Jin, B and Xu, X (2025) Rental price index forecasts of residential properties using Gaussian process regressions. Journal of Financial Management of Property and Construction, 30(3), pp. 416-454. ISSN 1366-4387
Abstract
Purpose – Since the Chinese real estate market has expanded so quickly over the past 10 years, investors and the government are both quite concerned about projecting future property prices. Design/methodology/approach – This work aims to investigate monthly rental price index forecasts of residential properties for ten major Chinese cities from 3M2012 to 5M2020 by using Gaussian process regressions with a diverse variety of kernels and basis functions. The authors conduct forecast exercises through use of Bayesian optimizations and cross-validation. Findings – With relative root mean square errors spanning the range of 0.0370%–0.8953%, the constructed models successfully forecast the ten price indices from 6M2019 to 5M2020 out of sample. Originality/value – The findings might be used independently or in combination with other projections to create theories about the trends in the rental price index of the residential property and carry out additional policy analysis.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Bayesian optimization; Chinese residential property; cross validation; Gaussian process regression; price projection; rental price index |
| Index terms: | methodology, validation, mean square error, investor, policy analysis, exercise, residential property, real estate |
| Subjects: | research methods, health behaviours and lifestyles, construction type, policy studies, sociology, professional development, probability and distributions, real estate economics |
| Topics: | Urban Studies, Information Management, Research Practice, Stakeholder Management, Governance, Construction Technology, Health and Safety |
| Descriptive scope: | 4 PCTA |
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