Thank you for this post (and the December post). Highlighted your work in my Alternative Data Weekly. I hope to drive more traffic and readers to this valuable content.
To seed, build, and nurture timeless, intangible human capitals — such as resilience, trust, truth, evolution, fulfilment, quality, peace, patience, discipline, relationships and conviction — in order to elevate human judgment, deepen relationships, and restore sacred trusteeship and stewardship of long-term firm value across generations.
A refreshing take on our business world and capitalism.
A reflection on why today’s capital architectures—PE, VC, Hedge funds, SPAC, Alt funds, Rollups—mostly fail to build and nuture what time can trust.
“Built to Be Left.”
A quiet anatomy of extraction, abandonment, and the collapse of stewardship.
"Principal-Agent Risk is not a flaw in the system.
I strongly feel that you are using survivorship biased data in your analysis of IPOs and stopped reading after that. Does your data include companies that have gone bankrupt?
ChatGPT gave several, but you should check they are real: Bridge Information Systems, Refco, Telerate, Thompson Financial. Ideally you would have a complete database of bias-free stock prices for these analyses but usually these are paid. Ironically, you can probably subscribe to one from one of your targeted companies.. lol
Ah the old suspects, yes these are valid names that were mismanaged into oblivion, but not significant bankruptcies of public companies I can include. Telerate came first, and was briefly public for two years in the 80s, changed ownership 3-4 times, before being acquired by Bridge and then Reuters.
Bridge itself had 1 year as a public company, before it was delisted and absorbed by Reuters. Bridge which ate Telerate was acquired for $275m which felt paltry to include in this analysis, a rounding error in the market cap of the industry.
Thomson Financial, was indeed significant, spun-out as Refinitiv, which was then acquired by LSEG, and is included in the analysis.
Hopefully, you agree, survivorship bias doesn’t meaningfully impact the findings of this post. Well run financial data companies are outlier performers!
As i understand it, survivorship bias is particularly relevant when analyzing aggregate industry returns or building investable indices, where excluding failed companies would indeed overstate overall industry performance. However, when examining individual company returns - as this analysis does - each company's performance stands on its own merits.
That said, my research has failed to identify any notable public bankruptcies among financial data companies. I welcome any examples I might have missed (there maybe some from the 80s for which data is scant) that will add to the context of this post.
Curious if you have any data or analysis on how much data buyers/subscribers “waste” on duplicate subscriptions, inefficient data calls and even data audit penalties. On top of “triple dipping” vendors make their contracts overly complex and opaque…
This data is impossible to come by, and vendors draw strength from the opacity in the market. There is certainly an opportunity to break the mould here and find a way for aggregate, non-confidential disclosures that brings transparency without breaking licensing contracts. A way of forcing the industry's hand.
Thank you for the post. Interested in seeing startups doing LLM work for activation and ui complexities 👀
Check out OpenBB run by Didier and team that is commoditizing the UI layer, at the same time providing LLM integrations far ahead of any incumbents.
Thank you for this post (and the December post). Highlighted your work in my Alternative Data Weekly. I hope to drive more traffic and readers to this valuable content.
https://farrall.substack.com/p/alternative-data-weekly-224
Thanks John, much appreciated 🙏🏼
Bravo!
Legend 💪
Quality as always
Hello there,
Huge Respect for your work!
New here. No huge reader base Yet.
But the work has waited long to be spoken.
Its truths have roots older than this platform.
My Sub-stack Purpose
To seed, build, and nurture timeless, intangible human capitals — such as resilience, trust, truth, evolution, fulfilment, quality, peace, patience, discipline, relationships and conviction — in order to elevate human judgment, deepen relationships, and restore sacred trusteeship and stewardship of long-term firm value across generations.
A refreshing take on our business world and capitalism.
A reflection on why today’s capital architectures—PE, VC, Hedge funds, SPAC, Alt funds, Rollups—mostly fail to build and nuture what time can trust.
“Built to Be Left.”
A quiet anatomy of extraction, abandonment, and the collapse of stewardship.
"Principal-Agent Risk is not a flaw in the system.
It is the system’s operating principle”
Experience first. Return if it speaks to you.
- The Silent Treasury
https://tinyurl.com/48m97w5e
I strongly feel that you are using survivorship biased data in your analysis of IPOs and stopped reading after that. Does your data include companies that have gone bankrupt?
ChatGPT gave several, but you should check they are real: Bridge Information Systems, Refco, Telerate, Thompson Financial. Ideally you would have a complete database of bias-free stock prices for these analyses but usually these are paid. Ironically, you can probably subscribe to one from one of your targeted companies.. lol
Ah the old suspects, yes these are valid names that were mismanaged into oblivion, but not significant bankruptcies of public companies I can include. Telerate came first, and was briefly public for two years in the 80s, changed ownership 3-4 times, before being acquired by Bridge and then Reuters.
Bridge itself had 1 year as a public company, before it was delisted and absorbed by Reuters. Bridge which ate Telerate was acquired for $275m which felt paltry to include in this analysis, a rounding error in the market cap of the industry.
Thomson Financial, was indeed significant, spun-out as Refinitiv, which was then acquired by LSEG, and is included in the analysis.
Hopefully, you agree, survivorship bias doesn’t meaningfully impact the findings of this post. Well run financial data companies are outlier performers!
You may also be interested in this, I feel like your thesis is similar but instead of data it’s land https://open.substack.com/pub/specialsituationinvesting/p/shorting-texas-pacific-land-tpl?r=20zihd&utm_medium=ios
Hi Matt, thank you for raising the question.
As i understand it, survivorship bias is particularly relevant when analyzing aggregate industry returns or building investable indices, where excluding failed companies would indeed overstate overall industry performance. However, when examining individual company returns - as this analysis does - each company's performance stands on its own merits.
That said, my research has failed to identify any notable public bankruptcies among financial data companies. I welcome any examples I might have missed (there maybe some from the 80s for which data is scant) that will add to the context of this post.
Curious if you have any data or analysis on how much data buyers/subscribers “waste” on duplicate subscriptions, inefficient data calls and even data audit penalties. On top of “triple dipping” vendors make their contracts overly complex and opaque…
This data is impossible to come by, and vendors draw strength from the opacity in the market. There is certainly an opportunity to break the mould here and find a way for aggregate, non-confidential disclosures that brings transparency without breaking licensing contracts. A way of forcing the industry's hand.