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We will also review the backtesting procedures used to evaluate Va R approach performance.

From a practical perspective, empirical literature shows that approaches based on the Extreme Value Theory and the Filtered Historical Simulation are the best methods for forecasting Va R.

In the specific case of market risk, a possible method of measurement is the evaluation of losses likely to be incurred when the price of the portfolio assets falls. The portfolio Va R represents the maximum amount an investor may lose over a given time period with a given probability.

Since the BCBS at the Bank for International Settlements requires a financial institution to meet capital requirements on the basis of Va R estimates, allowing them to use internal models for Va R calculations, this measurement has become a basic market risk management tool for financial institutions.

Empirical evidence shows that financial returns do not follow a normal distribution.

The second relates to the model used to estimate financial return conditional volatility.

In the context of the Non-parametric method, several Non-parametric density estimation methods have been implemented, with improvement on the results obtained by Historical Simulation.

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As is well known, all these methodologies, usually called standard models, have numerous shortcomings, which have led to the development of new proposals (see Jorion, 2001).

Basel I, also called the Basel Accord, is the agreement reached in 1988 in Basel (Switzerland) by the Basel Committee on Bank Supervision (BCBS), involving the chairmen of the central banks of Germany, Belgium, Canada, France, Italy, Japan, Luxembourg, Netherlands, Spain, Sweden, Switzerland, the United Kingdom and the United States of America.

This accord provides recommendations on banking regulations with regard to credit, market and operational risks.

Among Parametric approaches, the first model for Va R estimation is Riskmetrics, from Morgan (1996).

The major drawback of this model is the normal distribution assumption for financial returns.

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    Consequently, it is not surprising that the last decade has witnessed the growth of academic literature comparing alternative modelling approaches and proposing new models for Va R estimations in an attempt to improve upon those already in existence.

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