Forecasting the Term Structure of Government Bond Yields Center for Financial Studies Forecasting the Term Structure of Government Bond Yields
Forecasting the Term Structure of Government Bond Yields Center for Financial Studies Forecasting the Term Structure of Government Bond Yields
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预测政府债券收益率的期限结构 金融研究中心 预测政府债券收益率的期限结构
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通讯作者：
Stan Zin
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作者：
F. Diebold;Canlin Li;Pieter Jan;Krahnen;Wieland;Dave Backus;Rob Bliss;Michael Brandt;Todd Clark;Qiang Dai;Ron Gallant;Mike Gibbons;David Marshall;Monika Piazzesi;Eric Renault;Glenn D. Rudebusch;Til Schuermann;Stan Zin
金融研究中心是一个非营利性研究组织，由 120 多家银行、保险公司、工业公司和公共机构组成的协会支持。它成立于 1968 年，与法兰克福大学密切相关，在金融界和学术界之间建立了牢固的联系。粮安委工作论文系列介绍了货币、银行和金融领域选定主题的科学研究成果。作者要么是该中心研究员计划的参与者，要么是该中心研究项目之一的成员。如果您想了解更多有关金融研究中心的信息，请告诉我们您的兴趣。并可出于教育和研究目的自由复制，只要不作更改，本版权声明随其复制，且不得以营利为目的出售。摘要：尽管过去二十年来收益率曲线建模取得了巨大进步，但人们对预测收益率曲线这一关键实际问题的关注相对较少。在本文中我们这样做。我们既没有使用无套利方法，也没有使用均衡方法。无套利方法侧重于精确拟合任何给定时间的利率横截面，但忽略了时间序列动态；均衡方法则侧重于时间序列动态（主要是瞬时利率的动态），但相对较少关注拟合任何给定时间的整个横截面，并且已被证明预测效果很差。相反，我们使用 Nelson-Siegel 指数成分框架的变体来将整个收益率曲线逐个周期地建模为动态演化的三维参数。我们表明，这三个时变参数可以解释为与水平、坡度和曲率相对应的因素，并且可以高效地估计它们。我们提出并估计了这些因素的自回归模型，并且我们表明我们的模型与有关收益率曲线的各种程式化事实是一致的。我们使用我们的模型进行短期和长期的期限结构预测，并取得了令人鼓舞的结果。特别是，从长远来看，我们的预测比各种标准基准预测要准确得多。 1 将收益率建模为协整系统的实证文献在精神上是相似的，通常具有一个潜在的随机趋势（短期利率）和相对于短期利率的固定利差。
The Center for Financial Studies is a nonprofit research organization, supported by an association of more than 120 banks, insurance companies, industrial corporations and public institutions. Established in 1968 and closely affiliated with the University of Frankfurt, it provides a strong link between the financial community and academia. The CFS Working Paper Series presents the result of scientific research on selected topics in the field of money, banking and finance. The authors were either participants in the Center´s Research Fellow Program or members of one of the Center´s Research Projects. If you would like to know more about the Center for Financial Studies, please let us know of your interest. and may be freely reproduced for educational and research purposes, so long as it is not altered, this copyright notice is reproduced with it, and it is not sold for profit. Abstract: Despite powerful advances in yield curve modeling in the last twenty years, comparatively little attention has been paid to the key practical problem of forecasting the yield curve. In this paper we do so. We use neither the no-arbitrage approach, which focuses on accurately fitting the cross section of interest rates at any given time but neglects time-series dynamics, nor the equilibrium approach, which focuses on time-series dynamics (primarily those of the instantaneous rate) but pays comparatively little attention to fitting the entire cross section at any given time and has been shown to forecast poorly. Instead, we use variations on the Nelson-Siegel exponential components framework to model the entire yield curve, period-by-period, as a three-dimensional parameter evolving dynamically. We show that the three time-varying parameters may be interpreted as factors corresponding to level, slope and curvature, and that they may be estimated with high efficiency. We propose and estimate autoregressive models for the factors, and we show that our models are consistent with a variety of stylized facts regarding the yield curve. We use our models to produce term-structure forecasts at both short and long horizons, with encouraging results. In particular, our forecasts appear much more accurate at long horizons than various standard benchmark forecasts. 1 The empirical literature that models yields as a cointegrated system, typically with one underlying stochastic trend (the short rate) and stationary spreads relative to the short rate, is similar in spirit.