A New Class of Heavy-Tailed Distribution in GARCH Models for the Silver Returns

Andrew Maree; George Carr; Joe Howard

Andrew Maree Reserve Bank of New Zealand, Wellington, New Zealand
George Carr University of the Sunshine Coast, Sunshine Coast, Australia
Joe Howard University of Technology, Sydney, Australia.

Keywords: Normal Reciprocal Inverse Gaussion, GARCH Model, Silver Spot Returns.

Abstract

After serving as a medium of exchange for the human society, silver is still widely used in our daily life. From the jewellery, electronic and electrical industries as well as medicine, optics, the power industry, automotive industry and many other industries, silver is still playing a very active role. In addition to the industrial usage, silver also serves as an investment tool for many financial institutions. Thus, it is crucial to develop effective quantitative risk management tool for those financial institutions. In this paper, we investigate the conditional heavy tails of daily silver spot returns under the GARCH framework. Our results indicate that that it is important to introduce heavy-tailed distributions to the GARCH framework and the normal reciprocal inverse Gaussian (NRIG) distribution, a newly-developed distribution, has the best empirical performance in capture the daily silver spot returns dynamics.

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Author Biographies

Andrew Maree, Reserve Bank of New Zealand, Wellington, New Zealand

Macro Financial Policy Department

George Carr, University of the Sunshine Coast, Sunshine Coast, Australia

School of Business

Joe Howard, University of Technology, Sydney, Australia.

Economics Discipline Group,

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