Research on Investment Risks of Transportation REITs Based on the GARCH-VaR Model

This study focuses on China's transportation Real Estate Investment Trusts (REITs). Addressing the issues of complex return volatility characteristics and the inability of traditional risk models to accurately depict extreme risks, a dynamic risk measurement framework based on the GARCH-VaR model is constructed. Daily return data of three transportation REITs—Ping An Guangzhou-Guangzhou-Hengyang Expressway REIT, China Universal Yuexiu Expressway REIT, and Zheshang Shanghai-Hangzhou-Ningbo Expressway REIT—are selected. Descriptive statistics, stationarity tests, and ARCH effect tests are conducted to verify their leptokurtic, fat-tailed, and volatility clustering characteristics. On this basis, the GARCH model is established to calculate VaR values at the 95% confidence level, and the Kupiec failure rate test is used to evaluate model effectiveness. The results show that the GARCH-VaR model provides accurate risk measurement for Ping An Guangzhou-Guangzhou-Hengyang Expressway REIT and Zheshang Shanghai-Hangzhou-Ningbo Expressway REIT, but underestimates the risks of China Universal Yuexiu Expressway REIT. This study offers a more scientific dynamic risk early warning tool for REITs investors and empirical evidence for regulatory authorities to improve risk management mechanisms.