Analysis of spillover effects between stock market volatility and macroeconomic volatility using GARCH-MIDAS model
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We make use of the GARCH-MIDAS(Mixed Data Sampling) framework as a component volatility model and identify stock market volatility as the product of transitory financial volatility and smoothly varying macroeconomic volatility. Given the low frequency and high frequency volatilities, we measure dynamic spillovers between financial and macroeconomic volatilities through generalized impulse response analysis. It is found that macroeconomic components including domestic industrial production, inflation rates, crude oil prices and exchange rates have made significant contributions to financial volatilities in the Korean stock market. Our results are expected to deliver useful implications regarding financial stability and macroeconomic prudential regulations.
Abstract
We make use of the GARCH-MIDAS(Mixed Data Sampling) framework as a component volatility model and identify stock market volatility as the product of transitory financial volatility and smoothly varying macroeconomic volatility. Given the low frequency and high frequency volatilities, we measure dynamic spillovers between financial and macroeconomic volatilities through generalized impulse response analysis. It is found that macroeconomic components including domestic industrial production, inflation rates, crude oil prices and exchange rates have made significant contributions to financial volatilities in the Korean stock market. Our results are expected to deliver useful implications regarding financial stability and macroeconomic prudential regulations.
참고문헌 (26)
- Asgharian, H, "The importance of the macroeconomic variables in forecasting stock return variance: A GARCHMIDAS approach", Journal of Forecasting, 32(7), pp.600~612 (2013)
- 최완수, "주가·금리·환율 간의 가격 및 변동성 전이효과", 무역연구, 9(4), pp.55~74 (2013), 한국무역연구원[DOI]
- Conrad, C., "Anticipating long‐term stock market volatility", Journal of Applied Econometrics, 30(7), pp.1090~1114 (2015)
- Conrad, C., "On the macroeconomic determinants of long-term volatilities and correlations in US stock and crude oil markets", Journal of Empirical Finance, 29, pp.26~40 (2014)
- Macroeconomic volatility and stock market volatility, "Diebold, F. X.", National Bureau of Economic Research, ~ (2008)
- Diebold, F. X., "Better to give than to receive: Predictive directional measurement of volatility spillovers", International Journal of Forecasting, 28, pp.57~66 (2012)
- Engle R., "Cointegration, Causality, and Forecasting: A Festschrift in Honour of Clive WJ Granger", pp.475~497 (1999), Oxford University Press
- Engle, R., "Stock market volatility and macroeconomic fundamentals", Review of Economics and Statistics, 95(3), pp.776~797 (2013)
- Engle, R., "The spline-GARCH model for low-frequency volatility and its global macroeconomic causes", The Review of Financial Studies, 21(3), pp.1187~1222 (2008)
- Erdem, C., "Effects of macroeconomic variables on Istanbul stock exchange indexes", Applied Financial Economics, 15(14), pp.987~994 (2005)
- Ghysels, E., "The MIDAS touch: Mixed data sampling regression models", Finance, ~ (2004)
- Ghysels, Eric, "MIDAS regressions: Further results and new directions", Econometric Reviews, 26(1), pp.53~90 (2007)
- 강상훈, "Spillover Effects between Exchange Rate and Stock Price in Asian Emerging Markets", 金融工學硏究, 11(2), pp.147~165 (2012), 한국금융공학회[DOI]
- 김영일, "한국 주식시장의 지속적 변동성과 거시경제적 관련성 분석", KDI Journal of Economic Policy, 35(4), pp.63~94 (2013), 한국개발연구원[DOI]
- Koop, G., "Impulse response analysis in nonlinear multivariate models", Journal of Econometrics, 74(1), pp.119~147 (1996)
- 이영임, "혼합 빈도 GARCH 모형을 이용한 주식시장 변동성 예측", 금융안정연구, 18(1), pp.141~162 (2017), 예금보험공사[DOI]
- Liljeblom, E., "Macroeconomic volatility and stock market volatility: empirical evidence on Finnish data", Applied Financial Economics, 7(4), pp.419~426 (1997)
- Lütkepohl, H., "New introduction to multiple time series analysis" (2005), Springer
- Miller, T., "The Econometric Modelling of financial time series" (1999)
- Morelli, D., "The relationship between conditional stock market volatility and conditional macroeconomic volatility: Empirical evidence based on UK data", International Review of Financial Analysis, 11(1), pp.101~110 (2002)
- Paye, S., "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables", Journal of Financial Economics, 106(3), pp.527~546 (2012)
- Pesaran, M. H., "Generalized impulse response analysis in linear multivariate models", Economics Letters, 58, pp.17~29 (1998)
- Schwert, G. W., "Why does stock market volatility change over time?", The Journal of Finance, 44(5), pp.1115~1153 (1989)
- Schwert, G. W., "Stock returns and real activity: A century of evidence", The Journal of Finance, 45(4), pp.1237~1257 (1990)
- Wang, F., "Econometric analysis of volatility component models", Econometric Theory, 31(2), pp.362~393 (2015)
- 윤일현, "거시경제변수가 국내주가에 미치는 영향에 관한 연구", 지역산업연구, 39(2), pp.37~53 (2016), 산업경영연구소