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House price return volatility patterns in Turkey, Istanbul, Ankara and Izmir

House price return volatility patterns in Turkey, Istanbul, Ankara and Izmir PurposeThe 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/approachThe 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.FindingsEmpirical 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/implicationsThe 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/valueThe 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of European Real Estate Research Emerald Publishing

House price return volatility patterns in Turkey, Istanbul, Ankara and Izmir

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1753-9269
DOI
10.1108/JERER-03-2015-0015
Publisher site
See Article on Publisher Site

Abstract

PurposeThe 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/approachThe 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.FindingsEmpirical 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/implicationsThe 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/valueThe 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.

Journal

Journal of European Real Estate ResearchEmerald Publishing

Published: May 3, 2016

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