Abstract
In this research, we investigated the long-run and causal relationships between spot and futures prices of crude oil, natural gas, and gasoline using monthly data and considering the variables’ distribution. The quantile co-integration and quantile causality tests provided strong evidence for the long-run and causal relationships among the variables. Furthermore, we examined the optimal hedge ratio (OHR) at different quantiles of the series using the recently developed quantile on the quantile approach. For all three commodities, our results confirmed the asymmetric response of the spot market to the futures market. Furthermore, our findings show that in a bullish market and for a large positive shock, the value of OHR is significantly greater than one. We observed lower fluctuations in the OHR as the maturities of the futures contracts increased. We discuss the policy implications of our research in detail in the Conclusion section.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Billio, M., Casarin, R., & Osuntuyi, A. (2018). Markov switching GARCH models for Bayesian hedging on energy futures markets. Energy Economics, 70, 545–562.
Chang, C. P., & Lee, C. C. (2015). Do oil spot and futures prices move together? Energy Economics, 50, 379–390.
Chang, C. L., McAleer, M., & Tansuchat, R. (2010a). Analyzing and forecasting volatility spillovers, asymmetries, and hedging in major oil markets. Energy Economics, 32(6), 1445–1455.
Chang, C. Y., Lai, J. Y., & Chuang, I. Y. (2010b). Futures hedging effectiveness under the segmentation of bear/bull energy markets. Energy Economics, 32(2), 442–449.
Chang, C. L., McAleer, M., & Tansuchat, R. (2011). Crude oil hedging strategies using dynamic multivariate GARCH. Energy Economics, 33(5), 912–923.
Chen, K. C., Sears, R. S., & Tzang, D. N. (1987). Oil prices and energy futures. Journal of Futures Markets, 7(5), 501–518.
Cheng, F., Li, T., Wei, Y. M., & Fan, T. (2019). The VEC-NAR model for short-term forecasting of oil prices. Energy Economics, 78, 656–667.
Chun, D., Cho, H., & Kim, J. (2019). Crude oil price shocks and hedging performance: A comparison of volatility models. Energy Economics, 81, 1132–1147.
Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829–836.
Conlon, T., & Cotter, J. (2013). Downside risk and the energy hedger's horizon. Energy Economics, 36, 371–379.
Cotter, J., & Hanly, J. (2015). Performance of utility-based hedges. Energy Economics, 49, 718–726.
De Jong, A., De Roon, F., & Veld, C. (1997). Out-of-sample hedging effectiveness of currency futures for alternative models and hedging strategies. The Journal of Futures Markets, 17, 1057–1072.
Ederington, L. H. (1979). The hedging performance of the new futures markets. The Journal of Finance, 34(1), 157–170.
Ederington, L. H., & Salas, J. M. (2008). Minimum variance hedging when spot price changes are partially predictable. Journal of Banking & Finance, 32(5), 654–663.
Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods.Econometrica: Journal of the Econometric Society, 424–438.
Gupta, K., & Banerjee, R. (2019). Does OPEC news sentiment influence stock returns of energy firms in the United States? Energy Economics, 77, 34–45.
Gupta, R., Pierdzioch, C., Selmi, R., & Wohar, M. E. (2018). Does partisan conflict predict a reduction in US stock market (realized) volatility? Evidence from a quantile-on-quantile regression model. The North American Journal of Economics and Finance, 43, 87–96.
Halkos, G. E., & Tsirivis, A. S. (2019). Value-at-risk methodologies for effective energy portfolio risk management. Economic Analysis and Policy, 62, 197–212.
Han, L., Liu, Y., & Yin, L. (2019). Uncertainty and currency performance: A quantile-on-quantile approach. The North American Journal of Economics and Finance, 48, 702–729.
Hung, J. C., Chiu, C. L., & Lee, M. C. (2006). Hedging with zero-value at risk hedge ratio. Applied Financial Economics, 16(3), 259–269.
Hung, J. C., Wang, Y. H., Chang, M. C., Shih, K. H., & Kao, H. H. (2011). Minimum variance hedging with bivariate regime-switching model for WTI crude oil. Energy, 36(5), 3050–3057.
Independent Statistics & Analysis US Energy Information Administration [EIA]. (2019a). Use of energy explained. Retrieved from: https://www.eia.gov/energyexplained/use-of-energy/
Independent Statistics & Analysis US Energy Information Administration [EIA]. (2019b). Gasoline explained. Retrieved from: https://www.eia.gov/energyexplained/gasoline/use-of-gasoline.php
Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence ofregression residuals. Economics Letters, 6(3), 255–259.
Johnson, L. L. (1960). The theory of hedging and speculation in commodity futures. Review of Economic Studies, 27, 139–151.
Khalifa, A., Caporin, M., & Hammoudeh, S. (2017). The relationship between oil prices and rig counts: The importance of lags. Energy Economics, 63, 213–226.
Koenker, R., & Bassett, G., Jr. (1978). Regression quantiles. Econometrica: Journal of the Econometric Society, 46, 33–50.
Kroner, K. F., & Sultan, J. (1993). Time-varying distributions and dynamic hedging with foreign currency futures. Journal of Financial and Quantitative Analysis, 28(4), 535–551.
