Overall this study is about the hedging effectiveness of the four
commodities which are; gold, crude oil, crude palm oil, and tin. In order to
find the best commodity that has better hedging performance, the optimal hedge
ratio needs to be estimated. But before proceeding to calculate the optimal
hedge ratio, several general statistic tests on the time series data must be
measured. The tests on time series data are; test for stationary, test for
normality, test for autocorrelation and test for heteroscedasticity. Each
commodity was tested with those tests and for each commodity, the data of spot
and future price of the commodity are used.

When calculating optimal hedge ratio for each commodity, various
results are obtained. In this study, Diagonal VEC multivariate GARCH model is
used to estimate the optimal hedge ratio. In simple words, optimal hedge ratio
is the percentage of the portfolio that is hedged.  While hedging effectiveness is a process of
determining the effectiveness of the hedging process. From the tests that were
done in Eviews software and Microsoft Excel, it gives results that crude oil
future against crude oil spot is the best commodity since it got the highest
optimal hedge ratio and hedging effectiveness. Then, diagonal VEC GARCH model
is being used again to estimate the average value of the time-varying hedge
ratio series of crude oil future price against gold spot price, crude palm oil
spot price and tin spot price. The hedge ratio value of crude oil against gold
get the highest value while the hedge ratio of crude oil against crude palm oil
get a negative value. This negative result indicates that crude oil futures are
not suitable to hedge the price of crude palm oil.

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From this study, it can be known that companies that are dependent
on crude oil and gold can significantly reduce the risk by engaging the future
contracts since their optimal hedge ratio is close to one. 

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