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Volatility clustering, risk-return relationship and asymmetric adjustment in the Finnish housing market

Josephine Dufitinema (School of Technology and Innovation, Department of Mathematics and Statistics, University of Vaasa, Vaasa, Finland)

International Journal of Housing Markets and Analysis

ISSN: 1753-8270

Article publication date: 25 February 2020

Issue publication date: 16 June 2020




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.


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.


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.


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.



I thank Professor Seppo Pynnönen for his helpful discussions and suggestions. The financial support from the foundation for economic education (Liikesivistyrahasto) is gratefully acknowledged.


Dufitinema, J. (2020), "Volatility clustering, risk-return relationship and asymmetric adjustment in the Finnish housing market", International Journal of Housing Markets and Analysis, Vol. 13 No. 4, pp. 661-688.



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