Partially convertible economies face a market-design problem: trade integration, cross-border investment, and domestic balance-sheet exposure increase the demand for currency hedging before full financial integration is complete. China adopted a distinctive architecture for this problem by fostering a deliverable offshore Renminbi market (CNH) alongside the segmented onshore market (CNY), rather than relying only on non-deliverable forwards. This creates two venues for closely related claims on the same currency. Spot prices are tightly linked, yet CNY and CNH forwards display a persistent and economically large discrepancy. We study that discrepancy in a joint equilibrium model for spot and forward trading with transaction costs and segmented supply. In the benchmark case with common constant supply and deterministic costs, spot parity implies a forward differential with the wrong sign relative to the data. Random offshore stress, modeled as a jump in trading costs, overturns this benchmark while preserving tight spot parity. The model yields a semi-explicit representation in the CNY/CNH application and a calibration of the observed forward discrepancy in terms of the market-implied likelihood and severity of offshore liquidity stress.

How do global and domestic investors process institutional signals in emerging markets? We use China’s refined-oil pricing announcements as institutional communications to construct high-frequencymarketization surprises as deviations between actual prices and formula-implied expectations (2013–2025). Three heterogeneous patterns emerge. First, a 1% deviation toward weaker marketization triggers $30m equity and $10m bond outflows internationally while domestic futures appreciate. Second, Kalman filtering extracts latent institutional information differing across markets, with near-zero correlation. Third, international responses amplify quarterly while domestic dissipate immediately. A+H dual-listed firm analysis reveals implicit guarantees and market segmentation jointly drive this divergence.

In the Chinese context, the term “overseas” refers to countries and regions outside the sovereignty and jurisdiction of China. Overseas listing is an important strategy for firms to integrate into global capital markets and enhance their corporate investment efficiency. Using data from 600 Chinese companies listed exclusively overseas and 860 domestically listed firms for the period 2009–2023, this study analyzes the impact of overseas listing on corporate investment efficiency using empirical research methods, underlying mediating mechanisms, and the moderating role of economic policy uncertainty. The findings show that overseas listing improves Chinese firms’ investment efficiency. Compared to listing on the United States securities market (Nshares), listing on the Hong Kong securities market, (H-shares) has a pronounced effect on enhancing investment efficiency. Enhanced information disclosure quality improves the investment efficiency of Chinese enterprises listed overseas. Economic policyuncertainty can strengthen the positive impact of overseas listing on corporate investment efficiency. This study shows that overseas listing improves investment efficiency of firms in developing countries and offers new insights into advancing micro-level opening-up in these countries.

Traditional decision tree models, which rely exclusively on numerical variables, often encounter difficulties in handling high-dimensional data and fail to effectively incorporate textual information. To address these limitations, we propose the Integrated Multivariate Segmentation Tree (IMST), a comprehensive framework designed to enhance credit evaluation for small and medium-sized enterprises (SMEs) by integrating financial data with textual sources. The methodology comprises three core stages: (1) transforming textual data into numerical matrices through matrix factorization; (2) selecting salient financial features using Lasso regression; and (3) constructing a multivariate segmentation tree based on the Gini index or Entropy, with weakest-link pruning applied to regulate model complexity. Experimental results derived from a dataset of 1,428 Chinese SMEs demonstrate that IMST achieves an accuracy of 88.9%, surpassing baseline decision trees (87.4%) as well as conventional models such as logistic regression and support vector machines (SVM). Furthermore, the proposed model exhibits superior interpretability and computational efficiency, featuring a more streamlined architecture and enhanced risk detection capabilities.

This study investigates the link between market arbitrage risk and liquidity risk pricing in a conditional asset pricing framework. We estimate comparative models both at the portfolio and firm level in the Chinese A- and B-shares to test behavioral hypotheses with respect to foreign ownership restrictions and market segmentation. Results show that conditional liquidity premium and risk betas exhibit pronounced asymmetry across share classes which could be attributed to differentiated levels of market mispricing. Specifically, stocks with a greater degree of information asymmetry and retail ownership are more sensitive to liquidity risks when the market arbitrage risk increase. Further policy impact analysis shows that China’s market liberalization efforts, contingent upon its recent stock connect programs, conditionally reduce the price of liquidity risk for connected stocks.

