Modeling and forecasting interval time series with threshold models
Modeling and forecasting interval time series with threshold models
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DOI：
10.1007/s11634-014-0170-x
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发表时间：
2015-03
影响因子：
1.6
通讯作者：
P. Rodrigues;Nazarii Salish
中科院分区：
文献类型：
--
作者：
P. Rodrigues;Nazarii Salish
本文提出了阈值模型来分析和预测区间值时间序列。提出了一种相对简单的算法来获得阈值和斜率参数的最小二乘估计。文中还介绍和讨论了基于该模型的预测构造和预测性能分析方法，以及基于不同模型组合的预测步骤。为了说明所提方法的有效性，本文以S&P500指数周收益率为样本进行了实证分析。所获得的结果是令人鼓舞的，与现有的方法相比非常有利。
This paper proposes threshold models to analyze and forecast interval-valued time series. A relatively simple algorithm is proposed to obtain least square estimates of the threshold and slope parameters. The construction of forecasts based on the proposed model and methods for the analysis of their forecast performance are also introduced and discussed, as well as forecasting procedures based on the combination of different models. To illustrate the usefulness of the proposed methods, an empirical application on a weekly sample of S&P500 index returns is provided. The results obtained are encouraging and compare very favorably to available procedures.