Nonconstant optimal hedge ratio estimation and nested hypotheses tests

McNew, Kevin; Fackler, Paul L.

doi:10.1002/fut.3990140508

Cited by 29 publications

(12 citation statements)

References 20 publications

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“…for a given futures contract time-to-maturity. This article's findings are consistent with the live cattle and corn findings of McNew and Fackler (1994). It shows that the MU study's failure to reject the null hypothesis of nonstationarity was due to its small sample size and the overlapping HR calculation approach's bias towards failing to reject the random walk null hypothesis.…”

Section: Resultssupporting

confidence: 91%

“…The MU, Perfect and Wiles (1994), and McNew and Fackler (1994) findings could be reconciled in at least two ways. HRs may be stationary for some assets and follow a random walk for others.…”

Section: Introductionmentioning

confidence: 88%

“…In marked contrast, McNew and Fackler (1994) tested whether the HR is constant using a nested hypotheses tests approach. Their tests, using live cattle and corn data, support the constant HR hypothesis.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Are regression approach futures hedge ratios stationary?

Ferguson

Leistikow

1998

J. Fut. Mark.

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Section: Resultssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 88%

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Are regression approach futures hedge ratios stationary?

Ferguson

Leistikow

1998

J. Fut. Mark.

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“…First, the technically correct parameters to estimate are the conditional variances and covariances, which take account of possible systematic changes in the mean, at least of the spot prices (Myers & Thompson, 1989). Second, since the conditional variances and covariances likely are not constants, empirical estimates should allow for this possibility (for an example and related references, see McNew & Fackler, 1994). Nonetheless, such time-varying covariance estimation is costly and often does not result in greater hedging effectiveness relative to unconditional hedge ratios (Garcia, Roh, & Leuthold 1995;Myers, 1991).…”

Section: Defining and Estimating The Objective Functionmentioning

confidence: 99%

“…First, optimal hedges in futures depend on the parameters of the underlying probability distributions, and the estimates of these parameters depend, in turn, on the analyst's assumed model of the distribution (e.g., Baillie & Myers, 1991;McNew & Fackler, 1994). Second, models of options prices make assumptions about the nature of the probability distribution of the underlying asset, and, in the case of traded agricultural options, the underlying asset is a position in a futures contract.…”

Section: Futures Pricesmentioning

confidence: 99%

Risk Management in Agricultural Markets: A Review

Tomek

Peterson

2001

Journal of Futures Markets

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This article surveys and evaluates the current state of knowledge about producers' marketing strategies to manage price and revenue risk for farm commodities. The review highlights gaps between concepts and their implementation. Many well-developed models of price behavior exist, but appropriate characterization and estimation of the probability distributions of commodity prices remain elusive. Hence, the preferred measure of price risk is ambiguous. Numerous models of optimal marketing portfolios for farmers have been specified, but their behavior appears to be inconsistent with most, if not all, of these models. In addition, some research suggests that farmers can earn speculative profits, which is inconsistent with notions of efficient markets. The conclusions discuss what academic research can and cannot accomplish in relation to assisting producers with risk-management decisions.

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Multiperiod hedging with futures contracts

Low

Muthuswamy

Sakar

et al. 2002

Journal of Futures Markets

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The hedging problem is examined where futures prices obey the cost-ofcarry model. The resultant hedging model explicitly incorporates maturity effects in the futures basis. Formulas for the optimal static and dynamic hedges are derived. Although these formulas are developed for the case of direct hedging, the framework used is sufficiently flexible so that these formulas can be applied to many cross-hedging situations. The performance of the model is compared with that of several other models for two hedging scenarios: one involving a financial asset and the other involving a commodity. In both cases, significant maturity effects were found in the first and second moments of the futures basis. Our hedging formulas outperformed other hedging strategies on an ex-ante basis.

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Nonconstant optimal hedge ratio estimation and nested hypotheses tests

Cited by 29 publications

References 20 publications

Are regression approach futures hedge ratios stationary?

Are regression approach futures hedge ratios stationary?

Risk Management in Agricultural Markets: A Review

Multiperiod hedging with futures contracts

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