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Co-movement and Forecasting Analysis of Major Real Estate Markets by Wavelet Coherence and Multiple Wavelet Coherence

Author

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  • Cengiz KARATAS

    (Financial Economics Graduate Program, Yeditepe University 34755, Istanbul, Turkey)

  • Gazanfer UNAL

    (Financial Economics Graduate Program, Yeditepe University 34755, Istanbul, Turkey)

  • Adil YILMAZ

    (Financial Economics Graduate Program, Yeditepe University 34755, Istanbul, Turkey)

Abstract

Wavelet coherence of time series provides valuable information about dynamic correlation and its impact on time scales. Here, the authors analyze the wavelet coherence of major real estate markets data, and take the USA, Hong Kong of China, Canada, Japan, and Developed Europe real estate market prices as time series. The wavelet coherence results show relationships among these markets, the correlations between the two and three markets (by multiple wavelet coherence) and how these relationships vary in the time-frequency space. These relationships allow the authors to build VARMA models of real estate data which produce forecasts with small errors.

Suggested Citation

  • Cengiz KARATAS & Gazanfer UNAL & Adil YILMAZ, 2017. "Co-movement and Forecasting Analysis of Major Real Estate Markets by Wavelet Coherence and Multiple Wavelet Coherence," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-18, June.
    • Handle: RePEc:wsi:cjuesx:v:05:y:2017:i:02:n:s2345748117500105
    DOI: 10.1142/S2345748117500105
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    References listed on IDEAS

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    1. Adil YILMAZ & Gazanfer UNAL & Cengiz KARATAS, 2016. "Wavelet Based Analysis of Major Real Estate Markets," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 7(2), pages 107-116.
    2. Athanasopoulos, George & Vahid, Farshid, 2008. "VARMA versus VAR for Macroeconomic Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 237-252, April.
    3. repec:srs:journl:jasf:v:7:y:2016:i:2:p:107-116 is not listed on IDEAS
    4. Abdullah Almasri & Ghazi Shukur, 2003. "An illustration of the causality relation between government spending and revenue using wavelet analysis on Finnish data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(5), pages 571-584.
    5. Jozef BARUNÍK & Lukáš VÁCHA, 2013. "Contagion among Central and Eastern European Stock Markets during the Financial Crisis," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 443-453, November.
    6. Yilmaz, Adil & Unal, Gazanfer & Karatasoglu, Cengiz, 2016. "Wavelet Based Analysis Of Major Real Estate Markets," MPRA Paper 74083, University Library of Munich, Germany.
    7. Aguiar-Conraria, Luís & Azevedo, Nuno & Soares, Maria Joana, 2008. "Using wavelets to decompose the time–frequency effects of monetary policy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2863-2878.
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    Cited by:

    1. Indranil Ghosh & Manas K. Sanyal & R. K. Jana, 2021. "Co-movement and Dynamic Correlation of Financial and Energy Markets: An Integrated Framework of Nonlinear Dynamics, Wavelet Analysis and DCC-GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 503-527, February.
    2. Kola Ijasan & George Tweneboah & Maurice Omane-Adjepong & Peterson Owusu Junior, 2019. "On the global integration of REITs market returns: A multiresolution analysis," Cogent Economics & Finance, Taylor & Francis Journals, vol. 7(1), pages 1690211-169, January.

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