Using GTR1 to count stocks, there was a substantial increase in the number of stocks about the start of COVID. It was a rapid rise, but not all at one day/month. Does anyone know what caused the rapid increase?
One could probably take a look at styp.a & perform the count on that variable. That’d show where the increase in total equities occurred by security type.
The styp.a codes are described by the following …
Share Type - First Digit | Share Type - Second Digit | ||
---|---|---|---|
1 | Ordinary Common Shares | 0 | Securities Which Have Not Been Further Defined |
2 | Certificates, Americus Trust Components* | 1 | Securities Which Need Not Be Further Defined |
3 | ADRs (American Depositary Receipts) | 2 | Companies Incorporated Outside The U.S |
4 | SBIs (Shares Of Beneficial Interest) | 3 | Americus Trust Components*, Exchange Traded Funds** |
7 | Units, Exchange Traded Funds** | 4 | Closed-End Funds and Unit Investment Trusts |
5 | Closed-End Fund Companies Incorporated Outside The US | ||
6 | US-incorporated SPAC | ||
7 | Foreign-incorporated SPAC | ||
8 | REIT’s (Real Estate Investment Trusts) |
One possibility is that there were a lot of SPACs issued at about that time due to the ‘SPAC boom’ (typically styp.a of 16 or less likely 17) & if so that increase should be working its way out of the system soon-ish (as the typical 2 year life of an SPAC would have or be about to expire). More here - Message: MI Board Search. (Thanks for the caching in datahelper demonstrated here!)
Another option would be to explore the sector (sector.s) & industry codes (indc.s) & see where there was an increase? That’d be a more involved parse though.
Yes, an unexpected increase during the pandemic. The increase was roughly linear from August 2020 to January 2022: about a 15% increase over 16 months. (Active increased more because of all of the new ETFs.)
step0: [Security Type; lag=1 days] == 10,11,12,18,30,31,48
step1: [daily SI-adjusted Price; share_lag=1 days; quote_lag=1 days] > 0
step2: styp.a = param0
linkToTheScreen
Counts of stocks passing each step:
Date | Active | step0 | step1 | |
---|---|---|---|---|
20080528 | 6955 | 5402 | 5305 | |
20120620 | 6751 | 4700 | 4578 | |
20200828 | 7647 | 4700 | 4454 | |
20211227 | 9265 | 5400 | 5178 | |
20221012 | 9579 | 5437 | 5238 | |
increase | 21% | 15% | 16% | from 20200828 to 20211227 |
From 20200828 to 20211227, most of the new listings were in styp.a 11:
styp.a | increase | 20211227 | 20200828 |
---|---|---|---|
11 | 472 | 3929 | 3457 |
12 | 199 | 645 | 446 |
31 | 55 | 389 | 334 |
change = IPOs + stypChanges - delistings
The styp changes may have been SPACs converting to ordinary stocks. stypChanges had an unusual spike in 2021. The number of IPOs spiked higher at the same time. And there were fewer delistings. Net effect was more ordinary stocks.
SIP stocks with styp.a=11!12:
change = IPOs + stypChanges - delistings
From 20201029 to 20211029: 554 = 304 + 450 - 200
From 20181029 to 20191030: -32 = 149 + 232 - 413
links:
stypChange
IPOs
SIPstocks1112
Excluding SPACs from GTR1 Backtests discusses changes in styp.a