2014
DOI: 10.1287/mnsc.2013.1768
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Informed Bond Trading, Corporate Yield Spreads, and Corporate Default Prediction

Abstract: T aking advantage of recently augmented corporate bond transaction data, we examine the pricing implications of informed trading in corporate bonds and its ability to predict corporate defaults. We find that microstructure measures of information asymmetry seem to capture adverse selection in corporate bond trading reasonably well. We demonstrate that information asymmetry in bond trading has explanatory power for corporate bond yield spreads, and this result holds after controlling for the transaction costs o… Show more

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Cited by 62 publications
(16 citation statements)
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“…The signs and significance of the remaining control variables are generally consistent with the results of Model 1. These findings support Hypothesis H2a and the findings of related research (Han and Zhou, ). Information risk is an important risk factor to investors of bonds with a greater likelihood of default.…”
Section: Resultssupporting
confidence: 91%
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“…The signs and significance of the remaining control variables are generally consistent with the results of Model 1. These findings support Hypothesis H2a and the findings of related research (Han and Zhou, ). Information risk is an important risk factor to investors of bonds with a greater likelihood of default.…”
Section: Resultssupporting
confidence: 91%
“…In Table , Panel B, we re‐estimate Equation using the transaction‐level yield spread data. The main difference of this sample from the at‐issue sample is the elevated role of informed bond trading (Han and Zhou, ) that can further exacerbate the information uncertainty faced by uninformed bond investors. As a result, transaction‐level prices reflect information risk even more strongly via the trading process, leading to a pronounced Synchronicity effect on yield spread.…”
Section: Resultsmentioning
confidence: 99%
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“…The entrance of retail investors post registration will likely cause lower trading activity as they tend to behave more like "buy-and-hold" investors than QIBs. Retail investors may also interpret public information less efficiently than QIBs (e.g., Kandel andPearson 1995, Han andZhou 2014). The change of the investor base, post registration, may therefore lead to a clientele effect on our results.…”
Section: Alternative Liquidity Measures and Clientele Effectmentioning
confidence: 88%