Hedging Effectiveness on the Thailand Futures Exchange Market
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Abstract
This study examines hedge strategies through derivative instruments in an emerging market, with evidence from Thailand during the period 2011 to 2018. Focusing on a series of futures contracts on the Thailand Futures Exchange market (TFEX), namely SET50 futures, gold futures and interest rate futures, the study methods employed in both static and time-varying models: OLS, VECM, time-varying OLS, EGARCH, BEKK and DCC. In general, the results show that SET50 futures display the best hedge ratio and hedge effectiveness in Thailand, followed by gold futures and interest rate futures. Therefore, investors in Thailand will benefit from investing in SET50 futures only if their business or hedge assets relate to the composite index, particularly the SET50 index. Otherwise, the other types of derivatives or financial instruments may need to be considered more carefully for investment strategies. However, the hedge effectiveness of gold futures appears to be sensitive when the time-varying models are applied differently. Furthermore, these results are consistent with the previous literature and shed more light on the study of derivative products in Thailand.
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References
Acatrinei, M., Gorun, A., & Marcu, N. (2013). A DCC-GARCH model to estimate the risk to the capital market in Romania. Journal for Economic Forecasting, 0(1), 136-148.
Amornsiripanuwat, J. (2017). Hedging effectiveness of options on the Thailand Future Exchange (in Thai). WMS Journal of Management, 6(3), 1-16.
Awang, N., Azizan, N.A., Ibrahim, I., & Said, R.M. (2014). Hedging effectiveness stock index futures market: an analysis on Malaysia and Singapore futures markets. Paper presented at the 2014 International Conference on Economic, Management and Development, Bern.
Basher, S.A., & Sadorsky, P. (2016). Hedging emerging market stock prices with oil, gold, VIX and bonds: A comparison between DCC, ADCC and GO-GARCH. Energy Economics, 54, 235-247.
Bhaduria, S.N., & Durai, S.R.S. (2008). Optimal hedge ratio and hedging effectiveness of stock index futures: Evidence from India. Macroeconomics and Finance in Emerging Market Economies, 1(1), 121-134.
Black, F. & Scholes, M. (1973). The pricing options and corporate liabilities. Journal of Political Economy, 81(3), 637-654.
Bonga-Bonga, L. & Umoetok, E. (2016). The effectiveness of index future hedging in emerging markets during the crisis period of 2008-2010: Evidence from South Africa. Applied Economics, 48(42), 3999-4018.
Brooks, C. (2008). Introductory Econometrics for Finance (2nd ed.) Cambridge: Cambridge University Press.
Caporin, M., & McAleer, M. (2010). Do we really need both BEKK and DCC? A tale of two multivariate GARCH models (KIER Discussion Paper Series No.738). Kyoto: Institute of Economic Research.
Chang, C-L., McAleer, M., & Tansuchat, R. (2011). Crude oil hedging strategies using dynamic multivariate GARCH. Energy Economics, 33(5), 912-923.
Chevallier, J. (2012). Time-varying correlations in oil, gas and CO2 prices: An application using BEKK, CCC, and DCC-MGARCH models. Applied Economics, 44(32), 4257-4274.
Choudhry, T. (2003). Short-run deviations and optimal hedge ratio: Evidence from stock futures. Journal of Multinational Financial Management, 13(2), 171-192.
Cotter, J., & Hanly, J. (2012). Hedging effectiveness under conditions of asymmetry. The European Journal of Finance, 18(2), 135-147.
Dimitriu, M.C., & Paun, I.-D. (2012). Short term hedging using futures contracts. Economia Seria Management, 15(2), 436-445.
Ederington, L.H. (1979). The hedging performance of the new futures markets. Journal of Finance, 34(1), 157-170.
Engle, R.F. (2002). Dynamic conditional correlation: A simple class of multivariate generalised autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350.
Engle, R.F., & Kroner, K.F. (1995). Multivariate simultaneous generalised Arch. Econometrics Theory, 11(1), 122-150.
Ghosh, A. (1993). Hedging with stock index futures: Estimation and forecasting with error correction model. The Journal of Futures Markets, 13(7), 743-752.
Gitman, L.J., & Joehnk, M.D. (2002). Fundamentals of investing (8th ed). Boston, MA: Pearson Education, Inc.
Holmes, P. (1996). Stock index futures hedging: Hedge ratio estimation, duration effects, expiration effects and hedge ratio stability. Journal of Business Finance and Accounting, 23(1), 63-77.
Laws, J., & Thompson, J. (2005). Hedging effectiveness of stock index futures. European Journal of Operational Research, 163(1), 177-191.
Lee, C.L., & Lee, M-L. (2012). Hedging effectiveness of REIT futures. Journal of Property Investment and Finance, 30(3), 257-281.
Lypny, G., & Powallo, M. (1998). The hedging effectiveness of DAX futures. The European Journal of Finance, 4(4), 345-355.
Maddala, G.S. (2001). Introduction to Econometrics (3rd ed.). Chichester, UK: John Wiley & Sons Ltd.
Mody, A. (2004). What is an emerging market? (IMF Working Paper No. 04/177). Washington, DC: International Monetary Fund.
Rao, S.V.D.N., & Thakur, S.K. (2008). Optimal hedge ratio and hedge efficiency: An empirical investigation of hedging in Indian derivatives market. Paper presented at Shailesh J. Mehta School of Management, Mumbai.
Ripple, R., & Moosa, I. (2005). Futures maturity and hedging effectiveness: The case of oil future (Research paper 0513). Sydney: Department of Economics, Macquarie University.
Rossi, E. (2012). Multivariate GARCH models. Retrieved from https://www2.stat.unibo.it/cavaliere/cide2012/Rossi_multivariate_GARCH_CIdE_2012.pdf
Silvennoinen, A., & Teräsvirta, T. (2008). Multivariate GARCH models (SSE/EFI Working Paper Series in Economics and Finance No. 669). Stockholm: Stockholm School of Economics.
Su, W., & Huang, Y. (2010). Comparison of multivariate GARCH models with application to zero-coupon bond volatility. (Master’s thesis, Lund University, Lund, Sweden). Retrieved from https://lup.lub.lu.sc/student-papers/record/1619618
Syriopoulos, T., Mermigas, A., & Tsatsaronis, M. (2017). Different methods of estimating optimal hedge ratio in freight market and hedging effectiveness between freight derivatives and time charter. Paper presented at the 8th National Conference of the Financial Engineering and Banking Society, Athens.
Syriopoulos, T., & Tsatsaronis, M. (2018). Estimating and testing optimal hedge ratio efficiency in global commodities market. Paper presented at International Conference on Business and Economics of the Hellenic Open University, Athens.
Tangjitprom, N. (2010). Preholiday returns and volatility in Thai stock market. Asian Journal of Finance and Accounting, 2(2), 41-54.
Wattanatorn, W. (2014). Beyond Black-Scholes: the stochastic volatility option pricing model and empirical evidence from Thailand. Paper presented at the Conference of Professor Sangvien Indaravijiya on Thai Financial Market, Thammasart Business School, Bangkok.
Wen, X., Wei, Y., & Huang, D. (2011). Speculative market efficiency and hedging effectiveness of emerging Chinese index futures market. Journal of Transnational Management, 16, 252-269.
Wilmott, P. (1994). Discrete charms. Risk Magazine, 7(3), 48-51.
Yang, W., & Allen, D.E. (2005). Multivariate GARCH hedge ratios and hedging effectiveness in Australian future markets. Accounting and Finance, 45(2), 301-321.