IN PRINT ARCHIVE CIR Summer 2008
By Sebastien Page, CFA, Managing Director, Head of Portfolio and Risk Management Group, State Street Associates
With Canadian portfolios slowly but surely going global, investors must face new complexities—cash must be extracted from Canadian managers, transition risk must be managed, new managers must be identified, currency risk must be managed, and the list goes on. While investors spend a lot of resources determining the target asset mix and identifying new managers, the opportunity to use benefit payments to glide the asset mix towards its target (and simultaneously maximize expected risk-adjusted performance) is often overlooked. In this short review of my presentation at the 2008 Global Investment Conference, I discuss how three innovations in portfolio theory can be used to identify optimal cash extractions from Canadian managers. I present a systematic, quantitative process that maximizes the plan sponsor’s expected risk-adjusted return. For each innovation, I refer the interested reader to the original technical article.
1. Batting Averages
Constable and Armitage (2006) show that the batting average and the win/loss ratio provide a decomposition of alpha that allows for deeper insights into manager performance than the information ratio alone. Specifically, a manager with a high batting average can produce a poor information ratio if they have a relatively low win/loss ratio. Conversely, a manager with a low batting average can produce a large information ratio if their win/loss ratio is large enough.
2. Risk Regimes
Investors have long recognized that risk parameters such as standard deviation and correlation are not always stable through time. Chow, Jacquier, Kritzman, and Lowry (1999) address this important concern by partitioning historical returns into those returns associated with normal periods and those associated with periods of market turbulence. This separation allows investors to estimate risk parameters for each regime and to stress test the optimal cash extractions by substituting the risk parameters from the turbulent regimes.
3. Continuous Value at Risk
Investors typically measure risk as the probability of a given loss or the amount that can be lost with a given probability at the end of their investment horizon. This view of risk only considers the distribution of returns at the end of the investment horizon, whether the horizon lasts for one day, one week, one year, or many years. It ignores what might happen along the way. Investors should perceive risk differently. They should care about exposure to loss throughout their investment horizon and not just at its conclusion. Kritzman and Rich (2002) therefore introduce two new risk measures: within-horizon probability of loss and continuous value at risk.
Within-horizon probability of loss measures the likelihood that an investment will depreciate to a particular level from inception to any point during the specified horizon. Value-at-risk measured conventionally gives the worst outcome at a chosen probability at the end of an investment horizon. By contrast, continuous value-at-risk gives the worst outcome at a chosen probability from inception to any time throughout an investment horizon. These new risk measures reveal that within-horizon exposure to loss is substantially greater than investors normally assume.
Other Statistical Tools
These innovations can be combined with conventional statistical tools, such as:
Overall, this powerful quantitative toolset is designed to make the most of –but not replace– the use of due diligence and judgment by experienced pension professionals and consultants.
Chow, G., E.
Jacquier, M. Kritzman, and K. Lowry, “Optimal Portfolios
in Good Times and Bad,” Financial Analysts Journal, May/June