Forecasting realized volatility with wavelet decomposition

Ioannis Souropanis and Andrew Vivian

Journal of Empirical Finance, 2023, vol. 74, issue C

Abstract: Forecasting Realized Volatility (RV) is of paramount importance for both academics and practitioners. During recent decades, academic literature has made substantial progress both in terms of methods and predictors under consideration albeit with scarce reference to technical indicators. This paper examines the out-of-sample forecasting performance of technical indicators for S&P500 RV relative to macroeconomic predictors. Our main contribution is to demonstrate that these sets of predictors impact volatility at different frequencies and thus are complementary. Specifically, technical indicators perform especially strongly for forecasting the short frequency component which complements macroeconomic variables which perform strongly at longer frequencies. We demonstrate that amalgamation forecasts from these predictors that takes into account the frequency dimension leads to substantial improvements in forecast accuracy.

Keywords: Realized volatility; Technical indicators; Macroeconomic predictors; Volatility forecasting; Wavelet decomposition (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 G12 G17 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:74:y:2023:i:c:s0927539823000993

DOI: 10.1016/j.jempfin.2023.101432

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