Hedging Ratio Measurement Methods and Hedging Effectiveness in Jakarta Futures Exchanges

Buddi Wibowo

doi:10.23917/jep.v18i1.3473

Hedging Ratio Measurement Methods and Hedging Effectiveness in Jakarta Futures Exchanges

Buddi Wibowo^(1*)

(1) Faculty of economics and business, Universitas Indonesia
(*) Corresponding Author

Abstract

Estimation method of hedge ratio is a crucial step in hedging strategies in the commodity futures market. This study examines the effectiveness of hedging strategy against cash position in Indonesia’s cocoa beans and Robusta coffee spot market using three hedge ratio estimation methods: OLS, Vector Error Correction Model, and Threshold-ARCH. The results show the hedging effectiveness in the Jakarta Futures Exchange is considerably highly effective to reduce the impact of fluctuations of spot price. The effectiveness of hedging strategy using OLS as the simplest method is close to VECM method and TARCH. Implementation OLS hedge ratio resulted the highest hedging effectiveness and give a strong support for market players in executing a hedging strategy in Jakarta Futures Exchange due to OLS simplicity in estimation procedure

Keywords

Hedge ratio; hedging effectiveness; OLS; VECM; TARCH

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References

Alizadeh, A., N Nomikos. (2004). A Markov Regime Switching Approach for Hedging Stock Indices. The Journal of Futures Market 24 (7): 649-674.

Bhargava, V., D, Malhotra. 2007. Determining the Optimal Hedge Ratio: Evidence from Cotton and Soybean Markets. Journal of Business and Economic Studies 13 (1): 38-57

Cotter, J.,J. Hanly.2012.Hedging effectiveness under conditions of asymmetry. The European Journal of Finance 18(2), 2012.

Dickey, D., W Fuller. 1981. Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root , Econometrica , 49, 1057-1072

Engle, R. 1982.Autoregressive Conditional Heteroskedasticity With Estimates of the Variance of UK Inflation Econometrica 50 (1982): 987-1008.

Engle, R.,C, Granger.1987. Co-integration and Error Correction: Representation, Estimation and Testing, Econometrica 55 (1987): 251-276.

Galtier, F.2013. Managing food price instability in developing countries A critical analysis of strategies and instruments, Agence Française de Développement CIRAD-DIST

Gupta, K., M, Kaur.2015. Impact of financial crisis on hedging effectiveness of futures contract: Evidence of National Stock Exchanges of India. South East European Journal of Economics and Business Volume 10 (2) 2015, 69-88

Gupta, K., B.Singh. 2009. Estimating the Optimal Hedge Ratio in Indian Equity Futures Market. Journal of Financial Risk Management VI (3 ): 38-98.

International Cocoa Organization,2016, ICCO Quarterly Bulletin of Cocoa Statistics, Vol. XLII, No. 3, Cocoa year 2015/16

International Coffee Organization. 2016. Historical Data on the Global Coffee Trade-Exportable Production.

Juhl, T., I, Kawaller,. P, Koch. 2012. The Effect of the Hedge Horizon on Optimal Hedge Size and Effectiveness When Prices are Cointegrated. The Journal of Futures Markets 32 (9): 837–876.

Ku, Y., H, Chen,.K, Chen, On the application of the dynamic conditional correlation model in estimating optimal timevarying hedge ratios.Applied Economics Letters 14: 503–509, 2007.

Lien, D. 2005. A Note on the Superiority of the OLS Hedge Ratio. The Journal of Futures Markets 25 (11): 1121–1126.

Lien, D.2004. Cointegration and the Optimal Hedge Ratio: The General Case. The Quarterly Review of Economics and Finance 44(5), 654-658.

Moschini, G., R, Myers. 2002. Testing for Constant Hedge Ratios in Commodity Markets: A Multivariate GARCH Approach. Journal of Empirical Finance 9: 589–603

Yang, W., D, Allen, 2005. Multivariate GARCH hedge ratios and hedging effectiveness in Australian futures markets, Journal of Accounting & Finance 45(2): 301-321

DOI: 10.23917/jep.v18i1.3473