Hedge period length and Ex‐ante futures hedging effectiveness: The case of foreign‐exchange risk cross hedges

Benet, Bruce A.

doi:10.1002/fut.3990120205

Cited by 67 publications

(50 citation statements)

References 21 publications

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“…This suggests that there is more market uncertainty at short scales or in a statistical sense that there is greater noise, increasing the difficulty of measuring the hedge ratio accurately, Benet (1992). However, by the second scale (2 − 4 day horizon) the effectiveness is greater than that found using the original data, and then increases to a maximum of 0.98 (variance reduction) or 0.88 (VaR reduction) at long scales.…”

Section: Dynamic Scale Dependent Hedgingmentioning

confidence: 89%

“…In the context of hedging, a limited number of studies, including Ederington (1979); Hill and Schneeweis (1982); Malliaris and Urrutia (1991);Benet (1992); Geppert (1995), have demonstrated an increase in hedging effectiveness for longer horizons, by matching the frequency of the data with the hedging horizon. However, out-of-sample, Malliaris and Urrutia (1991); Benet (1992) found a lack of stability in the hedging effectiveness for longer horizons. More recently, Chen et al (2004) demonstrated, using subsampled data, that both the hedge ratio and effectiveness tend to increase with the length of time horizon.…”

Section: Introductionmentioning

confidence: 99%

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An Empirical Analysis of Dynamic Multiscale Hedging Using Wavelet Decomposition

Conlon

Cotter

2011

SSRN Journal

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This paper investigates the hedging effectiveness of a dynamic moving window OLS hedging model, formed using wavelet decomposed time-series. The wavelet transform is applied to calculate the appropriate dynamic minimum-variance hedge ratio for various hedging horizons for a number of assets. The effectiveness of the dynamic multiscale hedging strategy is then tested, both in-and out-of-sample, using standard variance reduction and expanded to include a downside risk metric, the time horizon dependent Value-at-Risk. Measured using variance reduction, the effectiveness converges to one at longer scales, while a measure of VaR reduction indicates a portion of residual risk remains at all scales. Analysis of the hedge portfolio distributions indicate that this unhedged tail risk is related to excess portfolio kurtosis found at all scales.

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Section: Dynamic Scale Dependent Hedgingmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

An Empirical Analysis of Dynamic Multiscale Hedging Using Wavelet Decomposition

Conlon

Cotter

2011

SSRN Journal

View full text Add to dashboard Cite

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“…This may suggest greater levels of noise in high frequency data, creating difficulty in measuring the hedge ratio accurately (Benet, 1992).…”

Section: Resultsmentioning

confidence: 99%

“…However, Benet (1992) found a lack of stability in the effectiveness at longer horizons out-of-sample, due to the sample reduction problem. To overcome the problem of reduced data at longer horizons, wavelet multiscaling techniques have been adopted.…”

Section: Introductionmentioning

confidence: 99%

“…Earlier studies considered data sampled at weekly, fortnightly and monthly horizons to demonstrate an increase in variance reduction effectiveness for hedgers at longer horizons (Benet, 1992;Ederington, 1979). However, Benet (1992) found a lack of stability in the effectiveness at longer horizons out-of-sample, due to the sample reduction problem.…”

Section: Introductionmentioning

confidence: 99%

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Downside Risk and the Energy Hedger's Horizon

Conlon

Cotter

2012

SSRN Journal

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In this paper, we explore the impact of investor time-horizon on an optimal downside hedged energy portfolio.Previous studies have shown that minimum-variance hedging effectiveness improves for longer horizons using variance as the performance metric. This paper investigates whether this result holds for different hedging objectives and effectiveness measures. A wavelet transform is applied to calculate the optimal heating oil hedge ratio using a variety of downside objective functions at different time-horizons. We demonstrate decreased hedging effectiveness for increased levels of uncertainty at higher confidence intervals. Moreover, for each of the different hedging objectives and effectiveness measures studied, we also demonstrate increasing hedging effectiveness at longer horizons. While small differences in effectiveness are found across the different hedging objectives, timehorizon effects are found to dominate confirming the importance of considering the hedgers horizon. The findings suggest that while downside risk measures are useful in the computation of an optimal hedge ratio that accounts for unwanted negative returns, hedging horizon and confidence intervals should also be given careful consideration by the energy hedger.

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An empirical analysis of the relationship between the hedge ratio and hedging horizon: A simultaneous estimation of the short‐ and long‐run hedge ratios

Chen

Lee

Shrestha

2004

Journal of Futures Markets

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This article analyzes the effects of the length of hedging horizon on the optimal hedge ratio and hedging effectiveness using 9 different hedging horizons and 25 different commodities. We discuss the concept of shortand long-run hedge ratios and propose a technique to simultaneouslyWe are grateful to an anonymous referee and the Editor for their helpful comments and suggestions. Chen, Lee, and Shrestha estimate them. The empirical results indicate that the short-run hedge ratios are significantly less than 1 and increase with the length of hedging horizon. We also find that hedging effectiveness increases with the length of hedging horizon. However, the long-run hedge ratio is found to be close to the naïve hedge ratio of unity. This implies that, if the hedging horizon is long, then the naïve hedge ratio is close to the optimum hedge ratio.

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Hedge period length and Ex‐ante futures hedging effectiveness: The case of foreign‐exchange risk cross hedges

Cited by 67 publications

References 21 publications

An Empirical Analysis of Dynamic Multiscale Hedging Using Wavelet Decomposition

An Empirical Analysis of Dynamic Multiscale Hedging Using Wavelet Decomposition

Downside Risk and the Energy Hedger's Horizon

An empirical analysis of the relationship between the hedge ratio and hedging horizon: A simultaneous estimation of the short‐ and long‐run hedge ratios

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