The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Estimation of Prediction Values in ARMA Models via the Transformation and Back-Transformation Method

변환-역변환을 통한 자기회귀이동평균모형에서의 예측값 추정

  • Yeo, In-Kwon (Dept. of Statistics, Sookmyung Women's University) ;
  • Cho, Hye-Min (Dept. of Statistics, Sookmyung Women's University)
  • 여인권 (숙명여자대학교 이과대학 통계학과) ;
  • 조혜민 (숙명여자대학교 이과대학 통계학과)
  • Published : 2008.06.30
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Abstract

One of main goals of time series analysis is to estimate prediction of future values. In this paper, we investigate the bias problem when the transformation and back- transformation approach is applied in ARMA models and introduce a modified smearing estimation to reduce the bias. An empirical study on the returns of KOSDAQ index via Yeo-Johnson transformation was executed to compare the performance of existing methods and proposed methods and showed that proposed approaches provide a bias-reduced estimation of the prediction value.

시계열자료 분석에 있어 주요 목적 중에 하나는 미래에 대한 예측 값을 추정하는 것이다. 이 논문에서는 정상자기회귀이동평균 모형에서 변환-역변환 방법을 이용하여 예측값을 구하는 과정에서 발생하는 문제에 대해 알아보고 회귀분석에서 제안되었던 smearing 추정방법을 시계열분석에서 사용할 수 있도록 붓스트랩을 이용하여 수정한 추정법을 소개한다. Yeo-Johnson 변환 (2000)을 이용한 KOSDAQ지수의 수익률 실증분석을 통해 기존에 사용되고 있는 방법의 문제점과 제안된 방법의 적절성에 대해 고찰해 보았다.

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References

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