Degiannakis, Stavros and Floros, Christos and Salvador, Enrique and Vougas, Dimitrios (2020): On the Stationarity of Futures Hedge Ratios. Forthcoming in: Operational Research (2020)
Preview |
PDF
MPRA_paper_102907.pdf Download (879kB) | Preview |
Abstract
Stationarity of hedge ratios can be viewed as a first step for portfolio hedging since it represents that the sensitivity of spot and futures returns follow a process whose main characteristics do not depend on time. However, we provide evidence that the hedge ratios of the main European stock indices are better described as a combination of two different mean-reverting stationary processes, which depend on the state of the market. Also, when analysing the dynamics of hedge ratios at intraday level, results display a similar picture suggesting that intraday dynamics of the hedge between spot and futures are driven mainly by market participants with similar perspectives of the investment horizon.
Item Type: | MPRA Paper |
---|---|
Original Title: | On the Stationarity of Futures Hedge Ratios |
English Title: | On the Stationarity of Futures Hedge Ratios |
Language: | English |
Keywords: | Futures, Hedge Ratios, Intra-day Data, Multivariate Volatility Modelling, Regime-Switching, Stationarity. |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics G - Financial Economics > G1 - General Financial Markets > G13 - Contingent Pricing ; Futures Pricing G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets |
Item ID: | 102907 |
Depositing User: | Dr. Stavros Degiannakis |
Date Deposited: | 15 Sep 2020 17:37 |
Last Modified: | 15 Sep 2020 17:37 |
References: | Anderson, R. W., & Danthine, J. P. 1981. Cross hedging. Journal of Political Economy, 89, 1182–96. Baillie, R. T., & Myers, R. J. 1991. Bivariate GARCH estimation of the optimal commodity futures hedge. Journal of Applied Econometrics, 6, 109–24. Billio, M., Casarin, R. and Osuntuyi, A. 2018. Markov switching GARCH models for Bayesian hedging on energy futures markets, Energy Economics, 70, 545-562. Bollerslev, T. 1986. Generalised Autoregressive Conditional Heteroscedasticty. Journal of Econometrics, 33, 307-327. Bollerslev, T., Engle, R.F. & Nelson, D.B 1994. ARCH models. in R.F. Engle, D. McFadden, Handbook of econometrics, Vol. 4 Elsevier Science B.V, Amsterdam. Brooks, C., Henry, O. T. & Persand, G. 2002. The effect of asymmetries on optimal hedge ratios. Journal of Business, 75(2), 333–352. Camacho, M. 2011. Markov-switching models and the unit root hypothesis in real US GDP, Economics Letters, 112, 161-164. Cecchetti, S. G., Cumby, R. E., & Figlewski, S. 1988. Estimation of optimal futures hedge. Review of Economics and Statistics, 70, 623-630. Chen, S.-S., Lee, C.-F., & Shrestha, K. 2003. Futures hedge ratios: A review. Quarterly Review of Economics and Finance, 43, 433-465. Chen, R-R, Leistikow, D. and Wang, A. 2019. Futures minimum variance hedge ratio determination: An ex-ante analysis, North American Journal of Economics and Finance, in press. Chiou-Wei, S-Z., Chen, S-H., and Zhu, Z. 2020. Natural gas price, market fundamentals and hedging effectiveness, Quarterly Review of Economics and Finance, in press. Chortareas, G.E., G. Kapetanios, G., and Shin, Y. 2002. Nonlinear mean reversion in real exchange rates. Economic Letters 77, 411-417. Conrad, J., Kaul, G., & Nimalendran, M. 1991. Asymmetric predictability of conditional variances. Review of Financial Studies, 4(4), 597-622. Cotter, J. & Hanley, J. 2012. Hedging effectiveness under conditions of asymmetry. European Journal of Finance, 18(2), 135-147. Cotter, J. & Salvador E., 2015, The non-linear trade-off between return and risk: a regime-switching multifactor framework. Working Paper Series. Cui, Y. and Feng, Y. 2020. Composite hedge and utility maximization for optimal futures hedging, International Review of Economics and Finance, 68, 15-32. Degiannakis, S., & Floros, C. 2010. Hedge Ratios in South African Stock Index Futures. Journal of Emerging Market Finance, 9(3), 285-304. Degiannakis, S., & Floros, C. 2013. Modeling CAC40 volatility using ultra-high frequency data. Research in International Business and Finance, 28, 68-81. Ederington, L. 1979. The hedging performance of the new Futures markets. Journal of Finance, 34, 157-170. Elliot, G., Rothenberg, T. J., & Stock, J. H. 1996. Efficient Tests for an Autoregressive Unit Root. Econometrica, 64, 813-836. Engle, R. F., & Kroner, K. F. 1995. Multivariate simultaneous generalized ARCH. Econometric Theory, 11, 122–50. Ferguson, R., & Leistikow, D. 1998. Are regression approach futures hedge ratios stationary? Journal of Futures Markets, 18(7), 851-866. Floros, C., & Vougas, D. V., 2004. Hedge ratios in Greek Stock Index Futures Markets. Applied Financial Economics, 14(15), 1125-1136. Floros, C., & Salvador, E. 2014. Calendar anomalies in cash and stock index futures: International Evidence. Economic Modelling, 37, 216-223. Floros, C., & Salvador, E. 2016. Volatility, trading volume and open interest in futures markets. International Journal of Managerial Finance, 12, 629-653. Francq, C., & Zakoïan J.M. 2001. Stationarity of Multivariate Markov-switching ARMA Models. Journal of Econometrics, 102, 