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MUST-WATCH: Why SIG Dominated Options Trading — Explained by an 8-Year Insider Kris Abdelmessih (Kris) spent 8 years trading energy derivatives at SIG, then ran options businesses at Parallax & Prime before founding Moontower —one of the world's most popular newsletters on options & volatility trading. "SIG understood there...

232,488 просмотров • 5 месяцев назад •via X (Twitter)

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Inside Susquehanna International Group with Todd Simkin Todd Simkin led trader education & development at SIG, one of the most elite prop trading firms on the planet, for decades. He's now Head of Insurance at River's Edge, Susquehanna's managing general underwriter. We cover: - Why SIG trains traders with poker before they touch a market - The one trait great traders have that can't be taught - How SIG's flat org structure (3 titles, total) creates true meritocracy - Why the flop in poker maps directly to the top of the order book - SIG's expansion into sports trading, private equity, venture & reinsurance - How River's Edge prices NIL deals, Eagles Super Bowl promos & catastrophe risk - SIG's 25-year bet on prediction markets — & their relationship with Kalshi - Why titles are cheap & what SIG rewards instead Highlights: 00:00 Intro 01:01 What makes a great quant trader 02:26 How Susquehanna trains decision-making under uncertainty 03:05 Susquehanna interview philosophy: process, updating, communication 03:41 Teaching derivatives, options pricing, and risk from scratch 04:21 Using games to model trading concepts 05:11 Poker as a controlled model of asymmetric information 05:41 Internal Susquehanna trading games and mock trading structure 06:51 How mock trading reveals signal vs. noise 11:30 What traits can’t be trained 16:19 How Susquehanna screens for untrainable traits in interviews 20:41 Why internship performance is noisy 24:41 How pods work inside Susquehanna 26:11 Titles are meaningless at Susquehanna 34:01 Building SEG RE and expanding insurance capacity 43:31 25-year internal belief in prediction markets at Susquehanna 55:01 Closing remarks

Ethan Kho

34,855 просмотров • 4 месяцев назад

EDGE REVEALED: How an Ex-Jane Street Trader Finds Edge in Markets & Life Agustin Lebron Agustin Lebron (former Jane Street trader, author of The Laws of Trading, now working at an AI startup applying reinforcement learning to market execution) breaks down what edge really means — and how to find yours in trading, careers & life. “Edge is something that either you know or you can do that the marginal participant in that market either doesn’t or can’t.” We cover: - What edge actually means & how Jane Street builds organizational edge (their worst skill is still "pretty decent") - Why you can never truly know if you have edge — the statistical vs intuitive approaches - The consolidation of quant trading: from dozens of options firms to a handful of giants - The gamblification of everything — retail trading, sports betting & prediction markets fueling quant profits - What it was like having Sam Bankman-Fried (SBF) as a Jane Street intern: "Day one, I'm going to ask all the questions" - How to apply edge thinking to your own career: find what you're differentially good at - Raising teenagers in the AI age: why the traditional path still works, but other paths are opening up 00:00 Introduction 00:44 What is edge in financial markets 01:43 Jane Street and organizational structures for quant trading 03:46 Identifying and validating edge in trading 06:22 Navigating extreme market events and volatility 09:37 Future of quant trading and consolidation 12:15 Why quant firm profits have increased 14:42 The gamblization of everything 15:55 Who should pursue a career in quant trading 18:19 Applying the concept of edge to career and life decisions 20:56 Advice for interns to excel in quant trading 23:44 Predicting long-term success in trading interns 25:08 Sam Bankman-Fried as an intern and FTX reflections 28:15 Reasons people leave Jane Street and what they do next 31:19 Advice for young people in a changing world 36:09 Navigating job insecurity in tech-driven roles 38:55 Where to live if you want to be successful 40:28 Raising kids for a rapidly changing future 42:55 Questions young people should ask themselves 44:45 Outro and book recommendation

