还有一点是,VaR估算是基于不充分的数据来计算的,这是VaR的另一个局限性。 一些经济学家认为,根据历史数据预测未来价值是不合适的,因为Va的英语翻译

还有一点是,VaR估算是基于不充分的数据来计算的,这是VaR的另一个局

还有一点是,VaR估算是基于不充分的数据来计算的,这是VaR的另一个局限性。 一些经济学家认为,根据历史数据预测未来价值是不合适的,因为VaR没有参考价值(Damodaran,2007年)。 尽管适用于使用历史数据来估计VaR,但仍然没有足够的数据来估计,尤其是信用风险和操作风险。 因此,数据不足限制了VaR模型的应用,可以通过自举法解决该问题(Danielsson等,2000)。 同时,还有其他局限性,例如评估VaR正确性的困难以及比回测频率更高的监管频率,这也限制了VaR模型的使用。
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结果 (英语) 1: [复制]
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Another point is, VaR estimates are based on insufficient data to calculate, this is another limitation of VaR. Some economists argue that, based on historical data to predict the future value is not appropriate, because VaR no reference value (Damodaran, 2007). Although suitable for use historical data to estimate VaR, but still not enough data to estimate, in particular credit risk and operational risk. Therefore, the data is insufficient to limit the application of VaR model can solve the problem (Danielsson et al., 2000) by a bootstrap method. At the same time, there are other limitations, such as difficult to assess the validity of VaR backtesting and higher than the frequency of the frequency regulation, which limits the use of VaR models.
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结果 (英语) 2:[复制]
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It is also important that VaR estimates are based on insufficient data, another limitation of VaR. Some economists argue that it is not appropriate to predict future value based on historical data because VaR has no reference value (Damodaran, 2007). Although it is useful to use historical data to estimate VaR, there is still not enough data to estimate, especially credit and operational risks. As a result, insufficient data limits the application of the VaR model, which can be solved by self-raising (Danielsson et al., 2000). At the same time, there are other limitations, such as the difficulty of evaluating VaR correctness and the higher regulatory frequency than the backtest frequency, which limits the use of the VaR model.
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结果 (英语) 3:[复制]
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Another point is that VaR Estimation is based on insufficient data, which is another limitation of var. Some economists believe that it is inappropriate to predict future value based on historical data, because VAR has no reference value (Damodaran, 2007). Although it is applicable to use historical data to estimate VaR, there is still not enough data to estimate, especially credit risk and operational risk. Therefore, the lack of data limits the application of VAR model, which can be solved by bootstrap method (Danielsson et al., 2000). At the same time, there are other limitations, such as the difficulty in evaluating the correctness of VaR and the higher frequency of supervision than the back testing frequency, which also limits the use of VAR model.<br>
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