  Reducing financial risk is of paramount importance to investors, financial
institutions, and corporations. Since the pioneering contribution of Johnson
(1960), the optimal hedge ratio based on futures is regularly utilized. The
current paper suggests an explicit and efficient method for testing the null
hypothesis of a symmetric optimal hedge ratio against an asymmetric alternative
one within a multivariate setting. If the null is rejected, the position
dependent optimal hedge ratios can be estimated via the suggested model. This
approach is expected to enhance the accuracy of the implemented hedging
strategies compared to the standard methods since it accounts for the fact that
the source of risk depends on whether the investor is a buyer or a seller of
the risky asset. An application is provided using spot and futures prices of
Bitcoin. The results strongly support the view that the optimal hedge ratio for
this cryptocurrency is position dependent. The investor that is long in Bitcoin
has a much higher conditional optimal hedge ratio compared to the one that is
short in the asset. The difference between the two conditional optimal hedge
ratios is statistically significant, which has important repercussions for
implementing risk management strategies.
