4 ms·
This is a very insightful remark, thank you. I focused on 10-Qs for the EDGAR filings module as you rightly pointed out - it seemed to be a good balance betwee
by muggermuch 4y ago
This is a very insightful remark, thank you.
I focused on 10-Qs for the EDGAR filings module as you rightly pointed out - it seemed to be a good balance between implicit information and usefulness of the data. TBH I didn't actually investigate the other (many) patterns.
Having said that, I have really enjoyed Kai Wu's research from Sparkline Capital (https://www.sparklinecapital.com/ https://www.sparklinecapital.com/), especially his extraction of the innovation factor from EDGAR filing texts. He's appeared in numerous podcasts, and they have all been super useful to listen to.
Maybe someday when I re-investigate EDGAR filings and go further, I might target these signals you talk about here.
- defrost 4y agoYou're welcome. 14+ years back a small group of West Australians put together what became https://www.spglobal.com/marketintelligence/en/campaigns/metals-mining https://www.spglobal.com/marketintelligence/en/campaigns/met... which was based upon integrating (GIS and regular DB) every daily mineral lease record across the accessable globe together with every publicly filed document across the relevant stock markets (AU, TSX, South Africa, London, etc) using (and updating|refing) templated patterns that appear in various classes of forms .. I would assume that territory has been revisited with better ML techniques.