Performance of a novel hybrid model through simulation and historical financial data

Hossain, Md. Jamal and Mohd Tahir Ismail, (2022) Performance of a novel hybrid model through simulation and historical financial data. Sains Malaysiana, 51 (7). pp. 2249-2264. ISSN 0126-6039


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It is thoroughly acknowledged that the historical financial time series is not linear, exhibits structural changes, and is volatile. It has been noticed in the current literature that because of the existence of structural breaks in the historical time series, the GARCH family models provide misleading results and poor forecasts. Thus, it is unavoidable to incorporate models with nonlinearity in the conditional mean and conditional variance to capture volatility dynamics more precisely than the existing models. Therefore, inspiring in this matter, this study proposes a novel hybrid model of exponential autoregressive (ExpAR) with a Markov-switching GARCH (MSGARCH) model. This study also examines volatility dynamics and performances through simulation and real-world financial data. Moreover, this study investigates downside risk management performances using 5% VaR (Value-at-Risk) back-testing. The empirical findings showed that the proposed model outperforms the benchmark model for both simulation and real-world time series data. The VaR results also showed that the proposed model captures downside risk more meticulously than the benchmark model.

Item Type:Article
Keywords:ExpAR model; ExpAR-MSGARCH model; MSGARCH model; Structural breaks; Value-at-risk
Journal:Sains Malaysiana
ID Code:20252
Deposited By: ms aida -
Deposited On:19 Oct 2022 07:12
Last Modified:25 Oct 2022 07:56

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