Price Discovery in Commodity Futures and Cash Markets with Heterogenous Agents

Sophie van Huellen

No 213, Working Papers from Department of Economics, SOAS University of London, UK

Abstract: The paper develops a price discovery model for commodity futures markets that accounts for two forms of limits to arbitrage caused by transaction costs and noise trader risk. Four market regimes are identified: (1) effective arbitrage, (2) transaction costs but no noise trader risk, (3) no transaction costs but noise trader risk and (4) both transaction costs and noise trader risk. It is shown that commodity prices are driven by both market fundamentals and speculative trader positions under the latter two regimes. Further, speculative effects spill over to the cash market under regime (3) but are confined to the futures market under regime (4). The model is empirically tested using data from six grain and soft commodity markets. While regime (4) is rare and short lived, regime (3) with some noise trader risk and varying elasticity of arbitrage prevails.

Keywords: commodity futures; index investment; price discovery; speculation (search for similar items in EconPapers)
JEL-codes: D84 G13 Q02 Q11 (search for similar items in EconPapers)
Pages: 23
Date: 2018-11
New Economics Papers: this item is included in nep-agr
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.soas.ac.uk/sites/default/files/2022-10/economics-wp213.pdf (application/pdf)

Related works:
Journal Article: Price discovery in commodity futures and cash markets with heterogeneous agents (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:soa:wpaper:213

Access Statistics for this paper

More papers in Working Papers from Department of Economics, SOAS University of London, UK Contact information at EDIRC.
Bibliographic data for series maintained by Chandni Dwarkasing ().