It is well known that zero coupon rates are not observable variables. Their estimation process may be cumbersome and time consuming. We explore the extent to which the set of security prices used in the yield curve construction of three popular interest rate datasets (from the Federal Reserve Board, the US Department of the Treasury, and Bloomberg) may determine the results of different analyses. Using the same US Treasury prices from GovPX and applying the same fitting technique, we estimate zero coupon rates using different baskets of assets, i.e., including/excluding bills, on-the-run, and off-the-run bonds, attempting to mimic those used by each data providers. To illustrate the uncertainty surrounding these alternatives representations of the underlying yield curve, we examine common uses of these data sets in pricing, risk management and macroeconomic purposes. We find significant and sometime overwhelming differences in the volatility term structure, the pricing of interest rate derivatives, and the correlations among different forward rates particularly in both ends of the yield curve. Relevant implications are also observed on a classic test of the expectations hypothesis. The simplest asset basket, which only includes the on-the-run bills and bonds, is probably the one with the best results.

中文翻译：

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不同债券数据集的收益率曲线

众所周知，零息票利率不是可观察的变量。他们的估计过程可能很麻烦且耗时。我们探讨了三种流行的利率数据集（来自美联储，美国财政部和彭博社）的收益率曲线构建中使用的一组证券价格可以确定不同分析结果的程度。使用来自GovPX的相同美国国债价格，并应用相同的拟合技术，我们使用不同的一篮子资产（包括/不包括票据，在运行和在运行的债券）来估算零息票利率，试图模仿每个数据提供者使用的那些。为了说明围绕收益率曲线的这些替代表示形式的不确定性，我们研究了这些数据集在定价中的常见用法，风险管理和宏观经济目的。我们发现波动性期限结构，利率衍生工具的定价以及不同远期利率之间的相关性（尤其是收益率曲线的两端）之间存在巨大的，有时是压倒性的差异。在预期假设的经典检验中也观察到了相关含义。最简单的资产篮子（其中仅包括运行中的票据和债券）可能是效果最好的篮子。