Rainman

$DOW and $LYB have been under pressure throughout 2025, largely due to the chronic oversupply of polyethylene (PE). However, for the first time, I’m seeing a sustained uptick in PE prices. I am wondering if we will see a structural turnaround in 2026 rather than a transient one. Falling natural gas prices are a massive tailwind for these companies because it serves as their primary feedstock.

Two of the largest polymers & solvents manufacturers- Sumitomo & Formosa Taiwan have announced force majeure on deliveries & have halted plant operations. Indian distributors sitting on stocks are selling chemicals at as high as +150% premium to needy customers.

$PGY CFO interview at the Morgan Stanley Conference today effectively cleared up market confusion. The interviewer prepared high-quality questions covering SaaS disruption fears, private credit crunch concerns, the competitive landscape, and capital allocation strategies. 1/ Impact of Agentic AI (The "SaaS Fear") “We’re not just about AI models. We’ve got a massive moat with $1 trillion in proprietary application data flowing through our network every year. A generic AI can't just copy what we do because they don't have access to this unique production data. Our infrastructure is already set. We can scale up without extra marketing or acquisition costs, which just fuels our profitability.” 2/ Moat? “You asked about our moat? It’s the data, hands down. We see $1 trillion in applications across all our partners. While each partner only sees their own slice, we see the whole pie. Good luck replicating this. It took massive investment and a first-mover advantage to get integrated with these partners and reach positive GAAP net income. There’s really no one else doing what we do in the B2B consumer lending space. We help partners convert more loans without them having to use their own capital.” 3/ Capital Allocation Strategy (Priority Order) - my take by reading between lines “Since our growth infrastructure is already fully built (1st), we will utilize excess cash to buy back mispriced bonds to lower our cost of debt (2nd), while maintaining dry powder for future M&A opportunities (3rd) and considering opportunistic stock buybacks (4th).”

$PGY CFO interview at the Morgan Stanley Conference today effectively cleared up market confusion. The interviewer prepared high-quality questions covering SaaS disruption fears, private credit crunch concerns, the competitive landscape, and capital allocation strategies. 1/ Impact of Agentic AI (The "SaaS Fear") “We’re not just about AI models. We’ve got a massive moat with $1 trillion in proprietary application data flowing through our network every year. A generic AI can't just copy what we do because they don't have access to this unique production data. Our infrastructure is already set. We can scale up without extra marketing or acquisition costs, which just fuels our profitability.” 2/ Moat? “You asked about our moat? It’s the data, hands down. We see $1 trillion in applications across all our partners. While each partner only sees their own slice, we see the whole pie. Good luck replicating this. It took massive investment and a first-mover advantage to get integrated with these partners and reach positive GAAP net income. There’s really no one else doing what we do in the B2B consumer lending space. We help partners convert more loans without them having to use their own capital.” 3/ Capital Allocation Strategy (Priority Order) - my take by reading between lines “Since our growth infrastructure is already fully built (1st), we will utilize excess cash to buy back mispriced bonds to lower our cost of debt (2nd), while maintaining dry powder for future M&A opportunities (3rd) and considering opportunistic stock buybacks (4th).”

$PGY CFO interview at the Morgan Stanley Conference today effectively cleared up market confusion. The interviewer prepared high-quality questions covering SaaS disruption fears, private credit crunch concerns, the competitive landscape, and capital allocation strategies. 1/ Impact of Agentic AI (The "SaaS Fear") “We’re not just about AI models. We’ve got a massive moat with $1 trillion in proprietary application data flowing through our network every year. A generic AI can't just copy what we do because they don't have access to this unique production data. Our infrastructure is already set. We can scale up without extra marketing or acquisition costs, which just fuels our profitability.” 2/ Moat? “You asked about our moat? It’s the data, hands down. We see $1 trillion in applications across all our partners. While each partner only sees their own slice, we see the whole pie. Good luck replicating this. It took massive investment and a first-mover advantage to get integrated with these partners and reach positive GAAP net income. There’s really no one else doing what we do in the B2B consumer lending space. We help partners convert more loans without them having to use their own capital.” 3/ Capital Allocation Strategy (Priority Order) - my take by reading between lines “Since our growth infrastructure is already fully built (1st), we will utilize excess cash to buy back mispriced bonds to lower our cost of debt (2nd), while maintaining dry powder for future M&A opportunities (3rd) and considering opportunistic stock buybacks (4th).”