The paper highlights the role of risk budgeting — how risk is ‘spent’ — in the investment management process and some of the practical issues encountered. Risk budgeting has received a great deal of interest from the investment management community recently, but no clear consensus has emerged on how it should be implemented. In this paper we outline a pragmatic risk budgeting method that can be applied at the portfolio level, and show that it can produce superior results when used in conjunction with cluster analysis techniques. There are practical implications for chief investment officers and chief executive officers on how they allocate human resources and capital in the investment management process.

A statistical factor model for stock returns is used to build a risk model of the market that separates the factor components (representing the market, investment themes and styles) and the stock specific component. Then cluster analysis techniques provide a visualisation of the changing risk structure of the market. Natural groupings of stocks emerge within the market often different to the classical industrial classification systems widely used today. These natural groupings clearly change over time reflecting the changing nature of equity markets, e.g. these techniques show very clearly the emergence of the telecommunications, media, technology phenomenon in the late 1990s and its subsequent demise in early 2001.

Using the framework of a statistical factor model, risk budgets can be aggregated or dis-aggregated. Aggregation can be to country, sector or any other group. Dis-aggregation will be to common factors (e.g. the market, growth, value and other styles) and stock specific factors, derived from a multi-factor model.