efficiency: Evidence from China.

In modern enterprises with a separation of powers, the ultimate controller can effectively influence the implementation of corporate strategy and operational management efficiency, as well as improve corporate governance by monitoring and limiting the management entrenchment effect within enterprises. Based on the information pertaining to ultimate controllers disclosed by enterprises in their annual reports, this study empirically tested whether the absence of the ultimate controller impacts investment efficiency using the data of Chinese A-share listed companies from 2007 to 2020. It was found that the investment efficiency of enterprises without ultimate controllers is relatively lower than those with ultimate controllers. This is reflected in the insufficient investment of enterprises without an ultimate controller. Moreover, the effect is more significant when the financial environment, internal governance environment, and external governance environment of firms are worse. The mechanism analysis demonstrated that the absence of an ultimate controller causes a more severe insider agency problem and a significantly higher degree of financing constraints, which leads to underinvestment and reduces investment efficiency of firms. The economic consequence test also found that the inefficient investment caused by the absence of ultimate controllers would damage the future value of enterprises, but would increase managers' compensation. Overall, this study suggests that ultimate controllers are an important part of a firm's internal governance, especially for monitoring management behavior and resolving agency conflicts.