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Spillover effects of Great Recession on Hong-Kong’s Real Estate Market: An analysis based on Causality Plane and Tsallis Curves of Complexity–Entropy

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  • Argyroudis, George S.
  • Siokis, Fotios M.

Abstract

This paper investigates the impact of the sub-prime loan crisis on the Real Estate Market of Hong-Kong. Based on permutation entropy, complexity–entropy causality plane and Tsallis complexity–entropy curve, we characterize the complexity of the housing indices-both in terms of size and region-and distinguish the level of informational efficiency. By calculating the quantifiers we report that most indices exhibit a behavior equivalent to a persistent stochastic dynamics with Hurst exponents between 0.5 and 0.7. The outbreak of the crisis had changed the dynamical structure of the indices decreasing the level of randomness and increasing considerably their regularity and predictability. Only the index of the Kowloon area seems not impacted by the crisis, exhibiting higher levels of informational efficiency. The results are robust based on the utilization of two different entropy definitions: The Shannon and Tsallis-q entropy. Lastly, with the temporal evolution of the indices, we identify periods where the underlying dynamical structure of the market was impacted by certain events like the SARS epidemic and the imposition of Special Stamp Duty on housing.

Suggested Citation

  • Argyroudis, George S. & Siokis, Fotios M., 2019. "Spillover effects of Great Recession on Hong-Kong’s Real Estate Market: An analysis based on Causality Plane and Tsallis Curves of Complexity–Entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 576-586.
  • Handle: RePEc:eee:phsmap:v:524:y:2019:i:c:p:576-586
    DOI: 10.1016/j.physa.2019.04.052
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    as
    1. Eddie Chi-Man Hui & Ivan Ng & Otto Muk-Fai Lau, 2011. "Speculative bubbles in mass and luxury properties: an investigation of the Hong Kong residential market," Construction Management and Economics, Taylor & Francis Journals, vol. 29(8), pages 781-793, July.
    2. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    3. Aurelio Fernández Bariviera & Luciano Zunino & María Belén Guercio & Lisana Martinez & Osvaldo Rosso, 2013. "Revisiting the European sovereign bonds with a permutation-information-theory approach," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(12), pages 1-10, December.
    4. Aurelio F. Bariviera & Luciano Zunino & Osvaldo A. Rosso, 2016. "Crude Oil Market And Geopolitical Events: An Analysis Based On Information-Theory-Based Quantifiers," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 21(1), pages 41-51, May.
    5. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
    6. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    7. Risso, Wiston Adrián, 2008. "The informational efficiency and the financial crashes," Research in International Business and Finance, Elsevier, vol. 22(3), pages 396-408, September.
    8. Ito, Mikio & Sugiyama, Shunsuke, 2009. "Measuring the degree of time varying market inefficiency," Economics Letters, Elsevier, vol. 103(1), pages 62-64, April.
    9. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    10. Yi-Cheng Zhang, 1999. "Toward a Theory of Marginally Efficient Markets," Papers cond-mat/9901243, arXiv.org.
    11. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    12. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    13. Aurelio Fernandez Bariviera & María Belén Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "The (in)visible hand in the Libor market: an information theory approach," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(8), pages 1-9, August.
    14. Bariviera, A.F. & Guercio, M. Belén & Martinez, Lisana B., 2012. "A comparative analysis of the informational efficiency of the fixed income market in seven European countries," Economics Letters, Elsevier, vol. 116(3), pages 426-428.
    15. Alvarez-Ramirez, Jose & Rodriguez, Eduardo & Espinosa-Paredes, Gilberto, 2012. "Is the US stock market becoming weakly efficient over time? Evidence from 80-year-long data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5643-5647.
    16. De Micco, L. & González, C.M. & Larrondo, H.A. & Martin, M.T. & Plastino, A. & Rosso, O.A., 2008. "Randomizing nonlinear maps via symbolic dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3373-3383.
    17. Martin, M.T. & Plastino, A. & Rosso, O.A., 2006. "Generalized statistical complexity measures: Geometrical and analytical properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 439-462.
    18. Robert J. Shiller, 2015. "Irrational Exuberance," Economics Books, Princeton University Press, edition 3, number 10421.
    19. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2009. "Forbidden patterns, permutation entropy and stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2854-2864.
    20. Oh, Gabjin & Kim, Seunghwan & Eom, Cheoljun, 2007. "Market efficiency in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 209-212.
    21. Eom, Cheoljun & Choi, Sunghoon & Oh, Gabjin & Jung, Woo-Sung, 2008. "Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(18), pages 4630-4636.
    22. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    23. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    24. Zhang, Yi-Cheng, 1999. "Toward a theory of marginally efficient markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(1), pages 30-44.
    25. Martina, Esteban & Rodriguez, Eduardo & Escarela-Perez, Rafael & Alvarez-Ramirez, Jose, 2011. "Multiscale entropy analysis of crude oil price dynamics," Energy Economics, Elsevier, vol. 33(5), pages 936-947, September.
    26. K. C. Lam & C. Y. Yu & K. Y. Lam, 2008. "An Artificial Neural Network and Entropy Model for Residential Property Price Forecasting in Hong Kong," Journal of Property Research, Taylor & Francis Journals, vol. 25(4), pages 321-342, November.
    27. Zunino, Luciano & Fernández Bariviera, Aurelio & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2012. "On the efficiency of sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4342-4349.
    28. Rosso, Osvaldo A & Mairal, Marı́a Liliana, 2002. "Characterization of time dynamical evolution of electroencephalographic epileptic records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 469-504.
    29. Lamberti, P.W & Martin, M.T & Plastino, A & Rosso, O.A, 2004. "Intensive entropic non-triviality measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 119-131.
    30. Jauregui, M. & Zunino, L. & Lenzi, E.K. & Mendes, R.S. & Ribeiro, H.V., 2018. "Characterization of time series via Rényi complexity–entropy curves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 498(C), pages 74-85.
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    2. Vincenzo Del Giudice & Pierfrancesco De Paola & Francesco Paolo Del Giudice, 2020. "COVID-19 Infects Real Estate Markets: Short and Mid-Run Effects on Housing Prices in Campania Region (Italy)," Social Sciences, MDPI, vol. 9(7), pages 1-18, July.
    3. Yuan, Ying & Du, Xinyu, 2023. "Dynamic spillovers across global stock markets during the COVID-19 pandemic: Evidence from jumps and higher moments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    4. Lahmiri, Salim & Bekiros, Stelios, 2020. "Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).

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