Constant & time-varying hedge ratio for FBMKLCI stock index futures
This paper examines hedging strategy in stock index futures for Kuala Lumpur Composite Index futures of Malaysia. We employed two different econometric methods such as-vector error correction model (VECM) and bivariate generalized autoregressive conditional heteroskedasticity (BGARCH) models to est...
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| Format: | Conference or Workshop Item |
| Language: | English English English |
| Published: |
2016
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| Online Access: | http://irep.iium.edu.my/54322/ http://irep.iium.edu.my/54322/1/QP_37_2016.pdf http://irep.iium.edu.my/54322/2/QP37_2016_Certificate.pdf http://irep.iium.edu.my/54322/3/QP_37_Programme%20%26%20Abstract%20Book.pdf |
| Summary: | This paper examines hedging strategy in stock index futures for Kuala Lumpur Composite Index futures of Malaysia. We employed two different econometric
methods such as-vector error correction model (VECM) and bivariate generalized autoregressive conditional heteroskedasticity (BGARCH) models to estimate
optimal hedge ratio by using daily data of KLCI index and KLCI futures for the period from January 2012 to June 2016 amounting to a total of 1107 observations.
We found that VECM model provides better results with respect to estimating hedge ratio for spot month futures and one-month futures, while BGACH shows
better for distance futures. While VECM estimates time invariant hedge ratio, the BGARCH shows that hedge ratio changes over time. As such, hedger should
rebalance his/her position in futures contract time to time in order to reduce risk exposure. |
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