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Title: Investing in high-yield debt: The case of U.S. bond market Authors:  Thomas Aeschbacher - University of St Gallen (Switzerland) [presenting]
Alexander Kostrov - University of St. Gallen (Switzerland)
Abstract: In the era of shrinking stock market returns, bond market attracts much investor's attention. We apply machine learning techniques to classify bond issues as distressed in the U.S. corporate bond market. There is a large-scale data preparation exercise behind our analysis. We describe some peculiarities in investor's behavior and try to exploit them in order to enhance investment strategies in the high-yield market segment. It is shown that improved prediction accuracy of bond defaults in statistical terms leads to higher economic gain for an investor.