North American Journal of Economics and Finance最新文献

This research examines the ability of 28 U.S. macroeconomic variables to forecast the volatility of six cryptocurrencies. In- and out-of-sample analyses are performed to validate their forecasting ability. Our analysis shows that during the full-sample period, 15 variables display forecasting ability, while post-COVID-19 period, this number is 17. Among these variables, the most influential include the consumer confidence index, leading economic index, consumer price index, U.S. exports and U.S. imports. Importantly, the predictive ability of these variables appears to have strengthened during the post-COVID-19 period. The out-of-sample results confirm the effectiveness of those macroeconomic variables in the in-sample tests. Furthermore, the robustness test reveals that incorporating these U.S. macroeconomic variables can enhance the performance of the GARCH volatility model. In this study, combination methods are used to enhance forecasting stability and are proven to have good forecasting ability. Our research also indicates that integrating global macroeconomic variables can enhance forecasting ability while recognizing the valuable information provided by U.S. macroeconomic variables. Additionally, we find that variables such as the short-term government bond yield and the M1 money supply emerge as important predictors of cryptocurrency bubbles.

This study suggests a simple test to assess the validity of employing a variable as an investor sentiment proxy by examining whether the variable exerts a long-run impact on prices. We also conduct the test using news sentiment indices for the U.S. and Korea, which represent a developed and influential market and a leading emerging market, respectively, as potential proxy variables. The test results, on the one hand, lead to a pessimistic view of employing news sentiment as a proxy for investor sentiment. On the other hand, the results also demonstrate a connection between news sentiment and investor sentiment, particularly in Korea. We suggest that a variable may not be appropriate as an investor sentiment proxy even when the variable is somewhat related to sentiment.

This study examines the impact of HSR, which is a green mode of transportation, on corporate risk-taking using the introduction of HSR in China as an exogenous shock. We find that the introduction of an HSR route leads to a significant increase in corporate risk-taking. The positive effect of HSR introduction on corporate risk-taking is more pronounced for firms with more severe financial constraints, poorer access to human capital, and lower information accessibility. These results show that HSR promotes corporate risk-taking through the channels of cross-regional resource provision of funds, personnel, and information essential for corporate risk-taking. In addition, tests considering spatial heterogeneity show that the positive relation is also stronger for firms located in small cities where resources are inadequate. Results also show that HSR increases the riskiness of corporate financing and investment policies, and leads to a boost in corporate green investment.

This paper asks how capital requirements differ in their effectiveness in the context of deposit competition and potential misreporting. We present a model in which banks face imperfect competition in the deposit market and choose between a prudent or a risky asset under each of the three capital policies: a leverage ratio, a risk-based capital ratio, and a combination of both. We consider a setting where banks might misreport risky asset choice for lower regulatory capital. We find that, without misreporting, deposit competition needs to be very high to incentivize risky asset choice under the combined policy compared to the others. When misreporting is possible, the risk-based capital ratio alone can incentivize prudent asset choice if competition is below a threshold, but exceeding the threshold renders the ratio ineffective, leading to risky asset choice and misreporting. Adding a leverage ratio can restore incentives for prudent asset choice. However, when competition is too intense, the combined policy may still be ineffective.

Driving the digital transformation of enterprises with the power of the capital market is a new key to comprehensively promoting the development of the digital economy. In this context, we investigate the impact of venture capital on the digital transformation of enterprises. Based on the data of A-share listed companies in Shanghai and Shenzhen from 2008 to 2022, we find that venture capital can promote digital transformation. State-owned and syndicated venture capital have more significant impacts on promoting digital transformation. In terms of the mechanism of action, venture capital plays three roles: financial assistance, governance empowerment, and capability support. It helps enterprises to obtain credit support and ease financing constraints, improve management efficiency and curb myopia, increase investment in R&D personnel and innovation output, and thus promote digital transformation. In addition, venture capital can enhance its value-added role through digital transformation and provide sufficient market incentives for it to promote digital transformation. Our study enriches the literature on venture capital and enterprise digital transformation and provides empirical reference for leveraging market forces to accelerate enterprise digital construction.

