An Analysis on the Asymmetric Time Varying Spillover Effect between Capesize and Panamax Markets

케이프사이즈와 파나막스 시장간의 비대칭 시간가변 파급효과에 관한 분석

  • 정상국 (인제대학교 인문사회과학대학 국제경상학부/동북아경제연구소)
  • Received : 2011.07.26
  • Accepted : 2011.09.27
  • Published : 2011.09.30

Abstract

This article investigates the interrelationships in daily returns using fractionally integrated error correction term and volatilities using constant conditional correlation and dynamic conditional correlation GARCH with asymmetries between Capesize and Panamax markets. Our findings are as follows. First, for the fractionally cointegrated error correction model, there is a unidirectional relationship in returns from the Panamax market to the Capesize market, but a bidirectional causal relationship prevails for the traditional error correction models. Second, the coefficients for the error correction term are all statistically significant. Of particular interest are the signs of the estimates for the error correction term, which are all negative for the Capesize return equation and all positive for the Panamax return. Third, there are bidirectional volatility spillovers between both markets and the direction of the information flow seems to be stronger from Panamax to Capesize. Fourth, the coefficients for the asymmetric term are all significantly positive in the Capesize market, but the Panamax market does not have a significant effect. However, the coefficients for the asymmetric term are all significant, implying that the leverage effect does exist in the Capesize and Panamax markets.

이 연구는 케이프사이즈 시장과 파나막스 시장간의 비대칭 시간 가변 파급효과를 분석하기 위해서 조건부 평균에 전통적인 공적분항과 부분공적분항을 고려하고 있고, 조건부 분산에 레버리지 효과를 고려한 고정상관관계 GARCH와 동적상관관계 GARCH 모형을 이용하였다. 연구결과는 다음과 같다. 첫째, 두 시장간의 선-후행관계에 대해서 부분공적분항을 고려한 결과로부터 전기의 케이프사이즈 가격은 파나막스 시장가격에 유의적으로 정(+)의 영향을 미치고, 일반적인 공적분항을 고려하는 경우 두 시장간의 선-후행효과는 모두 유의적으로 정(+)의 효과를 갖는 것으로 나타났다. 둘째, 두 시장간의 장기적인 균형관계가 성립하지 않는 경우, 개별시장은 어떻게 반응하는가를 나타내는 오차항의 계수는 모두 통계적으로 유의적이고, 케이프사이즈 시장에서는 모두 음(-)의 값을 가지고 파나막스 시장의 경우에는 모두 정(+)의 값을 갖는 것으로 나타났다. 셋째, 두 시장간의 변동성의 파급효과에 대해서는 모든 모형에서 서로 영향을 주고 받는 것으로 나타났고, 통계적으로 유의하게 나타났다. 넷째, 레버리지 효과는 케이프사이즈 시장에서는 모두 유의적으로 정(+)의 값을 가지나, 파나막스 시장에서는 모두 통계적으로 유의적인 결과를 얻지 못하였다. 그러나 두 시장 모두에서 비대칭의 효과는 통계적으로 유의적인 것으로 나타나고 있다.

