Study on Price Formation and Investor Structure in China's Public REITs Market——Analysis Based on ABM
Gaining a deep understanding of the operational patterns of the public REITs market is crucial for achieving high-quality financial development in China.By constructing an agent-based model comprising fundamental traders,momentum traders,and noise traders,and using machine learning methods to calibrate the model on 20 REITs listed before November 1,2022,the study sim-ulates the price formation process and analyzes the trader structure in the market.The results reveal that the return series of Chinese public REITs exhibit characteristics such as heavy tails,autocorrela-tion,and volatility clustering,similar to other financial assets.The model can effectively simulate the price formation process in the REITs market and possesses a certain predictive ability for future returns.In the REITs market,fundamental traders dominate,followed by momentum traders,while the influence of noise traders is negligible.The recommendations include closer monitoring of mar-ket volatility and risk exposure by regulatory authorities,leveraging the significance of agent-based models in regulatory decision-making,and enhancing investor education to emphasize long-term investment value and discourage excessive pursuit of short-term gains by considering fundamental factors.
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