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Article
Publication date: 7 August 2009

Chyi Lin Lee

The purpose of this paper is to examine the housing price volatility for eight capital cities in Australia over 1987‐2007. Specifically, the volatility of Australian…

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Abstract

Purpose

The purpose of this paper is to examine the housing price volatility for eight capital cities in Australia over 1987‐2007. Specifically, the volatility of Australian housing and its determinants were investigated.

Design/methodology/approach

An exponential‐generalised autoregressive conditional heteoskedasticity (EGARCH) model was employed to analyse the volatility for eight capital cities in Australia. The Engle LM test was also utilised to examine the volatility clustering effects in these cities.

Findings

The volatility clustering effects (ARCH effects) were found in many Australian capital cities. The importance of estimating each individual city's EGARCH model was also demonstrated in which the determinants of housing volatility vary from a city to another city. Asymmetric of the positive and negative shocks were also documented.

Research limitations/implications

This study has implications for investors and policy makers in which housing investors should estimate the conditional variance (EGARCH process) of a housing market in respect to the volatility of housing series is not always constant over time. Furthermore, policy makers should also address the importance of considering the sub‐national factors in formulating the national housing policy. The analysis and results are limited by the quality of the data.

Originality/value

This paper is one of the few studies in housing volatility. Additionally, it is probably the first attempt to assess the volatility spillover effects in the Australian housing market.

Details

International Journal of Housing Markets and Analysis, vol. 2 no. 3
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 3 May 2016

Yener Coskun and Hasan Murat Ertugrul

The purpose of this paper is to empirically analyze volatility properties of the house price returns of Turkey and Istanbul, Ankara and Izmir provinces over the period of…

Abstract

Purpose

The purpose of this paper is to empirically analyze volatility properties of the house price returns of Turkey and Istanbul, Ankara and Izmir provinces over the period of July 2007-June 2014.

Design/methodology/approach

The paper uses conditional variance models, namely, ARCH, GARCH and E-GARCH. As the supportive approach for the discussions, we also use correlation analysis and qualitative inputs.

Findings

Empirical findings suggest several points. First, city/country-level house price return volatility series display volatility clustering pattern and therefore volatilities in house price returns are time varying. Second, it seems that there were high (excess) and stable volatility periods during observation term. Third, a significant economic event may change country/city-level volatilities. In this context, the biggest and relatively persistent shock was the lagged negative shocks of global financial crisis. More importantly, short-lived political/economic shocks have not significant impacts on house price return volatilities in Turkey, Istanbul, Ankara and Izmir. Fourth, however, house price return volatilities differ across geographic areas, volatility series may show some co-movement pattern. Fifth, volatility comparison across cities reveal that Izmir shows more excess volatility cases, Ankara recorded the highest volatility point and Istanbul and national series show lower and insignificant volatilities.

Research limitations/implications

The study uses maximum available data and focuses on some house price return volatility patterns. The first implication of the findings is that micro/macro dimensions of house price return volatilities should be carefully analyzed to forecast upside/downside risks of house price returns. Second, defined volatility clustering pattern implies that rate of return of housing investment may show specific patterns in some periods and volatile periods may result in some large losses in the returns. Third, model results generally suggest that however data constraint is a major problem, market participants should analyze regional idiosyncrasies during their decision-making in housing portfolio management. Fourth, because house prices are not sensitive to relatively less structural shocks, housing may represent long-term investment instrument if it provides satisfactory hedging from inflation.

Originality/value

The evidences and implications would be useful for housing market participants aiming to manage/use externalities of housing price movements. From a practical contribution perspective, the study provides a tool that will allow measuring first time of the return volatility patterns of house prices in Turkey and her three biggest provinces. Local level analysis for Istanbul, Ankara and Izmir provinces, as the globally fastest growing cities, would be found specifically interesting by international researchers and practitioner.

Details

Journal of European Real Estate Research, vol. 9 no. 1
Type: Research Article
ISSN: 1753-9269

Keywords

Article
Publication date: 18 March 2019

Teresia Kaulihowa and Katrina Kamati

This paper aims to test the volatility and analyses the macroeconomic determinants of house price volatility in Namibia over the period 2007 Quarter 1 to 2017 Quarter 2…

Abstract

Purpose

This paper aims to test the volatility and analyses the macroeconomic determinants of house price volatility in Namibia over the period 2007 Quarter 1 to 2017 Quarter 2. It further explores the causal relations between house price volatility and its determinants.

Design/methodology/approach

The study used autoregressive conditional heteroskedastic and generalized autoregressive conditional heteroskedastic models to test for volatility. The vector error correction model was used to analyse the determinants and causal relations.

Findings

The results support the hypothesis that house prices in Namibia exhibits persistent volatility. It was further established that past period volatility’ GDP and mortgage loans are the key determinants of house price volatility. Additionally’ there exists unidirectional causality from GDP and mortgage loans to house price volatility.

