scholarly journals International Real Estate Review

2021 ◽  
Vol 24 (1) ◽  
pp. 113-138
Author(s):  
Shizhen Wang ◽  
◽  
David Hartzell ◽  
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Interest Rates ◽  
Real Estate Market ◽  
Housing Affordability ◽  
Commercial Real Estate ◽  
Price Ratio ◽  
Distributed Lag ◽  
Risk Free Rate ◽  
Free Rate

We apply the dynamic Gordon growth model to the Hong Kong real estate market to analyze quarterly data on four kinds of real estate—housing, office, retail, and factory properties—from 1999 to 2020. We find that factories have the highest total returns among the four types of real estate, and also a larger Sharpe ratio. The total returns of these four kinds of real estate are highly correlated. The results of an autoregressive distributed lag model show that the gross domestic product growth rate is the key determinant of real estate returns, while changes in foreign direct investment also influence housing and retail returns. The expected value of the risk-free rate is the key factor that determines the rent-price ratio. The decline in the risk-free rate in Hong Kong is the main reason that the real estate price-rent ratio has increased from 20 to 40 in the last twenty years. Our research represents an early contribution that compares the performance of housing and commercial real estate at the city level, with both types of real estate having similar determinants. Finally, we find that the fall in risk-free interest rates worsens housing affordability in Hong Kong.

Mobilitŕ urbana e scelte residenziali: un'analisi economica

2009 ◽  
pp. 71-87
Author(s):  
Marina Bravi ◽  
Sergio Giaccaria
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Real Estate Market ◽  
Housing Affordability ◽  
Urban Mobility ◽  
The Real Estate ◽  
Economic Segregation ◽  
The Real Estate Market ◽  
Very High ◽  
Economic Improvement

- This study explores the intricate relationships between urban mobility, residential choices (rent or ownership) and economic levels of housing affordability of the demand. During the residential changing, the families consider simultaneously many factors, both economic and territorial, that affect their decision. This research highlights as, in a situation characterized by very high prices and very important levels of the interest rates, the expectations of the economic improvement of the households are frustrated; the anomalies in the real estate market (rent and ownership) result, at the urban scale, in a sort of stoc s, as well as, economic segregation.Key words urban mobility, housing affordability, residential choices.Parole chiave: mobilitŕ urbana, accessibilitŕ ai servizi abitativi, scelte residenziali.

scholarly journals What influences real estate volatility in Hong Kong? An ARMA-GARCH approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shizhen Wang ◽  
David Hartzell
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Garch Model ◽  
Price Volatility ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Content Type ◽  
Volatility Clustering ◽  
Real Estate Price ◽  
Price Determinants

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.

scholarly journals OFFICE PRICE INDEX LAGGING IN SINGAPORE AND HONG KONG

2007 ◽  
Vol 11 (1) ◽  
pp. 33-46 ◽  
Author(s):  
Eddie Chi Man Hui ◽  
Ka Hung Yu ◽  
David Kim Hin Ho
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Stock Market ◽  
Price Discovery ◽  
State Space Model ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Test Case ◽  
Real Estate Investments ◽  
Kaiman Filter

Price discovery of real estate investment has been getting lots of attentions from researchers and it is generally believed that lagging errors exist in appraisal‐based returns of commercial real estate investments, in comparison to other investment instruments traded in the stock market. Due to fewer transactions in the commercial real estate market, it is reasonable to notice a difference in the handling of current market information. By introducing two study approaches along with a test case using Singapore's data, this paper explores the extent of lagging in Hong Kong's commercial (office) real estate values, in a State Space Model with Kaiman filter. The findings first suggest that whether appraisal‐based indices overstate or understate true values lies in the economy condition at the time. Then, commercial real estate values in Hong Kong are about three months behind the stock market property indices. Also, as indicated by the findings, data collection/selection bias may render a de‐lagged index not as efficient as it is supposed to be. This paper provides a different perspective on price discovery and the process of de‐lagging property values. Biurų kainų indekso atsilikimas Singapūre ir Honkonge Santrauka Investicijų į nekilnojamąjį turtą kainos mokslininkus itin domina. Dažnai manoma, kad, palyginti su kitais akcijų biržoje siūlomais investiciniais instrumentais, investicijų į komercini nekilnojamąjį turtą grąža vertinama klaidingai dėl atsilikimo. Kadangi komercinio nekilnojamojo turto rinkoje sandoriu sudaroma mažiau, verta pabrėžti, kaip skirtingai tvarkoma aktuali rinkos informacija. Pristatant du tyrimo būdus kartu su atvejo tyrimu pagal Singapūro duomenis, šiame darbe, remiantis būsenų erdves modeliu ir naudojant Kalmaro filtrą, nagrinėjamas Honkongo komercinio nekilnojamojo turto (biuru) verčiu atsilikimas. Išvados pirmiausia rodo, kad tai, ar vertinimu pagristi indeksai padidina ar sumažina realias vertes, priklauso nuo esamu ekonominiu sąlygų. Be to, komercinio nekilnojamojo turto vertes Honkonge nuo akcijų rinkoje naudojamu nuosavybes indeksu atsilieka apie tris mėnesius. Išvados rodo ir tai, kad dėl šališko duomenųrinkimo (atrankos), neatsiliekantis indeksas gali būti ne toks efektyvus, kaip turėtu būti. Šiame darbe pateikiamas kitas kainų nustatymo būdas ir aprašomas nuosavybes vertes atsilikimo panaikinimo procesas.

Excess Returns in the Hong Kong Commercial Real Estate Market

1997 ◽  
Vol 14 (2) ◽  
pp. 91-105
Author(s):  
Gerald Brown ◽  
K Chau
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Excess Returns

Valuers’ Perception of Sustainability in the UK Commercial Real Estate Market

2019 ◽  
Author(s):  
Sarah Sayce ◽  
Jorn Van De Wetering ◽  
Syeda Hossain
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
The Uk

Interest Rates and Investment: Evidence from Commercial Real Estate

2016 ◽  
Author(s):  
Liang Peng ◽  
Thomas G. Thibodeau
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Commercial Real Estate

The Determinants of the Ex Ante Risk Premiumin Commercial Real Estate

2019 ◽  
Vol 41 (3) ◽  
pp. 411-441
Author(s):  
El i Beracha ◽  
Julia Freybote ◽  
Zhenguo Lin
Keyword(s):  
Real Estate ◽  
Risk Premium ◽  
Predictive Power ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Stock Market Volatility ◽  
Switching Regression ◽  
Risk Premiums ◽  
Debt Capital ◽  
Ex Ante

We investigate the determinants of the ex ante risk premium in commercial real estate. Using a 20-year time series and Markov-switching regression, we find that the ex ante risk premium is affected by fundamental and non-fundamental determinants, albeit not symmetrically when risk premiums are increasing and decreasing. In particular, we find that changes in debt capital market conditions have a higher predictive power for changes in the ex ante risk premium when it is increasing, while changes in stock market volatility and commercial real estate market returns have a higher predictive power when the risk premium is on the decline. In addition, changes in commercial real estate sentiment and NAREIT returns can predict changes in the ex ante risk premium; however, the predictive power of these variables varies across property types and risk premium (risk perception) states.

The Impact of Investor Sentiment on Commercial Real Estate Market Liquidity

2018 ◽  
Vol 40 (4) ◽  
pp. 597-628 ◽  
Author(s):  
Julia Freybote ◽  
Philip Seagraves
Keyword(s):  
Real Estate ◽  
Investor Sentiment ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Market Liquidity ◽  
The Impact
Sign in / Sign up

Export Citation Format

Share Document