Analyzing Financial Models to Forecast Bankruptcy
A comprehensive dataset of 8,262 public companies' financial variables and bankruptcy status, spanning a period of 19 years (1999-2018), has been created by researchers at the University of Parma in Italy and the University of Florida in the United States. However, direct access details to this dataset are not readily available in search results.
The dataset, which includes 18 annual accounting and financial variables for each company, covers companies listed on two U.S.-based stock exchanges, the New York Stock Exchange and NASDAQ. It also indicates whether the company filed for bankruptcy the following year, although it does not specify the exact number of companies that filed for bankruptcy.
For those interested in accessing this dataset, several approaches can be taken:
- Check academic publications and supplementary materials where the dataset might be published or shared by the authors from these universities.
- Visit the University of Parma and University of Florida research or finance department websites, as they may provide repositories or contact information for dataset access.
- Contact the principal investigators or authors of the relevant study or dataset directly via their academic emails for access requests.
- Search academic data repositories such as Kaggle, Harvard Dataverse, or institutional repositories that often host financial and bankruptcy datasets.
If you have the names of authors or the title of the dataset/study, further assistance can be provided. Otherwise, direct contact with the universities’ relevant departments or authors is the best reliable method to access this dataset.
It's important to note that the dataset does not provide information on the current status of the companies as of the latest available data. The image credit for this article is Flickr user Ken Teegardin, but it is not a part of the dataset.
This dataset is intended for use by financial researchers to train bankruptcy prediction models, providing valuable insights into the financial health of companies over the past two decades.
- Utilizing AI and machine learning algorithms, researchers can analyze this dataset of 18 years' worth of financial variables and bankruptcy statuses of 8,262 companies listed on the New York Stock Exchange and NASDAQ to develop accurate predictive models for stock-market investing.
- By incorporating data from this comprehensive resource into their research, finance scholars aim to provide insights into the factors that impact a company's risk of bankruptcy, contributing to the development of effective investment strategies.
- This dataset, created through the joint efforts of researchers at the University of Parma and the University of Florida, offers valuable data for any AI or finance enthusiast interested in researching bankruptcy trends and investigating factors influencing stock-market performance over a span of 19 years.