Keywords

References

  1. 모수원, "운임의 인과성", "한국항만경제학회지" , 제23권 제4호, 2007, 215-226.
  2. 모수원, "발틱 건화물운임지수의 변동성과 뉴스충격", "한국항만경제학회지" , 제21권 제2호, 2005, 65-79.
  3. 모수원, "환율변동성과 건화물운임", "한국항만경제학회지" , 제14권 제2호, 1998, 515-530.
  4. 심재희.모수원, "계량기법을 이용한 발틱건화물선운임의 예측", "해운물류연구" , 제24권 제2호, 2008, 1-18.
  5. 임종관.김우호.고병욱, "백터자기회귀모형을 이용한 건화물선 시장분석", "해운물류연구" , 제26권 제1호, 2010.
  6. Alizadeh, A., "An Econometric Analysis of the Dry Bulk Shipping Industry; Seasonality, Efficiency and Risk Premia," Unpublished PhD Thesis, City University Business School, London, UK., 2001.
  7. Awartani, B.M.A. and Corradi, V., "Predicting the Volatility of the S&P 500 Stock Index via GARCH Models: The Role of Asymmetries," International Journal of Forecasting, Vol. 21, 2005, 167-183. https://doi.org/10.1016/j.ijforecast.2004.08.003
  8. Baillie, R.T. and Bollerslev, T., "Cointegration, Fractional Cointegration, and Exchange Rate Dynamics," Journal of Finance, Vol. 49, 1994, 737-745. https://doi.org/10.1111/j.1540-6261.1994.tb05161.x
  9. Bartlett, M.S., "On the Theoretical Specification of Sampling Properties of Autocorrelated Time Series," Journal of the Royal Statistical Society, B8, 1946, 27-41.
  10. Beenstock, M. and Vergottis, A., Econometric Modeling of World Shipping, 1st edn. London, UK: Chapman and Hall, 1993.
  11. Bierens, H. J., and Guo, S., "Testing Stationarity and Trend Stationarity against the Unit Root Hypothesis," Econometric Reviews, Vol. 12, 1993, 1-32.
  12. Bollerslev, T., "Modelling the Coherence in Short Run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, Vol. 72, 1990, 498-505. https://doi.org/10.2307/2109358
  13. Breitung, J., "Nonparametric Tests for Unit Roots and Cointegration," Journal of Econometrics, Vol. 108, 2002, 343-363. https://doi.org/10.1016/S0304-4076(01)00139-7
  14. Bollerslev, T. and Mikkelsen, H.O., "Modeling and Pricing Long-Memory in Stock Market Volatility," Journal of Econometrics, Vol. 73, 1996, 151-184. https://doi.org/10.1016/0304-4076(95)01736-4
  15. Cheung, Y.W., "Long Memory in Foreign Exchange Rates," Journal of Business and Economic Statistics, Vol. 11, 1993, 93-101.
  16. Chung, S.K., "Cointegrating Vectors in a Multivariate I(d) Regression and Monte Carlo Simulations for Size and Power," Department of Economics, Michigan State University, Unpublished manuscript, 1997.
  17. Davidson, J., "When is a Time-Series I(0)? Evaluating the Memory Properties of Nonlinear Dynamics Models," Discussion Paper, Cardiff Business School, U.K., 1999.
  18. Ding, Z., Granger, C.W.J. and Engle, R.F., "A Long Memory Property of Stock Market Returns and a New Model," Journal of Empirical Finance, Vol. 1, 1993, 83-106. https://doi.org/10.1016/0927-5398(93)90006-D
  19. Engle, R.F. and Sheppard, K., "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Paper 2001, 8554.
  20. Engle, R.F., "Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models," Journal of Business and Economic Statistics, Vol. 20, 2002, 339-359. https://doi.org/10.1198/073500102288618487
  21. Geweke J. and Porter.Hudak, S., "The Estimation and Application of Long Memory Time Series Models," Journal of Time Series Analysis, Vol. 4, 1983, 221-238. https://doi.org/10.1111/j.1467-9892.1983.tb00371.x
  22. Granger, C.W.J., "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Vol. 48, 1986, 213-228.
  23. Kavussanos, M.G. and Visvikis, I.D., "Market Interactions in Returns and Volatilities between Spot and Forward Shipping Markets," Journal of Banking and Finance, Vol. 28, 2004, 2015-2204. https://doi.org/10.1016/j.jbankfin.2003.07.004
  24. Kwiatkowski, D., Phillips, P.C.B., Schmidt, P. and Shin, Y., "Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root," Journal of Econometrics, Vol. 54, 1992, 159-178. https://doi.org/10.1016/0304-4076(92)90104-Y
  25. Lo, A.W., "Long Memory in Stock Market Prices," Econometrica, Vol. 59, 1991, 1279-1313. https://doi.org/10.2307/2938368
  26. Lien, D. and Tse, Y.K., "Hedging Time Varying Downside Risk," Journal of Futures Markets, Vol. 18, 1998, 705-722. https://doi.org/10.1002/(SICI)1096-9934(199809)18:6<705::AID-FUT4>3.0.CO;2-R
  27. Ljung G.M. and Box, G.E.P., "On a Measure of Lack of Fit in Time Series Models," Biometrika, Vol. 65, 1978, 297-303. https://doi.org/10.1093/biomet/65.2.297
  28. Martin, G.M., "Fractional Cointegration: Bayesian Inferences Using a Jeffreys prior. Mimeo," Department of Econometrics and Business Statistics, Monash University, 1997.
  29. Masih, R. and Masih, A.M.M., "A Fractional Cointegration Approach to Empirical Tests of PPP: New Evidence and Methodological Implications from an Application to the Taiwan/US Dollar Relationship," Weltwirtschaftliches Archiv, 1995, 673-693.