Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions
Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions
复制标题
持续预测回归中参数不稳定性和结构变化的测试
DOI：
10.2139/ssrn.3626692
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
R. T. Varneskov
中科院分区：
文献类型：
--
作者：
T. Andersen;R. T. Varneskov
本文发展了参数不稳定性和结构变化测试的预测回归的经济系统持续向量自回归动态。具体而言，在设置中的所有-或一个子集-的变量可能是分数集成和预测关系可能具有协整，我们提供了sup-Wald打破测试，使用本地speCtruM（LCM）的方法构建。新的测试涵盖了参数变化和多个结构变化与未知的休息日期，和休息的数量是已知的或未知的。我们建立了渐近极限理论的测试，表明它符合标准的测试程序。因此，现有的束缚贝塞尔过程的临界值可以应用，而无需修改。我们实施了新的结构变化检验来探索隐含波动率和已实现波动率（IV和RV）之间分数协整关系的稳定性。此外，我们评估了相对效率的IV预测对一个具有挑战性的时间序列基准构建的高频数据。与现有的研究不同，我们发现的证据表明，IV-RV协整关系是不稳定的，精心构建的时间序列预测比IV更有效地捕捉低频运动RV。
This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all -- or a subset -- of the variables may be fractionally integrated and the predictive relation may feature cointegration, we provide sup-Wald break tests that are constructed using the Local speCtruM (LCM) approach. The new tests cover both parameter variation and multiple structural changes with unknown break dates, and the number of breaks being known or unknown. We establish asymptotic limit theory for the tests, showing that it coincides with standard testing procedures. As a consequence, existing critical values for tied-down Bessel processes may be applied, without modification. We implement the new structural change tests to explore the stability of the fractionally cointegrating relation between implied- and realized volatility (IV and RV). Moreover, we assess the relative efficiency of IV forecasts against a challenging time-series benchmark constructed from high-frequency data. Unlike existing studies, we find evidence that the IV-RV cointegrating relation is unstable, and that carefully constructed time-series forecasts are more efficient than IV in capturing low-frequency movements in RV.