Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach

Kais Tissaoui ()

International Review of Financial Analysis, 2019, vol. 64, issue C, 232-249

Abstract: This paper investigates the predictive ability of the Unites States (US) volatility risk index toward the European and Asian volatility risk indexes, and vice versa. We use the Hammerstein-ARX approach to model dependency between the different volatility risk indexes. The unknown parameters of the non-linear Hammerstein-ARX model are estimated using particle swarm optimization (PSO), in order to minimize the error between the real output and the forecasted output. Our empirical findings provide that the US implied volatility risk index is particularly powerful in forecasting the European and Asian volatility risk indexes than in the opposite case. We also show that the US implied volatility risk index react to other international implied volatility risk indexes linearly and non-linearly, and vice versa. The simulation results confirm the fitness and performance of the proposed PSO identification tool.

Keywords: Volatility risk indexes; Forecasting; Spreading risk; Particle swarm optimization; Hammerstein-ARX; Long-memory behavior (search for similar items in EconPapers)
JEL-codes: C53 C55 D53 D81 G15 G17 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:64:y:2019:i:c:p:232-249

DOI: 10.1016/j.irfa.2019.06.001

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