Axel Cabrol, Wolfgang Drobetz, Tizian Otto, Tatjana Puhan
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Predicting Corporate Bond Illiquidity via Machine Learning
This paper tests the predictive performance of machine learning methods in estimating the illiquidity of US corporate bonds. Machine learning techniques outperform the historical illiquidity-based ...
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The Financial Analysts Journal aims to be the leading practitioner journal in the investment management community by advancing the knowledge and understanding of the practice of investment management through the publication of rigorous, peer-reviewed, practitioner-relevant research from leading academics and practitioners.
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