Tests for Jumps in Yield Spreads

Lars Winkelmann and Wenying Yao

Journal of Business & Economic Statistics, 2024, vol. 42, issue 3, 946-957

Abstract: This article studies high-frequency econometric methods to test for a jump in the spread of bond yields. We propose a coherent inference procedure that detects a jump in the yield spread only if at least one of the two underlying bonds displays a jump. Ignoring this inherent connection by basing inference only on a univariate jump test applied to the spread tends to overestimate the number of jumps in yield spreads and puts the coherence of test results at risk. We formalize the statistical approach in the context of an intersection union test in multiple testing. We document the relevance of coherent tests and their practicability via simulations and real data examples.

Date: 2024
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Working Paper: Tests for Jumps in Yield Spreads (2023)
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DOI: 10.1080/07350015.2023.2271039

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