Theory and practice of multivariate arma forecasting
Theory and practice of multivariate arma forecasting
复制标题
多元预测的理论与实践
DOI：
10.1002/for.3980030308
复制
发表时间：
1984
影响因子：
3.4
通讯作者：
Dag Tjozstheim
中科院分区：
文献类型：
--
作者：
T. Riise;Dag Tjozstheim
我们比较单变量和多变量预测的基础上阿尔马模型。从理论上讲，我们不会因为使用多变量模型而不是单变量模型而做得更差，但我们可能会冒得不到任何改进的风险。没有改善的条件进行了讨论，以及大的改善发生的情况下。估计参数的影响进行了检查，发现是小的假设，一个很好的估计方法被使用。然而，多变量模型可能对结构变化非常敏感。这是说明通过一个例子，涉及货币数据，其中的多变量预测表现得比单变量的。这似乎限制了多变量阿尔马预测模型的使用。
We compare univariate and multivariate forecasts based on ARMA models. In theory we cannot do worse by using a multivariate model instead of a univariate one, but we can risk getting no improvement. Conditions for no improvements are discussed as well as cases where large improvements occur. The effect of estimated parameters is examined and found to be small granted that a good method of estimation is used. However, multivariate models could be very sensitive to structural changes. This is illustrated via an example involving monetary data, where the multivariate forecasts perform considerably worse than the univariate ones. This seems to put a limitation on the use of multivariate ARMA forecasting models.