Ethan Kho

213,669 просмотров • 5 месяцев назад

DROPS E38: Vanta Trading - The Best Traders Won't Be Human Arrash is the founder and CEO of Vanta Trading, a decentralized prop trading platform built on Bittensor. He spent years as a quant trader building his own strategies before deciding the entire funded-account industry needed to be rebuilt from the ground up. We talk about: - Why most "funded accounts" trade on money that doesn't exist - Why your payout was never real - How prop firms intentionally change rules and spreads before you cash out - Why the best traders of the future won't be human And much more… Timestamps: 0:00 Introduction 1:48 Founder of Vanta 3:08 Explaining Vanta to an Uber Driver 3:26 Unfair vs Fair Funding 6:37 How do they make money? 8:33 How a Legit Prop Firm Makes Money 9:43 Founder's Journey Into Entrepreneurship 10:42 Discovering Crypto & Blockchain 13:03 From LinkedIn Engineer to Quant Trader 15:22 Trading Strategies 16:13 How Trading Is Changing? 18:39 Why TradFi Should Fear Hyperliquid 19:16 Building on BitTensor 21:43 Explaining BitTensor Simply 22:03 How BitTensor Creates Value 23:17 BitTensor's Structure 24:36 BitTensor as Crypto AI 25:35 Is the BitTensor Hype Justified? 27:09 Revenue & Profitability in BitTensor 29:17 Role of TAO 29:51 Advantages & Limitations of BitTensor ecosystem 31:56 What Is Vanta? 32:26 Why No One Fixed Prop Trading Before 33:12 Is the Entire Industry a Scam? 34:17 How Prop Firms Really Make Money 35:35 How Vanta Is Different 38:33 Copy Trading Explained 39:30 Vanta's Business Model 40:28 Dark Reality Behind Funded Accounts 43:48 Long-Term Vision for Vanta 44:50 What Happens If Too Many Traders Win? 46:25 Future Belongs to AI Traders 47:59 Vanta's Endgame 49:14 Conclusion

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37,896 просмотров • 1 месяц назад

Inside Goldman Sachs' natural gas trading desk with John Knorring John Knorring — former Managing Director & Head of Natural Gas Trading at Goldman Sachs. Traded through Katrina, Amaranth's collapse & the financial crisis. Now building electricity hedging markets in the emerging markets. "We priced Lehman's entire options book — 500,000 options, 17 million vega — in 30 minutes during the collapse. At Goldman, you had to know your position at all times or you got fired." We cover: - Trading in the actual pits vs today's algo-dominated markets — why electronic trading pushed him out - How shale dropped US nat gas from $16 to $1.50 & why Henry Hub futures unlocked the entire buildout - Absorbing Lehman's book during the crisis & managing massive dislocated positions - The information edge at Goldman vs pure price-taking at DRW — what you lose without client flow - Why discretionary trading can't be fully automated (gold hitting $4,000 wasn't in any model's history) - Building Green Tiger Markets — bringing forward curves to Philippine electricity (zero public pricing until 2 years ago) ~$2B notional in hedging orders processed, liquidity still early but growing - Manila vs New York business culture — "nobody wants to be first, everyone wants to be second" Timestamps: 00:00 Intro 01:35 Leading natural gas trading at Goldman Sachs 04:06 Trading hurricanes, Amaranth, and 2008 crisis volatility 04:48 How pit trading and voice execution worked 06:21 How Goldman risk systems handled massive positions 06:55 How electronic trading transformed energy markets 08:31 Did algorithmic trading kill discretionary edge? 09:59 Why coding became essential for commodity traders 11:10 What pit-era trading psychology felt like 12:34 How Dodd-Frank changed bank trading desks 14:19 Why John left Goldman for DRW prop trading 16:16 What discretionary traders actually did at DRW 19:14 How losing client flow changed information edges 21:20 What data powered discretionary energy strategies 24:19 Can discretionary trading ever be automated? 28:45 How traders detect paradigm shifts in commodities 30:21 John’s framework: ideas, execution, money management 34:30 John’s current trades in silver and gold 34:49 Why he built Green Tiger Markets in PH 36:30 How electricity forward hedging works in emerging markets 41:52 Growth outlook for Philippines electricity hedging 45:25 Are PH market participants sophisticated enough to hedge? 48:20 Cultural realities trading and doing business in Manila 51:20 How GTM differs from ICE and CME structures 59:20 Origin story: Carlos, technology, and building GTM 1:00:34 From Goldman trader to emerging-market exchange builder

