서비스연구 (Journal of Service Research and Studies)

  • 제7권4호
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  • Pages.139-150
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  • 2017
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  • 2234-2850(pISSN)
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  • 2466-1813(eISSN)
서비스사이언스학회 (The Society of service Science)
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해외금리 충격과 회사채 신용위험의 관계: 국내시장 분석

The Effect of Foreign Bond Yield Shock on Corporate Bond Credit Spread: Evidence form Korean Market

  • 송혁준 (덕성여자대학교 사회과학대학) ;
  • 이종용 (강원대학교 경영대학)
  • Song, HyuckJun (College of Social Studies, Duksung Women's University) ;
  • Lee, Jong-Ryong (College of Business Administration, Kangwon National University)
  • 투고 : 2017.10.18
  • 심사 : 2017.12.22
  • 발행 : 2017.12.29
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초록

국내 자본시장이 해외경제 변화에 매우 민감한 개방시장임을 감안하여, 본 연구에서는 해외금리 충격이 국내 회사채 금리 (정부채권 이자율 및 신용위험(credit spread))에 주는 영향에 관하여 분석하였다. 해외금리는 미국정부채권 이자율(yield)이며, 해외금리 충격은 해외금리 및 변동성 변화로 구분한다. 회사채 신용위험은 국내 회사채 금리의 로그(log yield)에서 한국정부채권 이자율의 로그를 차감한 값이다. 시계열 자료들은 만기3년 AA-등급 및 BBB-등급 회사채 금리, 만기3년 한국정부채권 이자율, 만기3년 미국정부채권 이자율과 대미환율에 관한 월간 자료이며 시계열 자료기간은 2008년 금융위기를 포함한 2000년 10월부터 2014년 09월까지이고, 분석결과는 다음과 같다. 첫째 당기(t)의 한국정부채권 이자율과 신용위험은 당기 해외금리의 증가와 변동성 증가에 민감한 편인데 비하여, 환율은 민감하다고 볼 수는 없었다. 둘째 당기의 해외금리가 상승하거나 변동성이 증가하면, 당기의 한국정부채권 이자율을 상승하지만 당기 회사채 신용위험은 감소하였다. 셋째 당기 한국정부채권 이자율의 상승은 차기(t+1)의 신용위험의 상승을 주도해서, 차기 회사채 금리를 상승시키는 경향이 존재하였다. 이런 결과들은 해외금리 충격이 국내 회사채 가격 및 금융회사의 안정성에 심대한 타격을 줄 수가 있다는 것을 의미한다.

Open economy tightly works with foreign economy. This paper investigates the effect of the shock of foreign bond yield on the credit spreads of domestic corporate bonds in Korea. Foreign bond is referred to as US treasury bond. Credit spreads are defined with the difference between log yields of domestic corporate bonds and log yield of Korea treasury bond. With the data of monthly three-year AA- and BBB- corporate bond yields- ratings, monthly three-year Korean treasury bond yields, monthly US dollar foreign exchange rates, and monthly three-year US Treasury bond yields during the period from October 2000 to September 2014 including global financial crisis period, the paper documents the results as follow. First of all, the yield of Korean treasury and the credit spreads are very sensitive to the increase in the level and the volatility of the yield of the US treasury bond. Changes in the level and the volatility little affect the change of the exchange rate. Second, the change in the level and the volatility negatively affect the level of Korean treasury bond yields but lead to the increase in the level of Korean treasury bond yields at the same time. Third, there exist time lags of the increases of credit spreads by the increase in the level and the volatility. These imply that credit spreads and bond yields are very sensitive to the change in the yields of foreign bonds such as US treasury bond.

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참고문헌

  1. Bao, J., Pan, J., and Wang, J. (2011). The illiquidity of corporate bonds. Journal of Finance, 66(3), 911-946. https://doi.org/10.1111/j.1540-6261.2011.01655.x
  2. Barnhill Jr, T. M., and Maxwell, W. F. (2002). Modeling correlated market and credit risk in fixed income portfolios. Journal of Banking and Finance, 26(2), 347-374. https://doi.org/10.1016/S0378-4266(01)00226-6
  3. Black, F., and Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637-654. https://doi.org/10.1086/260062
  4. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1
  5. Chen, L., Lesmond, D. A., and Wei, J. (2007). Corporate yield spreads and bond liquidity. Journal of Finance, 62(1), 119-149. https://doi.org/10.1111/j.1540-6261.2007.01203.x
  6. Dickey, D. A., Hasza, D. P., and Fuller, W. A. (1984). Testing for unit roots in seasonal time series. Journal of the American Statistical Association, 79(386), 355-367. https://doi.org/10.1080/01621459.1984.10478057
  7. Engle, R. F., and Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica,: 55(2), 251-276. https://doi.org/10.2307/1913236
  8. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 34(3), 424-438.
  9. Johansen, S., and Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169-210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x
  10. Longstaff, F. A., and Schwartz, E. S. (1995). A simple approach to valuing risky fixed and floating rate debt. Journal of Finance, 50(3), 789-819. https://doi.org/10.1111/j.1540-6261.1995.tb04037.x
  11. Longstaff, F. A., Mithal, S., and Neis, E. (2005). Corporate yield spreads: Default risk or liquidity? New evidence from the credit default swap market. Journal of Finance, 60(5), 2213-2253. https://doi.org/10.1111/j.1540-6261.2005.00797.x
  12. Lutkepohl, H. (2005). New introduction to multiple time series analysis. Springer Science and Business Media.
  13. Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2), 449-470.
  14. Naka, A., and Tufte, D. (1997). Examining impulse response functions in cointegrated systems. Applied Economics, 29(12), 1593-1603. https://doi.org/10.1080/00036849700000035
  15. Park, J., and Ratti, R. A. (2008). Oil price shocks and stock markets in the US and 13 European countries. Energy Economics, 30(5), 2587-2608. https://doi.org/10.1016/j.eneco.2008.04.003
  16. Sims, C. A. (1980). Macroeconomics and reality. Econometrica: 48(1), 1-48. https://doi.org/10.2307/1912017