Using the staggered intercity but within-province deregulation of local banks in China as exogenous variations, we evaluate the effect of banking integration across geographical segmentation on capital misallocation. Based on an administrative data set comprehensively covering Chinese manufacturing firms, we find that for firms with initially high marginal revenue products of capital (MRPK), the integration increases physical capital by 19.3%, and reduces MRPK by 33.1% relative to low MRPK ffrms. Our findings are more pronounced for non-statedowned firms and firms with higher exposure to integrated banks. Integration also significantly increases the responsiveness of firms’ investments to deposit shock on other cities within the same province.

This paper examines whether China’s switch back and forth from fixed to floating exchange rates in 2005 and 2008 changed the contribution to stock price discovery by foreign and domestic investors. During that time, mainland investors could only trade the RMB-denominated A-shares in the domestic Shanghai and Shenzhen markets, while the dual-listed HKD-denominated H-shares were available only to overseas investors. Using intraday data on overlapping trading hours, we find that the switch from a fixed rate to managed floating in July 2005 increased the H-shares’ contribution to price discovery; while the exchange rate regime reversal in July 2008 allowed the domestic stocks to regain their dominance in information shares. These results imply that, in a market subject to restrictions on capital flows, a flexible exchange rate regime increases the propensity of investors to trade foreign-issued stocks to speculate on the RMB exchange rate, which raises overseas investors’ contribution to price discovery.

Studying China’s credit market, we find improved price efficiency and, paradoxically, worsening segmentation as perceived government support for state-owned enterprises (SOEs) caused non-SOE credit spreads to explode rather dramatically relative to their SOE counterparts amid government-led credit tightening. Interestingly, the post-2018 credit-market stress helped improve price efficiency within non-SOEs, while SOEs saw no such improvement and instead became sensitive to issuer-level measures of government support, marking a shift of SOE premium beyond the SOE label. We further document the real impact of the deepening credit misallocations: non-SOEs in aggregate are losing their long-standing advantage in profitability over SOEs in China.

China repos trade in the over-the-counter interbank market as well as the stock exchange. This paper examines the behaviours, sources, and drivers of the spread between China’s exchange and interbank reporates from December 2006 to June 2018. After adjusting for different day-count quoting methods, I dissect the exchange to interbank repo spread into two components: cross-market segmentation between exchange and interbank markets for non-depository institutions (NDIs), and within-market counterparty segmentation between NDIs and depository institutions (DIs) in the interbank market. The 1-day repo markets are found to be more segmented, with the spread mainly driven by the cross-market segmentation for NDIs, reflecting the two different market mechanisms and trading frictions that prevent NDIs from effectively arbitraging across the two markets in the shorter tenor. On the other hand, the 7-day repo markets are found to be less segmented, with the spread mainly driven by the counterparty segmentation between NDIs and DIs within the interbank market, reflecting greater counterparty credit and liquidity risks for NDIs relative to DIs. Further analysis uncovers the impacts of quarter-end effect, monetary policies, and shadow banking activities on the cross-market and within-market segmentations in China’s repo markets.

China’s financial prices are informative enough for the PBC to introduce a monetary policy framework centered around interest rates. While bond yields are not fully efficient—reflecting regulation, liquidity, and segmentation—we find they contain considerable information about the state of the economy as well as evidence of an emerging transmission channel: changes in PBC rates influence the structure of Treasury, financial, and corporate bond yield curves, which are then associated with changes in growth and inflation. Coporate spreads are also a leading indicator of growth and inflation. While further liberalization will strengthen both efficiency and transmission, several necessary elements to move towards indirect monetary policy are already in place.