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Testing trend stationarity of functional time series with application to yield and daily price curves

机译:测试功能时间序列的趋势平稳性,并将其应用于收益率和每日价格曲线

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Econometric and financial data often take the form of a collection of curves observed consecutively over time. Examples include intraday price curves, term structure curves, and intraday volatility curves. Such curves can be viewed as functional time series. A fundamental issue that must be addressed, before an attempt is made to statistically model or predict such series, is whether they can be assumed to be stationary with a possible deterministic trend. This paper extends the KPSS test to the setting of functional time series. We propose two testing procedures: Monte Carlo and asymptotic. The limit distributions of the test statistics are specified, the procedures are algorithmically described and illustrated by application to yield curves and daily price curves.
机译:计量经济学和金融数据通常采取随时间连续观察到的曲线集合的形式。示例包括日内价格曲线,期限结构曲线和日内波动曲线。这样的曲线可以看作是功能时间序列。在尝试对这些序列进行统计建模或预测之前,必须解决的一个基本问题是,是否可以假设它们具有一定的确定性趋势是静止的。本文将KPSS测试扩展到功能时间序列的设置。我们提出了两种测试程序:蒙特卡洛和渐近线。规定了检验统计量的极限分布,通过对收益率曲线和日价格曲线的应用对算法进行了算法描述和说明。

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