Non-linear volatility dynamics and risk management of precious metals

Sercan Demiralay and Veysel Ulusoy

The North American Journal of Economics and Finance, 2014, vol. 30, issue C, 183-202

Abstract: In this paper, we investigate the value-at-risk predictions of four major precious metals (gold, silver, platinum, and palladium) with non-linear long memory volatility models, namely FIGARCH, FIAPARCH and HYGARCH, under normal and Student-t innovations’ distributions. For these analyses, we consider both long and short trading positions. Overall, our results reveal that long memory volatility models under Student-t distribution perform well in forecasting a one-day-ahead VaR for both long and short positions. In addition, we find that FIAPARCH model with Student-t distribution, which jointly captures long memory and asymmetry, as well as fat-tails, outperforms other models in VaR forecasting. Our results have potential implications for portfolio managers, producers, and policy makers.

Keywords: Long memory; Value-at-risk; Volatility modeling; Precious metals prices (search for similar items in EconPapers)
JEL-codes: C53 C58 G17 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (22)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:30:y:2014:i:c:p:183-202

DOI: 10.1016/j.najef.2014.10.002

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