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Article
Publication date: 20 September 2013

Dimitrios Asteriou and Kyriaki Begiazi

The purpose of this paper is to examine the US real estate investment trusts (REITs) for the 2000‐2012 period using GARCH models that include the day‐of‐the‐week effect and the…

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Abstract

Purpose

The purpose of this paper is to examine the US real estate investment trusts (REITs) for the 2000‐2012 period using GARCH models that include the day‐of‐the‐week effect and the stock‐market index as explanatory variables. This technique documents the return and volatility of equity, mortgage and hybrid REITs.

Design/methodology/approach

The study starts with a CAPM model and continues with GARCH(1,1), TGARCH(1,1) and EGARCH(1,1) models for each of the REIT subcategories with and without the days of the week as dummy variables.

Findings

The results show that the best‐fitted model is EGARCH except the equity REIT series without the dummy variables that is better described with the GARCH. The stock market has a significant impact on REIT returns but no remarkable significance in respect of the day‐of‐the‐week effect.

Practical implications

The findings suggest that there is not a significant risk diversification potential between REITs and common stocks. In the scope of the credit crisis which originated in the real estate market it must be taken seriously into consideration that REITs, except of the equity REITs, are more sensitive to bad news.

Originality/value

This paper uses daily returns for each of the three main REIT subcategories opposed to the monthly that are commonly used. We point out the evidence of asymmetric responses, suggesting the leverage effect and differential financial risk depending on the direction of price change movements.

Details

Journal of Property Investment & Finance, vol. 31 no. 6
Type: Research Article
ISSN: 1463-578X

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Article
Publication date: 17 February 2021

Shizhen Wang and David Hartzell

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…

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Abstract

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.

Details

International Journal of Housing Markets and Analysis, vol. 15 no. 1
Type: Research Article
ISSN: 1753-8270

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