Developing a Sustainable Risk Warning Framework for Short-Term Cross-Border Capital Flows: Empirical Analysis Based on Heterogeneous Exchange Rate Expectations

The supervision of and early warning about cross-border capital flows are crucial for maintaining financial stability. This study develops a sustainable risk warning framework that incorporates the heterogeneous exchange rate expectations of foreign exchange market participants into a comprehensive indicator system. Using the KLR signal analysis method and data for China covering the period from July 2005 to June 2022, the framework is empirically evaluated for its ability to predict short-term capital inflow and outflow risks. The results show that incorporating heterogeneous expectations significantly enhances the accuracy and robustness of early warning performance. Regardless of the specific estimation method, the proposed Weighted Heterogeneous Expectation Indicator demonstrates stable and effective predictive capacity across different market environments, underscoring its time-varying adaptability and robustness. Early warning indicators exhibit varying sensitivities, highlighting the importance of a holistic assessment that captures multiple market dimensions. Overall, the proposed sustainable framework strengthens the monitoring of short-term cross-border capital flow risks in China and provides methodological insights for improving risk warning systems in other economies.