Value Hive Podcast

The episode is packed with actionable frameworks - COVID normalization as a multi-sector unifying thesis, subprime lending prepayment/default mechanics, lease-return velocity as a leading indicator, CEO comp plans as conviction signals - with minimal true throat-clearing. The density drops during the opening setup and the oil section, which meanders, but the Leslie's and AGL breakdowns are genuinely educational for a practitioner.

“my best trades are when I buy value or a value situation and I sell growth a growth stock”

“the nuance with COVID that blew up a firm upstart, literally the entire subprime space was because of COVID stimulus and interest rates that those two things going up Covid stimulants meant more. All the good credit, you had all the good credits prepaid. And the bad people, the defaults were still massive.”

The COVID normalization thesis as a cross-sector framework (autos, pools, healthcare all sharing the same boom-bust-adjustment cycle) is a genuinely fresh organizing idea that most analysts apply sector-by-sector. The price-action-overrides-spreadsheet-over-time argument is not novel but is articulated with unusual precision from a distressed background. The episode doesn't break into truly contrarian territory - the OPEC bear case and value-based-care recovery are visible trades by now.

“you can only be a contrarian on a macro and overrule price action in the beginning. Every day that goes on with a major macro thing that goes on, the price action becomes more and more true.”

“I came up with it later because I realized all my thesises, or most of them really tied to Covid... Covid wasn't a one year thing. It was really, you know, it's 2019 versus today. You had a boom bust and then readjustment”

Judd Arnold is a genuine practitioner: distressed analyst at King Street (worked the Calpine bankruptcy) and Anchorage Capital, then ran a fund at a large asset manager before going independent. He has clearly done the primary work himself - management calls, covenant analysis, comp plan review - and his disclosed positions (TOI from 25 cents, AGL from $8) show a real track record rather than theorizing. He is not a famous institutional CIO, which caps the score.

“I started in finance in summer oh three at Lehman... I was in the power and utility group and then I was the power utility guy at my first hedge fund, King street. And I worked on the Calpine bankruptcy that filed a month after I joined King Street.”

“I worked at three mega hedge funds and then my team spun out of the last one and we launched a hedge fund at a big asset manager.”

The episode is unusually data-rich: balance sheet line items, Mannheim index moves, lease-return rate percentages at multiple points in time, AGL's exact cash/debt position at year-start, CEO strike prices, Leslie's EBITDA trajectory across five years with revenue figures, and OPEC barrel-per-day projections by country. Very few claims are left at the hand-waving level; nearly every thesis is anchored to named companies, specific metrics, and multi-year timelines.

“You have $750 million of term loan... 10 million of shares now trading at about 9 bucks a share. So 9, you have 90 behind 750... EBITDA, Pete in 2022 at 200 uh, 75 million I think. On Ah, 1.4 billion of revenue. And last year it did 1.1 billion of revenue and 60 million of EBITDA.”

“you started this year with, yeah, 370 of cash... you got 40 million bucks of debt. So call it 85 million. And they thought they could do EBITDA zero this year and go cash flow positive next year. And you could buy that business with... $5.5 billion of revenue”

The host is knowledgeable and asks a few substantive structural questions (on liquidity vs. process, on how ideas surface), but largely plays prompter rather than challenger. He does not push on the Leslie's terminal value math, does not interrogate the bear case on AGL, and never offers a counterpoint on any thesis. The conversation flows well but is fundamentally a monologue with cues rather than a genuine dialogue with productive friction.

“How do you. How do you kind of shift from making sure that stuff is liquid enough that people will care, but also maintaining the core pillars of, like, the reasons why you found those ideas.”

“So how did you, how did you find this? Like, how did, like how did this stock surface and hit your radar?”