Kais Tissaoui1,2,*, Sahbi Boubaker3,4, Waleed Saud Alghassab1, Taha Zaghdoudi1,5, Jamel Azibi6
CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4291-4309, 2022, DOI:10.32604/cmc.2022.028830
Abstract The application of optimization methods to prediction issues is a continually exploring field. In line with this, this paper investigates the connectedness between the infected cases of COVID-19 and US fear index from a forecasting perspective. The complex characteristics of implied volatility risk index such as non-linearity structure, time-varying and non-stationarity motivate us to apply a nonlinear polynomial Hammerstein model with known structure and unknown parameters. We use the Hybrid Particle Swarm Optimization (HPSO) tool to identify the model parameters of nonlinear polynomial Hammerstein model. Findings indicate that, following a nonlinear polynomial behaviour cascaded to an autoregressive with exogenous input… More >
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