Forecasting Nigerian Stock Market Volatilities using Bagging and Ensemble Averaging

Authors

Godknows Isenah, University of IbadanFollow

Keywords

Bagging, ensemble, ensemble member, forecast, volatility

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.

Issue

15

Volume

2

First Page

01

Last Page

35

Recommended Citation

Isenah, Godknows (2024) "Forecasting Nigerian Stock Market Volatilities using Bagging and Ensemble Averaging," CBN Journal of Applied Statistics (JAS): Vol. 15: No. 2, Article 1.
Available at: https://dc.cbn.gov.ng/jas/vol15/iss2/1