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 summarising 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 modelling, 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.
SAS offers a comprehensive platform for: automating the collection and preparation of market data; modelling risk factor evolution and instrument valuation to create profit/loss distributions; and accessing results at their most granular levels from interfaces that are already familiar to business users and quantitative resources. By eliminating time-consuming manual and redundant data management tasks, market risk analysts have more time to spend on more productive tasks, such as exploring strategies for controlling and managing market risk.
This is an extract from a White Paper published by SAS, a global provider of business analytics software and services.
For the full White Paper, please click on the link below:
¬ Haymarket Media Limited. All rights reserved.