Optimal Hedge Ratio and Hedging Effectiveness in Turkish Stock Index Futures Market

Year 2016, Volume: 16 Issue: 4, 719 - 732, 01.09.2016

İbrahim Yaşar Gök

Abstract

In this study, optimum hedge ratio and hedging effectiveness of Turkish index futures market are investigated and five different hedging horizons including daily hedging and one, two, three, and four weeks hedging are examined. In the study, six different models including ordinary least squares (OLS), error correction model (ECM), generalized autoregressive conditional heteroskedasticity (GARCH) model, ECM-GARCH model and from multivariate GARCH models diag VECH-GARCH and diag BEKK-GARCH models are applied and daily spot and futures data of BIST 30 index in the period of November 1, 1995 and October 30, 2014 is used. While the best hedge ratio for daily hedging is provided by ECM-GARCH model, for the other hedge horizons the best hedge ratios are provided by multivarite GARCH models. In the view of riskreturn hedging performance, although OLS model has the best performance in two and four week hedging horizons, for the other hedging horizons the best model differentiates. Also, hedging performance increases with extending the hedging horizon. In the perspective of these findings, it is concluded that though the performances of the models are close to each other and it is not reached one best model, BIST 30 index contracts are effective hedging instruments. In the view of riskreturn trade off, investors can benefit with the best performance by the proper model for the preferred hedging horizon

Keywords

Hedge Ratio, Hedging Effectiveness, Hedge Horizon, Futures Contract

Türkiye Pay Endeks Futures Piyasasında Optimum Korunma Oranı ve Korunma Etkililiği

Abstract

Bu çalışmada Türkiye endeks futures piyasasında optimal korunma oranı ve korunma performansı araştırılmış, günlük korunma ile bir, iki, üç ve dört haftalık korunma olmak üzere beş farklı korunma zamanı incelenmiştir. Çalışmada, en küçük kareler (OLS), hata düzeltme modeli (ECM), genelleştirilmiş otoregresif koşullu değişen varyans (GARCH) modeli, ECM-GARCH modeli ve çok değişkenli GARCH modellerinden diyagonal VECH-GARCH ve diyagonal BEKK-GARCH modelleri olmak üzere altı farklı model uygulanmış ve 1 Kasım 2005 ve 30 Ekim 2015 arası dönemde BIST 30 endeksi spot ve futures piyasalarına ait gün sonu veriler kullanılmıştır. Günlük korunmada en iyi korunma oranını ECMGARCH modeli sağlarken, diğer korunma zamanları için çok değişkenli GARCH modelleri en iyi korunma oranlarını sağlamaktadır. Risk-getiri korunma performansı açısından ise her ne kadar iki ve dört haftalık korunma zamanlarında en iyi performansa klasik OLS modeli sahip olsa da, diğer korunma zamanlarında en iyi model farklılaşmaktadır. Ayrıca, korunma zamanı uzadıkça korunma performansı da artmaktadır. Bu bulgular perspektifinde, modellerin performansları birbirine yakın olup, tüm korunma zamanları için tek bir en iyi modele erişilemese de, BIST 30 endeks futures kontratların etkin korunma araçları olduğuna ulaşılmıştır. Risk-getiri dengelemesi açısından, tercih edilen korunma zamanı için uygun olan modelle, yatırımcılar en iyi performansı elde edebileceklerdir

