CRSP US Indices will start using the UES classification

The Intercontinental Exchange (ICE) and The Center for Research in Security Prices (CRSP) yesterday announced the change for it’s US indices through separate media: a newsletter and press release. This will make sure that the US indices from CRSP follow the proprietary UES classification system from ICE instead of the ICB classification.

The Industry Classification Benchmark (ICB) is an industry classification taxonomy launched by Dow Jones and FTSE in 2005. The ICB is used globally to divide the equity market into increasingly specific industry categories. The ICB system replaced the legacy FTSE and Dow Jones classification systems. An overview of the consequences of the introduction of the ICB at that time can be found at the CRSP website.

The Uniform Entity Sectors (UES) methodology from the ICE is a schema that is used for the entire US market: equities, corporate bonds and government securities. The UES system was designed in 2019 and it provides five levels of granularity with 14 Entity Sectors, 27 Entity Industry Groups, 73 Entity Industries, 118 Entity Sub-Industry Groups and 273 Entity Sub-Industries. Each classification level provides both a coded value and description. A full explanation of the classification is available at the ICE website. A direct link to the PDF reference document is available (t)here.

Python projects and GitHub

Not too long ago I started learning and working with Python. It seemed a popular language and I keep hearing about it more and more. Some platforms offer the option to connect to them and download data using software like Python (WRDS). Other database owners or platforms even have built an environment within their platform to make use of it (LSEG Workspace’s CodeBook).

Programs like Stata 17 and up make it possible to use Python from within it’s program interface. Recently Microsoft announced their it’s plans to allow Python to be used from Excel (within Microsoft 365). This will make powerful Python options like Pandas, Numpy and data visualization options to be available there.

I have started making test programs and using and adapting existing programs. Some of my efforts can be found at this blog. I have started to share some code now through the platform GitHub and make these files available and free of use. In the future I will post programs there for people to use and adapt on their own: GitHub Repositories.