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An industry best practice for estimating the market risk of trading operations involves projecting profit-and-loss distributions of portfolios of financial instruments over short time horizons and then summarizing that information into single numbers, such as value at risk (VaR) and expected shortfall. Easy to understand and conceptually straightforward, VaR has long been an industry standard for estimating market risk. The means by which it is calculated and used in practice to manage risk, however, present a number of modeling, data management and reporting challenges. This paper addresses ways in which SAS can help clients overcome these challenges to better measure and manage their market risk.
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