Predictions of Residential Property Prices for Ningbo City of Zhejiang Province in China Using Machine Learning

Up to the current fall patterns that started at the end of 2021, the Chinese real estate market has developed at such a rapid pace over the course of the previous few decades. Investors and the government have found it more difficult to accurately forecast future property values as a consequence of this challenge. It is because of the current status of the economy that this has come about. For the purpose of this study, we use Gaussian process regressions using a wide range of kernels and basis functions to investigate the monthly residential property prices in Ningbo City, which is located in Zhejiang Province, China. The time period covered by this study is from May 2011 to July 2024. Estimated models are used in our forecasting endeavors. These models are trained using a mix of cross-validation and Bayesian optimizations. The models that were developed were effective in accurately forecasting the prices that would be seen out of sample from December 2021 to July 2024. With a relative root mean square error of 0.1626 percent, these models may be considered accurate. It is possible that our results might be utilized on their own or in conjunction with further forecasts in order to construct hypotheses about variations in the values of residential real estate and to carry out additional policy research.