Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of Identifying the Explanatory Variables of Public Debt and Its Importance on The Economy - ICMRED 2024
Series Vol. 95 , 27 June 2024
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Research on Hedging Ratio of Stock Index Futures to ETF Fund
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Abstract
Exchange Traded Funds (ETF) can largely avoid non-systematic risk, but investors often cannot avoid systemic risk, and the hedging function of stock index futures can do this. Therefore, hedging ETF with stock index futures has become a good investment strategy. Based on the trading data of the China Securities Index (CSI) 300 stock index futures and CSI 300 Exchange-Traded Fund (ETF), this paper analyzes the optimal hedging ratio of CSI 300 stock index futures by Ordinary Least Squares (OLS) and dynamic Error Correction Model - Generalized Autoregressive Conditional Heteroskedasticity (ECM-GARCH) model and compares the hedging performance predicted by the model to avoid the systematic risk of ETF. The results show that the hedging effect of the dynamic hedging model is better than that of the static model, and the ability to avoid systemic risk is also better. The predictions of both models show that stock index futures hedge ETFs very well. The dynamic model is more able to reduce the heteroscedasticity of the transaction data.
Keywords
CSI 300 stock index futures, hedging ratio, ETF, ECM-GARCH
References
1. Xiao, C. (2014). Research on the hedging ratio of Shenzhen 100ETF based on CSI 300 Stock index Futures. Xi 'an: Northwest University.
2. Zheng, Z. Chen, R. (2020). Financial Engineering.5 Ed. Beijing: Higher Education Press.
3. Chen, Q. (2020). Research on the hedging efficiency of stock index futures in China. Forum on Industry and Technology, 19(1): 90-91.
4. Wang, J. Y., Zheng, Y. W. (2014). Hedging efficiency measurement of CSI 300 stock index futures. Journal of Chengdu University of Technology (Social Science Edition), 22(6).
5. Wang, J., Xianmin, C., Lexin, Z. (2007). Hedging research of stock index futures in ETF investment management. Journal of Dalian University of Technology (Social Science Edition), 28(1).
6. Gu, C. Lyu, W. (2021). Research on Optimal hedging ratio of CSI 300 Stock Index Futures based on High Frequency data. Journal of Natural Science of Harbin Normal University, 37(5): 8-16.
7. Zhong, C. Y. (2023). Hedging ratio between CSI 300 stock index futures and ETF funds. China market, 23.
8. Yanhong, S., Guangping, F. (2015). Research on hedging ratio of stock index futures with VaR minimization. Journal of Mathematical Statistics and Management, 34(04): 750-760.
9. Ederington, L. H. (1979). The Hedging Performance of the New Futures Markets. Journal of France, (34): 157-170.
10. Ghosh, A. (1993). Hedging with stock index futures: estimation and forecasting with error correction model. The Journal of Futures Markets, 13(7), 743-752.
11. Chihchiang, H., Chihping, T., Yawhuei, W. (2018). Dynamic hedging with futures: A couple-based GARCH model. Journal of Futures Markets, 28(11): 1095-1116.
Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of Identifying the Explanatory Variables of Public Debt and Its Importance on The Economy - ICMRED 2024
- ISBN (Print)
- 978-1-83558-499-6
- ISBN (Online)
- 978-1-83558-500-9
- Published Date
- 27 June 2024
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/95/2024MUR0075
- Copyright
- 27 June 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited