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Ex-Equity Crypto Trader Reveals His Systematic Trading Mindset To Conquer the Market w/ pedma 00:00 Pedma intro: Viewing trading as a business rather than predicting market cycles 01:32 Rejecting the 4-year cycle theory to focus on structural risk premia 02:24 Starting in 2017 trading US equities penny stocks pumping...

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14,131 просмотров • 1 месяц назад •via X (Twitter)

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Raoul Pal

534,295 просмотров • 1 год назад

Why do most traders close their profits too early? Answered 167 questions from subscribers in one sitting. Psychology, risk management, finding a system that actually works, stop losses, handling emotions on size, where the market goes from here, and what AI is doing to all of it. If you've ever wanted to ask a professional trader with 9 years in the market something specific, the answer is probably in here. Submit your question for part two: TIMECODES 00:00 Teaser 00:39 Welcome 02:15 Handling losses and fear without closing early 03:09 How to stop cutting winners short 04:32 My current BTC and ETH positions 06:28 Controlling emotions on large positions 08:00 The turning point in a trader's career 10:46 When you want to quit trading 12:17 Where a beginner should actually start 13:06 Finding your own profitable system 13:27 Best book on trading psychology 15:09 Entry points and trading breakouts 17:05 Elliott waves and Fibonacci in practice 18:19 Calculating position size properly 20:39 When altseason and meme season arrive 23:39 Thoughts on LAB, ASTER, PUMP, NEAR, SOL, XRP 23:52 AI agents and vibecoding in trading 24:00 How the weather bot works on Polymarket 25:12 The free trading bot 25:29 Is prop trading worth it in 2026 25:35 Will I go back to copy trading 25:52 Public $1,000 to $10,000 marathon? 26:25 Personal questions 26:39 Banks, payment systems and crypto cards I use 27:19 Best countries in East Asia to live in 29:24 Software I use every day 30:39 The private traders club Enjoy! 🤝
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Why do most traders close their profits too early? Answered 167 questions from subscribers in one sitting. Psychology, risk management, finding a system that actually works, stop losses, handling emotions on size, where the market goes from here, and what AI is doing to all of it. If you've ever wanted to ask a professional trader with 9 years in the market something specific, the answer is probably in here. Submit your question for part two: TIMECODES 00:00 Teaser 00:39 Welcome 02:15 Handling losses and fear without closing early 03:09 How to stop cutting winners short 04:32 My current BTC and ETH positions 06:28 Controlling emotions on large positions 08:00 The turning point in a trader's career 10:46 When you want to quit trading 12:17 Where a beginner should actually start 13:06 Finding your own profitable system 13:27 Best book on trading psychology 15:09 Entry points and trading breakouts 17:05 Elliott waves and Fibonacci in practice 18:19 Calculating position size properly 20:39 When altseason and meme season arrive 23:39 Thoughts on LAB, ASTER, PUMP, NEAR, SOL, XRP 23:52 AI agents and vibecoding in trading 24:00 How the weather bot works on Polymarket 25:12 The free trading bot 25:29 Is prop trading worth it in 2026 25:35 Will I go back to copy trading 25:52 Public $1,000 to $10,000 marathon? 26:25 Personal questions 26:39 Banks, payment systems and crypto cards I use 27:19 Best countries in East Asia to live in 29:24 Software I use every day 30:39 The private traders club Enjoy! 🤝

Ruslan Khairullin

28,936 просмотров • 1 месяц 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
42:18

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

Ethan Kho

17,408 просмотров • 7 месяцев назад

Episode 14 of The Y-Axis Pod with Kevin McCordic (intern) on all things Monad. Tech, community building, crypto marketing strategies, and more! Chapters: 00:00 Introduction to Monad and Kevin's Journey 05:12 The Current State of Monad's Testnet 10:10 Understanding Monad's Unique Approach to EVM Scaling 15:04 Community Building and Ecosystem Development 20:11 The Future of Monad and Its Impact on Ethereum 29:16 The Dangers of Vanity Metrics 30:46 Building Authentic Communities 34:03 The Importance of Genuine Interaction 37:07 Transitioning Community Energy to Mainnet 43:30 The Monad Company Culture 56:02 User-Driven Development vs. Engineer-Driven Development 01:00:06 The Importance of In-Person Collaboration 01:03:12 Embracing Risk and Learning from Failure 01:06:53 Building a Strong Company Culture 01:10:03 Preparing for Mainnet Launch 01:15:25 The Art of Engaging on Social Media 01:22:27 Advice for Entering the Crypto Industry
1:26:56

