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Generalized Autoregressive Conditional Heteroskedastic Model to Examine Silver Price Volatility and Its Macroeconomic Determinant in Ethiopia Market

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  • Amare Wubishet Ayele
  • Emmanuel Gabreyohannes
  • Hayimro Edmealem

Abstract

Like most commodities, the price of silver is driven by supply and demand speculation, which makes the price of silver notoriously volatile due to the smaller market, lower market liquidity, and fluctuations in demand between industrial and store value use. The concern of this article was to model and forecast the silver price volatility dynamics on the Ethiopian market using GARCH family models using data from January 1998 to January 2014. The price return series of silver shows the characteristics of financial time series such as leptokurtic distributions and thus can suitably be modeled using GARCH family models. An empirical investigation was conducted to model price volatility using GARCH family models. Among the GARCH family models considered in this study, ARMA (1, 3)-EGARCH (3, 2) model with the normal distributional assumption of residuals was found to be a better fit for price volatility of silver. Among the exogenous variables considered in this study, saving interest rate and general inflation rate have a statistically significant effect on monthly silver price volatility. In the EGARCH (3, 2) volatility model, the asymmetric term was found to be positive and significant. This is an indication that the unanticipated price increase had a greater impact on price volatility than the unanticipated price decrease in silver. Then, concerned stockholders such as portfolio managers, planners, bankers, and investors should intervene and pay due attention to these factors in the formulation of financial and related market policy.

Suggested Citation

  • Amare Wubishet Ayele & Emmanuel Gabreyohannes & Hayimro Edmealem, 2020. "Generalized Autoregressive Conditional Heteroskedastic Model to Examine Silver Price Volatility and Its Macroeconomic Determinant in Ethiopia Market," Journal of Probability and Statistics, Hindawi, vol. 2020, pages 1-10, May.
  • Handle: RePEc:hin:jnljps:5095181
    DOI: 10.1155/2020/5095181
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    Cited by:

    1. Zhang, Yanyan & chang, Hsuling & Saliba, Chafic & Hasnaoui, Amir, 2022. "Metallic natural resources commodity prices volatility in the pandemic: Evidence for silver, platinum, and palladium," Resources Policy, Elsevier, vol. 78(C).
    2. Zurika, Robinson, 2023. "A macroeconomic viewpoint using a structural VAR analysis of silver price behaviour," Working Papers 30192, University of South Africa, Department of Economics.
    3. Srivastava, Mrinalini & Rao, Amar & Parihar, Jaya Singh & Chavriya, Shubham & Singh, Surendar, 2023. "What do the AI methods tell us about predicting price volatility of key natural resources: Evidence from hyperparameter tuning," Resources Policy, Elsevier, vol. 80(C).

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