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These results stand somewhat in contrast to the findings in Jorion (2002), who concludes that value-at-risk models are good predictors of future trading revenue variability.
See Hendricks and Hirtle (1997) for a discussion of the rationale behind the use of value-at-risk models for regulatory capital requirements and the choice of supervisory parameters specified in the capital standards.
This means that the profit and loss figures used in the backtest could reflect influences not incorporated into the value-at-risk model, potentially introducing bias into the backtest results.
Thus, the supervisory backtest is calibrated to a one-day standard to strike a balance between the need to have a sufficient amount of data to give the backtest statistical power and the desire to determine the accuracy of the value-at-risk model used in the capital calculations.
12) Under the most recent announcement by the Basle Committee on Banking Supervision (1997), these model-based specific risk estimates are subject to a scaling factor of four until market practice evolves and banks can demonstrate that their models of specific risk adequately address both idiosyncratic risks and "event risks" that might not be captured in a value-at-risk model.
Backtesting is a process of confirming the accuracy of value-at-risk models by comparing value-at-risk estimates with subsequent trading outcomes.
More important, inaccurate value-at-risk models or models that do not produce consistent estimates over time will undercut the main benefit of a models-based capital requirement: the closer tie between capital requirements and true risk exposures.
securities firms, has also advocated the use of value-at-risk models as an important way to measure market risk.
Clearly, the use of value-at-risk models is increasing, but how, well do they perform in practice?
Although this article considers value-at-risk models only in the context of market risk, the methodology is fairly general and could in theory address any source of risk that leads to a decline in market values.
Value-at-risk models assume that the portfolio's composition does not change over the holding period.
These factors have tended to be incorporated into value-at-risk models after the initial phases of model development.