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Inconsistencies in bond market quotes: Is it the wrong model or the wrong data?

机译:债券市场报价不一致:是错误的模型还是错误的数据?

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摘要

We use the linear programming approach to quantify quote inconsistencies in risk-free bond markets. We present an algorithm to identify whether an inconsistency is probably due to the insufficient framework flexibility, the insufficient data quality, or the non-homogeneity of the dataset. In the latter case we study the problem of filtering out some instruments so that the remaining dataset be homogeneous. We show that the traditional filtering approach performs unacceptably poor and propose new algorithms. We find that the bonds, which get mispriced the most by a fitting algorithm, surprisingly are not the bonds, which cause the inconsistencies. (C) 2017 Elsevier B.V. All rights reserved.
机译:我们使用线性规划方法来量化无风险债券市场中的报价不一致。我们提出一种算法来确定不一致是否可能是由于框架灵活性不足,数据质量不足或数据集的不均匀性所致。在后一种情况下,我们研究了滤除某些工具的问题,以便其余数据集是同质的。我们证明了传统的过滤方法表现不佳,并提出了新的算法。我们发现,通过拟合算法定价错误最严重的债券不是那些导致不一致的债券。 (C)2017 Elsevier B.V.保留所有权利。

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