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Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets

Author

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  • Ma, Feng
  • Wahab, M.I.M.
  • Zhang, Yaojie

Abstract

We propose new jump indexes that are aligned with the jump information on the G7 stock markets to predict the U.S. stock market volatility. We present several noteworthy findings. First, in-sample tests indicate that the impacts of the aligned jump indexes on one-step-ahead U.S. stock market volatility are significantly negative. Second, the aligned jump index based on the Partial Least Squares (PLS) approach remarkably exhibits a higher predictive power, showing that this new jump index can contain much more predictive information than jump itself or jump index based on the Principal Component Analysis (PCA). Third, the results are consistent across the direction-of-change test and a variety of robustness tests. Consequently, this research provides a new insight and constructs a powerful predictive variable for the U.S. stock market volatility forecasting.

Suggested Citation

  • Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
  • Handle: RePEc:eee:pacfin:v:54:y:2019:i:c:p:132-146
    DOI: 10.1016/j.pacfin.2019.02.006
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    More about this item

    Keywords

    Volatility forecasting; G7 stock markets; Realized volatility; Jumps; Partial least squares;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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