Wednesday, November 4, 2026

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@MultiplesCap

Multiples Capital on X

I recently sat down with @StockJabber at @IdeaBrunchEmail to discuss the strategy behind Multiples Capital's outperformance in 2025. The full interview is behind a paywall, but here are 4 core themes we discussed: 1/ The Multi-Asset Edge While many leaned on the "Magnificent 7," we found alpha in global de-dollarization and the massive electricity demands of AI data centers. This approach delivered a 3.15 Sharpe Ratio—with roughly half the turbulence of the S&P 500. 2/ Garrett Motion ($GTX) Update Since my last feature, $GTX has surged ~170%. We discussed the "perfect storm" of index inclusion and aggressive capital allocation that drove this run, and why the "EV-only" fear proved to be premature. 3/ AI Disruption vs. Mispricing The market is correctly identifying "AI Losers" in SaaS, but it’s applying that same anxiety with broad stroke. We broke down why Expedia ($EXPE) is a prime example of this mispricing, trading at a 12%+ FCF yield despite its essential role in the global travel ecosystem and it's growing B2B setment. 4/ My Favorite "Tokenization" Play We closed with a deep dive into the digitalization of finance. I shared my top idea for playing the tokenization trend, a company currently acting as the "digital infrastructure provider" for institutions and growing it's subscription and service revenues. Read the full deep dive here: Note: As this is premium content, I cannot share the PDF on a open platform. However, if you’d like to join my quarterly investor letter distribution list to see how we are positioning for the "Broadening Trade" in 2026, please send a DM.
@HaydenCapital 2 clicks

Fred Liu on X

AppLovin - Interview with Xiaochuan (architect of $APP's Axon engine). Thought this was the most in-depth public conversation on AppLovin's business to date. (P.S. Youtube has great subtitle translation) Axon & Technical Philosophy - Axon was built by just 5 people in 3 months - AppLovin was the first to implement models with prediction windows exceeding 7 days - Deliberately avoids developing its own LLMs, preferring to use the best available models on the market — building LLMs in-house wouldn't generate the best ROI E-Commerce Expansion - Decision to enter e-commerce made in May 2024, with the product launching later that year; original team was only 10 people - Entering e-commerce was effectively building a new model from scratch - The gaming and e-commerce algorithms share nothing except infrastructure and accumulated organizational experience Core Competency & Culture - AppLovin's edge isn't industry-specific — it's rooted in how the company approaches problems (the culture itself), which he believes positions them to tackle challenges well beyond gaming and e-commerce - His relish for being called an "underdog" comes through clearly throughout the interview Social Media Ambitions - Already working on building a next-generation social media platform - Strategic logic: Meta started with captive organic traffic and built an ad platform on top; AppLovin is doing the reverse - starting with the ad platform and building toward organic traffic - Owning that organic traffic, if achieved, would be a significant advantage Short Seller Response - When the short reports were published, Xiaochuan personally reviewed the systems and code to assess whether the claims had merit Hiring Philosophy - After 2023, overhauled hiring: moved to paying among the highest salaries in Silicon Valley, and shifted focus away from seasoned veterans toward people with fewer than 2 years of experience - Core belief: experience is overrated, the capacity to learn is underrated; breakthroughs come from willingness to abandon convention - "You can't operate like a large company if you don't have a large company's resources" - Most prominent AI researchers are overpriced — high visibility and intense competition drives salaries beyond their marginal value - Targets talent at the "periphery of the spotlight": technically strong but undervalued by the market, and still carrying the underdog mentality that well-known names often lack (i.e. "Moneyball") - Entire engineering org runs on fewer than 100 people

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