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Bid-Ask Spreads, Volume, and Volatility: Evidence from Livestock Markets

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  • Julieta Frank
  • Philip Garcia

Abstract

Using literature-based measures and a modified Bayesian method specified here, we estimate liquidity costs and their determinants for the live cattle and hog futures markets. Volume and volatility are simultaneously determined and significantly related to the bid-ask spread. Daily volume is negatively related to the spread while volatility and average volume per transaction display positive relationships. Electronic trading has a significant competitive effect on liquidity costs, particularly in the live cattle market. Results are sensitive to the bid-ask spread measure, with our modified Bayesian method providing estimates most consistent with expectations and the competitive structure in these markets. Copyright 2010, Oxford University Press.

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File URL: http://hdl.handle.net/10.1093/ajae/aaq116
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Bibliographic Info

Article provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.

Volume (Year): 93 (2010)
Issue (Month): 1 ()
Pages: 209-225

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Handle: RePEc:oup:ajagec:v:93:y:2010:i:1:p:209-225

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  1. Henry Bryant & Michael Haigh, 2004. "Bid-ask spreads in commodity futures markets," Applied Financial Economics, Taylor & Francis Journals, vol. 14(13), pages 923-936.
  2. Sanders, Dwight R. & Irwin, Scott H. & Merrin, Robert P., 2008. "The Adequacy of Speculation in Agricultural Futures Markets:Too Much of a Good Thing?," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37615, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  3. Thompson, Sarahelen R. & Eales, James S. & Seibold, David, 1993. "Comparison Of Liquidity Costs Between The Kansas City And Chicago Wheat Futures Contracts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(02), December.
  4. Hausman, Jerry A, 1978. "Specification Tests in Econometrics," Econometrica, Econometric Society, vol. 46(6), pages 1251-71, November.
  5. Cumby, Robert E & Huizinga, John, 1992. "Testing the Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions," Econometrica, Econometric Society, vol. 60(1), pages 185-95, January.
  6. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 631-53, October.
  7. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," CERT Discussion Papers 0706, Centre for Economic Reform and Transformation, Heriot Watt University.
  8. Thompson, Sarahelen R. & Waller, Mark L., 1987. "The Execution Cost of Trading in Commodity Futures Markets," Food Research Institute Studies, Stanford University, Food Research Institute, issue 02.
  9. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-35, November.
  10. Thompson, S. & Waller, M.L., 1988. "Determinants Of Liquidity Costs In Commodity Furures Markets," Papers 172, Columbia - Center for Futures Markets.
  11. Hasbrouck, Joel, 2004. "Liquidity in the Futures Pits: Inferring Market Dynamics from Incomplete Data," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(02), pages 305-326, June.
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Cited by:
  1. Irwin, Scott H. & Sanders, Dwight R., 2012. "Financialization and Structural Change in Commodity Futures Markets," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 44(03), August.
  2. Janzen, Joseph P. & Smith, Aaron D. & Carter, Colin A., 2012. "The Quality of Price Discovery and the Transition to Electronic Trade: The Case of Cotton Futures," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125024, Agricultural and Applied Economics Association.

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