Modeling Realized Variance with Realized Quarticity
This paper proposes a model for realized variance that exploits information in realized quarticity. The realized variance and quarticity measures are both highly persistent and highly correlated with each other. The proposed model incorporates information from the observed realized quarticity proces...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Stats |
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| Online Access: | https://www.mdpi.com/2571-905X/5/3/50 |
| _version_ | 1827656585827057664 |
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| author | Hiroyuki Kawakatsu |
| author_facet | Hiroyuki Kawakatsu |
| author_sort | Hiroyuki Kawakatsu |
| collection | DOAJ |
| description | This paper proposes a model for realized variance that exploits information in realized quarticity. The realized variance and quarticity measures are both highly persistent and highly correlated with each other. The proposed model incorporates information from the observed realized quarticity process via autoregressive conditional variance dynamics. It exploits conditional dependence in higher order (fourth) moments in analogy to the class of GARCH models exploit conditional dependence in second moments. |
| first_indexed | 2024-03-09T22:31:26Z |
| format | Article |
| id | doaj.art-f54634a46c4646868089a2c8fda11953 |
| institution | Directory Open Access Journal |
| issn | 2571-905X |
| language | English |
| last_indexed | 2024-03-09T22:31:26Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Stats |
| spelling | doaj.art-f54634a46c4646868089a2c8fda119532023-11-23T18:57:57ZengMDPI AGStats2571-905X2022-09-015385688010.3390/stats5030050Modeling Realized Variance with Realized QuarticityHiroyuki Kawakatsu0Business School, Dublin City University, Dublin 9, D09 Dublin, IrelandThis paper proposes a model for realized variance that exploits information in realized quarticity. The realized variance and quarticity measures are both highly persistent and highly correlated with each other. The proposed model incorporates information from the observed realized quarticity process via autoregressive conditional variance dynamics. It exploits conditional dependence in higher order (fourth) moments in analogy to the class of GARCH models exploit conditional dependence in second moments.https://www.mdpi.com/2571-905X/5/3/50realized variancerealized quarticityvolatility of volatility |
| spellingShingle | Hiroyuki Kawakatsu Modeling Realized Variance with Realized Quarticity Stats realized variance realized quarticity volatility of volatility |
| title | Modeling Realized Variance with Realized Quarticity |
| title_full | Modeling Realized Variance with Realized Quarticity |
| title_fullStr | Modeling Realized Variance with Realized Quarticity |
| title_full_unstemmed | Modeling Realized Variance with Realized Quarticity |
| title_short | Modeling Realized Variance with Realized Quarticity |
| title_sort | modeling realized variance with realized quarticity |
| topic | realized variance realized quarticity volatility of volatility |
| url | https://www.mdpi.com/2571-905X/5/3/50 |
| work_keys_str_mv | AT hiroyukikawakatsu modelingrealizedvariancewithrealizedquarticity |