Forward-Looking Measures of Higher-Order Dependencies with an Application to Portfolio Selection

This paper provides implied measures of higher-order dependencies between assets. The measures exploit only forward-looking information from the options market and can be used to construct an implied estimator of the covariance, co-skewness, and co-kurtosis matrices of asset returns. We implement the estimator using a sample of US stocks. We show that the higher-order dependencies vary heavily over time and identify which driving them. Furthermore, we run a portfolio selection exercise and show that investors can benefit from the better out-of-sample performance of our estimator compared to various historical benchmark estimators. The benefit is up to seven percent per year