Lang, K., & Auer, B. R. (2019). The economic and financial properties of crude oil: A review. The North American Journal of Economics and Finance, 52, 100914. Retrieved from: https://doi.org/10.1016/j.najef.2019.01.011
Lanza, A., Manera, M., & McAleer, M. (2006). Modeling dynamic conditional correlations in WTI oil forward and futures returns. Finance Research Letters, 3(2), 114–132.
Li, X., Sun, M., Gao, C., & He, H. (2019). The spillover effects between natural gas and crude oil markets: The correlation network analysis based on multi-scale approach. Physica A: Statistical Mechanics and its Applications, 524, 306–324.
Lien, D., & Tse, Y. K. (2000). A note on the length effect of futures hedging. Advances in Investment Analysis and Portfolio Management, 7(1), 131–143.
Lien, D., Shrestha, K., & Wu, J. (2016). Quantile estimation of optimal hedge ratio. Journal of Futures Markets, 36(2), 194–214.
Lin, L., Zhou, Z., Liu, Q., & Jiang, Y. (2019). Risk transmission between natural gas market and stock markets: Portfolio and hedging strategy analysis. Finance Research Letters, 29, 245–254.
Mallick, H., Padhan, H., & Mahalik, M. K. (2019). Does skewed pattern of income distribution matter for the environmental quality? Evidence from selected BRICS economies with an application of Quantile-on-Quantile regression (QQR) approach. Energy Policy, 129, 120–131.
Manera, M., McAleer, M., & Grasso, M. (2006). Modelling time-varying conditional correlations in the volatility of Tapis oil spot and forward returns. Applied Financial Economics, 16(07), 525–533.
Markopoulou, C. E., Skintzi, V. D., & Refenes, A. P. N. (2016). Realized hedge ratio: Predictability and hedging performance. International Review of Financial Analysis, 45, 121–133.
Meneu, V., & Torro, H. (2003). Asymmetric covariance in spot-futures markets. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 23(11), 1019–1046.
Mo, B., Chen, C., Nie, H., & Jiang, Y. (2019). Visiting effects of crude oil price on economic growth in BRICS countries: Fresh evidence from wavelet-based quantile-on-quantile tests. Energy, 178, 234–251.
Park, J. S., & Shi, Y. (2017). Hedging and speculative pressures and the transition of the spot-futures relationship in energy and metal markets. International Review of Financial Analysis, 54, 176–191.
Reboredo, J. C., & Ugolini, A. (2016). Quantile dependence of oil price movements and stock returns. Energy Economics, 54, 33–49.
Shahzad, S. J. H., Mensi, W., Hammoudeh, S., Sohail, A., & Al-Yahyaee, K. H. (2019). Does gold act as a hedge against different nuances of inflation? Evidence from Quantile-on-Quantile and causality-in-quantiles approaches. Resources Policy, 62, 602–615.
Shalit, H. (1995). Mean-Gini hedging in futures markets. Journal of Futures Markets, 15(6), 617–635.
Shrestha, K. (2014). Price discovery in energy markets. Energy Economics, 45, 229–233.
Shrestha, K., Subramaniam, R., Peranginangin, Y., & Philip, S. S. S. (2018). Quantile hedge ratio for energy markets. Energy Economics, 71, 253–272.
Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8.
Stein, J. L. (1961). The simultaneous determination of spot and futures prices. American Economic Review, 51, 1012–1025.
Stone, C. J. (1977). Consistent nonparametric regression. The Annals of Statistics, 5, 595–620.
Turner, P. A., & Lim, S. H. (2015). Hedging jet fuel price risk: The case of US passenger airlines. Journal of Air Transport Management, 44, 54–64.
Wang, B., & Wang, J. (2019). Energy futures prices forecasting by novel DPFWR neural network and DS-CID evaluation. Neurocomputing, 338, 1–15.
Wang, Y., Wu, C., & Yang, L. (2015). Hedging with futures: Does anything beat the naïve hedging strategy? Management Science, 61(12), 2870–2889.
Wang, Y., Geng, Q., & Meng, F. (2019). Futures hedging in crude oil markets: A comparison between minimum-variance and minimum-risk frameworks. Energy, 181, 815–826.
Wu, G., & Zhang, Y. J. (2014). Does China factor matter? An econometric analysis of international crude oil prices. Energy Policy, 72, 78–86.
Zhang, J. L., Zhang, Y. J., & Zhang, L. (2015). A novel hybrid method for crude oil price forecasting. Energy Economics, 49, 649–659.
**ao, Z. (2009). Quantile cointegrating regression. Journal of Econometrics, 150(2), 248–260.
Zhu, H., Guo, Y., You, W., & Xu, Y. (2016). The heterogeneity dependence between crude oil price changes and industry stock market returns in China: Evidence from a quantile regression approach. Energy Economics, 55, 30–41.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Barati, K., Sharif, A., Gökmenoğlu, K.K. (2023). Hedge Ratio Variation Under Different Energy Market Conditions: New Evidence by Using Quantile–Quantile Approach. In: Özataç, N., Gökmenoğlu, K.K., Balsalobre Lorente, D., Taşpınar, N., Rustamov, B. (eds) Global Economic Challenges. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-031-23416-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-23416-3_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-23415-6
Online ISBN: 978-3-031-23416-3
eBook Packages: Economics and FinanceEconomics and Finance (R0)