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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...

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Ethan Kho

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17,408 просмотров • 6 месяцев назад •via X (Twitter)

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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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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

Ethan Kho

82,254 просмотров • 6 месяцев назад

New episode with rbit A conversation with someone who has seen almost every era of crypto market structure firsthand. We talk through the shift from early inefficiencies and manual trading to stat arb, HFT, execution, and competing in a much harder market. 00:00 Getting into Bitcoin in 2010, mining, Mt. Gox, and coming back in 2017 13:37 ICO mania, BitMEX, and the Bitcoin fork trade 17:14 Why 2018 pushed him toward quant trading 24:52 Building a profitable stat arb business on FTX 40:21 Stat arb vs HFT, and why crypto got more competitive 49:09 What his trading operation looks like today 55:13 The future of crypto market structure and where edge is going 01:05:04 Advice for newer traders and why quant thinking differs from retail
1:06:30

New episode with rbit A conversation with someone who has seen almost every era of crypto market structure firsthand. We talk through the shift from early inefficiencies and manual trading to stat arb, HFT, execution, and competing in a much harder market. 00:00 Getting into Bitcoin in 2010, mining, Mt. Gox, and coming back in 2017 13:37 ICO mania, BitMEX, and the Bitcoin fork trade 17:14 Why 2018 pushed him toward quant trading 24:52 Building a profitable stat arb business on FTX 40:21 Stat arb vs HFT, and why crypto got more competitive 49:09 What his trading operation looks like today 55:13 The future of crypto market structure and where edge is going 01:05:04 Advice for newer traders and why quant thinking differs from retail

Insilico Terminal

48,691 просмотров • 4 месяцев 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
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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

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70,455 просмотров • 6 месяцев назад

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44:46

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

214,514 просмотров • 6 месяцев назад

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59:58

“Quant trading is simpler than people think.” Goon joins the Insilico Terminal Podcast to talk about finding crypto edges, market making, and why the best trades often come from clicking around broken markets before anyone else notices. We covered TradFi, early DeFi rugs, solo trading, perp DEXs, Hyperliquid, prediction markets, bad bots, points farming, and the on-chain casino arb that turned into PvP. 00:00 Intro + CryptoGoon’s background 04:31 Getting rugged and discovering early DeFi 07:08 Why TradFi-style edges worked in 2021 crypto 11:03 Solo trading vs trading inside a firm 15:25 The on-chain casino arb that became PvP 24:13 Finding edge early on new perp DEXs 31:10 Why quant trading is simpler than people think 38:39 Why points farming can reveal real edge 53:01 Crypto morale, HYPE, and where the market is now

Insilico Terminal

19,138 просмотров • 2 месяцев назад

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 was an abnormal amount of edge in the market. They came from gambling—sports betting, poker—where edge was tiny. A bookie makes 5% margins. But trading a $2.5 call spread for $2.20 when it's worth $2.50? That's a ridiculous amount of edge compared to gambling, with the same risk distribution." We cover: - Why SIG was called "the evil empire" & how they crushed competitors by trading massive size for tighter spreads - The exact structure of prop shop deals: 50/50 splits, escrow accounts, how you get to 60% then 70% payouts - Why markets look efficient from most vantage points & how trading is ultimately about labor—getting your vantage point close enough that it stops looking random - The tyranny of beta: why the best operator in a melting ice cube business will lose to a mediocre performer in a great market - How to escape the "striver" trap & tune out status optimization (hint: find what you got obsessed with before college applications mattered) - Teaching his 12-year-old options market making & involving his 9-year-old in building a trading card game—scattered cards on the bedroom floor that'll become a finished product Thanks to Kris for the masterclass. Highlights: 02:05 How Kris first recognized real trading edge 04:01 How early market structure created easy edge 05:27 Why improvement in trading comes from hindsight 07:08 The core SIG frameworks that shaped his edge 09:37 Why uncovering edge requires labor and precision 11:02 How informed order flow forces trader humility 12:53 What truly differentiated SIG from competitors 13:23 How SIG built a world-class education pipeline 16:30 How SIG captured edge by refusing to hedge 18:11 How centralized risk controlled exposure and variance 19:09 How SIG used size and spreads to dominate markets 23:20 What Kris learned working with Jason McCarthy 25:40 Why elite traders share extreme competitiveness 26:06 How top performers operate across domains and PM roles 28:22 How Kris transitioned from SIG to prop trading 31:56 What shifting into senior roles taught him about trading 33:46 How Kris built training and feedback systems for traders 35:00 How the backer model works inside prop shops 38:41 How escrow capital protects traders from tail events 41:03 How natural gas options trading changed with regime shifts 42:13 How Kris applies trading edge concepts to life decisions 45:46 Why personal alignment beats chasing status in trading 47:13 How status games distort decision-making for young traders 52:23 Why striver behavior is actually risk management 56:27 How Kris teaches opportunity cost through parenting 1:01:28 How exposing kids to decisions builds intuition 1:04:46 How Kris teaches EV using homemade trading games 1:08:05 How iteration and feedback loops shape real learning
1:09:23

