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Use of value at risk by institutional investors

Listed author(s):
  • Katerina Simons
Registered author(s):

    In recent years, risk management has been of growing interest to institutional investors, including pension funds, insurance companies, endowments, and foundations, as well as the asset management firms that manage funds on their behalf. Traditionally, institutional investors, and particularly pension funds, have emphasized measuring and rewarding investment performance by their portfolio managers. In the past decade, however, many U.S. pension funds have significantly increased the complexity of their portfolios by broadening the menu of acceptable investments. At the same time, well-publicized losses among pension funds, hedge funds, and municipalities have underlined the importance of risk management and measuring performance on a risk-adjusted basis. ; One approach to risk management, known as Value at Risk (or VaR), has gained increasing acceptance in the last five years. VaR originated on derivatives trading desks and then spread to other trading operations. It is a measure of risk based on a probability of loss and a specific time horizon in which this loss can be expected to occur. VaR has become an accepted standard in the banking industry and it forms the basis of bank capital requirements for market risk. VaR adoption has been slower in the investment management industry, but as demand grows and consensus about the standards emerges, its use can be expected to accelerate. The author discusses the issues surrounding measures of risk adjusted performance, and she describes the major difficulties institutional investors may encounter when implementing VaR analysis. She concludes with a discussion of possible policy implications of widespread VaR adoption.

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    Article provided by Federal Reserve Bank of Boston in its journal New England Economic Review.

    Volume (Year): (2000)
    Issue (Month): Nov ()
    Pages: 21-30

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    Handle: RePEc:fip:fedbne:y:2000:i:nov:p:21-30
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    1. Katerina Simons, 1997. "Model error," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 17-28.
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