Ethan Kho

70,455 просмотров • 5 месяцев назад

Ex-Global Trading & Risk Director at Cargill on how edge is formed in commodities markets Kristine Engman spent 20+ years at Cargill—one of America's largest agriculture conglomerates—trading billions in physical & financial commodities across energy & agriculture. "Edge in commodities? It's a lot about relationships. The intel you get through those relationships—that's information not readily accessible to the rest of the marketplace that can give you an edge." We cover: - How edge actually works in commodities—relationships, capital access & information arbitrage - Why you can trade on "insider information" in commodities (unlike equities) - Managing physical risk—forecast accuracy, weather shocks & transportation nightmares - The negative power trade—selling electricity below zero & getting hauled into the boss's office - Why Cargill traders performed best when equities markets performed worst - Quantitative (and even technical) vs fundamental trading styles—finding what works & sticking to it - The Ukraine war position—going extended limit long before the invasion - Life lessons from trading—"have your house in order" & taking risks with incomplete information Timestamps: 00:00 Intro 01:15 Edge in commodities trading? Relationships, capital, information 04:40 Commodities market efficiency, information flows, and AI 08:32 Hedge funds vs. ABCDs, commodity trading strategies 13:34 When commodities outperform equities, the 2022 boom 17:45 Headline risk, social media impact on markets 19:08 Risk management strategies in physical commodities trading 26:14 Probability, forecasting, and scenarios for trading decisions 31:00 What makes a great commodities trader today 37:53 Contrarian trading strategies, alpha generation in commodities 42:24 Russia–Ukraine war impact on commodity markets, trading 45:35 Life and career lessons from commodities trading 51:30 Careers, uncertainty, and learning in commodities markets

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82,254 просмотров • 5 месяцев назад

Inside the mind of an ex-SIG quant trader who can't turn off the EV brain - even for his kid's school choice Andrew Courtney (Andrew Courtney) ran the International ETFs Trading Desk at Susquehanna International Group for ~15 years before leaving in 2023. He now runs Kalshionomics (Kalshinomics), a prediction markets analytics tool, and writes the Whirligig Bear, one of the sharpest prediction markets Substacks out there. "I think of everything as a bet. I kind of don't understand how you talk to normal people — they do not do that." SIG trains their junior traders with poker, spending 2hrs/day turning over cards after every hand, justifying every decision quantitatively AND qualitatively. 15 years later, Andrew views prediction markets the same way: read who's on the other side, size accordingly, fold when the whale comes back at you 10x. We cover: - Why SIG pays junior traders to play poker for 2hrs/day — & what happens after every single hand - The "one eye on the market, always" attention tax that destroys most people's careers - How to find edge in prediction markets by asking: who am I actually trading against? - Why meme-heavy, overhyped markets (Taylor Swift at the Super Bowl) might be the juiciest trades - The insider trading debate in prediction markets — & why it's "socially corrosive" - Floor trading vs. upstairs quant: why the transition saved his career - 40 connections after ~15 years at one of the world's best firms — the hidden cost of prop trading - Why he doesn't have collision insurance on his car (& the EV math behind it) Thank you so much Andrew Courtney for coming on the pod! Timestamps: 00:00 Intro 05:00 Floor trading vs. electronic trading 06:28 What makes an upstairs trader 10:16 Poker as trader training 13:00 Thinking in bets as a mental framework 15:11 Decision trees in real life 16:40 Where prediction markets actually have edge 19:00 Why the LLM forecasting layer falls short 19:40 Liquidity incentives and trading low-volume markets 22:00 Limiting downside even when the model is wrong 24:32 Executing in illiquid markets 25:44 Fair value vs. directional conviction 27:11 Bayesian updating when liquidity responds 28:40 Fading hype and crowded narratives 31:07 Longshot bias vs. fanbase bias 34:20 How to judge whether you really have edge 36:40 Building analytics tools for prediction markets 38:20 The temporary edge for smart amateurs 40:35 Where prediction markets fit best 41:20 Markets that shouldn’t exist 43:20 Why insider trading corrodes incentives 46:52 Are prediction markets a net good or bad 50:47 Minimizing degeneracy and maximizing signal 53:32 A simple EV mindset anyone can use

