UCLA

High Yield bonds are a major component of the investment portfolios of institutions and individuals, and credit analysts use a wide range of variables to predict their returns. This study explores the nature of quarterly High Yield bond returns from June 30 2018 to June 30 2023 of a sample of High Yield bonds issued by US companies, and several of the variables commonly used by credit analysts. Using methods such as Bivariate Regression, Multiple Regression, and Random Forest, this research analyzes the relationship between Bond Returns and the independent variables, and uses different validation techniques to assess the quality of those models.