Abstract
This paper proposes new dynamic conditional futures hedge ratios and compares their hedging performances along with those of common benchmark hedge ratios across three broad asset classes. Three of the hedge ratios are based on the upward-biased carry cost rate hedge ratio, where each is augmented in a different bias-mitigating way. The carry cost rate hedge ratio augmented with the dynamic conditional correlation between spot and futures price changes generally: (1) provides the highest hedging effectiveness and (2) has a statistically significantly higher hedging effectiveness than the other hedge ratios across assets, sub-periods, and rolling window sizes.
Highlights
The goal of futures hedging is to reduce the firm’s risk and increase its value
A key consideration for a futures hedger is the ratio of futures assets to short over the number of spot assets long, i.e., the futures hedge ratio
It focuses on: (1) the economics-based carry-cost rate hedge ratio introduced in Leistikow et al (2020) and employed in Leistikow and Chen (2019), (2) a hedge ratio based on the Engle (2002)
Summary
The goal of futures hedging is to reduce the firm’s risk and increase its value. A key consideration for a futures hedger is the ratio of futures assets to short over the number of spot assets long, i.e., the futures hedge ratio. Statistics-based dynamic conditional correlation model, and (3) three bias-adjusted versions of the carry-cost rate hedge ratio, one of which incorporates the Engle (2002) dynamic conditional correlation model. It compares the hedge ratios’ hedging performances across three broad asset classes to those of each other and those of two common benchmark hedge ratios. The carry-cost rate hedge ratio when augmented with the dynamic conditional correlation between the spot and futures price changes generally (1) provides the highest hedging effectiveness and (2) has a statistically significantly higher hedging effectiveness than either that of the common benchmark hedge ratios or the other approaches across: assets, sub-periods, and rolling window sizes.
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