Practical implications

Policy implications emanating from the study implies that macroeconomic fundamentals should be monitored closely to mitigate the issues of house price volatility.

Originality/value

The study is the first of its kind in Namibia to address the pertinent issues of ever increasing housing prices.

Details

International Journal of Housing Markets and Analysis, vol. 12 no. 4
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 22 March 2021

Sudeshna Ghosh

The purpose of this paper is to examine the asymmetric impact of economic policy uncertainty (EPU) on the volatility of the housing price index (RP) based on quarterly…

Abstract

Purpose

The purpose of this paper is to examine the asymmetric impact of economic policy uncertainty (EPU) on the volatility of the housing price index (RP) based on quarterly observations from major European countries, namely, France, Germany, Sweden, Greece Italy and the UK.

Design/methodology/approach

The nonlinear autoregressive distributed lag model method is used to investigate the asymmetric impact of EPU on RP. In addition to considering EPU as the explanatory variable, industrial production (IP) (as a proxy for economic growth), interest rate (I), inflationary tendency (Consumer Price Index) and share prices (S) are included as major control variables. The period of the observations runs from 1996Q1 to 2019Q1.

Findings

The Wald test confirms the long-run asymmetric relationship for all countries. The alternative specification of the data sets reconfirms the asymmetric impact on RP in the long run, thereby verifying the robustness of the study.

Research limitations/implications

The study has implications for investors seeking to incorporate housing price behaviour within their portfolio structure. The analysis and findings are constrained by the availability of data.

Originality/value

This is one of the few studies on housing price dynamics related to the major economies of the European region that explore asymmetries. Additionally, it is the first to explore the asymmetry dynamics using the EPU variable.

Details

International Journal of Housing Markets and Analysis, vol. 14 no. 5
Type: Research Article
ISSN: 1753-8270

Keywords

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…

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

Keywords

Article
Publication date: 25 February 2020

Josephine Dufitinema

The purpose of this paper is to examine whether the house prices in Finland share financial characteristics with assets such as stocks. The studied regions are 15 main…

Abstract

Purpose

The purpose of this paper is to examine whether the house prices in Finland share financial characteristics with assets such as stocks. The studied regions are 15 main regions in Finland over the period of 1988:Q1-2018:Q4. These regions are divided geographically into 45 cities and sub-areas according to their postcode numbers. The studied type of dwellings is apartments (block of flats) divided into one-room, two rooms and more than three rooms apartment types.

Design/methodology/approach

Both Ljung–Box and Lagrange multiplier tests are used to test for clustering effects (autoregressive conditional heteroscedasticity effects). For cities and sub-areas with significant clustering effects, the generalized autoregressive conditional heteroscedasticity (GARCH)-in-mean model is used to determine the potential impact that the conditional variance may have on returns. Moreover, the exponential GARCH model is used to examine the possibility of asymmetric effects of shocks on house price volatility. For each apartment type, individual models are estimated; enabling different house price dynamics, and variation of signs and magnitude of different effects across cities and sub-areas.

Findings

Results reveal that clustering effects exist in over half of the cities and sub-areas in all studied types of apartments. Moreover, mixed results on the sign of the significant risk-return relationship are observed across cities and sub-areas in all three apartment types. Furthermore, the evidence of the asymmetric impact of shocks on housing volatility is noted in almost all the cities and sub-areas housing markets. These studied volatility properties are further found to differ across cities and sub-areas, and by apartment types.

Research limitations/implications

The existence of these volatility patterns has essential implications, such as investment decision-making and portfolio management. The study outcomes will be used in a forecasting procedure of the volatility dynamics of the studied types of dwellings. The quality of the data limits the analysis and the results of the study.

Originality/value

To the best of the author’s knowledge, this is the first study that evaluates the volatility of the Finnish housing market in general, and by using data on both municipal and geographical level, particularly.

Details

International Journal of Housing Markets and Analysis, vol. 13 no. 4
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 5 June 2017

Chyi Lin Lee

Extensive studies have investigated the relation between risk and return in the stock and major asset markets, whereas little studies have been done for housing

Abstract

Purpose

Extensive studies have investigated the relation between risk and return in the stock and major asset markets, whereas little studies have been done for housing, particularly the Australian housing market. This study aims to determine the relationship between housing risk and housing return in Australia.

Design/methodology/approach

The analysis of this study involves two stages. The first stage is to estimate the presence of volatility clustering effects. Thereafter, the relation between risk and return in the Australian housing market is assessed by using a component generalised autoregressive conditional heteroscedasticity-in-mean (C-CARCH-M) model.