Ethan Kho

436,074 просмотров • 5 месяцев назад

What It's Like Building a Proprietary Power Trading Firm with Cory Paddock Cory Paddock (Cory Paddock) has been trading the physical power grid since the early 2000s. He built his own firm from scratch in 2014 — trading his own capital — and has navigated every major paradigm shift in U.S. energy markets since coal dominated the grid. "It's the perfect amount of darkness. The information is public — but it's in the dark." We cover: - How Cory built a point of view on paradigm shifts before the market caught up - Why power trading sits at the intersection of economics & physics — and why that matters for edge - Why backtesting more than a few years of power data is basically useless — the grid isn't the same grid - LMP & locational marginal pricing: how physical grid constraints turn into alpha if you know where to look - The 5–10 trades that make your year — and why forcing setups in the lean periods kills you - How GBE stripped pay uncertainty out of trader comp so people can just focus on trading well - What it actually feels like watching your own money swing in real-time — and when it stops feeling that way Thanks so much Cory for coming on Odds on Open! Timestamps: 00:00 Intro 01:09 Starting GBE and finding trading edge 01:38 Overview of electricity markets and pricing 02:05 Power trading structure and deregulated markets 04:11 Research pipeline for market data analysis 04:56 Domain knowledge and renewable energy trading 06:39 LLMs and AI tools for quants 07:49 Grid data and intraday market signals 09:25 Finding alpha in electricity markets 10:13 Paradigm shifts and regime change insights 13:19 Coal to gas, wind, and solar trends 14:39 Data centers, EVs, and load growth 16:47 Recruiting talent in energy trading firms 17:38 Gen Z quants and algorithmic trading skills 21:55 Outliers, agency, and Gen Z traders 24:11 Culture and innovation in quant finance 27:29 Trading personal capital and risk management 28:06 PJM West Hub and market dynamics 32:19 Five-minute tick data and volatility 34:49 High-conviction trades and alpha generation 35:35 Incentive alignment and trader performance 36:42 Pay structure and removing stress capital 39:22 Motivation and purpose in trading careers 40:00 Passing knowledge to the next generation 42:04 Host reflections on electricity trading 42:14 Closing thoughts and sign-off

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17,408 просмотров • 5 месяцев назад