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 was an abnormal amount of edge in the market. They came from gambling—sports betting, poker—where edge was tiny. A bookie makes 5% margins. But trading a $2.5 call spread for $2.20 when it's worth $2.50? That's a ridiculous amount of edge compared to gambling, with the same risk distribution." We cover: - Why SIG was called "the evil empire" & how they crushed competitors by trading massive size for tighter spreads - The exact structure of prop shop deals: 50/50 splits, escrow accounts, how you get to 60% then 70% payouts - Why markets look efficient from most vantage points & how trading is ultimately about labor—getting your vantage point close enough that it stops looking random - The tyranny of beta: why the best operator in a melting ice cube business will lose to a mediocre performer in a great market - How to escape the "striver" trap & tune out status optimization (hint: find what you got obsessed with before college applications mattered) - Teaching his 12-year-old options market making & involving his 9-year-old in building a trading card game—scattered cards on the bedroom floor that'll become a finished product Thanks to Kris for the masterclass. Highlights: 02:05 How Kris first recognized real trading edge 04:01 How early market structure created easy edge 05:27 Why improvement in trading comes from hindsight 07:08 The core SIG frameworks that shaped his edge 09:37 Why uncovering edge requires labor and precision 11:02 How informed order flow forces trader humility 12:53 What truly differentiated SIG from competitors 13:23 How SIG built a world-class education pipeline 16:30 How SIG captured edge by refusing to hedge 18:11 How centralized risk controlled exposure and variance 19:09 How SIG used size and spreads to dominate markets 23:20 What Kris learned working with Jason McCarthy 25:40 Why elite traders share extreme competitiveness 26:06 How top performers operate across domains and PM roles 28:22 How Kris transitioned from SIG to prop trading 31:56 What shifting into senior roles taught him about trading 33:46 How Kris built training and feedback systems for traders 35:00 How the backer model works inside prop shops 38:41 How escrow capital protects traders from tail events 41:03 How natural gas options trading changed with regime shifts 42:13 How Kris applies trading edge concepts to life decisions 45:46 Why personal alignment beats chasing status in trading 47:13 How status games distort decision-making for young traders 52:23 Why striver behavior is actually risk management 56:27 How Kris teaches opportunity cost through parenting 1:01:28 How exposing kids to decisions builds intuition 1:04:46 How Kris teaches EV using homemade trading games 1:08:05 How iteration and feedback loops shape real learning

Ethan Kho

233,306 просмотров • 6 месяцев назад

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead
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My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead

Raoul Pal

172,640 просмотров • 1 год назад

Full interview with the founder and CEO of Propr Lou sits down with me to discuss Hyperliquid and the future of prop trading Timestamps: 00:00:00 Intro 00:00:16 Meet Louis: from TradFi to crypto 00:01:52 How the crypto market has changed 00:03:49 Why build on Hyperliquid 00:06:52 How propr got started 00:08:40 Scaling a lean team (and the grind) 00:12:24 What a prop firm actually is 00:15:33 Agents, bots, and the future of trading 00:18:32 What Louis is most proud of 00:21:02 Thinking about the token and TGE 00:24:14 Where propr goes in 5 years 00:25:57 Best and worst trades 00:27:50 Life outside crypto + shoutouts
29:41

Full interview with the founder and CEO of Propr Lou sits down with me to discuss Hyperliquid and the future of prop trading Timestamps: 00:00:00 Intro 00:00:16 Meet Louis: from TradFi to crypto 00:01:52 How the crypto market has changed 00:03:49 Why build on Hyperliquid 00:06:52 How propr got started 00:08:40 Scaling a lean team (and the grind) 00:12:24 What a prop firm actually is 00:15:33 Agents, bots, and the future of trading 00:18:32 What Louis is most proud of 00:21:02 Thinking about the token and TGE 00:24:14 Where propr goes in 5 years 00:25:57 Best and worst trades 00:27:50 Life outside crypto + shoutouts

ryandcrypto

42,836 просмотров • 2 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
50:55

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

MR SHIFT 🦁

37,896 просмотров • 2 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
56:48

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 • 6 месяцев назад

How I Made Crazy Profits with DLMM: LP Army Member jAIsus Shares His Strategies This podcast is packed with pure alpha right until the end get amongst it ⏰Timestamps⏰ 00:00 Introduction and Guest Welcome 00:44 BBJ's Background and Entry into Crypto 02:30 Full-Time Crypto Journey 03:01 Meteor Community and Profitability 03:47 DLMM Tools and Strategies 12:22 Impact of Meteor on Solana and Crypto 14:02 Daily Routine and Strategies 22:10 Personal Trading Strategies 23:09 In and Out Strategy Explained 23:58 Navigating Market Manipulation 24:46 Using Fibonacci in Trading 26:35 Avoiding Big Losses 29:09 Balancing Life and Trading 32:27 Current Market Sentiment 37:22 Advice for New Traders 40:02 Valuable Life Lessons 41:06 Closing Remarks The LP Army & Meteora are the community to join to level up your speed
41:38

How I Made Crazy Profits with DLMM: LP Army Member jAIsus Shares His Strategies This podcast is packed with pure alpha right until the end get amongst it ⏰Timestamps⏰ 00:00 Introduction and Guest Welcome 00:44 BBJ's Background and Entry into Crypto 02:30 Full-Time Crypto Journey 03:01 Meteor Community and Profitability 03:47 DLMM Tools and Strategies 12:22 Impact of Meteor on Solana and Crypto 14:02 Daily Routine and Strategies 22:10 Personal Trading Strategies 23:09 In and Out Strategy Explained 23:58 Navigating Market Manipulation 24:46 Using Fibonacci in Trading 26:35 Avoiding Big Losses 29:09 Balancing Life and Trading 32:27 Current Market Sentiment 37:22 Advice for New Traders 40:02 Valuable Life Lessons 41:06 Closing Remarks The LP Army & Meteora are the community to join to level up your speed

Seb Monty

14,089 просмотров • 1 год назад

🚨 This Is The Only Video You Need To Watch To Prepare For This Bull Market. Live Breakdowns, Sector Insights, Alpha on Hidden Gems and How To Find 100x Altcoins In Real Time. 0:01 - Introduction 2:50 - The Evolution of the Internet 6:10 - The Role of Bitcoin and Ethereum 9:02 - Decentralized Finance and NFTs 11:58 - Stablecoins and Institutional Adoption 14:50 - AI and Crypto 18:11 - The future of crypto 22:25 - Bitcoin's predictions & Market Dynamics 23:52 - The Role of AI in Crypto Trading 29:13 - Investment Framework for Crypto Investors 31:07 - Finding Promising Crypto Projects 33:04 - Emerging Technologies in Web3 and AI 35:32 - Real World Assets and Decentralized Finance 36:59 - Finding Alpha with Token Metrics 42:43 - Conclusion
45:41

🚨 This Is The Only Video You Need To Watch To Prepare For This Bull Market. Live Breakdowns, Sector Insights, Alpha on Hidden Gems and How To Find 100x Altcoins In Real Time. 0:01 - Introduction 2:50 - The Evolution of the Internet 6:10 - The Role of Bitcoin and Ethereum 9:02 - Decentralized Finance and NFTs 11:58 - Stablecoins and Institutional Adoption 14:50 - AI and Crypto 18:11 - The future of crypto 22:25 - Bitcoin's predictions & Market Dynamics 23:52 - The Role of AI in Crypto Trading 29:13 - Investment Framework for Crypto Investors 31:07 - Finding Promising Crypto Projects 33:04 - Emerging Technologies in Web3 and AI 35:32 - Real World Assets and Decentralized Finance 36:59 - Finding Alpha with Token Metrics 42:43 - Conclusion

Token Metrics

21,891 просмотров • 1 год назад

Ex-Citadel Quant Researcher on Trading Power & Gas — One of the Most Asymmetric Markets in the World Neel Somani (Neel Somani) — ex-Citadel commodities QR. Built the models the discretionary traders used to price power. "It's table stakes to put down seven figures of collateral in order to seriously trade power." We cover: - What a commodities QR actually does — building models traders use, sitting in PM meetings & how "slope" (your real cut of P&L) works - Where power edge comes from: congestion — the physics of a wire that heats up, droops, and can't carry more - How a hub trade gets built from the ground up: weather → demand → which units switch on → your price vs. the market's - Why blindly going long power is a structurally losing trade — skew assets always price above expected value - The anatomy of a blow-up: doubling down into the Feb 2021 Texas freeze as the price ran to $9,000/MWh - Why hedge funds trade power & gas but mostly steer clear of oil — geopolitics & risk you can't model - "Binding constraints" — the pricing model he carried off the grid and into startups, AI & supply chains - Why the guys who take risk for a living buy index funds with their own money Highlights: (00:00) Intro (01:12) Quant researcher execution models within multi-manager hedge funds (07:35) How transmission line congestion drives alpha in power markets (13:24) Capital intensity and managing risk profiles of high-skew assets (19:19) Why commodity desks prefer domestic power over geopolitical oil risk (22:55) Portfolio construction and risk mitigation during tail-risk freeze events (31:36) Capitalizing on the physical infrastructure constraints of AI data centers (36:25) How agentic architecture redefines software engineering and technical moats (43:04) Quant career opportunity cost relative to the AI paradigm shift (56:15) Variant views on venture multiples and agentic customer acquisition economics
1:00:13

Ex-Citadel Quant Researcher on Trading Power & Gas — One of the Most Asymmetric Markets in the World Neel Somani (Neel Somani) — ex-Citadel commodities QR. Built the models the discretionary traders used to price power. "It's table stakes to put down seven figures of collateral in order to seriously trade power." We cover: - What a commodities QR actually does — building models traders use, sitting in PM meetings & how "slope" (your real cut of P&L) works - Where power edge comes from: congestion — the physics of a wire that heats up, droops, and can't carry more - How a hub trade gets built from the ground up: weather → demand → which units switch on → your price vs. the market's - Why blindly going long power is a structurally losing trade — skew assets always price above expected value - The anatomy of a blow-up: doubling down into the Feb 2021 Texas freeze as the price ran to $9,000/MWh - Why hedge funds trade power & gas but mostly steer clear of oil — geopolitics & risk you can't model - "Binding constraints" — the pricing model he carried off the grid and into startups, AI & supply chains - Why the guys who take risk for a living buy index funds with their own money Highlights: (00:00) Intro (01:12) Quant researcher execution models within multi-manager hedge funds (07:35) How transmission line congestion drives alpha in power markets (13:24) Capital intensity and managing risk profiles of high-skew assets (19:19) Why commodity desks prefer domestic power over geopolitical oil risk (22:55) Portfolio construction and risk mitigation during tail-risk freeze events (31:36) Capitalizing on the physical infrastructure constraints of AI data centers (36:25) How agentic architecture redefines software engineering and technical moats (43:04) Quant career opportunity cost relative to the AI paradigm shift (56:15) Variant views on venture multiples and agentic customer acquisition economics

Ethan Kho

116,875 просмотров • 2 месяцев назад

Your ICT Strategy Is Incomplete Without This | Casper SMC In this weeks Order Book episode I sit down with Casper SMC to break down how he combines ICT concepts with orderflow to sharpen his entries and reads. We get into why ICT alone leaves gaps, how orderflow fills them, and the exact way Casper layers the two on live charts. If you've been trading SMC/ICT and feel like something's missing, this conversation is for you. Timestamps: 00:00 - Intro with Casper SMC 2:09 - Caspers Backstory (Legal trouble, found trading, hardship to success) 6:55 - Managing Risk, The Perception Of Money, Dissociative Trading 10:09 - The Evolution of Caspers Trading Strategy and View On Markets 16:10 - Taking Advantage of All Available Market Information 19:09 - Casper Explains How Heatmaps Work 26:12 - Casper Explains Volume Profiles 31:55 - Putting Together The Flow and Direction Data To Form A Trade 35:22 - Thinking Like An Institution (and Using Their Tools) 37:55 - The Book That Changed Caspers Life and How Your Mindset Shapes Your Reality 46:24 - Maynes Polymarket Picks (World Cup, SpaceX IPO, Crude Oil, Gold)
57:08

Your ICT Strategy Is Incomplete Without This | Casper SMC In this weeks Order Book episode I sit down with Casper SMC to break down how he combines ICT concepts with orderflow to sharpen his entries and reads. We get into why ICT alone leaves gaps, how orderflow fills them, and the exact way Casper layers the two on live charts. If you've been trading SMC/ICT and feel like something's missing, this conversation is for you. Timestamps: 00:00 - Intro with Casper SMC 2:09 - Caspers Backstory (Legal trouble, found trading, hardship to success) 6:55 - Managing Risk, The Perception Of Money, Dissociative Trading 10:09 - The Evolution of Caspers Trading Strategy and View On Markets 16:10 - Taking Advantage of All Available Market Information 19:09 - Casper Explains How Heatmaps Work 26:12 - Casper Explains Volume Profiles 31:55 - Putting Together The Flow and Direction Data To Form A Trade 35:22 - Thinking Like An Institution (and Using Their Tools) 37:55 - The Book That Changed Caspers Life and How Your Mindset Shapes Your Reality 46:24 - Maynes Polymarket Picks (World Cup, SpaceX IPO, Crude Oil, Gold)

Mayne

26,582 просмотров • 3 месяцев назад

INSIDE JUPITER: TRADING THE NEWS WITH PREDICTION MARKETS This episode with Julian breaks down why prediction markets are becoming a core primitive of Web4, how the Polymarket partnership fits the Jupiter full-stack vision, and why the future isn’t a separate product it’s prediction embedded everywhere. time stamps : 00:00 Intro Inside Jupiter HQ 00:18 Who's Julian and what's his role 00:44 What JuPredict actually is: “trading the news” 01:11 Polymarket × Jupiter 02:01 Why prediction markets are emerging 03:00 Markets vs commentators 04:24 Local & social prediction markets 05:15 On-chain transparency & global accessibility 06:27 Prediction markets in the Jupiter Web4 stack 07:48 The vision: predicting from any interface 09:28 Why people misread market prices 10:20 The real edge: studying trade flow before events 11:05 What prediction markets are best at predicting 11:40 Consistency & accuracy of the markets 12:10 Message to the community
13:01

INSIDE JUPITER: TRADING THE NEWS WITH PREDICTION MARKETS This episode with Julian breaks down why prediction markets are becoming a core primitive of Web4, how the Polymarket partnership fits the Jupiter full-stack vision, and why the future isn’t a separate product it’s prediction embedded everywhere. time stamps : 00:00 Intro Inside Jupiter HQ 00:18 Who's Julian and what's his role 00:44 What JuPredict actually is: “trading the news” 01:11 Polymarket × Jupiter 02:01 Why prediction markets are emerging 03:00 Markets vs commentators 04:24 Local & social prediction markets 05:15 On-chain transparency & global accessibility 06:27 Prediction markets in the Jupiter Web4 stack 07:48 The vision: predicting from any interface 09:28 Why people misread market prices 10:20 The real edge: studying trade flow before events 11:05 What prediction markets are best at predicting 11:40 Consistency & accuracy of the markets 12:10 Message to the community

JUP AND JUICE (🧃)

20,990 просмотров • 6 месяцев назад

5 free GitHub bots for trading on Polymarket… 5 different strategies for 5 different trading situations. Each of these tools comes with a detailed step by step setup and usage guide in English: 1. This bot can automatically manage your limit orders to maximize liquidity rewards (useful for liquidity providers on Polymarket). GitHub: 2. The bot, which analyzes the real behavior of any Polymarket trader, finds repeated patterns in his trades, explains which strategies he uses and how you can actually adapt them to your own trading. GitHub: 3. A bot with 118+ ready to use strategies and tools for prediction markets, including Smart Money, Binance-Polymarket latency, Mean Reversion and more… The most interesting one is Polymarket - Kalshi Cross Arbitrage - it finds differences in prices between platforms and can manage trades automatically. GitHub: 4. A Chinese weather bot that analyzes multiple sources in real time, like forecasts, public airport data and aviation observations (METAR + SPECI) and then generates a detailed weather report for a specific city and day. GitHub: 5. This is a bot-toolkit that includes copy trading, arbitrage, market making, spread farming, whale alerts, sports trading and more… GitHub: Almost every tool here has a DRY RUN mode, so you can test them on real markets, but with fake funds.
0:23

5 free GitHub bots for trading on Polymarket… 5 different strategies for 5 different trading situations. Each of these tools comes with a detailed step by step setup and usage guide in English: 1. This bot can automatically manage your limit orders to maximize liquidity rewards (useful for liquidity providers on Polymarket). GitHub: 2. The bot, which analyzes the real behavior of any Polymarket trader, finds repeated patterns in his trades, explains which strategies he uses and how you can actually adapt them to your own trading. GitHub: 3. A bot with 118+ ready to use strategies and tools for prediction markets, including Smart Money, Binance-Polymarket latency, Mean Reversion and more… The most interesting one is Polymarket - Kalshi Cross Arbitrage - it finds differences in prices between platforms and can manage trades automatically. GitHub: 4. A Chinese weather bot that analyzes multiple sources in real time, like forecasts, public airport data and aviation observations (METAR + SPECI) and then generates a detailed weather report for a specific city and day. GitHub: 5. This is a bot-toolkit that includes copy trading, arbitrage, market making, spread farming, whale alerts, sports trading and more… GitHub: Almost every tool here has a DRY RUN mode, so you can test them on real markets, but with fake funds.

Recogard

14,162 просмотров • 3 месяцев назад

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
55:13

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 • 5 месяцев назад