339-364. Grammatikos, T., & Saunders, A. 1983. Stability and the Hedging Performance of Foreign Currency Futures. Journal of Futures Markets, 3, 295-305. Hafner, R., & Wallmeier, M. 2007. Volatility as an Asset Class: European Evidence. European Journal of Finance, 13(7-8), 621-644. Hafner, R., & Wallmeier, M. 2007. Volatility as an Asset Class: European Evidence. European Journal of Finance, 13(7-8), 621-644. Hall, S. G., Psaradakis, Z. & Sola, M. 1999. Detecting Periodically Collapsing Bubbles: A Markov-Switching Unit Root Test. Journal of Applied Econometrics, 14(2), 143-154. Holmes, M. J. 2010. Are Asia-Pacific real exchange rates stationary? A regime-swithcing perspective. Pacific Economic Review, 15(2), 189-203. Kanas, A. & Genius, M. 2005. Regime (non)stationarity in the US/UK exchange rate. Economics Letters, 87, 407-413. Kroner, K. F., & Sultan, J. 1993. Time varying distribution and dynamic hedging with foreign currency futures. Journal of Financial and Quantitative Analysis, 28, 535-551. Lai, Y.S., & Lien, D. 2017. A bivariate high-frequency-based volatility model for optimal futures hedging. Journal of Futures Markets, 37, 913–929. Lai, Y. S., Sheu, H. J., & Lee, H. T. 2017. A multivariate Markov regime-switching high-frequency-based volatility model for optimal futures hedging. Journal of Futures Markets, 37, 1124– 1140. Lai, Y-S. & Sheu, H-J. 2010. The incremental value of a futures hedge using realized volatility. Journal of Futures Markets 30:9, 874-896. Lee, G.G.J. 1999. Contemporary and Long-Run Correlations: A Covariance Component Model and Studies on the S&P 500 Cash and Futures Markets. Journal of Futures Markets, 19(8), 877-894. Leistikow, D. and Chen, R-R. 2019. Carry cost rate regimes and futures hedge ratio variation, Journal of Risk and Financial Management, 12(2), 78, 2-17. Leistikow, D., R. Chen, and Y. Xu. 2019. Spot Asset Carry Cost Rates and Futures Minimum Risk Hedge Ratios, SSRN Working Paper 3373739. Levin, A., Lin, F., & Chu, C. 2002. Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108, 1-24. Lien, D. 2012. A Note on the Performance of Regime Switching Hedge Strategy. Journal of Futures Markets, 32(4), 389-396. Lien, D., Tse, Y.K., & Tsui, A. 2002. Evaluating hedging performance of the constant-correlation GARCH model. Applied Financial Economics, 12, 791–798. Lien, D., Wang, Z., and Yu, X. 2020. Optimal quantile hedging under Markov regime switching, Empirical Economics, in press. Lien, D., & Yang, L. 2004. Alternative settlement methods and Australian individual share futures contracts. Journal of International Financial Markets, Institutions and Money, 14(5), 473-490. Malliaris, A. G., & Urrutia, J. 1991. Tests of random walk of hedge ratios and measures of hedging effectiveness for stock indices and foreign currencies. Journal of Futures Markets, 11, 55–68. Masset, P., & Wallmeier, M. 2008. A High-Frequency Investigation of the Interaction between Volatility and DAX Returns. European Financial Management, 16(3), 327-344. Moschini, G. C., & Myers, R. J. 2002. Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach. Journal of Empirical Finance, 9, 589–603. Park, T. H., & Switzer, L. N. 1995. Time-varying distributions and the optimal hedge ratios for stock index futures. Applied Financial Economics, 5, 131–7. Phillips, P.C.B., & Perron, P. 1998. Testing for Unit Roots in Time Series Regression. Biometrika, 75, 335-346. Qu, H., Wang, T., Zhang, Y., & Sun, P. 2019. Dynamic hedging using the realized minimum-variance hedge ratio approach–Examination of the CSI 300 index futures. Pacific-Basin Finance Journal, 57, 101048. Salvador, E. & Arago, V. 2014. Measuring hedging effectiveness of index futures contracts: Do dynamic models outperform static models? A Regime-Switching approach. Journal of Futures Markets, 34(4), 374-398. Samitas A, Armenatzoglou A. 2014. Regression tree model versus Markov regime switching: a comparison for electricity spot price modelling and forecasting. Operational Research International Journal, 14, 319–340. Schwarz, G. 1978. Estimating the Dimension of a Model. Annals of Statistics, 6, 461-464. Sollis, R., Leybourne, S. and Newbold, P. (2002). Tests for Symmetric and Assymetric Nonlinear Mean Reversion in Real Exchange Rates. Journal of Money, Credit and Banking 34(3), 686-700. Timmermann, A., 2000. Moments of Markov switching models. Journal of Econometrics, 96(1), 75-111. Tse, Y. & Williams M. R. 2013. Does Index Speculation Impact Commodity Prices? An Intraday Analysis. Financial Review 48, 365-383. Wang Y, Geng Q, and Meng F. 2019. Futures hedging in crude oil markets: a comparison between minimum-variance and minimum-risk frameworks. Energy, 181, 815–826. Wang, G-J., Xie, C., He, L-Y., & Chen, S. 2014. Detrented minimum-variance hedge ratio: A new method for hedge ratio at different time scales. Physica A: Statistical Mechanics and its Applications, 405, 70-79. Xekalaki, E. & Degiannakis, S. 2010. ARCH Models for Financial Applications. John Wiley and Sons, New York. Yang, M., 2000. Some properties of vector autoregressive processes with Markov-switching coefficients. Econometric Theory 16, 23-43. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/102907 |