Purpose This paper aims to examine real estate price volatility in Hong Kong. Monthly data on housing, offices, retail and factories in Hong Kong were analyzed from February 1993 to February 2019 to test whether volatility clusters are present in the real estate market. Real estate price determinants were also investigated. Design/methodology/approach Autoregressive conditional heteroscedasticity–Lagrange multiplier test is used to examine the volatility clustering effects in these four kinds of real estate. An autoregressive and moving average model–generalized auto regressive conditional heteroskedasticity (GARCH) model was used to identify real estate price volatility determinants in Hong Kong. Findings There was volatility clustering in all four kinds of real estate. Determinants of price volatility vary among different types of real estate. In general, housing volatility in Hong Kong is influenced primarily by the foreign exchange rate (both RMB and USD), whereas commercial real estate is largely influenced by unemployment. The results of the exponential GARCH model show that there were no asymmetric effects in the Hong Kong real estate market. Research limitations/implications This volatility pattern has important implications for investors and policymakers. Residential and commercial real estate have different volatility determinants; investors may benefit from this when building a portfolio. The analysis and results are limited by the lack of data on real estate price determinants. Originality/value To the best of the authors’ knowledge, this paper is the first study that evaluates volatility in the Hong Kong real estate market using the GARCH class model. Also, this paper is the first to investigate commercial real estate price determinants.

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This study examines the impact of COVID-19 sentiment on office building rents and vacancy rates in China with a COVID-19 sentiment index constructed based on Baidu search queries on COVID-19-related keywords. We analyzed the data of office buildings and economic data from 2013 Q3 to 2022 Q2 in seven major Chinese cities with a two-stage Error Correction Model framework. We found that a heightened level of COVID-19 sentiment significantly and adversely affects the Chinese office buildings market. Specifically, office building rents decrease more than 8% if a city is exposed to an increase of one unit of COVID-19 sentiment for an entire quarter. The interaction terms model further reveals that the COVID-19 sentiment has a more substantial impact on office building rents where office vacancy is higher, reflecting an asymmetric effect. The findings here support the fear sentiment hypothesis. The findings suggest that a heightened level of investors’ COVID-19 sentiment resulted in a deterioration of office rents, reinforcing the role of investors’ sentiment in the pricing of office buildings. The findings suggest that investors should consider investor sentiment, particularly COVID-19 sentiment, in their decision-making.