MUST-WATCH: Inside high-frequency trading & building the future of markets with Annanay Kapila Annanay Kapila (ak0) — former quant trader at Flow Traders & Tower Research, now founder of QFEX (YC-backed). Building the first 24/7 perpetual futures exchange for equities, commodities & FX — bringing crypto-level UX to traditional assets. "My friends at Cambridge have been making $5M+ a year for the last few years. They don't have to work anymore. But no one retires early. Why? Everyone who gets selected has that desire to win that transcends money, even rationality." We cover: - What it's really like inside elite HFT shops — international math Olympiad winners, professional poker players & zero room for error - Why the smartest traders keep working after making generational wealth (hint: it's pure competitive ego) - The two schools of quant trading: Chicago pit traders vs MIT mathematicians — and which strategies they dominate - How his team navigated the FTX collapse in real-time (including friends who escaped via Dogecoin withdrawals) - Building QFEX : 24/7 perpetual futures on equities with crypto-level UX — "We're building FTX without the fraud" - YC insider stories: meeting Sam Altman & Paul Graham, raising from Paul Graham (Paul Graham) personally, why the $125k for 7% is worth it - Culture secrets from Citadel & Tower: when your dev environment pages you at 2am on Saturday - The one interview hack VCs use that most founders miss (interrupt their CV walkthrough relentlessly) - Why doomerism is dead wrong: "My life would've been worse if I was born 10 years ago. I dread to think how much better it would be if I was born 10 years from now" Huge thanks to ak0 for the transparency. Follow his journey building the future of financial markets. 01:12 Inside high frequency trading culture and competition 03:00 What drives top performers in HFT 03:47 Why elite traders never retire early 04:50 How Tower structures quant trading work 06:14 Chicago versus MIT quant trading styles 10:29 How modern market making actually works 12:25 Why prop firms struggle to scale capital 16:36 Annanay's work at Tower and Flow 19:15 Tower's crypto trading and API edge 19:24 How firms handled the FTX collapse 23:42 Inside FTX culture and HK crypto scene 27:11 What QFEX is building for traders 29:37 QFEX beta launch and early rollout 29:56 Why building an exchange is exciting 32:48 QFEX execution edge and team DNA 36:24 Why quants leave HFT for startups 38:22 QFEX culture versus HFT culture 41:46 How meritocracy works inside QFEX 47:52 How QFEX hires true A players 53:05 Backchanneling and evaluating candidates 53:27 What YC actually teaches founders 55:21 Lessons from meeting Paul Graham and Sam Altman 58:41 Why startups fail and how to pivot 1:00:48 Why young people should stay optimistic 1:11:22 Closing remarks and QFEX vision

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162,520 просмотров • 5 месяцев назад

🎙 The Sujal Show Ep. 11: Arthur Hayes “Why I’m Betting Big on Hyperliquid (Over Bitcoin)” The man behind BitMEX, Arthur Hayes, reveals why 90% of traders lose money, says decentralization is “mostly marketing,” why he’s all-in on Hyperliquid & Zcash, 3 altcoins, & gives his 2028 election thesis and how it will affect Bitcoin. We Discussed on The Sujal Show: - The 2017 moment BitMEX started printing real money - Why insider trading should be legal - Why 90% of traders lose money (90/10 rule of trading) - How to build wealth in crypto - His $150 price target for Hyperliquid by end of August - Why Hyperliquid could become the largest exchange in the world - His take on Gracy Chen's "Hyperliquid is centralized" claim - Narrative that will make stupid money - His portfolio revealed - The timeline for Bitcoin to hit $500k (gave a specific year) - Why Ethereum is still the best L1 - Zcash to $2,000–$3,000? & 10% Of Bitcoin His privacy thesis - 3 coins to outperform Bitcoin TIMESTAMPS 00:00 Intro 02:08 How to Get Rich in Crypto Without Gambling 03:30 Why 90% of Traders Lose Money 05:32 Will AI Replace 99% of Traders? 06:23 How Salaried People Should Build Wealth in Crypto 07:25 Arthur Hayes’ Current Portfolio 07:35 Is Ethereum Still a Long-Term Bet? 08:19 Zcash to $2,000–$3,000? 09:09 Can Quantum Computing Threaten Bitcoin & Zcash? 09:42 Hyperliquid Price Prediction 10:14 How Big Can Hyperliquid Become? 11:05 Is Hyperliquid Really Decentralized? 13:11 Is Bitcoin Truly Decentralized? 13:50 Has Bitcoin Bottomed Already? 14:47 Bitcoin Future Prediction 16:34 Should Insider Trading Be Legal? 17:37 Would Legal Insider Trading Make Markets More Manipulative? 19:25 The Sujal Show Prediction Round 23:59 Is Trump Good or Bad for Crypto? 25:22 Advice for the Younger Generation From Citibank fired to crypto billionaire. His trading psychology will good for to recover loss Watch now 👇

