The Information Hidden in Derivatives Markets

Abstract

One of the most important aspects in portfolio management is having an accurate understanding of the future possible returns of the underlying assets. Unfortunately, estimating such return distributions is anything but trivial. In this research, we consider the information embedded in the derivatives market. Derivatives are forward-looking instruments by design and thus should contain forward-looking information about their underlying assets. We describe how forward-looking information on the statistical properties of an asset can be extracted directly from options market data and how this can be used practically in portfolio management. While the extraction of a forward-looking risk-neutral distribution is well-established in the literature, obtaining information on future real-world distributions was until recently thought to be impossible. However, recent work by Ross (2015) has shown that it is indeed possible to derive exactly this distribution purely from options market data. We describe a robust implementation of Ross’s method on a history of weekly Top40 Index and USDZAR implied volatility surfaces. We outline some graphical ideas on how one can use this information descriptively and prescriptively and furthermore analyse the recovered moments – expected return, volatility, skewness and kurtosis – from the implied distributions. These recovered real-world moments are shown to be in line with economic rationale and also show promising results when used as signals within a simple TAA framework.