Do prices drive commercial trader positions in grains and oilseeds markets?

We examine the impacts of futures price changes on commercial traders’ aggregate net positioning in grains and oilseeds markets during the pre-harvest period from 2007-2019. We proceed in two steps. First, we modify and extend the analysis of optimal hedging proposed by Jacobs, Li, and Hayes (AJAE 2018) to: (i) confirm its applicability for the two largest agricultural markets (soybeans and corn) over a longer period of time than previously tested (13-year period vs. 5); (ii) provide evidence regarding the relevance of the Chicago Board Options Exchange (CBOE) Volatility Index-VIX in determining commercial hedging decisions; (iii) provide evidence that the Disaggregated Commitment of Traders Reports (DCOT) data can be used as a benchmark for examining hedging behavior. Second, we develop a Structural Vector Auto-Regressive Model (SVAR) to account for endogeneity issues in the analysis of the effects of futures prices and of the VIX on commercial positioning in grains and oilseeds markets. The results from Impulse Response Functions (IRFs) retrieved from the SVAR confirm the role of futures price changes in driving position changes, shedding new light on whether commercial traders hedge or instead speculate.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Agricultural & Applied Econ

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2020

Author dc:creator

• Le, Han Thi Ngoc

Contributors dc:contributor

• Robe, Michel A

• Hedging behavior
• speculation
• commercial traders positions
• optimal hedging model
• DCOT data
• futures prices
• VIX
• agricultural market
• grains and oilseeds markets
• corn
• soybeans
• SVAR
• IFRs
• OLS regression

Statement dc:rights

• Copyright 2020 Han Thi Ngoc Le

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/108518

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/108518