Episode 14 of The Y-Axis Pod with Kevin McCordic (intern) on all things Monad. Tech, community building, crypto marketing strategies, and more! Chapters: 00:00 Introduction to Monad and Kevin's Journey 05:12 The Current State of Monad's Testnet 10:10 Understanding Monad's Unique Approach to EVM Scaling 15:04 Community Building and Ecosystem Development 20:11 The Future of Monad and Its Impact on Ethereum 29:16 The Dangers of Vanity Metrics 30:46 Building Authentic Communities 34:03 The Importance of Genuine Interaction 37:07 Transitioning Community Energy to Mainnet 43:30 The Monad Company Culture 56:02 User-Driven Development vs. Engineer-Driven Development 01:00:06 The Importance of In-Person Collaboration 01:03:12 Embracing Risk and Learning from Failure 01:06:53 Building a Strong Company Culture 01:10:03 Preparing for Mainnet Launch 01:15:25 The Art of Engaging on Social Media 01:22:27 Advice for Entering the Crypto Industry

Tristan

26,412 просмотров • 1 год назад

I CAUGHT THE $436,000 INSIDER Episode 3 of PredictTime is live - and you'll hear this story straight from the source tre 🇨🇦, founder of Polysights. We go deep - into how his platform catches insiders on Polymarket before the news drops and into his life journey Everything you need to know about insider trading in prediction markets - is in this episode Timecodes: 00:00 — Cold open / Highlights 00:51 — The $436k profit case: how a $34k order paid out before the news 01:05 — Meet Tre, founder of Polysights 01:35 — How Polysights spots anomalies: radar score and wallet clusters 03:17 — What Polysights actually does: advanced analytics for prediction markets 04:00 — From aircraft engineering to the Canadian Air Force 05:01 — Entrepreneurial roots: e-commerce and dropshipping 06:13 — Selling the first company at 23 and getting paid in crypto 08:21 — Were meme coins detrimental or a launchpad into Web3? 09:46 — The "Fatherhood Buff": how a son changes drive and risk 12:03 — Rank 1 in WoW: gaming as training for founders 14:35 — From PredictFun on Blast to Polymarket: trader-first, builder-second 16:35 — Building Insider Finder: scoring every trade on Polymarket 19:34 — The Maduro case in detail: why it wasn't posted publicly 21:18 — Mayor Eric Adams dropout: prediction markets vs mainstream media 22:24 — MicroStrategy markets: 6–0 on recycled wallets 26:50 — Philosophy: why insider trading accelerates truth 30:56 — Disagreeing with Kalshi's CEO: the centralized vs decentralized divide 35:19 — If the CFTC bans insider trading: validation or death? 48:09 — Arbitrage across Polymarket, Kalshi and sportsbooks 50:48 — Why prediction markets finally boomed in 2024–2025 54:39 — Alpha decay and growing to 45,000 users 55:59 — The Bloomberg / WSJ / NYT moment 58:08 — Fundraising $1.5M from Halifax: the lead VC drama 01:02:26 — Business model: moving away from subscriptions 01:04:21 — No-code automated trading strategies as the future 01:13:20 — Roadmap: V1 by Q2 and a regulated prediction market in Canada 01:16:24 — Solo founder reality: from intern-only to an ex-Meta tech lead 01:18:46 — Crucial advice: don't build another trading terminal 01:20:27 — Breaking in with no connections, no VCs, no hub 01:24:58 — Rapid-fire: Ferrari, Bitcoin to $1M, Hyperliquid vs Kalshi 01:27:35 — The biggest insider trade he can't prove: Lord Miles 01:28:12 — Role models: CZ, Kobe, Shane, Elon 01:30:00 — Final advice: stop overthinking and take the swing
1:32:53

I CAUGHT THE $436,000 INSIDER Episode 3 of PredictTime is live - and you'll hear this story straight from the source tre 🇨🇦, founder of Polysights. We go deep - into how his platform catches insiders on Polymarket before the news drops and into his life journey Everything you need to know about insider trading in prediction markets - is in this episode Timecodes: 00:00 — Cold open / Highlights 00:51 — The $436k profit case: how a $34k order paid out before the news 01:05 — Meet Tre, founder of Polysights 01:35 — How Polysights spots anomalies: radar score and wallet clusters 03:17 — What Polysights actually does: advanced analytics for prediction markets 04:00 — From aircraft engineering to the Canadian Air Force 05:01 — Entrepreneurial roots: e-commerce and dropshipping 06:13 — Selling the first company at 23 and getting paid in crypto 08:21 — Were meme coins detrimental or a launchpad into Web3? 09:46 — The "Fatherhood Buff": how a son changes drive and risk 12:03 — Rank 1 in WoW: gaming as training for founders 14:35 — From PredictFun on Blast to Polymarket: trader-first, builder-second 16:35 — Building Insider Finder: scoring every trade on Polymarket 19:34 — The Maduro case in detail: why it wasn't posted publicly 21:18 — Mayor Eric Adams dropout: prediction markets vs mainstream media 22:24 — MicroStrategy markets: 6–0 on recycled wallets 26:50 — Philosophy: why insider trading accelerates truth 30:56 — Disagreeing with Kalshi's CEO: the centralized vs decentralized divide 35:19 — If the CFTC bans insider trading: validation or death? 48:09 — Arbitrage across Polymarket, Kalshi and sportsbooks 50:48 — Why prediction markets finally boomed in 2024–2025 54:39 — Alpha decay and growing to 45,000 users 55:59 — The Bloomberg / WSJ / NYT moment 58:08 — Fundraising $1.5M from Halifax: the lead VC drama 01:02:26 — Business model: moving away from subscriptions 01:04:21 — No-code automated trading strategies as the future 01:13:20 — Roadmap: V1 by Q2 and a regulated prediction market in Canada 01:16:24 — Solo founder reality: from intern-only to an ex-Meta tech lead 01:18:46 — Crucial advice: don't build another trading terminal 01:20:27 — Breaking in with no connections, no VCs, no hub 01:24:58 — Rapid-fire: Ferrari, Bitcoin to $1M, Hyperliquid vs Kalshi 01:27:35 — The biggest insider trade he can't prove: Lord Miles 01:28:12 — Role models: CZ, Kobe, Shane, Elon 01:30:00 — Final advice: stop overthinking and take the swing

