소파동(Wavelet)분석을 활용한 정책금리와 수익률곡선 간 관계 분석 (Wavelet Analysis of the Linkage between Call Rate and Yield Curve in Korea)

서지정보

· 발행기관 : 보험연구원
· 수록지 정보 : 보험금융연구 / 23권 / 2호 / 3 ~ 44페이지
· 저자명 : 박창균, 허석균

초록

물가안정목표제를 통화정책지표로 채택하고 있는 경우 정책당국이 직접적인 조작수단인정책금리와 수익률곡선 사이에 존재하는 상호작용에 대하여 정확히 파악하는 것은 매우중요한 과제이다. 본 연구는 소파동분석을 활용하여 정책금리의 변동으로 인하여 발생한충격이 수익률 곡선에 전달되는 정도와 경로를 실증적으로 규명하려는 노력의 일환이다.
주요 분석 결과를 요약하면 다음과 같다. 첫째, 콜금리의 변동으로 인한 충격은 모든주기의 소파동에서 만기가 짧은 채권의 수익률에 강하게 전달되며 오랜 기간 동안지속되는 것으로 나타났다. 둘째, 콜금리 변화와 그에 따른 통화량 지표 변동으로 인하여발생하는 유동성 효과와 피셔 효과는 각기 다른 파장 대에서 발현하는 것으로관측되었다. 이는 채권수익률 시계열을 별도의 처리 없이 그대로 사용한 기존 연구에서는확인할 수 없었던 결과라는 점에서 시계열 분야에서 소파동분석의 유용성을 확인해 주고있다.

영어초록

Our paper explores the dynamic relationship between the call rate and the term structure of interest rates. Under inflation targeting regime, the monetary authority intends to change the shape of the yield curve by adjustingshort-term interests rate such as the call rate in Korea, the movement of which, in turn, is anticipated to influence the yields of bonds with varying maturities. Employing wavelet transformation known for its flexibility and effectiveness in dealing with time series data, we investigate the relationship between the movement of call rate and that of the yield curve to fill the gap untouched by the current literature.
We choose an orthogonalized wavelet filter, Daubechies wavelets, and apply it to the time series of various interest rates with different maturities to obtain five wavelet details and a wavelet approximation, whose sum, by definition, equals to the corresponding original time series. Jointly with these properties of an orthogonal wavelet method, the no-arbitrage conditions in the bond market are extended to hold for each wavelet detail and wavelet approximation. Based on the extended bond market equilibrium conditions, we construct VAR/VECM models with the decomposed time series by frequencies.
A couple of important empirical findings merit our attention. First, the shorter the time scale of a wavelet detail and time to maturity, the stronger the tie between the movement of the call rate and the consequent movement of the yield curve. Second, we could discern the liquidity effect from the Fisher effect as each effect manifests itself on different time scales of wavelets. Third, the call rate adjustment induces the contemporaneous shift of the yield curve, which in turn supports the presence of the liquidity effect. These results could not be obtained by the traditional analysis utilizing unfiltered raw time series. The merit of wavelet decomposition is self-evident because it closely resembles de-noising processes. Noisy signals do not contain useful information and should be filtered out so that we benefit from more efficient analysis with time series sharpened by a de-noising procedure.

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