Price Discovery in the Hong Kong Real Estate Market

1998 ◽  
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Price Discovery ◽  
Real Estate Market

Short Sales and Price Discovery in the Hong Kong Real Estate Market

2015 ◽  
Vol 45 (1) ◽  
pp. 133-153 ◽  
Author(s):  
Siu Kei Wong ◽  
Thomas C. C. Lai ◽  
Kuang Kuang Deng
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Price Discovery ◽  
Real Estate Market ◽  
Short Sales

Price discovery in the Hong Kong real estate market

2001 ◽  
Vol 18 (3) ◽  
pp. 187-216 ◽  
Author(s):  
K.W. Chau ◽  
Bryan D. MacGregor ◽  
Gregory M. Schwann
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Price Discovery ◽  
Real Estate Market

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.

scholarly journals International Real Estate Review

2016 ◽  
Vol 19 (1) ◽  
pp. 27-49
Author(s):  
William Mingyan Cheung ◽  
◽  
James Chicheong Lei ◽  
Desmond Tsang ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Price Discovery ◽  
Common Factor ◽  
Significant Proportion ◽  
Real Estate Market ◽  
Reverse Causality ◽  
Public And Private ◽  
Real Estate Markets ◽  
The Public ◽  
Private Real Estate

This study examines whether property transaction affects the price discovery process in real estate markets. Prior literature shows that price discovery generally first takes place in the securitized public real estate investment trust (REIT) market. We conjecture that property transaction provides novel information to the direct real estate market and can change the dynamics between public and private real estate returns. We employ a unique dataset of property transactions to construct "transaction windows¨ and specifically examine the causality between public and private real estate markets around these periods. We form firm-level pairs of public and private price series, and estimate the normalized common factor loadings per Gonzalo and Granger (1995) by using a vector error-correction model. Our findings show that a significant proportion of price discovery happens in the private market instead of the public REIT market. Our results are robust to investments of different property types and different lengths of transaction windows. Overall, the findings in this study imply that property acquisition and disposition provide crucial information to the private real estate market and induce a reverse causality between the public and private markets.

Real estate market cyclical dynamics

2014 ◽  
Vol 10 (2) ◽  
pp. 241-262 ◽  
Author(s):  
Kim Hin/David Ho ◽  
Kwame Addae-Dapaah
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Real Estate Market ◽  
Var Model ◽  
Kuala Lumpur ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Price Response ◽  
Real Estate Cycle

Purpose – The purpose of this paper is to help us understand the real estate cycle and offers an analysis using a vector auto regression (VAR) model. The authors study the key international cities of Hong Kong, Kuala Lumpur and Singapore. The authors find four key outcomes. One, the real estate cycle is generally different from the underlying business cycle in local markets for the cities studies. Two, the real estate cycle is more exaggerated in the construction and development areas than in rents and vacancies. Three, the vacancy cycle tends to lead the rental cycle. And four, new construction completions tend to peak when vacancy is also peaking. The authors believe that future research should try to help understand the linkages that drive these outcomes. For example, are rigidities in the local permit and construction markets responsible for the link between construction peaks and vacancy peaks? Design/methodology/approach – Real estate market cyclical dynamics and its estimation via VAR model offers an insightful set of practical and empirical models. It affirms a comprehensive theoretical underpinning for analysing the prime office and residential sectors of the capitol cities of Kuala Lumpur, Singapore and Hong Kong in the fast developing Asia region. Its unrestricted form also provides an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, furnished by real estate market data providers. Findings – The office rental VAR model for Singapore (SOR), KL (KOR) and HK (HOR) show good fits. In the HOR model, rents and vacancies are negatively signed and significant for certain lagged relationships with other variables and with rents themselves. The office CV VAR model for Singapore (SOCV), KL (KOCV) and HK (HOCV) show good fits. In the HOCV model, capital values (CVs) and initial yields are negatively signed and significant for certain lagged relationships with other variables and with CVs themselves. Impulse response functions specified for seven years to mirror a medium-term real estate market cycle “die out” to zero for the stationary VAR models that are estimated for the endogenous variables. The accumulated responses asymptote to some non-zero constant. Practical implications – The VAR model offers a complete and meaningful dynamic system of solely real estate variables for international real estate investors and policy makers in decision making. Its unrestricted form offers an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, which can be reliably provided by a dedicated real estate information and consultancy provider of international standing. Originality/value – The theoretical model offers a complete dynamic model system of the real estate space market, comprising a unique system of six linked equations that denote the relationship among supply, demand, construction, vacancy and rent over time, inclusive of price response slopes and lags. The VAR model enables the investigation of the effect of the lagged values of all the variables concerned. It also enables the explicit and rigorous quantitative forecasts of say rents and CVs when the rest of the variable can be forecasted beforehand.

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