Wavelet Based Analysis of Major Real Estate Markets

  • Adil YILMAZ Yeditepe University
  • Gazanfer UNAL Yeditepe University
  • Cengiz KARATAS Yeditepe University

Abstract

Wavelet coherence of time series provide valuable information about dynamic correlation and its impact on time scales. Here, we analyze the wavelet coherence of major real estate markets data. Our paper is the first to link co-movement in terms of wavelet coherence. Here we consider USA, Canada, Japan, China and Developed Europe real estate market prices as time series. Wavelet coherence results reveal interconnected relationships between these markets and how these relationships vary in the time-frequency space. These relationships allow us to build VARMA models of real estate data which yield forecast results with small errors.

References

[1] Aguiar-Conraria, L., Azevedo N., and Soares, M.J. (2008). Using wavelets to decompose the time-frequency effects of monetary policy. Physica A 387 (12): 2863-2878.
[2] Almasri A., Shukur, G. (2003). An Illustration of the Causality Relation between Government Spending and Revenue Using Wavelet Analysis on Finnish Data. Journal of Applied Statistics, 30(5): 571-584.
[3] Athanasopoulos, G. and Vahid, F. (2008). VARMA versus VAR for Macroeconomic Forecasting. Journal of Business & Economics Statistics, 26(2): 237-252.
[4] Barunik, J., E. and Vacha, L. (2013). Contagion among Central and Eastern European stock markets during the financial crisis, Czech Journal of Economics anf Finance, 63(5): 443-453.
[5] Dias, G.F. and Kapetanios, G. (2011). Forecasting Medium and Large Datasets with Vector Autoregressive Moving Average (VARMA) Models, Queen Mary University of London.
[6] Gallegati, M. (2005). A Wavelet Analysis of MENA Stock Markets. Mimeo, Universita Politecnica Delle Marche, Ancona, Italy.
[7] Grinsted, A., Moore, J. C., and Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Non-linear Processes in Geophysics, 11: 561-566.
[8] Lau, K.-M., and Weng, H.-Y. (1995) Climate signal detection using wavelet transform: How to make a time series sing. Bull. Amer. Meteor. Soc., 76: 2391–2402.
[9] Lutkepohl, H. (2004). Forecasting with VARMA Models, EUI Working Paper, Eco No. 2004/25.
[10] Oh, S., Lau E., Puah, C. and Mansor, S. (2010). Volatlity Co-movement of ASEAN-5 Equity Markets. Journal of Advanced Studies in Finance, Volume I, 1(1): 23- 33.
[11] Rua, A. and Nunes, L.C. (2009). International comovement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16 (4): 632- 639.
[12] Simionescu, M. (2013). The Use of VARMA Models in Forecasting Macroeconomic Indicators. Economics and Sociology, 6 (2): 94-102.
[13] Tiwari, A. K. (2013), Oil prices and the macroeconomy reconsideration for Germany: Using continuous wavelet. Economic Modelling, 30: 636-640.
[14] Tiwari, A. K. (2012), Decomposing Time-Frequency Relationship between Interest Rates and Share Prices in India through Wavelets, MPRA Paper No. 39693.
[15] Torrence, C. and Compo G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79 (1): 61-78.
[16] Vacha L., Barunik J. (2012). Co-movement of energy commodities revisited. Evidence from wavelet coherence analysis. Energy Economics, 34(1): 241-247.
Published
2017-01-30
How to Cite
YILMAZ, Adil; UNAL, Gazanfer; KARATAS, Cengiz. Wavelet Based Analysis of Major Real Estate Markets. Journal of Advanced Studies in Finance, [S.l.], v. 7, n. 2, p. 107-116, jan. 2017. ISSN 2068-8393. Available at: <https://journals.aserspublishing.eu/jasf/article/view/550>. Date accessed: 19 apr. 2024.
Section
Journal of Advanced Studies in Finance

Keywords

real estate markets; REIT; co-movement; wavelet coherence; VARMA