 | Surrogate Data Models: Interpreting Large-scale Machine Learning Crisis Prediction Models Author/Editor: Jorge A Chan-Lau, Ruofei Hu, Maksym Ivanyna, Ritong Qu, Cheng Zhong. Release Date:February, 2023 Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs more...
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| Understanding and Predicting Systemic Corporate Distress: A Machine-Learning Approach Author/Editor: Burcu Hacibedel, Ritong Qu. Release Date:July, 2022 In this paper, we study systemic non-financial corporate sector distress using firm-level probabilities of default (PD), covering 55 economies, and spanning the last three decades. Systemic corporate more...
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