Quantitative financial analysis
Mentor 1
John Huck
Start Date
28-4-2023 12:00 AM
Description
The goal of this research project is to investigate the illiquidity of OTC (over-the-counter) markets, specifically through the lens of PIPEs (private investment in public equity). The focus of the project is to create a map from PIPEs to OTC and PIPEs to CRSP, two databases, based on common identifiers such as ticker symbol, company name, and date. The task involves verifying the matches between the databases for files provided. The initial focus is on figuring out how to match as many as possible programmatically using SAS string functions such as TRANWRD, SOUNDEX, COMPGED, COMPLEV, SPEDIS, and NYSIIS. The programmatic matches that need to be verified include ticker matches and name matches, with NODT matches indicating that the dates used to match the securities did not align. This research project also involves finding matches by hand, as some matches will be more difficult than others. The matches that can be found will be coded as a match in the “match” column and will indicate the source of the match in the “notes” column. The findings of this research will provide valuable insights into the illiquidity of OTC markets and how to improve their liquidity.
Quantitative financial analysis
The goal of this research project is to investigate the illiquidity of OTC (over-the-counter) markets, specifically through the lens of PIPEs (private investment in public equity). The focus of the project is to create a map from PIPEs to OTC and PIPEs to CRSP, two databases, based on common identifiers such as ticker symbol, company name, and date. The task involves verifying the matches between the databases for files provided. The initial focus is on figuring out how to match as many as possible programmatically using SAS string functions such as TRANWRD, SOUNDEX, COMPGED, COMPLEV, SPEDIS, and NYSIIS. The programmatic matches that need to be verified include ticker matches and name matches, with NODT matches indicating that the dates used to match the securities did not align. This research project also involves finding matches by hand, as some matches will be more difficult than others. The matches that can be found will be coded as a match in the “match” column and will indicate the source of the match in the “notes” column. The findings of this research will provide valuable insights into the illiquidity of OTC markets and how to improve their liquidity.
