Disadvantages of Using the Value at Risk (VaR) Model

The value at risk (VaR) model has several advantages, which is why it is used widely in different parts of the world. However, the model also has some very distinct disadvantages. The existence of these disadvantages does not mean that the model should not be used. It is still one of the best tools at our disposal when it comes to market risk management. However, it is important for risk management practitioners to be aware of the possible risks of the value at risk (VaR) model since ignoring those risks can lead to disastrous consequences in the long run.

1. False Sense of Security: The biggest problem with the value at risk (VaR) model is that it brings a false sense of security in people. This is because people begin making assumptions that are not true. For instance, people start falsely believing that the value at risk (VaR) number provides the maximum amount of loss that can happen on any given day. They tend to forget the fact that this number is probabilistic in nature and hence confidence level is important.

   Even if a company calculates the value at risk (VaR) at a 99% confidence level, there is still a chance that the actual loss will be greater than the value at risk (VaR) number 1% of the time. 1% of the team means that on average, a trading loss will exceed the expected amount 2-3 times in a year! Also, the value at risk (VaR) model does not provide any information about the extent to which this loss will exceed the calculated number.

   In many cases, catastrophic events may occur and the actual loss may exceed the expected loss by a huge amount. In some severe cases, the solvency of the firm may also be threatened by sudden huge losses. It is therefore important for the firms to realize that there is a huge difference between 99% confidence level and 100% confidence level. Not knowing the difference can cost them the existence of their firm.

2. Assumptions: The value at risk (VaR) model is a mathematical model. This means that any organization has to make certain mathematical assumptions before they run the model. Hence, the validity of the results of the model is based on the validity of the assumptions that have been used in the model.

   For instance, it is common to assume that the losses have a normal distribution and make the calculations accordingly. However, in many industries, it may not be true. In some market scenarios using the binomial distribution may be more beneficial as compared to the normal distribution.

3. Subjective Results: The value at risk (VaR) model is not a single model. Instead, it is a type of model which provides broad guidelines. Hence, there are several variants of this model available. The problem is that many times, the variants are not consistent with each other. This means that the value at risk calculated using one variant may differ wildly from the value at risk calculated using a completely different variant.

   The end result is that the values given by the VaR model are quite subjective. It is possible for the management to understate or overstate some risks simply by tweaking some of the assumptions in the VaR model.

4. Difficult to Estimate for Diverse Portfolios: The value at risk (VaR) model is easy to calculate when the number of assets in a portfolio is less. As the number of assets in a portfolio increases, the complexity increases in an exponential manner. This is because the value at risk model takes into account the correlation between all types of assets.

   Hence, when the number of assets increases, the correlations that have to be taken into account also increases. This can become mathematically challenging. The software programs used to calculate the value at risk number usually have a limitation when it comes to the maximum number of assets in the portfolio.

5. Not Additive: It is important to note that value at risk is not additive. This means that if the company has a portfolio A with value at risk X and it acquires another portfolio B with value at risk Y, the resultant value at risk will not be X plus Y. This is because we have already discussed above that there is a correlation between assets. Hence, it is not possible to simply add the VaR numbers! This poses a practical problem because the portfolio of many companies keeps changing at a rapid pace.

   However, the value at risk value cannot simply be adjusted for the portfolio changes. Instead, it has to be calculated from the very beginning. Even though technology helps in quickly calculating the value at risk, this poses several difficulties in the day-to-day management of the firm.

Based on the above arguments, it would be fair to say that the value at risk (VaR) model has its own fair share of limitations. However, it would also be fair to say that these limitations do not completely undermine the benefits provided by this model. This is the reason why the value at risk number is extensively used. However, the risk management practice is considered more prudent if the limitations posed by this model are understood before using the output generated in the decision-making process.

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