Financial Data for Paper Default Forecasting

The files stored here are : 1) raw data in Excel (Name : Financial Data of all firms.xlsx) , 2) source code (in Python), name "ensemble_learning.ipynb and 3) Read Me file associated with the Source code---all were used to support the research paper " Forecasting China Bond Default with Severe Class-Imbalanced Data: A Simple Learning Model with Causal Inference " , submitted to Economic Modeling. i) The majority of the raw data were sourced from East Money, one major financial data vendor in China; Some variables were directly taken from the raw data (e.g. standard financial metrics); some were computed ones. All are organized and stored in the Excel files attached ii) The Python code takes the data file as inputs, with each column being the本文件夹存储的文件包括：1）Excel格式原始数据（文件名为"全体企业金融数据.xlsx"）；2）Python源代码，文件名为"ensemble_learning.ipynb"；3）与该源代码配套的自述文件（Read Me）。所有文件均用于支撑已投稿至《经济建模（Economic Modeling）》的研究论文《基于严重类别不平衡数据的中国债券违约预测：一种结合因果推断的简易学习模型》。 i) 该原始数据的主要来源为中国主流金融数据服务商东方财富（East Money）。部分变量直接取自原始数据集（如标准金融指标），其余变量则为计算所得。所有数据均经过整理并存储于附带的Excel文件中。 ii) 本Python代码以该数据文件作为输入，每一列对应一个。