Semiparametric ARCH-X Model for Leverage Effect and Long Memory in Stock Return Volatility

• 발행기관: 한국계량경제학회
• 저자명: Shen Zhang Heejoon Han
• 간행물 정보: 『JOURNAL OF ECONOMIC THEORY AND ECONOMETRICS』Vol.25 No.3, 81~100쪽, 전체 19쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2014.09.30

영문 초록

This paper investigates a new semiparametric ARCH-X model to account for both leverage effect and long memory property in volatility. It is a partial linear model combining a nonparametric ARCH component and an exogenous covariate that is persistent in memory. This model can allow for a flexible functional form of the asymmetric relationship between stock return and volatility and generate the long memory property in volatility. We adopt a realized volatility measure as the covariate in our model. For the daily FTSE 100 Index return series, the nonparametric component of our model captures the leverage effect and is estimated to be a complex nonlinear function. It is shown that our model outperforms other parametric or nonparametric volatility models both in within-sample and out-of-sample forecasts.

목차

Abstract

1. INTRODUCTION

2. MODEL AND ESTIMATION METHOD

3. EMPIRICAL APPLICATION

4. CONCLUSION

REFERENCES

키워드

nonparametric ARCH semiparametric volatility model local maximum log-likelihood leverage effect long memory property