The two-component Beta-t-QVAR-M-lev: a new forecasting model
| dc.contributor.author | Haddad, MFC | en_US |
| dc.contributor.author | Blazsek, S | en_US |
| dc.contributor.author | Arestis, P | en_US |
| dc.contributor.author | Fuerst, F | en_US |
| dc.contributor.author | Sheng, HH | en_US |
| dc.date.accessioned | 2023-10-19T10:22:05Z | |
| dc.date.issued | 2023-12-01 | en_US |
| dc.identifier.issn | 1934-4554 | en_US |
| dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/91429 | |
| dc.description.abstract | We introduce a new joint model of expected return and volatility forecasting, namely the two-component Beta-t-QVAR-M-lev (quasi-vector autoregression in-mean with leverage). The maximum likelihood estimator for the two-component Beta-t-QVAR-M-lev is an extension of theoretical results of the one-component Beta-t-QVAR-M. We compare the volatility forecasting performance of the two-component Beta-t-QVAR-M-lev and two-component GARCH-M (generalized autoregressive conditional heteroscedasticity), also considering their one-component frameworks. The results for G20 stock market indices indicate that the forecasting performance of the two-component Beta-t-QVAR-M-lev is superior compared with the two-component GARCH-M and their one-component versions. | en_US |
| dc.format.extent | 379 - 401 | en_US |
| dc.relation.ispartof | Financial Markets and Portfolio Management | en_US |
| dc.rights | Attribution 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
| dc.title | The two-component Beta-t-QVAR-M-lev: a new forecasting model | en_US |
| dc.type | Article | |
| dc.identifier.doi | 10.1007/s11408-023-00431-4 | en_US |
| pubs.issue | 4 | en_US |
| pubs.notes | Not known | en_US |
| pubs.publication-status | Accepted | en_US |
| pubs.volume | 37 | en_US |
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