Economic indicators and stock market volatility in an emerging economy |
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| Institution: | 1. College of Business, Korea Advanced Institute of Science and Technology, Seoul, Republic of Korea;2. College of Economics, Sungkyunkwan University, Jongno-gu, Seoul, 03063, Republic of Korea;1. Department of Business Administration, Yeungnam University, Gyeongsangbuk-do, Republic of Korea;2. Department of Finance, Hallym University, Gangwon-do, Republic of Korea;3. Department of Economics, Sungkyunkwan University, 25-2, Sungkyunkwan-ro, Jongno-gu, Seoul, Republic of Korea;1. School of Economics and Management, Southwest Jiaotong University, Chengdu, China;2. School of Finance, Nanjing University of Finance and Economics, Nanjing, China;3. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, Ontario, Canada |
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| Abstract: | By analyzing the daily realized volatility series calculated from intraday stock price observations, this study examines the direct causality between one-day-ahead aggregate stock market volatility and several economic and financial indicators in the Korean market, a leading emerging market. Using the predictive regression and superior predictive ability tests, we find that the model-free implied volatility index (VKOSPI) and stock market indicators both lead the daily market volatility. However, daily economic indicators provide no predictive information beyond that contained in historical volatility. Though in-sample causality does not guarantee a better out-of-sample forecasting performance, the VKOSPI and combinations of predictors exhibit significant predictive ability regardless of the time period. Our study verifies the information role of the VKOSPI as an indicator of daily market risk. |
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| Keywords: | Economic indicators Market volatility Predictive regression Superior predictive ability Volatility forecasting |
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