Modeling Commodity Market Returns: The Challenge of Leptokurtic Distributions

Arnab Kumar Laha () and A. C. Pravida Raja ()
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Arnab Kumar Laha: Indian Institute of Management Ahmedabad
A. C. Pravida Raja: Indian Institute of Management Ahmedabad

A chapter in Advances in Analytics and Applications, 2019, pp 203-224 from Springer

Abstract: Abstract In this chapter, we consider modeling leptokurtic daily log-return distributions of three commodities: gold, silver, and crude oil. Three modeling approaches are tried out namely (a) a two-component mixture of normal distributions model, (b) Variance Gamma (VG) distribution model, and (c) Generalized Secant Hyperbolic (GSH) distribution model. The two-component mixture of normal distributions model is found to be a reasonable model for log-returns on gold and crude oil. The VG distribution model and the GSH distribution model are not found to be suitable for modeling log-returns for any of the three commodities considered in this chapter.

Keywords: Generalized secant hyperbolic distribution; Variance Gamma distribution; Sampling importance (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-981-13-1208-3_17

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DOI: 10.1007/978-981-13-1208-3_17

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