Findings

The empirical results show that there is a strong positive risk-return relationship in all Australian housing markets. Specifically, comparable results are also evident in all housing markets in various Australian capital cities, reflecting that Australian home buyers, in general, are risk reverse and require a premium for higher risk level. This could be attributed the unique characteristics of the Australian housing market. In addition, there is evidence to suggest that a stronger volatility clustering effect than previously documented in the daily case.

Practical implications

The findings enable more informed and practical investment decision-making regarding the relation between housing return and housing risk.

Originality/value

This paper is the first study to offer empirical evidence of the risk-return relationship in the Australian housing market. Besides, this is the first housing price volatility study that utilizes daily data.

Details

International Journal of Housing Markets and Analysis, vol. 10 no. 3
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 10 April 2009

I‐Chun Tsai and Ming‐Chi Chen

The purpose of this paper is to show an indication that the asymmetric volatility between house price movement may account for the defensiveness of the housing market.

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Abstract

Purpose

The purpose of this paper is to show an indication that the asymmetric volatility between house price movement may account for the defensiveness of the housing market.

Design/methodology/approach

First the UK nation‐wide house price data from the last quarter (Q4) of 1955 to the last quarter of 2005 are used and then the most suitable mean and variance equations to estimate the conditional heteroscedasticity volatilities of the returns of house prices are selected. Second, a variable that examines the leverage effect of volatility is incorporated into the model. The GJR‐GARCH model is used.

Findings

The results of the empirical test show that while the lagged innovations are negatively correlated with housing return, that is when there is bad news, the current volatility of housing return might decline.

Research limitations/implications

The results indicate that the volatilities between house prices moving up and moving down are asymmetric.

Practical implications

The results show that there is a defensive effect in the UK housing market during the data periods used.

Originality/value

Although several articles have documented that there is heteroscedasticity and autocorrelation in the volatilities of real estate prices, few of those papers have noted one of the most important advantages of the housing market, its defensiveness, from the viewpoint of volatile behavior.

Details

Property Management, vol. 27 no. 2
Type: Research Article
ISSN: 0263-7472

Keywords

Article
Publication date: 19 May 2022

Ting Fan, Asadullah Khaskheli, Syed Ali Raza and Nida Shah

In the past few years, numerous economic uncertainty challenges have occurred globally. These uncertainties grasp the attention of the researchers and they examine the…

Abstract

Purpose

In the past few years, numerous economic uncertainty challenges have occurred globally. These uncertainties grasp the attention of the researchers and they examine the role of economic policy uncertainties in several aspects. Therefore, this study contributes to the literature by exploring the house prices volatility and economic policy uncertainty nexus in G7 countries.

Design/methodology/approach

The authors applied the newly introduced econometric technique, the GARCH-MIDAS model, to the sample size of January 1998–May 2021.

Findings

The result shows a significant relationship between house prices volatility and economic policy uncertainty. Moreover, economic policy uncertainty acts as a significant determinant of house prices volatility. In addition, the out-of-sample also shows that the economic policy uncertainty is an effective predictor and the GARCH-MIDAS has a better predictive ability.

Originality/value

This paper makes a unique contribution to the literature with reference to developed economies, being a pioneering attempt to investigate the GARCH-MIDAS model to analyze the relationship between housing prices volatility and economic policy uncertainty by applying more rigorous and advanced econometric techniques.

Details

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

Keywords

Article
Publication date: 22 May 2018

Steve Cook and Duncan Watson

This paper aims to extend existing research in relation to both the importance of volume effects within housing markets and the specific behaviour of the London housing

Abstract

Purpose

This paper aims to extend existing research in relation to both the importance of volume effects within housing markets and the specific behaviour of the London housing market. A detailed borough-level examination is undertaken of the relationships between volume, house prices and house price volatility. Support for alternative housing market theories, the degree of heterogeneity in house price behaviour across boroughs and the extent to which housing displays differing properties to other financial assets are examined.

Design/methodology/approach

Correlation analyses, causality testing and volatility modelling are undertaken in extended forms which synthesise and extend approaches within the housing, economics and finance literatures. The various modelling and testing techniques are supplemented via the use of alternative variable transformations to evaluate housing market behaviour in detail.

Findings

Novel findings are provided concerning both volume effects within housing markets generally and the specific properties of London housing market. Evidence concerning bubbles, the volatility-reducing effects of volume, the importance of geographical and price-related factors underlying the relationship between volume and both house price growth and volatility and the presence of asymmetric adjustment in the London housing market are all provided. The extent and nature of the support available for alternative housing market theories are evaluated.

Originality/value

The volatility-reducing effects of volume within housing markets, along with volume effects and the presence of asymmetric adjustment within the London housing market are examined for the first time. New empirical evidence on the support for alternative housing market theories and the differing empirical characteristics of housing relative to other financial assets are presented.

Details

International Journal of Housing Markets and Analysis, vol. 11 no. 3
Type: Research Article
ISSN: 1753-8270

Keywords

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