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Estimation of time-varying hedge ratios for corn and soybeans BGARCH and random coefficient approaches by Anil K. Bera

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Published by Bureau of Economic and Business Research, University of Illinois at Urbana-Champaign in Urbana, Ill .
Written in English

Subjects:

  • Economics,
  • Hedge ratios

Book details:

Edition Notes

Bibliography; p. [40-41].

StatementAnil K. Bera, Philip Garcia & Jae-Sun Roh
SeriesOFOR paper -- no. 97-06, BEBR faculty working paper -- no. 0140, BEBR faculty working paper -- no. 0140.
ContributionsRoh, Jae Sun, Garcia, Philip
The Physical Object
Pagination41 p., [8] p. ;
Number of Pages41
ID Numbers
Open LibraryOL24999552M
OCLC/WorldCa39056088

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  FacultyWorkingPaper s"rx TheLibraryofthe Aub J • i»^ UniversityofliUnols ofUr&ana-ChampalQf! EstimationofTime-VaryingHedgeRatiosforCornand Soybeans   In this paper we introduce the use of a random coefficient autoregressive (RCAR) model to estimate time varying hedge ratios. Using daily data of spot and futures prices of corn and soybeans we find substantial presence of conditional heteroskedasticity, and also of random coefficients in the regression of return from the spot market on the ?abstract_id=   We introduce the use of a random coefficient autoregressive (RCAR) model to estimate time varying hedge ratios. Using daily data of spot and future prices of corn and soybeans we find substantial presence of both ARCH and random coefficient ://?abstract_id= Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches: Author(s): Bera, Anil K.; Garcia, Philip; Roh, Jae Sun: Subject(s): optimal hedge ratios RCAR model: Abstract: This paper deals with the estimation of optimal hedge ://

Downloadable! This paper deals with the estimation of optimal hedge ratios. A number of recent papers have demonstrated that the ordinary least squares (OLS) method which gives constant hedge ratio is inappropriate and recommended the use of bivariate autoregressive conditional heteroskedastic (BGARCH) model. In this paper we introduce the use of a random coefficient autoregressive (RCAR Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches This paper deals with the estimation of optimal hedge ratios. A number of recent papers have demonstrated that the ordinary least squares (OLS) method which gives constant hedge ratio is inappropriate and recommended the use of bivariate December Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches * This paper deals with the estimation of optimal hedge ratios. A number of recent papers have demonstrated that the ordinary least squares (OLS) method which gives constant hedge ratio is inappropriate and recommended the   at time t can be written as flt¡1 = ¡Cov(Rs t;R f t jFt¡1) Var(RftjF ¡1); (1) where Rs t = P s t ¡P s t¡1 and R f t = P f t ¡P f t¡1 are the returns of spot and futures prices denoting the natural logarithms of spot and futures prices at time t as Ps t and P f t, respectively, and Ft¡1 is the ¾-algebra generated by all the available information up to time t ¡ 1. Since flt¡1 is

  representation of bivariate GARCH model to estimate time-varying hedge ratios for corn and soybeans. Recently, Moschini and Myers (), using weekly corn prices, show that a new parameterization of bivariate GARCH processes establishes statistical superiority of time-varying hedge ratios over constant hedges. To derive Estimation and hedging effectiveness of time‐varying hedge ratio: Flexible bivariate garch approaches bivariate generalized autoregressive conditional heteroskedasticity (BGARCH) models are usually used to estimate time‐varying hedge ratios. Using daily data of the spot and futures returns of corn and soybeans we find asymmetric and BibTeX @MISC{Bera_decemberestimation, author = {Anil K. Bera and Philip Garcia and Jae-sun Roh and Anil K. Bera and Philip Garcia and Jae-sun Roh}, title = {December Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH ?doi= The primary objectives of this study are to identify procedures which can be used to find appropriate model specifications for the improved estimation of time-varying hedge ratios and to develop testing procedures for the constancy of the correlation coefficient in