환율 변동성 측정과 GARCH모형의 적용

• 영문명: Exchange Rate Volatility Measures and GARCH Model Applications: Practical Information Processing Approach
• 발행기관: 한국통상정보학회
• 저자명: 문창권(Chang-Kuen Moon)
• 간행물 정보: 『통상정보연구』제12권 제1호, 99~121쪽, 전체 23쪽
• 주제분류: 사회과학 > 무역학
• 파일형태: PDF
• 발행일자: 2010.03.30

영문 초록

This paper reviews the categories and properties of risk measures, analyzes the classes and structural equations of volatility forecasting models, and presents the practical methodologies and their expansion methods of estimating and forecasting the volatilities of exchange rates using Excel spreadsheet modeling. We apply the GARCH(1,1) model to the Korean won(KRW) denominated daily and monthly exchange rates of USD, JPY, EUR, GBP, CAD and CNY during the periods from January 4, 1998 to December 31, 2009, make the estimates of long-run variances in the returns of exchange rate calculated as the step-by-step change rate, and test the adequacy of estimated GARCH(1,1) model using the Box-Pierce-Ljung statistics Q and chi-square test-statistics. We demonstrate the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the monthly series except the semi-variance GARCH(1,1) applied to KRW/JPY100 rate. But we reject the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the daily series because of the very high Box-Pierce-Ljung statistics in the respective time lags resulting to the self-autocorrelation. In conclusion, the GARCH(1,1) model provides for the easy and helpful tools to forecast the exchange rate volatilities and may become the powerful methodology to overcome the application difficulties with the spreadsheet modeling.

목차

Ⅰ. 서론

Ⅱ. 위험 측정과 변동성의 추정 및 예측

Ⅲ. GARCH(1,1)모형의 환율변동성 추정 적용

Ⅳ. 추정모형의 타당성 검정과 변동성 예측

Ⅴ. 요약 및 결론

참고문헌

Abstract

키워드

volatility GARCH(1,1) long-run variance Box-Pierce-Ljung statistics Q self-autocorrelation