Machine learning-based forecasts of residential property prices in Hangzhou City, Zhejiang Province, China

The Chinese real estate market has grown at such a quick rate over the last few decades, up to the current falling patterns that began at the end of 2021. This difficulty has made it more difficult for the government and investors to predict future property prices effectively. This has occurred as a result of the state of the economy at the moment. In this research, we examine the monthly residential property prices in Hangzhou City, Zhejiang Province, China, using Gaussian process regressions with a variety of kernels and basis functions. This research spans the months of January 2009 through July 2024. We use estimated models in our forecasting efforts. A combination of cross-validation and Bayesian optimisations is used to train these models. The prices that would be seen outside of the sample from June 2021 to July 2024 were successfully predicted by the generated models. These models have an accuracy of 1.0419 per cent for the relative root mean square error. It is plausible that our findings may be used alone or in combination with further projections to formulate theories about fluctuations in residential real estate prices and to conduct supplementary policy analysis.