Research on the Hedge Ratio of China's Crude Oil Futures — Based on DCC-GARCH Model
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v2i3.390
Abstract
Crude oil plays an important role in economic development. This paper chooses China’s crude oil futures and crude oil actuals as the research objects, and builds the DCC-GARCH model to study the hedge ratio under the risk minimization standard. The hedge ratios obtained from the DCC-GARCH model will be compared with those obtained from OLS, B-VAR and VECM models. The empirical results prove that: China’s crude oil futures and actuals have a significant reverse “leverage effect”; China’s crude oil futures have a variance reduction of more than 70% under all models; the DCC-GARCH model achieves the best hedging performance in the four models.
Keywords
crude oil futures, DCC-GARCH, hedge ratio
Full Text
PDF - Viewed/Downloaded: 30 TimesReferences
[2] Ederington L H. The hedging performance of the new futures markets[J]. Journal of Finance,1979,34.
[3] Engle R F.Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation[J]. Econometria,1982(50).
[4] Ghosh A.Hedging with stock index futures: estimation and forecasting with error correction model[J]. Journal of Futures Markets,1993,13(7).
[5] Johnson L.The theory of hedging and speculation in commodity futures[J]. Review of Economic Studies,1960,27(3).
[6] Lien D. The effect of the cointegration relationship on futures hedging: a note[J]. Journal of Futures Markets,1996,16(7).
[7] Myers R J, Thompson S R. Generalized optimal hedge ratio estimation[J]. American Journal of Agricultural Economics,1989,71(4).
[8] Tae H P.Time-varying distributions and the optimal hedge ratios for stock index futures[J]. Applied Financial Economics,1995,5(3).
[9] Yang W. Multivariate GARCH hedge ratios and hedging effectiveness in Australian futures markets[J]. Accounting & Finance,2005,45(2).
[10] Fu Jianru, Ye Menghua, Wan Wenhao. Model reset and futures hedging efficiency[J]. Journal of Jiangxi Normal University (Natural Science Edition), 2019, 43(02).
[11] Hua Junzhou, Wu Chongfeng, Liu Hailong, Zou Yan. An Empirical Study on the Effectiveness of Futures Copper Hedging[J]. System Engineering Theory Method Application, 2003(03).
[12] Song Bo, Xing Tiancai. Copper futures volatility spillover effect test based on price discovery and statistical hedging[J]. Statistics and Decision, 2020, 36(12).
[13] Yang Jie, Guo Junfeng. Empirical research on the hedging effect of Shanghai and Shenzhen 300 stock index futures[J]. Journal of Fujian Normal University (Philosophy and Social Sciences Edition), 2017(03).
[14] Yuan Xiang, Cao Fanyu. The influence of cointegration relationship on futures hedging strategy[J]. Mathematical Statistics and Management, 2003, 22(2).
[15] Yuan Chen, Fu Qiang. The dynamic correlation of China's stock index futures and actuals stocks and its hedging effect: new evidence from the Shanghai Stock Exchange 50, Shanghai and Shenzhen 300 and China Securities 500 Indexes[J]. System Engineering, 2017, 35( 10).
[16] Zhao Shuran, Wu Yunxia, Ren Peimin. Futures dynamic CVaR hedging model based on ECM-DCC model and its empirical analysis[J]. Operations Research and Management, 2016, 25(04).
Copyright © 2021 Hao Du
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License