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https://hdl.handle.net/1822/54675| Título: | Modelling and forecasting WIG20 daily returns |
| Autor(es): | Amado, Cristina Silvennoinen, Annastiina Teräsvirta, Timo |
| Palavras-chave: | Autoregressive conditional heteroskedasticity Forecasting volatility Modelling volatility Multiplicative time-varying GARCH Smooth transition |
| Data: | 2017 |
| Editora: | Polish Academy of Sciences |
| Revista: | Central European Journal of Economic Modelling and Econometrics |
| Citação: | Amado, C., Silvennoinen, A., & Teräsvirta, T. (2017). Modelling and Forecasting WIG20 Daily Returns. Central European Journal of Economic Modelling and Econometrics, 9, 173–200. |
| Resumo(s): | The purpose of this paper is to model daily returns of the WIG20 index. The idea is to consider a model that explicitly takes changes in the amplitude of the clusters of volatility into account. This variation is modelled by a positive-valued deterministic component. A novelty in speci cation of the model is that the deterministic component is speci ed before estimating the multiplicative conditional variance component. The resulting model is subjected to misspeci cation tests and its forecasting performance is compared with that of commonly applied models of conditional heteroskedasticity. |
| Tipo: | Artigo |
| URI: | https://hdl.handle.net/1822/54675 |
| ISSN: | 2080-0886 |
| Arbitragem científica: | yes |
| Acesso: | Acesso restrito autor |
| Aparece nas coleções: | NIPE - Artigos em Revistas de Circulação Internacional com Arbitragem Científica |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| WIG20modelling170329.pdf Acesso restrito! | 584,21 kB | Adobe PDF | Ver/Abrir |
