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What is 'Value At Risk - VaR'

Value at risk is a statistic that measures and quantifies the level of financial risk within a firm, portfolio or position over a specific time frame. It is a statistical technique used to measure and quantify the level of financial risk within a firm or investment portfolio over a specific time frame. This metric is most commonly used by investment and commercial banks to determine the extent and occurrence ratio of potential losses in their institutional portfolios. Risk managers use VaR to measure and control the level of risk exposure. One can apply VaR calculations to specific positions or whole portfolios, or to measure firm-wide risk exposure.

BREAKING DOWN 'Value At Risk - VaR'

VaR modeling determines the potential for loss in the entity being assessed and the probability of occurrence for the defined loss. One measures VaR by assessing the amount of potential loss, the probability of occurrence for the amount of loss and the time frame. For example, a financial firm may determine an asset has a 3 percent one-month VaR of 2 percent, representing a 3 percent chance of the asset declining in value by 2 percent during the one-month time frame. The conversion of the 3 percent chance of occurrence to a daily ratio places the odds of a 2 percent loss at one day per month.

Applying Value at Risk

Investment banks commonly apply VaR modeling to firm-wide risk due to the potential for independent trading desks to expose the firm to highly correlated assets unintentionally. Using a firm-wide VaR assessment allows for the determination of the cumulative risks from aggregated positions held by different trading desks and departments within the institution. Using the data provided by VaR modeling, financial institutions can determine whether they have sufficient capital reserves in place to cover losses or whether higher-than-acceptable risks require then to reduce concentrated holdings.

Problems With VaR Calculations

There is no standard protocol for the statistics used to determine asset, portfolio or firm-wide risk. For example, statistics pulled arbitrarily from a period of low volatility may understate the potential for risk events to occur and the magnitude. Risk may be further understated using normal distribution probabilities, which rarely account for extreme or black-swan events.

The assessment of potential loss represents the lowest amount of risk in a range of outcomes. For example, a VaR determination of 95 percent with 20 percent asset risk represents an expectation of losing at least 20 percent one of every 20 days on average. In this calculation, a loss of 50 percent still validates the risk assessment.

The financial crisis of 2008 exposed these problems as relatively benign VaR calculations understated the potential occurrence of risk events posed by portfolios of subprime mortgages. Risk magnitude was also underestimated, which resulted in extreme leverage ratios within subprime portfolios. As a result, the underestimations of occurrence and risk magnitude left institutions unable to cover billions of dollars in losses as subprime mortgage values collapsed.

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