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Futures Hedge Profit Measurement, Error-Correction Model vs Regression Approach Hedge Ratios and Data Error Effects

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Listed:
  • Robert Ferguson
  • Dean Leistikow

Abstract

This study explains why a modified regression method, which calculates hedge profits and hedge ratios using cost-of-carry-adjusted price changes, provides greater accuracy than the unadjusted regression method. It shows that the modified regression method and the error-correction model lead to similar hedging performance unless there are significant data errors.

Suggested Citation

  • Robert Ferguson & Dean Leistikow, 1999. "Futures Hedge Profit Measurement, Error-Correction Model vs Regression Approach Hedge Ratios and Data Error Effects," Financial Management, Financial Management Association, vol. 28(4), Winter.
    • Handle: RePEc:fma:fmanag:ferguson99
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    Cited by:

    1. Dean Leistikow & Ren-Raw Chen, 2019. "Carry Cost Rate Regimes and Futures Hedge Ratio Variation," JRFM, MDPI, vol. 12(2), pages 1-17, May.
    2. Dean Leistikow & Ren-Raw Chen & Yuewu Xu, 2022. "Spot asset carry cost rates and futures hedge ratios," Review of Quantitative Finance and Accounting, Springer, vol. 58(4), pages 1741-1779, May.
    3. Chen, Ren-Raw & Leistikow, Dean & Wang, Andrew, 2020. "Futures minimum variance hedge ratio determination: An ex-ante analysis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    4. Choudhry, Taufiq, 2004. "The hedging effectiveness of constant and time-varying hedge ratios using three Pacific Basin stock futures," International Review of Economics & Finance, Elsevier, vol. 13(4), pages 371-385.

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