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An Empirical Evaluation of Hedging Effectiveness of Crude Palm Oil Futures Market in Malaysia

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  • Mohd Aminul Islam

    (Department of computational and theoretical sciences, Faculty of Science, International Islamic University Malaysia Bandar Indera Mahkota, 25200 Kuantan, Pahang, Malaysia)

Abstract

This paper evaluates the hedging effectiveness of the Malaysian crude palm oil futures market using daily settlement prices over the periods from January 4, 2010 to August 30, 2017. Hedge ratios and the hedging effectiveness are determined by employing four competing econometric models namely: the standard ordinary least square (OLS) regression model, vector error correction model (VECM) and two variations of the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models namely; diagonal-VECH and diagonal-BEKK GARCH models. The first two models estimate constant hedge ratios while the other two models estimate time varying hedge ratios. Hedging performance is evaluated and compared in terms of in-sample (Jan 2010 – Dec 2016) and out-of sample periods (Jan 2017 – Aug 2017) of the four hedge ratio models. The empirical results show that the MGARCH models particularly diagonal-BEKK GARCH model performs better than the other three models indicating that this model fits better in designing hedging strategy. The empirical finding suggests that the investors in crude palm oil markets in Malaysia can use CPO futures contract as an effective instrument to minimize the risk.

Suggested Citation

  • Mohd Aminul Islam, 2017. "An Empirical Evaluation of Hedging Effectiveness of Crude Palm Oil Futures Market in Malaysia," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 3(11), pages 303-314, 11-2017.
    • Handle: RePEc:arp:ijefrr:2017:p:303-314
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Hedge ratio; Hedging effectiveness; Crude palm oil Malaysia; Vector error correction mechanism; OLS; MGARCH.;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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