Institutional investors are putting increased emphasis on integrating market-driven measures of risk into both portfolio return analysis and portfolio development forecasting.These investors, who include plan sponsors, insurance companies and investment managers, have come to the conclusion that they need a deeper understanding of the factors that contribute to portfolio returns-along with an understanding of the volatility that jeopardizes those returns. This, they believe, will lead to more effective product development and portfolio management.
Measurement and tracking are the keys to success. The risk that affects forecasted returns can be better managed if the risk to delivered returns have been properly measured and tracked-more specifically if performance has been gauged on a risk-adjusted basis.
Behind the curve
As they size up all these factors and ways to deal with them, institutional investors have to catch up to competitors. Generally, commercial and investment banks have focused on risk-adjusted performance measurement for a much longer time than institutional investors have.
This has occurred for two reasons, including:
* The development and aggressive use of derivatives and structured products rendered meaningless accounting-based measures of leverage or market risk. Senior management moved quicker than regulators to demand more informative measures of risk-adjusted returns and forward-looking measures of current portfolio risk.
* Credit loss events led to a rapid regulatory response and, for commercial banks, a new regime of capital requirements with incentives to develop internal models to calculate risk-adjusted capital.
In recent years, as institutional investors have adopted more aggressive and sophisticated approaches to managing the asset side of the balance sheet, they've tackled many of the same challenges that long confronted investment banks.
For example, derivatives provide great flexibility to alter the risk/return profile of a portfolio, but also require specialized tools for pricing, hedging and credit risk management. An integrated view of the return distribution of a balanced portfolio then becomes more complicated since "balanced" now means more than one asset class.
This is true because each asset class includes securities, derivatives and structured products.
Until recently, very few of the established buy-side vendors could handle non-securitized products. On the other hand, very few of the sell-side vendors were prepared to calculate long-holding period returns in their scenario sets or benchmark relative risk for large portfolios.
Leading technology companies on both the buy-side and the sell-side have responded by altering their risk management tools to take into account new instruments, new portfolio development approaches and new hedging techniques.
Several companies now offer simulation-based applications that provide a consistent modeled view of multiple asset classes and diverse instrument sets.
Most offer flexibility in selecting the holding period that's factored into the calculations. Investment managers have also been able to turn to sell-side vendors for solutions not only for pricing but also middle- and back-office support for growing trading activities in derivatives.
Credit risk options
Capital markets now offer investors more options for creating and managing credit exposure in their portfolios. Asset-backed structured products have proliferated in the debt markets, both with and without intrinsic leverage.
At the security and basket level, credit derivatives represent a new class of tools that support risk mitigation and risk transfer. These tools engender a more active approach to portfolio credit risk management based on methods similar to those developed in the commercial bank arena. This approach is critical since a great majority of OTC derivatives generate credit exposure that needs to be measured and managed.
But even though institutional investors don't operate in a capital adequacy regime as banks do, many have recognized the importance of understanding inter- relationships between all the various credit exposures in their portfolios. This understanding helps to better manage the risks.
To augment this effort, the early adopters have entered into arrangements with vendors traditionally focused on corporate bank portfolio credit risk quantification.
The first problem attacked typically has been counterparty exposure from derivatives and other forward-settled transactions. In the absence of a requirement to compute risk-based capital, the movement toward broader portfolio credit risk quantification has been a gradual process.
For many institutions, the current challenge is less a case of which model to use, and more a matter of how to manage data better.
Once established, the goal of risk-adjusted performance measurement-and the goal of most all risk-based approaches to pricing and portfolio development-is to improve returns for a given level of risk throughout the organization.
The volume of data necessary to support these activities is significant. Moreover, the data must be assembled, verified and used in a consistent manner in order to produce reliable results. Often this must take place in an environment of increasing transaction volume coupled with inconsistent data treatment within multiple disparate legacy accounting systems.
An increasing number of institutional investors have come to understand that data administration is a key function of the process. Once this commitment is established, a number of middleware applications can facilitate the data integration that is necessary to support risk-adjusted performance measurement and broad scale risk management.
Richard Fein is a principle with PricewaterhouseCoopers, New York.
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