This paper investigates the existence of herding movements towards several systematic risk factors derived from the Capital Asset Pricing Model (CAPM) and its extensions. The measure of herding is estimated using the dispersion of the risk factor loadings. The state space model is employed to extract time series of herding dynamics. We empirically survey the herding behaviors in the BRICS stock markets (i.e., Brazil, Russia, India, China, and South Africa) using monthly stock index data from 2006 to 2022, and identify various herding patterns towards specific factors. We also examine the impact of unanticipated shocks in crucial macroeconomic variables on the degree of herding measure in these countries. Lastly, we test the contagion hypothesis of herding across markets using correlation analysis. The results show that the level of herding linkages increases significantly in periods of market stress, casting doubt on the effectiveness of asset allocation in these markets for the sake of diversity.

We examine expertise acquisition incentives in a model of debt funding markets in which expertise reduces the cost of acquiring information about underlying collateral. Lenders acquiring expertise gain advantages in financial contracts with borrowers and extract rents from them by creating fear of information acquisition that gives rise to illiquidity. As information about collateral decays over time, there is growth in credit and expertise acquisition, making the economy more vulnerable to an aggregate shock. This result suggests that expertise acquisition is an endogenous amplification mechanism of an aggregate shock.

While FinTech has contributed to the improvement of efficiency and cost reduction for commercial banks, it has also brought about risks for them. Especially during the outbreak of major public emergencies, the degree of risk spillover among financial institutions increased significantly. In this paper, we constructed a high-dimensional risk spillover network using the elastic net shrinkage technique to investigate the impact of public health emergencies on the risk spillovers between FinTech institutions and commercial banks. The total spillover index was utilized to access the overall coupling between FinTech institutions and commercial banks. Furthermore, we employed the sectoral spillover index and institutional centrality index to examine the spillover intensity across different sectors and institutions. Additionally, we analyzed the changes in the risk spillover network structure and institutional risk role during emergencies, aiming to uncover the impact mechanism of public health emergencies on risk spillovers. The results reveal that (1) public health emergencies, such as the COVID-19 pandemic, have intensified the industry correlation between the FinTech and banking sectors, and the primary risks of the system have shifted from intraindustry risks to interindustry risks. (2) Public health emergencies have changed the risk transmission roles of FinTechs and banks. FinTechs transitioned from being risk recipients to risk contributors, while banks shifted from being risk contributors to risk recipients. (3) FinTechs play a crucial role in facilitating indirect risk transmission within the system, acting as influential adjacent institutions that bridge the gap between critical institutions. (4) Compared with large commercial banks, small and medium-sized banks are more sensitive to FinTech risks. This study provides supporting evidence for regulatory agencies to enhance risk management in financial innovation during public health emergencies and in the post-pandemic era.

This paper discusses how various uncertainties interact with the return connectedness among commodity and financial markets from the time–frequency perspective. To begin with, the TVP-VAR is employed to examine the return connectedness among commodity and financial markets. Subsequently, the wavelet coherence is applied to examine the dependent relationship between uncertainty indices (EPU, VIX, and GPR) and the return connectedness index. Our results show that the interactions between uncertainty indices and the return connectedness index are dependent upon investment horizons and susceptible to significant crisis events. Besides, EPU and VIX displays a positive dependent on the total return connectedness in the short- and medium-term but transitions to a negative correlation in the long-term, whereas GPR primarily exert positive effect on the total return connectedness in the long-term. Moreover, the interdependence between the net return connectedness for each market and uncertainty indices displays noteworthy heterogeneity. These findings provide important reference for all market participants to respond to cross-market spillover effects under the shock of uncertainty.

As a leading indicator of sovereign debt risk, the performance of the sovereign CDS market during the Russia-Ukraine conflict deserves attention. This paper calculates the marginal net spillover index, constructs the sovereign CDS network based on the index, identifies the important countries in the network, and analyzes the network stability considering the differences in the roles of the countries in the network. By further analyzing the daily sovereign CDS network before and after the Russia-Ukraine conflict, we show the evolution pattern of the risk of the important countries in the network and the main risk contagion paths between countries. The paper shows that the Russia-Ukraine conflict significantly exacerbated the network’s overall risk level and instability. The major transmitters in the sovereign CDS network are characterized by the risk switch from receiving to transmitting, and the major receivers are characterized by the risk switch from latent to manifest. The risk contagion process is characterized by four stages: risk contagion to neighboring countries, risk exacerbation between Russia and Ukraine, further outward spillover, and weakening but persistent spillover. This study helps to provide a reference for investors to mitigate risk contagion in the sovereign CDS market.