Transcript
A (0:00)
Luke, welcome to the Network State podcast. Great to have you here.
B (0:03)
It's great to be here. Thanks for having me on blaji.
A (0:05)
Yeah. So you know, we have been carry on a fairly long running conversation, a sidebar on the world stage. You know, one of the things as a meta comment, like the group chats are actually good because they are, it's, it's like everybody's busy so you can have like an asynchronous conversation and then you can, you know, hang out in person. Like, you know, sometimes they'll see Kathleen Tyson or some other people from the group and it's always great because you could pick up right where you left off and everybody knows all the same references over the last several months. So anyway, so welcome. Great, great to, great to have you here.
B (0:41)
It's great to talk to you. I know we've talked before offline, but it's, it's. I've been looking forward to this.
A (0:45)
Awesome. So, okay, so you are, you know, you've got force for the trees. LC do you want to just give your quick bio, you're pretty, you know, big account on Twitter, but just for those are X. You know, I should say nowadays, give, give the, give the Luke on Luke spiel, if you wouldn't mind.
B (0:59)
Yeah, sure. I'll give you the elevator pitch. So nearly 30 years in finance. Started out in investment research. Was a partner at two different firms that were pioneers in bottoms up fundamental channel check research. At both of those places, I was one of the founding editors of a weekly piece that basically aggregated the bottoms up fundamental research we were doing into sort of a macro, the thematic piece that became one of the more widely read research pieces on Wall street, heard in the Midwest, and then straight from the source at the two different shops. Hung up my own shingle as FFTT in 2014, doing the same type of work with publicly available information. And what we do is I have what I think is the best job in the world. I get to sit around, read, comprehend, think all day, and aggregate large amounts of publicly available data into. What I'm looking for are developing economic bottlenecks. Because for me, my 30 years in finance have taught me that how a developing economic bottleneck will affect various sectors in the economy is the biggest attribution for investment outperformance. Perfect example, in the housing downturn, it didn't matter if you owned the best home builder. It was only down 90% while all the others went down 95 to 100%. Right? And maybe not home builder, but mortgage broker you get it, right. The most important thing was getting the bottleneck correct in that time. And that's something we try to do. So that's the short version of where I've come from, my background, and what we do today.
