Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index

Mengxi He, Yudong Wang, Qing Zeng and Yaojie Zhang

Research in International Business and Finance, 2023, vol. 65, issue C

Abstract: In this paper, we aim to improve the predictability of aggregate stock market volatility with industry volatilities. The empirical results show that individual industry volatilities can provide useful predictive information, while the predictive contribution is limited. We further consider the spillover index between industry volatilities and find it displays strong predictive power for stock market volatility. Based on the portfolio exercise, we find that a mean-variance investor can achieve sizeable economic gains by using volatility forecasts of the spillover index. In addition, we conduct three extended analyses and further demonstrate the superior performance of the spillover index. Also, our results show robustness to a series of alternative settings. Finally, we investigate why the spillover index performs better and answer what information it contains. The results show that the spillover index can reflect and explain investor sentiments that are related to stock market volatility.

Keywords: Volatility forecasting; Industry volatility; Spillover index; Investor sentiment; Portfolio exercise (search for similar items in EconPapers)
JEL-codes: C22 C53 G11 G17 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:65:y:2023:i:c:s0275531923001095

DOI: 10.1016/j.ribaf.2023.101983

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