Develop Python Script to Retrieve Historical Credit Ratings Data via LSEG (Refinitiv) API
Budget: $250 – $750 AUD
Seeking a Python programmer to develop a script (that I can paste into Jupyter with my existing LSEG access and API key) to retrieve the historical issuer-level credit ratings for every American firm rated by Moody's and/or Fitch for the 20 years ending 2023-12-31, as at the end of each calendar month.
Key Requirements:
- Long-term issuer-level credit ratings from Moody's and/or Fitch (my LSEG subscription doesn't include S&P).
- As at the end of each month from 2003-01-31 to 2023-12-31. Refinitiv returns rating changes, so where a rating is unchanged (i.e., not reported in a particular month) forward-filled from the most recent rating change event.
- Formatted with the following columns: TICKER, COMMON NAME, CUSIP, MOODY's RATING, FITCH RATING, DATE (YYYY-MM-DD). Returning N/A if the firm is not rated by a particular rating agency.
- Exported to CSV.
- Provided as a code block that I can paste in Jupyter Notebook and run using my local Refinitiv access and API key.
I'm available over email for any clarifications or testing.
Ideally, following retrieval of the ratings data, the time-series data retrieval will be expanded to include:
- A range of market and financial data as each monthly date.
- The rating agency announcements accompanying each rating change (for sentiment analysis).
This secondary requirement can be included in the initial scope, if preferred, or otherwise as a separate secondary engagement.
Ideal Freelancer:
- Well-versed in Python programming.
- Familiarity with LSEG (Refinitiv) API.
- Experience in financial data extraction and handling.
Please note, the focus of this project is data collection and not analysis. The need for this project is immediate, thus keen to start as soon as a suitable freelancer is found.
Key Requirements:
- Long-term issuer-level credit ratings from Moody's and/or Fitch (my LSEG subscription doesn't include S&P).
- As at the end of each month from 2003-01-31 to 2023-12-31. Refinitiv returns rating changes, so where a rating is unchanged (i.e., not reported in a particular month) forward-filled from the most recent rating change event.
- Formatted with the following columns: TICKER, COMMON NAME, CUSIP, MOODY's RATING, FITCH RATING, DATE (YYYY-MM-DD). Returning N/A if the firm is not rated by a particular rating agency.
- Exported to CSV.
- Provided as a code block that I can paste in Jupyter Notebook and run using my local Refinitiv access and API key.
I'm available over email for any clarifications or testing.
Ideally, following retrieval of the ratings data, the time-series data retrieval will be expanded to include:
- A range of market and financial data as each monthly date.
- The rating agency announcements accompanying each rating change (for sentiment analysis).
This secondary requirement can be included in the initial scope, if preferred, or otherwise as a separate secondary engagement.
Ideal Freelancer:
- Well-versed in Python programming.
- Familiarity with LSEG (Refinitiv) API.
- Experience in financial data extraction and handling.
Please note, the focus of this project is data collection and not analysis. The need for this project is immediate, thus keen to start as soon as a suitable freelancer is found.