Sujal Jethwani

105,622 просмотров • 2 месяцев назад

Leaving Citadel & launching a $1B AI hedge fund — how Renee Yao built NeoIvy Capital from scratch Renee Yao walked away from two of the most elite hedge funds on Wall Street — Citadel & Millennium — and built a quant fund on a fundamentally different model: modern AI instead of human-powered alpha generation. The result: $1B+ in regulatory AUM, uncorrelated returns through COVID, & a fund Business Insider named one of the top transforming investing in North America. We cover: - Why large multi-manager quant firms rely on massive global researcher headcounts — & why Renee saw that as a model worth disrupting - The 3 barriers to entry in AI-driven quant — & why legacy sequential infrastructure can be a disadvantage compared to modern parallel distributed systems - How NeoIvy's self-evolving models adapted in real time during the March 2020 crash — while traditional quant managers had a nightmare month - The difference between beta returns, factor returns & pure alpha — & why size is the enemy of true idiosyncratic returns - Why the "black box" reputation of quant funds has been the #1 fundraising obstacle - How a 4-year-old girl visiting her uncle's room-sized supercomputer in China set the foundation for all of this - The edge/breadth/constraint framework from Grinold & Kahn — & how it shaped Renee's thinking on diversification - Renee's raw advice on staying disciplined when everyone around you is chasing beta in a bull market Transcript: 00:00 Intro 01:14 Renee Yao’s journey to founding Neo Ivy 02:28 Joining Citadel after the financial crisis 04:13 Hedge fund diversification and breadth of edge 04:45 Why Neo Ivy trades with AI strategies 07:50 How self-learning AI adapts to markets 09:40 Causation vs correlation in AI hedge funds 10:33 Barriers to entry for AI hedge funds 14:47 Risks of crowded factor bets explained 16:39 Why big funds struggle with AI talent 17:29 From PM at Citadel to hedge fund founder 18:47 Challenges of launching a quant hedge fund 20:25 Biggest constraint for AI hedge fund startups 22:08 How AI hedge funds adapted during COVID 24:04 Modern AI tools used in quant trading 25:13 Building hedge fund infrastructure from scratch 26:26 Career advice for aspiring quants and traders 28:55 Adapting career goals to changing job markets 31:57 Life lessons from trading and risk management 32:51 Staying disciplined while running a hedge fund 34:38 Obsession and belief in AI hedge funds 35:41 Closing thoughts on hedge funds and life

Ethan Kho

138,224 просмотров • 5 месяцев назад

MUST-WATCH: Macro Hedge Fund Founder Alfonso Peccatiello Reveals his Edge in Macro Trading Alfonso Pecatiello (former large global bank PM, founder of The Macro Compass & Palinuro Capital) breaks down how to create durable edge in macro investing and why concentration is the death of many fund managers. "You can hear from Druckenmiller and Soros about concentration — but you won't hear from the thousands of managers who went bankrupt trying the same approach." We cover: - Why bank reserves (QE "liquidity") have NO direct pipe to the S&P 500 - The real money creators: commercial banks & government deficits — not the Fed - Why the second derivative of money creation drives nominal growth & asset prices - How to run 40-50 ideas/year & arrive at 10-12 truly independent bets - The "Trump error term": modeling exogenous volatility injections - The handbrake rule: when models fail, cut risk (the math of negative compounding destroys you) - Launching Palinuro with zero GP stakes & why 80% of funds fail in year 1-5 Thanks to Alf (Alf) for pulling back the curtain on finding edge in macro trading and the unglamorous reality of fund building. Highlights: 00:00 Understanding Money Creation and Strict Process as a Macro Edge 04:21 Commercial Banks and Government Deficits Drive Real Money Creation 12:52 Why Diversification and Risk Parity Beat Concentrated Bets 19:30 Using the "Handbrake" to Cut Risk During Black Swan Events 27:47 Why Factor Neutral Mandates Don't Make Sense for Macro Investors 32:22 The Underestimated Challenges of Building a Macro Hedge Fund 43:20 Passion, Delegation, and the Grinder Mentality for Fund Founders 52:13 The High Probability of Failure and Necessary Financial Runway 56:58 Building an Empathetic Team Through Intentional Hiring Frameworks 1:02:11 Why Communication Skills Are Crucial for Success in Finance

