As China's bond market expands rapidly, the complexity of financial guarantee networks and their implications for credit risk have become critical issues in both academic research and financial practice. Utilizing micro-level data from China's credit bond market spanning 2014 to 2024, this study constructs a multi-layer network incorporating bonds, guarantors, and issuing firms to empirically examine the impact of guarantor network centrality on bond credit spreads. The results reveal a significant U-shaped relationship: moderate centrality reduces spreads by bolstering market confidence, whereas excessive centrality increases them due to heightened systemic risk. Mechanism analyses identify systemic risk and information asymmetry as key mediating channels through which centrality affects credit risk premiums. Heterogeneity tests indicate that this U-shaped pattern is more pronounced among state-owned guarantors, real estate firms, and high-risk clusters within the network. Furthermore, both cross-layer connectivity within the multi-layer structure and regional financial development levels significantly moderate the centrality-spread relationship. These findings offer a structural perspective on credit risk pricing in emerging markets and provide valuable policy insights for credit rating system design, guarantee regulation, and systemic risk prevention. International investors could also leverage these findings to better assess systemic risk in interconnected financial markets across emerging economies.

As companies and investors globalize, we are increasingly faced with estimation questions about the risk associated with this globalization. When investors invest in China Mobile, Infosys or Vale, they may be rewarded with higher returns, but they are also exposed to additional risk. When Siemens and Apple push for growth in Asia and Latin America, they clearly are exposed to the political and economic turmoil that often characterize these markets. In practical terms, how, if at all, should we adjust for this additional risk? We will begin the paper with an overview of overall country risk, its sources and measures. We will continue with a discussion of sovereign default risk and examine sovereign ratings and credit default swaps (CDS) as measures of that risk. We will extend that discussion to look at country risk from the perspective of equity investors, by looking at equity risk premiums for different countries and consequences for valuation. In the fourth section, we argue that a company’s exposure to country risk should not be determined by where it is incorporated and traded. By that measure, neither Coca Cola nor Nestle are exposed to country risk. Exposure to country risk should come from a company’s operations, making country risk a critical component of the valuation of almost every large multinational corporation. In the final section, we will also look at how to move across currencies in valuation and capital budgeting, and how to avoid mismatching errors.

We investigate the impact of state ownership structure on asset prices and corporate policies. By primarily focusing on China’s corporations, we show that the relationship between expected returns and capital investment varies significantly across state owned enterprises (SOE) and private owned enterprises (POE). A portfolio that longs low investment and shorts high investment firms earns an average annual excess stock return of 5% in the SOE sector. In contrast, there is no relationship between investment and expected returns in the POE sector. We show that the difference in the link between expected returns and investment across SOE and POE firms is driven by their differential exposures to the debt issuance shocks, which captures the monetary supply shocks in China. As SOE firms have easier access to bank loans, the high investment firms in the SOE sector are more able to raise debt despite that debt supply is shrinking, and hence they are less risky. We develop a dynamic model with SOE and POE firms facing different frictions in debt markets. The economic mechanism emphasizes that heterogeneous access to the debt market is an important determinant of equilibrium risk premiums across sectors with different state ownership.

We analyze return predictability for the Chinese stock market, including the aggregate market portfolio and the components of the aggregate market, such as portfolios sorted on industry, size, book-to-market and ownership concentration. Considering a variety of economic variables as predictors, both in-sample and out-of-sample tests highlight significant predictability in the aggregate market portfolio of the Chinese stock market and substantial differences in return predictability across components. Among industry portfolios, Finance and insurance, Real estate, and Service exhibit the most predictability, while portfolios of small-cap and low ownership concentration firms also display considerable predictability. Two key findings provide economic explanations for component predictability: (i) based on a novel out-of-sample decomposition, time-varying macroeconomic risk premiums captured by the conditional CAPM model largely account for component predictability; (ii) industry concentration and market capitalization significantly explain differences in return predictability across industries, consistent with the information-flow frictions emphasized by Hong, Torous, and Valkanov (2007).

We study the connection between the stock market and the labor market. When aggregate risk premiums are time-varying, predictive variables for market excess returns should forecast longhorizon growth in the marginal bene?t of hiring and thereby long-horizon aggregate employment growth. Consistent with this logic, we document that high values of the risk premiums forecast low payroll growth and increases in unemployment rate in the short run, but high payroll growth and decreases in unemployment rate in the long run. High values of lagged payroll growth and decreases in lagged unemployment rate also forecast low stock market excess returns.

It is well documented that bond excess returns are time-varying and that they can be explained by predetermined risk factors. This paper builds a theoretical model to forecast excess returns on treasury bonds in the context of China’s unique monetary system. Empirical evidence shows that bond excess returns in China are highly predictable when compared to those in developed markets. Further investigation suggests that the predicted components are primarily driven by the inflexible term structures of official interest rates set by China’s central bank.

In this article we offer an explanation for price differentials between A and H shares based on the conventional asset pricing theory. We find that the risk premiums associated with the Hong Kong and Mainland Chinese Markets in a two-factor model successfully explain the cross section of returns on the A and H shares. We show that discounts on H shares relative to A shares are highly related to the contemporaneous discounts of H-share local market index relative to A-share local market index, as well as the spread of Hong Kong savings interest rate to Mainland China. The evidence suggests that the risk premiums associated with the segmented A- and H-share markets exert crucial impacts on the price differentials between the two classes of shares. The results thereby indicate that the movements of price discounts of H shares owned by non-Mainland investors in the Chinese stock markets is in accord with the rationality of Chinese investors.