Futures price volatility in commodities markets: The role of short term vs long term speculation
AbstractThis paper evaluates how different types of speculation affect the volatility of commodities’ futures prices. We adopt four indexes of speculation: Working’s T, the market share of non-commercial traders, the percentage of net long speculators over total open interest in future markets, which proxy for long term speculation, and scalping, which proxies for short term speculation. We consider four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) and seven non-energy commodities (cocoa, coffee, corn, oats, soybean oil, soybeans and wheat) over the period 1986-2010 analyzed at weekly frequency. Using GARCH models we find that speculation significantly affects volatility of returns: short term speculation has a positive and significant impact on volatility, while long term speculation generally has a negative effect. The robustness exercise shows that: i) scalping is positive and significant also at higher and lower data frequencies; ii) results remain unchanged through different model specifications (GARCH-in-mean, EGARCH, and TARCH); iii) results are robust to different specifications of the mean equation.
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Bibliographic InfoPaper provided by University of Pavia, Department of Economics and Management in its series DEM Working Papers Series with number 042.
Length: 28 pages
Date of creation: Apr 2013
Date of revision:
Commodities futures markets; Speculation; Scalping; Working’s T; Data frequency; GARCH models;
Other versions of this item:
- Matteo Manera & Marcella Nicolini, 2013. "Futures Price Volatility in Commodities Markets: The Role of Short Term vs Long Term Speculation," Working Papers 2013.45, Fondazione Eni Enrico Mattei.
- Matteo Manera & Marcella Nicolini & Ilaria Vignati, 2013. "Futures price volatility in commodities markets: The role of short term vs long term speculation," Working Papers 243, University of Milano-Bicocca, Department of Economics, revised May 2013.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
- Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
- Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
This paper has been announced in the following NEP Reports:
- NEP-AGR-2013-05-11 (Agricultural Economics)
- NEP-ALL-2013-05-11 (All new papers)
- NEP-FMK-2013-05-11 (Financial Markets)
- NEP-MST-2013-05-11 (Market Microstructure)
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