Modules

Module Documentation

correlation.py

This script calculates financial correlations and stores the results in a PostgreSQL database.

Modules:

• psycopg2: For connecting to and interacting with a PostgreSQL database.
• pandas: For handling and processing tabular data.
• dotenv: For loading environment variables from a .env file.
• os: For accessing environment variables.
• numpy: For numerical operations.

Environment Variables:

• POSTGRES_USER: PostgreSQL username (default: ‘myuser’).
• POSTGRES_PASSWORD: PostgreSQL password (default: ‘mypassword’).
• POSTGRES_DB: PostgreSQL database name (default: ‘mydatabase’).
• POSTGRES_HOST: PostgreSQL host (default: ‘localhost’).
• POSTGRES_PORT: PostgreSQL port (default: ‘5432’).

Functions:

• fetch_data(query): Fetches data from the PostgreSQL database based on the provided SQL query.

• calculate_codes(data): Calculates codes based on percentage changes in the data.

  • Code 1: Positive change.
  • Code 0: Small negative or no change (-7% to 0%).
  • Code -1: Large negative change (less than -7%).

• calculate_correlation(revenue, market_cap, roic): Calculates the correlation between revenue, market cap, and ROIC codes.

  • Correlation is incremented when all three codes are either 1 or -1.

• calculate_consecutive_ones(data): Calculates the number of periods with more than two consecutive code 1 values.
• main(): Main function that fetches data, processes it, and stores the results in a PostgreSQL table.

Database Schema:

• Table: company_correlation

  • symbol (TEXT): Primary key representing the company symbol.
  • revenue (INTEGER[]): Array of calculated revenue codes.
  • market_cap (INTEGER[]): Array of calculated market cap codes.
  • roic (INTEGER[]): Array of calculated ROIC codes.
  • correlation (FLOAT): Correlation value between revenue, market cap, and ROIC.
  • consecutive_ones (INT): Number of periods with more than two consecutive code 1 values.

Usage:

• Ensure the required environment variables are set in a .env file.
• Run the script to calculate financial correlations and store the results in the database.

advisor.correlation.calculate_codes(data)

advisor.correlation.calculate_consecutive_ones(data)

advisor.correlation.calculate_correlation_all(revenue, market_cap, roic)

advisor.correlation.calculate_correlation_rev_cap(revenue, market_cap)

advisor.correlation.calculate_correlation_rev_roic(revenue, roic)

advisor.correlation.calculate_correlation_roic_cap(roic, market_cap)

advisor.correlation.fetch_data(query)

advisor.correlation.main()

fastapp.py

report.py

update_postgres.py

show-json.py