In order for hedge fund managers (and investors) to make informed investment decisions it is essential that a range of statistical analyses and investigations are performed. This will usually involve analysing a time series of monthly returns (or NAVs) to ascertain relevant properties of the data in order to make critical inference about the characteristics and performance of the hedge fund. Many visual and mathematical methods are available that allow hedge fund managers to understand the underlying data structure and identify potential anomalies that may need further investigation whilst also allowing them to make better informed decisions. It is also important for a serious investor or hedge fund manager to have a working knowledge of many of the probability and statistical concepts encountered in the industry so as to be confident and knowledgeable when explaining their investment strategies to potential investors.
This chapter covers the main concepts, principles and techniques employed in the statistical analysis of hedge fund returns. Both visual and theoretical methods are presented which show how to extract and interpret the informational content and underlying characteristics within a time series of hedge fund returns.