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

Emmanuel Gabreyohannes,Amare Wubishet Ayele,Hayimro Edmealem

doi:10.1155/2020/5095181

Emmanuel Gabreyohannes, Amare Wubishet Ayele + Show 1 more

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https://doi.org/10.1155/2020/5095181

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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.

Highlights

Silver is a natural precious metal that holds high economic value, either as a currency or as an industrial commodity [1]
Is paper incorporates the following elements in the scientific literature: (1) From a statistical modeling point of view, this paper demonstrates the realistic application of the generalized autoregressive conditional heteroskedasticity (GARCH) family model to financial risk management in a precious metal perspective
Descriptive Statistics. e data used in this study was the monthly price of silver in the Ethiopian market for the period from January 1998 through January 2014, and the logarithmic return series were computed from the monthly price series pt to examine the price volatility

Summary

Introduction

Silver is a natural precious metal that holds high economic value, either as a currency or as an industrial commodity [1]. Prices in precious metals such as silver have increased dramatically over the period from 1991 to 2011 Such intense increases are due to several factors, such as inflation expectations, the recent economic crisis, and higher demand from emerging markets [2, 3]. As a result, these intense changes in both markets have attracted investor attention since precious metals such as silver serve as important storehouses of value and play a role in risk diversification [4]. Volatility is one of the key aspects of financial markets, which is the range and speed of price movements showing the degree of variation in a trading price series over time as measured by the standard deviation of logarithmic returns [5, 6]

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