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Modeling Gold Volatility: Realized GARCH Approach

Author

Listed:
  • Esmaiel Abounoori

    (Department of Economics, Semnan University, Semnan, Iran.)

  • Mohammad Amin Zabol

    (Department of Economics, Semnan University, Semnan, Iran.)

Abstract

Forecasting the volatility of a financial asset has wide implications in finance. Conditional variance extracted from the GARCH framework could be a suitable proxy of financial asset volatility. Option pricing, portfolio optimization, and risk management are examples of implications of conditional variance forecasting. One of the most recent methods of volatility forecasting is Realized GARCH (RGARCH) that considers a simultaneous model for both realized volatility and conditional variance at the same time. In this article, we estimate conditional variance with GARCH, EGARCH, GIR-GARCH, and RGARCH with two realized volatility estimators using gold intraday data. We compared models, for in-sample fitting; by the log-likelihood value and used MSE and QLIKE lose functions to evaluate predicting accuracy. The results show that the RGARCH method for GOLD outperforms the other methods in both ways. So, using the RGARCH model in practical situations, like pricing and risk management would tend to better results.

Suggested Citation

  • Esmaiel Abounoori & Mohammad Amin Zabol, 2020. "Modeling Gold Volatility: Realized GARCH Approach," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 24(1), pages 299-311, Winter.
    • Handle: RePEc:eut:journl:v:24:y:2020:i:1:p:299
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    Cited by:

    1. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021. "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 489-502.
    2. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Latasha Mohapatra & Adel M. Sarea, 2020. "The Impact of COVID-19 on Price Volatility of Crude Oil and Natural Gas Listed on Multi Commodity Exchange of India," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 422-431.
    3. Kumar SANTOSH & Meher Kumar BHARAT & Ramona BIRAU & Mircea Laurentiu SIMION & Anand ABHISHEK & Singh MANOHAR, 2023. "Quantifying Long-Term Volatility for Developed Stock Markets: An Empirical Case Study Using PGARCH Model on Toronto Stock Exchange (TSX)," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 61-68.
    4. Andrey Leonidovich Poltarykhin & Valentina N. Ivanova & Andrzej Szromnik, 2020. "Sustainable functioning of educational institutions based on the risk-management implementation mechanism," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(1), pages 390-397, September.
    5. Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
    6. Wang, Lu & Zhao, Chenchen & Liang, Chao & Jiu, Song, 2022. "Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 48(C).

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