Initially, the VaR has been anticipating to quantify the available risks in derivatives markets, but it has grown widely and it has now been applied in measuring all kinds of risks, primarily credit and market risks. It also developed from a tool that quantifies risk to a tool that is applied in active risk management. Today VaR has shifted beyond application in financial institutions. In the beginning, companies with largely exposed to financial markets used other kinds of activities before spreading to other businesses. Today, an ever-growing numbers of individual businesses apply and appreciate VaR as an effective tool for quantifying financial risksKrause (2003). This trend is evidently aided by the fact that non-specialists easily understand VaR. The risks of the prevalent use of VaR are an overdependence on the results it gives, misconception, and even abuse. It is as a result that, essential individuals using VaR understand its problems and limitations. In this paper, I will explore in depth these constraints, which unluckily do not mark prominently.
To begin with, the VaR estimate is founded on precedent data, that is, it uses past distribution of effects of the investment. However, to calculate the peril of an investment, it is of no concern how big this risk has been in the earlier period, but fairly on how much exposure there is within the existing period; therefore, the future distribution of outputs would be the appropriate to consider. As long as the division of outcomes stays steady, the VaR can simply be removed from the past distribution. In reality, the distributions are not steady over time; most remarkably, the inconsistency of outcomes and the correlations vary. Relying exclusively on past data can as a result give a poor risk measure Oldfield, et al (2000).
Unluckily, even with this problem resolved, there lingers an issue with the evaluation of the VaR itself. Since the true probability circulation is not well known in general, it has