Predict Time

58,555 просмотров • 4 месяцев назад

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks
1:15:17

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks

The Knowledge Project

453,197 просмотров • 1 год назад

How shaams 🐂 made $45,000,000 in crypto and advice to profitability (FULL INTERVIEW) 0:00 - Introduction 1:30 - How He Started 4:55 - Losing 6 Figures 10:20 - The Comeup 13:46 - Trading in College 14:34 - Making $500k+ on 1 Trade 15:54 - Dropping Out of College 18:45 - Trading in Miami 19:40 - Thesis Behind Trades 21:08 - How to Become Profitable 24:39 - Why Traders Lose 25:41 - Habits 28:14 - The Alpha Filter 30:29 - Risk Management 33:58 - Journaling 35:45 - Community 39:16 - Working with Fortune 44:22 - Taking Action 46:15 - Beginners Advice 51:27 - Building Connections 52:06 - Why Trade? 54:23 - What's Next? 56:52 - Final Steps (Fortune Inner Circle)
57:46

How shaams 🐂 made $45,000,000 in crypto and advice to profitability (FULL INTERVIEW) 0:00 - Introduction 1:30 - How He Started 4:55 - Losing 6 Figures 10:20 - The Comeup 13:46 - Trading in College 14:34 - Making $500k+ on 1 Trade 15:54 - Dropping Out of College 18:45 - Trading in Miami 19:40 - Thesis Behind Trades 21:08 - How to Become Profitable 24:39 - Why Traders Lose 25:41 - Habits 28:14 - The Alpha Filter 30:29 - Risk Management 33:58 - Journaling 35:45 - Community 39:16 - Working with Fortune 44:22 - Taking Action 46:15 - Beginners Advice 51:27 - Building Connections 52:06 - Why Trade? 54:23 - What's Next? 56:52 - Final Steps (Fortune Inner Circle)

James Wang

29,203 просмотров • 3 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
56:21

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 • 7 месяцев назад

The firms leading in market making figured out early that infrastructure compounds. Austin Federa | 🇺🇸 sits down with Rahul Jain, Rahul Jain (Ellipsis Labs), to trace how crypto market making evolved: why being early matters, how MEV and transaction landing reshaped execution, and what it will take for onchain finance to scale beyond crypto-native users. Understanding the infrastructure layer is a prerequisite for competing with traditional trading environments. Timestamps and links below ↓ 00:00 - Introduction 03:53 - What Makes Solana Trading Different 07:17 - Trust and Retail Outcomes 12:04 - Infra Arms Race 2025 14:27 - Prop AMMs vs Order Books 17:05 - Spot Market Equilibrium 18:12 - MCP and Perps Security 21:22 - Why MCP Matters 24:25 - ACE For Safer Perps 25:47 - RWAs And Oracle Risk 29:28 - Why Retail Loves Perps 34:23 - Hypothetical VIX perps 35:29 - The Different MCP Camps 37:07 - Latency And Block Full 40:41 - Conclusion
42:09

The firms leading in market making figured out early that infrastructure compounds. Austin Federa | 🇺🇸 sits down with Rahul Jain, Rahul Jain (Ellipsis Labs), to trace how crypto market making evolved: why being early matters, how MEV and transaction landing reshaped execution, and what it will take for onchain finance to scale beyond crypto-native users. Understanding the infrastructure layer is a prerequisite for competing with traditional trading environments. Timestamps and links below ↓ 00:00 - Introduction 03:53 - What Makes Solana Trading Different 07:17 - Trust and Retail Outcomes 12:04 - Infra Arms Race 2025 14:27 - Prop AMMs vs Order Books 17:05 - Spot Market Equilibrium 18:12 - MCP and Perps Security 21:22 - Why MCP Matters 24:25 - ACE For Safer Perps 25:47 - RWAs And Oracle Risk 29:28 - Why Retail Loves Perps 34:23 - Hypothetical VIX perps 35:29 - The Different MCP Camps 37:07 - Latency And Block Full 40:41 - Conclusion

Validated

27,660 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
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 • 3 месяцев назад