확률적 변동성 모형을 이용한 원화 환율 변동성 추정
Volatility Estimation with Stochastic Volatility Model: Application in Korean Exchange Market
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초록
본 연구에서는 GARCH 타입의 모형 보다 환율 변화를 잘 추정하는 것으로 알려진 확률적 변동성 모형으로 주요 원화 환율을 추정하였다. 실증 분석을 위하여 원/달러, 원/엔, 원/유로, 원/파운드 총 네 개의 주요 환율의 변동성을 확률적 변동성 모형과 GARCH(1,1) 모형을 이용하여 추정하고 비교 분석하였다. 추정 결과 모든 환율에 대해 확률적 변동성 모형의 적합도가 GARCH(1,1) 모형보다 높은 것으로 나타났다. 정규성 검정 결과 GARCH(1,1) 모형이 변동성의 극단치를 잘 추정하지 못하는 데 반해 확률적 변동성 모형은 극단적인 변동성 또한 잘 추정하는 것으로 나타났다. 변동성의 변화가 심할 경우 극단치 추정에서 경쟁력이 있는 확률적 변동성 모형이GARCH(1,1) 모형 보다 높은 적합성을 보이는 것으로 판단된다. 외표본 검정 결과 원/유로 환율의 경우 확률적 변동성 모형이 예측력이 높으며, 다른 환율들의 경우 GARCH(1,1) 모형의 예측력이 높게 나타남을 확인하였다.
Abstract
In this paper, we estimate the important KRW exchange rates as a stochastic volatility model, which is known as better estimate of the exchange rate series than the GARCH type model. We estimate the volatility of KRW/USD, KRW/JPY, KRW/EURO, and KRW/GBP with stochastic volatility model and the GARCH (1,1) model and compare each other. The results show that the fit of the stochastic volatility model is higher than the GARCH (1,1) model. The results of the normality test demonstrate that GARCH (1,1) does not estimate the extremes of the volatility, while the stochastic volatility model estimates extreme volatility well. The extreme values of estimated volatility errors are attributed to the fact that the stochastic volatility model fit in-sample data more suitable than GARCH (1,1). However, the results of the out-of-sample test show that the stochastic volatility model is better only for KRW/EURO exchange rate and the GARCH (1,1) model is better for the other exchange rates in terms of prediction.
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