论文标题
使用功能主成分分析推断利率术语结构中模型错误指定
Inference for Model Misspecification in Interest Rate Term Structure using Functional Principal Component Analysis
论文作者
论文摘要
级别，斜率和曲率是利率期限结构中的三个普遍粘贴的主要成分，因此被广泛用于建模。本文表征了这些模型如何通过时间流逝的异质性。在尼尔森 - 雪绿色模型中呈现可解释为三个因素的正直基础，我们设计了两个非参数测试，以考虑分别考虑到特征函数的序列，是否与数据驱动的功能主体组件基础基础相同。最终，我们在罕见事件发生时发现了两个基础之间的高度分散，即使模型的总体表现力也是偶尔的规格。
Level, slope, and curvature are three commonly-believed principal components in interest rate term structure and are thus widely used in modeling. This paper characterizes the heterogeneity of how misspecified such models are through time. Presenting the orthonormal basis in the Nelson-Siegel model interpretable as the three factors, we design two nonparametric tests for whether the basis is equivalent to the data-driven functional principal component basis underlying the yield curve dynamics, considering the ordering of eigenfunctions or not, respectively. Eventually, we discover high dispersion between the two bases when rare events occur, suggesting occasional misspecification even if the model is overall expressive.
