2026-06-27T10:19:06Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/228782023-08-11T07:27:04Zcom_20.500.14352_14col_20.500.14352_17

Asai, Manabu McAleer, Michael 2023-06-18T05:38:01Z 2023-06-18T05:38:01Z 2017 2341-2356 https://hdl.handle.net/20.500.14352/22878 https://www.ucm.es/icae For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers the stochastic volatility model with asymmetry and long memory, using high frequency data for the underlying asset. Empirical results for Nikkei 225 futures indicate that the adjusted R2 supports the appropriateness of the indirect method, and that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting model based on the direct method using the pseudo long time series. eng https://creativecommons.org/licenses/by-nc-sa/3.0/es/ open access Atribución-NoComercial-CompartirIgual 3.0 España Forecasting the volatility of Nikkei 225 futures technical report