The two-component Beta-t-QVAR-M-lev: a new forecasting model
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Volume
37
Pagination
379 - 401
DOI
10.1007/s11408-023-00431-4
Journal
Financial Markets and Portfolio Management
Issue
ISSN
1934-4554
Metadata
Show full item recordAbstract
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.
Authors
Haddad, MFC; Blazsek, S; Arestis, P; Fuerst, F; Sheng, HHCollections
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