Less is more? New evidence from stock market volatility predictability

Fei Lu, Feng Ma and Qiang Guo

International Review of Financial Analysis, 2023, vol. 89, issue C

Abstract: The complex nature of stock market volatility has motivated researchers to apply a variety of predictors to obtain reliable predictive information for precise forecasting. This study seeks to examine the effectiveness of the novel Global Financial Uncertainty (GFU) indices, comprising of only five sub-indices, in predicting stock market volatility using the widely used mixed-data sampling (MIDAS) model. The results demonstrate the remarkable and stable predictive power of GFU, even during crises and global financial uncertainty shocks. Specifically, the financial uncertainty index from Europe plays a significant role in our analysis. Importantly, we find that the GFU index outperforms a large number of other indicators in stock volatility forecasting. The statistical and economic significance of the predictive power of GFU is remarkable. Our study provides significant insights for market participants and policymakers that highlight the need to prioritize global financial uncertainty.

Keywords: Global financial uncertainty; Stock market; Volatility forecasting; Uncertainty shocks; MIDAS (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:89:y:2023:i:c:s1057521923003356

DOI: 10.1016/j.irfa.2023.102819

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