Intraday volatility forecasting: analysis of alternative distributions
Volatility forecasting has been of great interest both in academic and professional fields all over the world. However, there is no agreement about the best model to estimatevolatility. New models include measures of skewness, changes of regimes and different distributions; few studies, though, have...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Brazilian Society of Finance
2011-06-01
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| Series: | Revista Brasileira de Finanças |
| Subjects: | |
| Online Access: | http://bibliotecadigital.fgv.br/ojs/index.php/rbfin/article/view/2586/2216 |
| _version_ | 1811204793833619456 |
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| author | Paulo Sérgio Ceretta Fernanda Galvão de Barba Kelmara Mendes Vieira Fernando Casarin |
| author_facet | Paulo Sérgio Ceretta Fernanda Galvão de Barba Kelmara Mendes Vieira Fernando Casarin |
| author_sort | Paulo Sérgio Ceretta |
| collection | DOAJ |
| description | Volatility forecasting has been of great interest both in academic and professional fields all over the world. However, there is no agreement about the best model to estimatevolatility. New models include measures of skewness, changes of regimes and different distributions; few studies, though, have considered different distributions. This paper aims to investigate how the specification of a distribution influences the performance of volatility forecasting on Ibovespa intraday data, using the APARCH model. The forecasts were carried out assuming six distinct distributions: normal, skewed normal, t-student, skewed t-student, generalized and skewed generalized. The results evidence that the model considering the skewed t-student distribution offered the best fit to the data inside the sample, on the other hand, the model assuming a normal distribution provided a better out-of-the-sample performance forecast. |
| first_indexed | 2024-04-12T03:18:43Z |
| format | Article |
| id | doaj.art-762197cf49a64615ba50445e97656eb5 |
| institution | Directory Open Access Journal |
| issn | 1679-0731 1984-5146 |
| language | English |
| last_indexed | 2024-04-12T03:18:43Z |
| publishDate | 2011-06-01 |
| publisher | Brazilian Society of Finance |
| record_format | Article |
| series | Revista Brasileira de Finanças |
| spelling | doaj.art-762197cf49a64615ba50445e97656eb52022-12-22T03:49:58ZengBrazilian Society of FinanceRevista Brasileira de Finanças1679-07311984-51462011-06-0192227256Intraday volatility forecasting: analysis of alternative distributionsPaulo Sérgio CerettaFernanda Galvão de BarbaKelmara Mendes VieiraFernando CasarinVolatility forecasting has been of great interest both in academic and professional fields all over the world. However, there is no agreement about the best model to estimatevolatility. New models include measures of skewness, changes of regimes and different distributions; few studies, though, have considered different distributions. This paper aims to investigate how the specification of a distribution influences the performance of volatility forecasting on Ibovespa intraday data, using the APARCH model. The forecasts were carried out assuming six distinct distributions: normal, skewed normal, t-student, skewed t-student, generalized and skewed generalized. The results evidence that the model considering the skewed t-student distribution offered the best fit to the data inside the sample, on the other hand, the model assuming a normal distribution provided a better out-of-the-sample performance forecast.http://bibliotecadigital.fgv.br/ojs/index.php/rbfin/article/view/2586/2216volatilityforecasting modelsdifferent distributions |
| spellingShingle | Paulo Sérgio Ceretta Fernanda Galvão de Barba Kelmara Mendes Vieira Fernando Casarin Intraday volatility forecasting: analysis of alternative distributions Revista Brasileira de Finanças volatility forecasting models different distributions |
| title | Intraday volatility forecasting: analysis of alternative distributions |
| title_full | Intraday volatility forecasting: analysis of alternative distributions |
| title_fullStr | Intraday volatility forecasting: analysis of alternative distributions |
| title_full_unstemmed | Intraday volatility forecasting: analysis of alternative distributions |
| title_short | Intraday volatility forecasting: analysis of alternative distributions |
| title_sort | intraday volatility forecasting analysis of alternative distributions |
| topic | volatility forecasting models different distributions |
| url | http://bibliotecadigital.fgv.br/ojs/index.php/rbfin/article/view/2586/2216 |
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