Representing Evidence-Public Policy and Evaluation

Representing Evidence-Public Policy and Evaluation Design

The Urban Institute

Evaluating the Viability of Value at Risk (VaR)

The year 2007 had hit the world economy hard. The economic crunch resulted in the collapse of major corporate houses and primarily financial institutions. The collapse of financial institutions based in United States of America did not only contribute in the crash of the American economy, but also in turn affected the international economy, especially the stocks and commodity markets. This made the investors reluctant to invest in these financial institutions; while the financial institution continued to claim that there risk analysis shows that the economic crunch was not a very major problem. Investors and financial institutions around the world use various measurement tools in order to assess the degree of risk involved in investing in a certain portfolio. The most widely used risk measurement tool is the Value at Risk model (VaR). Economic and financial researchers are now blaming the over dependence of financial institutions and investors on the Value at Risk model for the recent financial crisis and the collapse of financial giants. We are proposing to undertake a case study in order to assess and evaluate the practical viability of the Value at Risk model. This is important in order to protect the common investor from falling prey to over expectations of financial institutions and investment firms.

The Value at Risk Model

The value at risk model is a combination of various mathematical and statistical tools that are combined together to calculated the level of risk and uncertainty involved in taking a decision. The primary reason behind the popularity of the Value at Risk model among financial institutions is the fact that it is flexible and is easily applicable to almost all kinds of assets.

The Value at Risk model works on the lines of probability and statistics to measure a drop in value of asset over a period of time. In general, it is calculated between the confidence level of 1% and 5%. There are various methods for measuring the Value at Risk for a project including the Variance -- Covariance methods, the Risk Metrics Contribution method, Historical Simulation methods, and Monte Carlo simulation methods. While, these methods are simple to use and compute the potential level of risk involved, these are based on a variety of assumptions. Generally, all approaches involved using historical trends and data and probability distributions are defined based on historical trends. A major problem with Value at Risk model is that it does not take into account the changing conditions and trends and it still claims to compute risk in rare conditions.