Sains Malaysiana 51(7)(2022): 2249-2264

http://doi.org/10.17576/jsm-2022-5107-25

Performance of a Novel Hybrid Model through Simulation and Historical Financial Data

(Prestasi Model Hibrid Novel melalui Simulasi dan Data Kewangan Sejarah)

MD. JAMAL HOSSAIN^1,2 & MOHD TAHIR ISMAIL³

¹School of Mathematical Sciences, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia

²Department of Applied Mathematics, Noakhali Science and Technology University, Noakhali-3814, Bangladesh

³School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Penang, Pulau Pinang, Malaysia

Diserahkan: 24 Mei 2021/Diterima: 1 Januari 2022

Abstract

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.

Keywords: ExpAR model; ExpAR-MSGARCH model; MSGARCH model; structural breaks; value-at-risk

Abstrak

Diakui secara benar bahawa siri masa kewangan masa lampau adalah tidak linear, menunjukkan perubahan struktur dan meruap. Dapat dilihat dalam kepustakaan semasa oleh kerana adanya putusan berstruktur dalam siri masa lampau, model keluarga GARCH memberikan hasil yang tidak benar dan ramalan yang lemah. Oleh itu, tidak dapat dielak untuk menggabungkan model yang tidak linear pada min dan varians bersyarat untuk menguasai dinamik kemeruapan dengan lebih tepat daripada model sedia ada. Maka, berinspirasi daripada hal ini, kajian ini mencadangkan model hibrid baharu eksponen autoregresif (ExpAR) dengan model pertukaran Markov GARCH (MSGARCH). Kajian ini juga mengkaji prestasi dan dinamik kemeruapan melalui simulasi dan data kewangan dunia yang betul. Lebih-lebih lagi, penyelidikan ini mengkaji prestasi pengurusan risiko penurunan menggunakan ujian semula 5% VaR (risiko pada nilai). Penemuan empirik menunjukkan bahawa model yang dicadangkan mengungguli model penanda aras untuk kedua-dua simulasi dan data siri masa yang betul. Hasil VaR juga menunjukkan bahawa model yang dicadangkan menangkap risiko penurunan lebih teliti daripada model penanda aras.

Kata kunci: Model ExpAR; model ExpAR-MSGARCH; model MSGARCH; putusan berstruktur; risiko pada nilai

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^*Pengarang untuk surat-menyurat; email: z_math_du@yahoo.com