Hi Matt, thanks for writing. How the top 1% investors make decisions is a mystery to us. We have reached out to at least 300 or 400 by now and tried to engage. They will hardly talk to us. At best, they are uncomfortable talking with us.
But here is a little game we play with founders that speaks volumes about the best investors which we call SuperTRACers. When we get a founder on a Zoom call, we like to tell them we think we can name their favorite investor, the one they are most likely to seek out if a problem comes up. The founders loved it. We name the SuperTRACers on their cap table. The founders always agree. But I repeat, the best investors won't talk with us.
If the most heavily weighted data in the model is who else invested, they'll always need human investors at other firms to model after. I wonder how the investors they model after are making decisions.
Good question! We have no idea how those investors are making decisions. We have identified them on LinkedIn and their resumes show this: Eighty eight percent of top 0.01% of investors, we call them SuperTRACers, have worked in an early-stage startup for an average of 10.2 years; the median is eight. years Seventy percent of SuperTRACers have founded a company. The average SuperTRACer has founded 1.7 startups. Finally, they rarely invest outside their sphere of competence. If they worked in FinTech, they invest in FinTech.
Great post - really reminded me of Moneyball. I guess AI will amplify the success of this approach but maybe also speed up the stage where everyone else starts to adopt the same philosophy?
here is the problem with all these models....reality is constantly changing and quant models use present reality...so when reality really changes they get destroyed....the numbers look great until they don't..having been in the financial investment world and started 2 research companies there, I've watched people state that these events that crush performance are 1 in thousand years ones....lol happened at least 4 times in the last 50 years
Craig, our models are based on data that is at least ten years old. I was in the hedge fund business. I ran a fund of funds. I never talked with a quant who would tell me anything about their algorithms. But I know one thing: RenTech remains the GOAT.
Hi Matt, thanks for writing. How the top 1% investors make decisions is a mystery to us. We have reached out to at least 300 or 400 by now and tried to engage. They will hardly talk to us. At best, they are uncomfortable talking with us.
But here is a little game we play with founders that speaks volumes about the best investors which we call SuperTRACers. When we get a founder on a Zoom call, we like to tell them we think we can name their favorite investor, the one they are most likely to seek out if a problem comes up. The founders loved it. We name the SuperTRACers on their cap table. The founders always agree. But I repeat, the best investors won't talk with us.
If the most heavily weighted data in the model is who else invested, they'll always need human investors at other firms to model after. I wonder how the investors they model after are making decisions.
Matt,
Good question! We have no idea how those investors are making decisions. We have identified them on LinkedIn and their resumes show this: Eighty eight percent of top 0.01% of investors, we call them SuperTRACers, have worked in an early-stage startup for an average of 10.2 years; the median is eight. years Seventy percent of SuperTRACers have founded a company. The average SuperTRACer has founded 1.7 startups. Finally, they rarely invest outside their sphere of competence. If they worked in FinTech, they invest in FinTech.
for current reality...I agree but not for any black swan event not considered
Great post - really reminded me of Moneyball. I guess AI will amplify the success of this approach but maybe also speed up the stage where everyone else starts to adopt the same philosophy?
Kenny,
If you have read Moneyball, you see the connection. Thank you.
I have - great book and enjoyed the reminder so thank you
here is the problem with all these models....reality is constantly changing and quant models use present reality...so when reality really changes they get destroyed....the numbers look great until they don't..having been in the financial investment world and started 2 research companies there, I've watched people state that these events that crush performance are 1 in thousand years ones....lol happened at least 4 times in the last 50 years
Craig, our models are based on data that is at least ten years old. I was in the hedge fund business. I ran a fund of funds. I never talked with a quant who would tell me anything about their algorithms. But I know one thing: RenTech remains the GOAT.