Keywords

Korunma Oranı, Korunma Etkililiği, Korunma Zamanı, Futures Kontrat

References

• Bollerslev, T. (1986) “Generalized Autoregressive
• Conditional Heteroskedasticity” Journal of Econometrics, 31(3): 307-327. Bollerslev, T., Engle, R. F. ve Wooldridge, J. M. (1988)
• “A Capital Asset Pricing Model with Time-Varying Covariances” Journal of Political Economy, 96(1): 116- Chang, C.-L., McAleer, M. ve Tansuchat, R. (2011) “Crude
• Oil Hedging Strategies Using Dynamic Multivariate GARCH” Energy Economics, 33(5): 912–923. Çelik, İ. (2014) «Vadeli İşlem Piyasasında Optimal
• Hedge Rasyosunun Statik ve Dinamik Teknikler Yardımıyla Hesaplanması» Uluslararası Alanya İşletme Fakültesi Dergisi, 6(3): 1-13. Degiannakis, S. ve Floros, C. (2010) “Hedge Ratios in South African Stock Index Futures” Journal of
• Emerging Market Finance, 9(3): 285–304. Ederington, L. H. (1979) “The Hedging Performance of the New Futures Markets” The Journal of Finance, (1): 157-170.
• Engle, R. F. (1982) “Autoregressive Conditional
• Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation” Econometrica, 50(4): 987- Engle, R. F. ve Kroner, K. F. (1995) “Multivariate
• Simultaneous Generalized ARCH” Econometric Theory, (1): 122-150. Engle, R. ve Granger, C. (1987) “Cointegration and Error Correction: Representation, Estimation, and Testing” Econometrica, 55(2): 251–276.
• Figlewski, S. (1985) “Hedging with Stock Index
• Futures: Theory and Application in a New Market” The Journal of Futures Markets, 5(2): 183-199. Floros, C. ve Vougas, D. V. (2004) “Hedge Ratios in
• Greek Stock Index Futures Market” Applied Financial Economics, 14(15): 1125-1136.
• Hatemi-J, A. ve Roca, E. (2006) “Calculating the Optimal Hedge Ratio: Constant, Time Varying and the Kalman Filter Approach” Applied Economics Letters, (5): 293-299.
• Holmes, P. (1995) “Ex Ante Hedge Ratios and the Hedging Effectiveness of the FTSE-100 Stock Index
• Futures Contract” Applied Economics Letters, 2(3): 56- Holmes, P. (1996) “Stock Index Futures Hedging:
• Hedge Ratio Estimation, Duration Effects, Expiration Effects and Hedge Ratio Stability” Joumat of Business Finance & Accounting, 23(1): 63-77. Hsu, Y.-C. ve Chen, A.-P. (2014) “A Clustering Time
• Series Model for the Optimal Hedge Ratio Decision Making” Neurocomputing, 138: 358–370. In, F. ve Kim, S. (2006) “The Hedge Ratio and the Empirical Relationship between the Stock and Futures
• Markets: A New Approach Using Wavelet Analysis” The Journal of Business, 79(2): 799-820. Johnson, L. L. (1960) “The Theory of Hedging and Speculation in Commodity Futures” The Review of
• Economic Studies, 27(3): 139-151. Kavussanos, M. G. ve Visvikis, I. D. (2008) “Hedging
• Effectiveness of the Athens Stock Index Futures Contracts” The European Journal of Finance, 14(3): –270. Lee, C.-F., Wang, K. ve Chen, Y. L. (2009) “Hedging and Optimal Hedge Ratios for International Index Futures
• Markets” Review of Pacific Basin Financial Markets and Policies, 12(4): 593–610. Lien, D. ve Shrestha, K. (2005) “Estimating the Optimal
• Hedge Ratio with Focus Information Criterion” The Journal of Futures Markets, 25(10): 1011–1024.
• Lien, D. ve Shrestha, K. (2007) “An Empirical Analysis of the Relationship between Hedge Ratio and Hedging
• Horizon Using Wavelet Analysis” The Journal of Futures Markets, 27(2): 127–150. Lien, D., Shrestha, K. ve Wu, J. (2015) “Quantile
• Estimation of Optimal Hedge Ratio” The Journal of Futures Markets. doi:10.1002/fut.21712
• Lindahl, M. (1989) “Measuring Hedging Effectiveness
• With R2: A Note” The Journal of Futures Markets, 9(5): 475. Lindahl, M. (1992) “Minimum Variance Hedge Ratios
• For Stock Index Futures: Duration and Expiration Effects” The Journal of Futures Markets, 12(1): 33-53. Olgun, O. ve Yetkiner, I. H. (2011) “Determination of
• Optimal Hedging Strategy for Index Futures: Evidence from Turkey” Emerging Markets Finance & Trade, 47(6): –79. Salvador, E. ve Aragó, V. (2014) “Measuring Hedging
• Effectiveness of Index Futures Contracts: Do Dynamic Models Outperform Static Models? A Regime‐ Switching Approach” The Journal of Futures Markets, (4): 374–398. Stein, J. L. (1961) “The Simultaneous Determination of
• Spot and Futures Prices” American Economic Review, (5): 1012-1025.
• Sultan, J. ve Hasan, M. S. (2008) “The Effectiveness of
• Dynamic Hedging: Evidence from Selected European Stock Index Futures” The European Journal of Finance, (6): 469-488. Working, H. (1953) “Futures Trading and Hedging” The American Economic Review, 43(3): 314-343.
• Yang, W. ve Allen, D. E. (2004) “Multivariate GARCH
• Hedge Ratios and Hedging Effectiveness in Australian Futures Markets” Accounting and Finance, 45(2): 301–