新西兰论文代写-信用风险模型。根据VaR模型的评估，有一个比较信用风险模型预测的能力，可以实际观察到理想的结果。可以引用一个例子，如Nickell et al，(1998)，指出实际价格用于公开交易的担保集，用于比较两种信用风险模型的信用损失预测性能。根据Granger等人(1997)的研究，过程通常用于时间序列分析中的模型规范和预测评估(Crouhy等人，2000)。这可以与信用风险建模等面板数据分析相结合使用。论文范文新西兰论文代写-信用风险模型分享给留学生阅读。
In accordance to the VaR model evaluation, however, there is a capability of comparing a forecast of credit risk model for actually observing desirable outcomes. An example can be quoted such as Nickell et al, (1998), stating that actual prices are used for a publicly traded bonding set for comparing the credit loss forecasts performance from 2 kinds of models of credit risk. In accordance to Granger et al., (1997), processes are used commonly for specification of model and evaluation of forecast within the analysis of time series (Crouhy et al., 2000). This can be adapted to use in alignment with analysis of panel data such as modelling credit risk.
The common idea is behind time series analysis with forecast evaluation for testing whether out of sample forecast series result in exhibiting accurate forecasts properties features. An essential characteristic of point forecasting for example is that the errors are not dependent on one another and this is a result of models specified properly. This idea can further be extended for the panel data analysis consisting cross section elements. In any specific year, cross section observations with out of sample predictions cannot be utilized for estimating this model (Gordy, 2003). The model and its data along with can be utilized for evaluation of accuracy. As far as such out of sample data is additionally and independently drawn from the sample population of cross section, the prediction error observed needs independence.