Financial Stability Analysis Using Multivariate Insolvency Risk Model

Project Overview:
This project involves analyzing the financial stability of Colombia's largest companies using a multivariate insolvency risk model. The analysis utilizes financial data publicly available from the "Superintendencia de Sociedades" to assess the risk of bankruptcy.

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What Was Done:
1. Extracted and processed financial data from public reports.
2. Employed financial ratios and the Altman Z2-Score model to evaluate the financial stability of companies.

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How It Was Done:

1. Data Extraction and Storage:
   - Extracted data from individual reports available on the "Superintendencia de Sociedades" webpage.
   - Employed a Python-based ETL (Extract, Transform, Load) process to store the data in a SQL Server database.
   - Crafted a SQL query to filter and include only year-end information for the fiscal years 2018 to 2022.

2. Financial Analysis:
   - Calculated financial ratios essential for the Altman Z2-Score model:
     - X1 = Working Capital / Total Assets (WC/TA)
     - X2 = Retained Earnings / Total Assets (RE/TA)
     - X3 = Earnings Before Interest and Taxes / Total Assets (EBIT/TA)
     - X4 = Market Value of Equity / Book Value of Total Liabilities (MVE/TL)
   - Applied the Altman Z2-Score model to classify companies into risk zones: High-risk, Alert, Precautionary, and Safe.

3. Theoretical Framework:
   - Utilized the Altman Z2-Score model, designed by NYU Professor Edward Altman, to predict the near-term likelihood of companies falling into bankruptcy or insolvency.

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Achievements:
- Successfully assessed the financial stability of Colombian enterprises using a robust and widely recognized risk model.
- Provided a clear classification of companies' risk levels, aiding in understanding their financial health.
- Demonstrated the utility of automated data extraction and processing for comprehensive financial analysis.