但是，VaR模型在三个方面都有缺点。 第一个方面是模型假设，这些假设过

However, VaR model in three aspects drawbacks. The first is the model assumptions, these assumptions are too strong and can not be established. The second reason is its simplicity. Although VaR is easy to understand, but contained little information, no further reference. Other estimated value (for example, the expected gap) can be measured as a supplement to the VaR. In addition, the risk VaR estimates only market risk. It is necessary to estimate VaR other risks, such as credit risk and operational risk. Finally, a disadvantage of insufficient VaR calculated data, thus weakening the reliability of an estimate VaR. Therefore, we should adopt other risk management techniques, such as stress testing, sensitivity analysis and principal component analysis to fully understand the risk exposure.

However, the VaR model has drawbacks in three ways. The first aspect is the model assumptions, which are too powerful to hold up. The second reason is its simplicity. Although VaR is easy to understand, it contains very little information for further reference. Other estimates, such as expected gaps, can be measured as a supplement to VaR. In addition, VaR estimates that the risk is only a market risk. It is necessary to estimate vaR for other risks, such as credit risk and operational risk. The final drawback is that there is insufficient data to calculate VaR, which weakens the reliability of VaR estimation. Therefore, other risk management techniques, such as stress testing, sensitivity analysis and master component analysis, should be used to gain a comprehensive view of exposure.

However, VAR model has shortcomings in three aspects. The first is model assumptions, which are too strong to hold. The second reason is its simplicity. Although VaR is easy to understand, it contains little information and cannot be further referenced. Other estimates, such as expected gaps, can be measured in addition to var. In addition, the risk of VaR Estimation is only market risk. It is necessary to estimate the VaR of other risks, such as credit risk and operational risk. The last disadvantage is the lack of data to calculate VaR, which weakens the reliability of VaR Estimation. Therefore, other risk management techniques, such as stress testing, sensitivity analysis and principal component analysis, should be used to fully understand the risk exposure.<br>