Hedging with Futures: Does Anything Beat the Naïve Hedging Strategy?
This paper investigates out-of-sample performance of the naïve hedging strategy relative to that of the minimum variance hedging strategy, in which the covariance parameters are estimated from 18 econometric models. Hedging performance is compared across 24 futures markets. Our main findings suggest...
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| Published in: | Management science Vol. 61; no. 12; pp. 2870 - 2889 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Linthicum
INFORMS
01.12.2015
Institute for Operations Research and the Management Sciences |
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| ISSN: | 0025-1909, 1526-5501 |
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| Abstract | This paper investigates out-of-sample performance of the naïve hedging strategy relative to that of the minimum variance hedging strategy, in which the covariance parameters are estimated from 18 econometric models. Hedging performance is compared across 24 futures markets. Our main findings suggest that it is difficult to find a strategy under the minimum variance framework that outperforms the naïve hedging strategy both consistently and significantly. Our findings are robust to different sample periods, estimation windows, and hedging horizons and can be partly explained by the effects of estimation error and model misspecification.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mnsc.2014.2028
.
This paper was accepted by Itay Goldstein, finance. |
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| AbstractList | This paper investigates out-of-sample performance of the naïve hedging strategy relative to that of the minimum variance hedging strategy, in which the covariance parameters are estimated from 18 econometric models. Hedging performance is compared across 24 futures markets. Our main findings suggest that it is difficult to find a strategy under the minimum variance framework that outperforms the naïve hedging strategy both consistently and significantly. Our findings are robust to different sample periods, estimation windows, and hedging horizons and can be partly explained by the effects of estimation error and model misspecification. This paper investigates out-of-sample performance of the naive hedging strategy relative to that of the minimum variance hedging strategy, in which the covariance parameters are estimated from 18 econometric models. Hedging performance is compared across 24 futures markets. Our main findings suggest that it is difficult to find a strategy under the minimum variance framework that outperforms the naive hedging strategy both consistently and significantly. Our findings are robust to different sample periods, estimation windows, and hedging horizons and can be partly explained by the effects of estimation error and model misspecification. This paper investigates out-of-sample performance of the naïve hedging strategy relative to that of the minimum variance hedging strategy, in which the covariance parameters are estimated from 18 econometric models. Hedging performance is compared across 24 futures markets. Our main findings suggest that it is difficult to find a strategy under the minimum variance framework that outperforms the naïve hedging strategy both consistently and significantly. Our findings are robust to different sample periods, estimation windows, and hedging horizons and can be partly explained by the effects of estimation error and model misspecification. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.2028 . This paper was accepted by Itay Goldstein, finance. This paper investigates out-of-sample performance of the naïve hedging strategy relative to that of the minimum variance hedging strategy, in which the covariance parameters are estimated from 18 econometric models. Hedging performance is compared across 24 futures markets. Our main findings suggest that it is difficult to find a strategy under the minimum variance framework that outperforms the naïve hedging strategy both consistently and significantly. Our findings are robust to different sample periods, estimation windows, and hedging horizons and can be partly explained by the effects of estimation error and model misspecification. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.2028 . This paper was accepted by Itay Goldstein, finance. This paper investigates out-of-sample performance of the naive hedging strategy relative to that of the minimum variance hedging strategy, in which the covariance parameters are estimated from 18 econometric models. Hedging performance is compared across 24 futures markets. Our main findings suggest that it is difficult to find a strategy under the minimum variance framework that outperforms the naive hedging strategy both consistently and significantly. Our findings are robust to different sample periods, estimation windows, and hedging horizons and can be partly explained by the effects of estimation error and model misspecification. Data, as supplemental material, are available at Keywords: hedging with futures; naive strategy; minimum variance hedge ratios; estimation error; model misspecification History: Received February 11, 2013; accepted May 27, 2014, by Itay Goldstein, finance. Published online in Articles in Advance January 23, 2015. |
| Audience | Trade Academic |
| Author | Yang, Li Wu, Chongfeng Wang, Yudong |
| Author_xml | – sequence: 1 givenname: Yudong surname: Wang fullname: Wang, Yudong – sequence: 2 givenname: Chongfeng surname: Wu fullname: Wu, Chongfeng – sequence: 3 givenname: Li surname: Yang fullname: Yang, Li |
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| SubjectTerms | Analysis of covariance Econometrics Estimation estimation error Futures market Hedges Hedging Hedging (Finance) hedging with futures Methods minimum variance hedge ratios model misspecification naïve strategy Parameter estimation Strategies |
| Title | Hedging with Futures: Does Anything Beat the Naïve Hedging Strategy? |
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