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Economic indicators and stock market volatility in an emerging economy

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  • Chun, Dohyun
  • Cho, Hoon
  • Ryu, Doojin

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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  • Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    • Handle: RePEc:eee:ecosys:v:44:y:2020:i:2:s0939362518305594
    DOI: 10.1016/j.ecosys.2020.100788
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    17. Xingguo Luo & Wenye Cai & Doojin Ryu, 2022. "Information contents of intraday SSE 50 ETF options trades," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 580-604, April.
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    More about this item

    Keywords

    Economic indicators; Market volatility; Predictive regression; Superior predictive ability; Volatility forecasting;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

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