Time-varying hedge ratios are derived which account for the dynamic characteristics of prices in the soybean complex. A multivariate generalized autogressive heteroskedastic (MGARCH) model, along with other conditional models, is used to specify the relevant covariance matrix. While the time-varying representations of the variance matrix are statistically appropriateex anteand ex posthedging effectiveness indicate that they provide minimal gain to hedging in terms of mean return and reduction in variance over a constant conditional procedure. Whether similar findings arise from other applications of GARCH models to optimal hedging is a question for further research.
No takes yet. Share an insight, caveat, or question.
Garcia et al. (1995) studied this question.
Synapse has enriched 2 closely related papers on similar clinical questions. Consider them for comparative context: