Hot Spots and Hedges

Abstract

Abstract This chapter is a tutorial on portfolio risk management. It describes how to identify the primary sources of risk in complex portfolios—the “hot spots”—and how to identify the trades that will reduce those risks—the “hedges.” While this topic, identifying and reducing risk, would seem to be at the heart of risk management, many of the ideas presented here are not well-understood. Unfortunately, too much of the recent focus in risk management has been directed elsewhere—for example, toward under-standing and incorporating the risks of derivative securities. While derivtives can create complex and highly nonlinear payoffs, they are often not the primary source of risk in a portfolio. Also, while risk managers have focused much attention recently on developing firm wide systems to aggregate information from many traders or portfolio managers, they have generally not yet concentrated on how to use that information to obtain a comprehensive understanding of enterprise risk. More generally, while risk managers have also recently developed a greater appreciation of the statistical nature of risk and the need to use statistical measures such as value-at-risk (VaR)1 to quantify, monitor, and set limits on risk-taking activities, the tools required to understand and incorporate these statistical measures in portfolio risk management have lagged behind.2 This most important area of risk management—the development of portfolio analytics based on the statistical understanding of risk—has not received as much attention as it deserves. We hope this chapter helps to address this concern by describing a number of portfolio analysis tools that we have developed at Goldman Sachs in recent years to better understand, manage, and monitor the risks in our clients’ investment portfolios as well as our own trading positions. We focus on the concepts of risk management and how they apply in realistic trading and portfolio management contexts rather than on details of implementation.