Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/327972 
Year of Publication: 
2024
Citation: 
[Journal:] CBN Journal of Applied Statistics [ISSN:] 2476-8472 [Volume:] 15 [Issue:] 2 [Year:] 2024 [Pages:] 01-35
Publisher: 
The Central Bank of Nigeria, Abuja
Abstract: 
This paper using bagged GARCH-type model, with ensemble averaging estimators models and compares the forecast performances to those of some classical GARCH- type models. Using Mean Absolute Forecast Error (MAFE) and Root Mean Squared Forecast Error (RMSFE) as forecast-error measures, the results shows bagging- ensemble based methods to out-perform the alternative volatility models. The study recommended that volatility estimates obtained via bagged ensemble methods should be used as inputs to facilitate financial operations such as derivatives pricing, risk hedging, computations of Value-at-Risk (VaR) estimates, and for financial decision making.
Subjects: 
Bagging
ensemble
ensemble member
forecast
volatility
JEL: 
E22
C53
C58
Persistent Identifier of the first edition: 
Document Type: 
Article

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