Land and Housing Review (토지주택연구)

Land and Housing Research Institute (한국토지주택공사 토지주택연구원)
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The Empirical Information Spillover Effect between the Housing Market and the Stock Market

주택시장과 주식시장 간의 정보 이전효과의 연구

  • 최차순 (남서울대학교 부동산학과)
  • Received : 2021.08.02
  • Accepted : 2021.10.08
  • Published : 2021.10.30
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Abstract

This paper empirically examined the relationship between the housing market and the stock market to investigate the price and the asymmetric volatility spillover effects. The monthly housing price index and the monthly KOSPI were used for analysis. This research employed the EGARCH model. The analysis period was from January 1986 until June 2021 with periodization centered on the Asian Financial Crisis: before and after the crisis - the end of December 1997. The EGARCH model allows analysis of 'good news' and 'bad news' in understanding volatility. The price spillover effect was observed one way from the stock market to the housing market. On the contrary, the spillover effect was not found from the housing market to the stock market. The empirical evidence suggests that there are price and asymmetric volatility effects in the entire period of analysis in both housing and the stock markets. In the housing market, the negative effects of information were found pre-financial crisis while the positive effects, in other periods. However, in the stock market, the negative effects of information were found in the pre- and post-financial crisis periods. This means that the housing market is more affected by 'good news' than 'bad news' when information spreads to the markets while the stock market is more affected by 'bad news' than 'good news'. It is of significance to discover the variable returns by different information.

본 연구에서는 주택시장과 주식시장 간의 가격 및 비대칭적 변동성 이전효과(asymmetric volatility spillover)관계를 살펴보기 위해 주택 및 주식 가격지수를 이용하여 EGARCH 모형으로 분석하였다. 분석기간은 1986년 1월부터 2021년 6월까지 이고, IMF 외환위기 전후기간의 정보 연관성을 살펴보고자 하위기간으로 1986년 1월부터 1997년 12월까지 IMF 외환위기 이전기간과 1998년 1월부터 2021년 6월까지 이후기간으로 구분하여 분석하였다. 주택시장과 주식시장 간의 비대칭 변동성 이전효과 분석에 EGARCH 모형이 적합한 것으로 나타났다. 가격 이전효과는 주식시장에서 주택시장으로 일방향으로 존재하는 것으로 분석되었으나, 반대로 주택시장에서 주식시장으로의 이전효과는 존재하지 않는 것으로 나타났다. 비대칭적 변동성 이전효과는 주택 및 주식시장 양 시장에 존재하는 것으로 나타났다. 주택시장에서는 IMF 외환위기 이전기간에는 비대칭적 변동성이 부(-)의 효과이나 그 외에는 모두 양(+)의 효과를 보였고, 반면 주식시장에서는 IMF 외환위기 전후 모든 기간에서 부(-)의 효과를 보였다. 이는 주택시장은 악재보다 호재에 더 영향을 받고, 주식시장은 호재보다 악재에 더 영향을 받는다는 것이다. 따라서 정보의 유형별로 수익의 변동성을 식별하는 것이 중요하다.

Keywords

References

  1. 김상배(2018), "주택시장과 주식시장 사이의 상관관계에 관한 연구", 「부동산연구」, 28(2): 21~34.
  2. 김재경(2013), "VAR 모혀을 이용한 주가, 금리, 물가, 주택가격의 관계에 대한 실증연구", 「유통과학연구」, 11(10): 63~72. https://doi.org/10.13106/jds.2013.vol11.no10.63.
  3. 신종협(2019), "자산수익률 간 연관성 분석", 「시장경제연구」 , 48(3): 43~67.
  4. 유한수(2017), "주택시장과 주식시장 간의 연관성", 「부동산정책연구」, 8(2): 1~14.
  5. 이강용.이종아.정준호(2015), "주택시장과 주식시장의 동적 네트워크 구조 비교", 「부동산학보」, 61: 195~207.
  6. Black, F. (1976), "Studies of stock price volatility changes", Proceedings of the 1976 Meeting of the Business and Economic Statistics Section, American Statistical Association, Washington DC, 177~181.
  7. Campbell, Y. and L. Hentschel (1992), "No news is good news: An asymmetric model of changing volatility in stock return", Journal of Financial Economics, 31: 281~318. https://doi.org/10.1016/0304-405X(92)90037-X
  8. Dickey, D. and W. A. Fuller (1979), "Distribution of estimates for autoregressive time series with a unit root", Journal of the American Statistical Association, 74: 427~431. https://doi.org/10.2307/2286348
  9. Dolde, W. and D. Tirtiroglu (1997), "Temporal and spatial information diffusion in real estate price changes and variances", Real Estate Economics, 25(4): 539~565. https://doi.org/10.1111/1540-6229.00727
  10. Engle, R. F. and V. K. Ng (1993), "Measuring and testing the impact of news on volatility", The Journal of Finance, 48(5): 1749~1778. https://doi.org/10.1111/j.1540-6261.1993.tb05127.x
  11. Engle, R. F. and R. Susmel (1994), "Hourly volatility spillovers between international equity markets", Journal of International Money and Finance, 13(1): 3~25. https://doi.org/10.1016/0261-5606(94)90021-3
  12. French, K. R. and R. Roll (1986), "Stock return variances: The arrival of information and the return of traders", Journal of Financial Economics, 17: 5~26. https://doi.org/10.1016/0304-405X(86)90004-8
  13. Hamao, Y., R. W. Masulis and Vitor Ng (1990), "Correlation in price changes and volatility across international stock markets", Review of Financial Studies, 3: 281~307. https://doi.org/10.1093/rfs/3.2.281
  14. Jebran, K. and A. Iqbal (2016), "Examining volatility spillover between Asian countries' stock markets", China Finance and Economic Review, 6(6): 1~13.
  15. Koutmos, G. and G. G. Booth (1995), "Asymmetric volatility transmission in international stock markets", Journal of International Money and Finance, 14: 747~762. https://doi.org/10.1016/0261-5606(95)00031-3
  16. Ling, D. C. and A. Naranjo (2015), "Returns and information transmission dynamics in public and private Real Estate Markets", Real Estate Economics, 43(1): 163~208. https://doi.org/10.1111/1540-6229.12069
  17. Liow, K. and H. Yang (2005), "Long-term Co-memories and short-run adjustment: Securitized real estate and stock markets", Journal of Real Estate Finance and Economics, 31(3): 283~300. https://doi.org/10.1007/s11146-005-2790-6
  18. Ng, A. (2000), "Volatility spillover effects from Japan and the US to the Pacific-Basin", Journal of International Money and Finance, 19(2): 207~233. https://doi.org/10.1016/S0261-5606(00)00006-1
  19. Nelson, D. B. (1991), "Conditional heteroskedasticity in asset returns: A new approach", Econometrica, 59(2): 347~370. https://doi.org/10.2307/2938260
  20. Phillips, P. C. and P. Perron (1988), "Testing for a unit root in time series regression", Biometrica, 75: 335~346. https://doi.org/10.1093/biomet/75.2.335
  21. Willcocks, W. (2010), "Conditional variences in UK regional house prices", Spatial Economic Analysis, 5(3): 339~354. https://doi.org/10.1080/17421772.2010.493951