Buying a stock at 100 on Monday and buying it at 100 on Friday are not the same trade. Most investors can’t see why: Joe Walsh is the Founding Partner of hedge fund Code Partners. 60% annualized, Sortino over 2 in his personal account. Joe Walsh explains: “There’s a concept Lance Breitstein (@TheOneLanceB) popularized called the right side of the V. The expected value of buying a stock at 100 on a certain day and 100 on a different day, they’re not the same.” “Most people hear that and say, if you’re buying it at 100, you’re buying it at 100. No, it’s not. This is a game of missing information. That’s what investing and trading is.” “If you buy while it’s still cratering because it’s really cheap, you don’t have a defined stop. You’re just saying, I like the price. I’m ignoring the trend, I’m ignoring everything else.” “If you’re doing the classic Buffett and Munger of, if the market closes for 10 years I couldn’t care less, that’s fine. But in a hedge fund structure with LP liquidity, it would matter a great deal if the market was shut for 10 years.” “Where I’m really sizing up, I can’t think of a situation in recent history where I’ve done that against the trend. It’s quite reckless from a risk perspective.” “Once you’ve made a bottom and turned, you may be back at 100 having gone through 95 first. Now you can add at 100 with a defined stop at 95.” “You’re still paying the same price, but the trend is with you. You have a defined stop, and you can risk a lot more. You have a tailwind at your back, not a headwind at your face.”

How Chris Camillo figured out Stranger Things was going to move Netflix's subscriber numbers, while hedge funds were still counting viewers: Featured in Schwager's Unknown Market Wizards. Turned $20K into ~$80M. Built TickerTags, sold to Jefferies' M Science. Chris Camillo (@ChrisCamillo) explains: "There was a time when you couldn't really assess the impact each Netflix show was having on user growth. Funds had a couple of metrics they used to assess viewership." "But the truth was that every top Netflix show had roughly the same number of viewers. Orange Is the New Black was roughly the same as Stranger Things." "What you had to assess was the cultural depth of interest in a show. Not how many people are watching it on Netflix. How many people are talking about it at the water cooler at work." "That's what spreads to family and friends. People saying, 'You know what? I keep hearing about this show, Stranger Things. Maybe I'll get a Netflix subscription and watch it.'" "The only way to assess that was monitoring the volume of conversational data around the show, and comparing it to historic benchmarks of other hit Netflix shows." "When I was able to assess that, it was one of the biggest trades in the history of Netflix. The quarter Stranger Things came out, and how much it actually grew new subscribers." "Stranger Things was about 3x any other show they had ever made in the history of the company. If you weren't monitoring conversational data, and no one really was back then besides me, you just didn't have an insight into it."

Retail investors vs. hedge fund managers: who wins? Ex-Tudor quant PM Tom Costello (20%/yr, 1.4% max drawdown) DEBATES Market Wizard Chris Camillo ($20K → $80M, tells you to expect 70% drawdowns). Chris Camillo (@ChrisCamillo) turned $20K into ~$80M over 18 years, audited by Jack Schwager for Unknown Market Wizards at 77% annualized. Founded TickerTags, sold to Jefferies. Co-founder of Dumb Money. Tom Costello (@tcoste110) ran money at Tudor, Moore Capital, and Caxton. Started as a quant on JPM's exotic swaps desk. Now CIO at Bedrock Digital Assets. We cover: - Why a 50% drawdown is "a career-ending event" for a PM and "completely rational" for a retail investor with a 20-year horizon - Chris's case that everyone should have a levered, concentrated risk bucket, and expect a 70% drawdown in it - Tom's pushback: "At least half of the aspiring engineering students who wanna be day traders are gonna go broke" - Why hedge funds don't beat the S&P, and why that's a category error - 3x leveraged S&P ETFs held for decades: ~1.85x market returns, and the futures roll cost buried inside - The e.l.f. trade: one YouTube video, a full day sitting in a Walgreens, and every cosmetics analyst on Wall Street asleep - Chris spent 5 years selling social data to the biggest funds. They couldn't institutionalize it because "the words keep changing" - Vita Coco: a viral TikTok sound → the biggest quarter in company history → +34% on earnings - Tom's bet: LLMs hand social arb to the quants. Chris: "there's still plenty of time" - "I know very few day traders who ever made anything like real money" - Why Chris gives the strategy away after an 18-year run Highlights: 00:00 Intro 00:50 Who's better positioned to take risk: retail or hedge funds? 05:58 A message from ONYX 06:30 Why a 50% drawdown is rational for concentrated retail capital 08:57 Beta vs alpha: what two-and-twenty actually pays for 18:56 Should retail embrace 70% drawdowns? Bucketing risk capital 23:59 Can ordinary investors really compound 2–3x market returns? 30:08 Fair value, mistakes, and why 99% of day traders lose 35:32 Are 3x leveraged S&P ETFs a long-term buy? 43:31 Too big to fail: AI concentration and the case for leverage 46:06 Situational Awareness, crypto correlation, and overfit backtests 53:44 Social arb explained: Beacon Roofing, Hunger Games, Stranger Things 01:01:07 Is social arb crowded? Tiger Cubs, Ticker Tags, e.l.f. 01:07:42 Will Citadel and LLMs arb away TikTok alpha? 01:17:09 Incentives: why "hedge funds don't beat the S&P" is a category error 01:19:35 Why Chris shares social arb: $20K to $80M and the wealth gap 01:25:45 Closing: retail freedom vs institutional resources

Ex-IMC semiconductor options trader Lihong Wang on seeing the whole market's flow, betting the entire AI stack, & why foundation models are good enough to beat the S&P 500. Lihong Wang (@Lihong062) | Discretionary semiconductor options trader @ IMC Trading | Now co-founder of Freeport, a YC-backed event-driven perps exchange "You see what everyone's doing, you trade against the people who are stupid, and you get out of the way or you follow the people who are smart." We cover: - How a bet actually gets made on a vol desk: not predicting the future, just selling what's expensive and buying what's cheap - The edge of the seat: being counterparty to 20-40% of flow in certain options markets, a view "maybe a few dozen people on the entire planet" have - Knowing who HAS to trade: reverse-engineering banks' structured-product hedging from issuance data - How desks blow up: overestimating correlation, and why NVDA -17% on DeepSeek didn't mean AMD -12% - The trader group chats: ~3x beta to the S&P, median 30% drawdown in July, and everyone still bullish - His portfolio: 50 chip/AI stocks covering the entire stack, up 470% bottom-to-peak, then a 70% drawdown ("I'm literally down an entire Ferrari today") - Why trading firms may be the third-largest consumers of AI tokens on the planet - Moats vs. growth: why Cursor got funded with no moat, and what that means for careers in the age of AI - His hot take: foundation models can already beat the S&P 500 risk-adjusted. The model isn't the hard part, the harness is Highlights: 00:00 Intro 01:09 How discretionary options bets get made — and blow up 10:23 A message from Onyx 10:53 Warehousing benign flow through July's deleveraging 16:40 Seat leverage and how trading firms allocate talent 22:03 Why quant traders are levered long the AI stack 26:27 Playing the AI hand: leverage, moats, personal brand 36:42 From IMC to Freeport: AI agents for event-driven trading 45:26 Perp DEX endgame: liquidity, fragmentation, and SEC rulemaking 51:21 Sourcing semiconductor alpha from trader dinners 56:05 Narrative edge, DeepSeek puts, and a 70% drawdown 01:04:24 Is AI a bubble? Compounding, path, and Kelly leverage 01:08:39 US, China, and comparative advantage under ASI 01:12:17 Risk-taking when you're post-economic