Ethan Kho

77,233 просмотров • 4 месяцев назад

I sat down with Nicolas Sharp, founder of Attio, to talk in depth about how his company is disrupting the $80 billion CRM market. Attio has raised $116m, is 4x'ing ARR and is one of the fastest growing companies in Europe. We talk about: - Why Attio went against all conventional wisdom and spent years 3 years building the product before launching - Why Attio doesn’t hire ‘Software Engineers’ and who they hire instead. - How Attio chose investors who would back a long-term bet against multi-billion $ incumbents - How Attio is building CRM from first principles for the AI era - Who should you avoid hiring at all costs, and who should you hire for your startup And so much more. If you’re interested in learning about the story of how Nick built Attio into the incredible company it is today and is disrupting one of the most important software categories, you’re going to want to see this. Enjoy // Timestamps 00:00 Intro 00:39 Why Attio spent 3 years building their product before launch 5:05 The Power of Building Systems, Not a Box of Features 9:05 How to know when it’s time to launch 13:30 Nick’s Playbook For a Killer Product Launch 18:09 How To Go From an Investor to a Founder 23:05 How Failure Led to Attio's Big Break 28:07 Why startups need to hire "Hidden Gems," 34:05 Fundraising 49:36 Why Attio Invests In Inexperienced Talent 55:07 The Case For Not Hiring Software Engineers (& Who You Should Hire Instead) 1:02:46 The 8 Persona Hiring Framework 1:09:05 How Attio doesn’t use OKR's 1:27:11 Where does Nick's Ambition and Grit come from? 1:36:59 How Attio is Building CRM from First Principles for the AI era 1:45:29 How to Successfully Market In A Crowded Industry 1:51:10 Breaking Down Attio’s Viral Marketing Strategies 2:02:15 The Change That Had The Biggest Impact on Customer Conversion 2:05:04 Why Attio created A “Reverse Trial” 2:10:16 Why Nick is building from London, not Silicon Valley 2:22:48 The 10-Year Vision for Attio

Wouter Teunissen

26,369 просмотров • 9 месяцев назад

Inside Two Sigma & AQR with Bill Mann: How Early Quants Built Edge Before the Modern Tools Existed Bill Mann spent nearly 11 years across two of the world's most elite quant funds — AQR & Two Sigma — rising to Senior Vice President while building alpha models, establishing quantamental research teams, & designing the ML/AI systems that powered their forecasts. "A real edge you used to have 15 years ago was creating your own version of someone else's data." We cover: - How Two Sigma's fundamentals team built proprietary data pipelines before vendors existed - Why point-in-time databases were a secret weapon — & how look-ahead bias destroyed competitors - The crowding problem hiding inside everyone's favorite value factor - LLMs in quant research: what agents can already replace & what still requires human intuition - Why junior quants are at risk — & the one mindset that keeps senior researchers irreplaceable - How HarmoniQ Insights pivoted from advising buy-side firms to backing fintech startups with sweat equity - The New Barbarians thesis: crypto natives meeting old Wall Street, & why both sides need each other - Bill's one piece of advice for aspiring quants: build your own model, put real money behind it, learn from the losses Timestamps: 00:00 Intro 00:57 Life as a Quant at Two Sigma 02:36 Finding Edge in Fundamental Data 07:04 Creating a Creative Quant Research Culture 11:19 How LLMs Change Quantitative Trading 15:52 AI’s Impact on Junior Quant Careers 22:56 Using AI Tools for Learning 23:57 HarmoniQ Insights: Advising Fintech Startups 30:47 The New Barbarians Podcast Explained 33:26 Crypto and Market Makers vs TradFi 34:54 Career Advice for Aspiring Quants 38:46 Final Takeaways

Ethan Kho

23,460 просмотров • 5 месяцев назад