Odds on Open

Join Vinesh Jha, founder of Extract Alpha and former director at PDT Partners, as he dives into the tumultuous lessons from the 2007 Quant Quake. He reveals the inside story of PDT's $500M loss and the cultural differences with other hedge funds. Vinesh discusses the rise of alternative data, how smaller firms can thrive against giants, and the impact of AI on quant finance careers. He also explores the intricacies of predictive modeling and the importance of adaptability in today's trading landscape.

Bill Mann, a former fundamental researcher at Two Sigma and founder of Harmonic Insights, shares his insights into the world of quantitative trading. He discusses the transformative influence of AI, LLMs, and automation on research and trading workflows. Mann explains how hedge funds can leverage proprietary data pipelines for alpha generation while avoiding crowding in popular factors. He emphasizes the importance of hacker creativity in systematic investing and outlines the skills junior quants need to thrive in an AI-driven landscape.

Chris Kantos, Head of Quantitative Research at Alexandria Technology, specializes in using natural language processing and AI to generate investment insights. He discusses how hedge funds analyze social media and earnings calls to identify alpha signals. Kantos highlights the importance of tailored NLP techniques and the challenges of data commoditization. He also explains the future role of AI in systematic investing and how sentiment analysis from platforms like Reddit can inform trading strategies. Tune in for invaluable insights into navigating the noisy world of financial data!

Grant Stenger, the founder of Kinetic and a former intern at Jane Street, dives into the similarities between trading and poker. With a passion for games and mathematical edge, he shares insights from his experiences at QuantRes and Numerai, emphasizing decision-making under uncertainty. He explains how decentralized exchanges operate and the advantages of trading on Solana over Ethereum. Grant also reflects on the collapse of FTX, discussing the importance of being early in emerging asset classes and the parallels between gambling strategies and market trading.

In this engaging discussion, Robert Carver, former head of fixed income at Man AHL—a massive systematic trading hedge fund—dives into his journey as an independent quant trader. He shares vital insights on breaking into quantitative trading without a PhD and the essential skills required. Carver critiques the Sharpe ratio, advocating for better risk metrics, and emphasizes the importance of realistic backtesting. He also discusses managing 200+ trading strategies solo and navigating alpha decay, offering practical advice for aspiring traders.

Agustin Lebron, a former quant trader at Jane Street and author of The Laws of Trading, shares deep insights into the evolving world of trading. He explains the concept of 'edge' and its significance in distinguishing top traders. Agustin discusses how elite firms maintain their competitive advantage, and the role of statistical analysis and judgment in trading. He also gives practical advice for aspiring traders, covering essential skills, internship realities, and the future of quant trading in a tech-driven landscape.

If venture capital underperforms the public markets, is it still worth the investment? For Avik Ashar, the answer is yes—but not for the reasons you think. Avik, a Principal at Riverwalk Holdings, an India-focused VC firm, argues that most people misunderstand how venture capital works and how to fairly evaluate VC fund performance.Venture capital, he explains, isn’t just about chasing unicorns or short-term IRRs. It’s a strategic investment tool, especially in Asia, used by family offices and conglomerates not only for returns but also for M&A, R&D, and market expansion. In markets like India, venture capital is helping industrial groups future-proof their businesses while tapping into innovation. He also highlights how India’s maturing public markets and mutual fund sector are making early-stage investing and startup exits far more viable than in places like Southeast Asia, where liquidity is still limited.He breaks down:– Why VC returns vs public markets often look misleading—unless you know how to analyze them– How family offices in India are using venture funding for strategic acquisitions– Why M&A is finally taking off in Asia—and what that means for founders– The key differences between venture capital in India, Southeast Asia, and the U.S.– Why India’s public markets are becoming a critical exit path– How startup exits work in markets without strong IPO pipelines– Why Southeast Asia’s VC boom from 2014–2018 underperformed– What Gen Z needs to understand about building in a noisy, AI-native world– How venture capital vs private equity differs in terms of outcomes, strategy, and timelinesHe also shares an important reminder for our age of endless short-form content: “The most expensive thing you can give today isn’t your time—it’s your attention.”00:00 Intro00:33 Why invest in venture capital?01:01 How venture returns work03:01 Venture as an R&D and acquisition pipeline04:11 The outlier nature of VC returns05:11 Why family offices invest in venture05:52 Examples of conglomerate acquisitions in India09:43 Differences in VC ecosystems: US, Singapore, and India16:29 Do family-backed VCs perform better in India?16:50 Riverwalk Holdings’ experience in India18:22 Maturity of India’s financial ecosystem for startups23:59 Where will venture gains come from?27:51 Indian conglomerates embracing startups28:52 Challenges of building companies in Asia30:22 Advice for young people in an uncertain world32:44 Tech’s share of the US market cap38:04 Staying focused amidst noise40:57 Advice for recent graduates42:24 Outro

Is venture capital dead? Not for Guy Horowitz, who boasts 20+ years in the VC ecosystem, holding the title of partner at firms like DTCP, 33N, and ESH.vc. In this episode of Build to Last, we unpack the changing face of early-stage investing and startup funding—from the 2000s hardware boom to the rise of software unicorns, and now the new frontier: AI-first companies. Guy shares battle-tested insights on identifying founder-market fit, navigating VC cycles, and why understanding capital formation is just as important as finding the next big tech innovation.We also dive into the future of work, education, and the middle class. What happens when generative AI and automation replace white-collar jobs faster than traditional schools can adapt? What happens when AI agents arrive at desks, offices, and boardrooms? With three kids of his own, Guy reflects on raising future-proof talent and what young people today really need to succeed in a world defined by machine learning, venture-backed disruption, and rapid technological change. Spoiler: it's not just about coding bootcamps—it's about curiosity, adaptability, and a willingness to learn from people who aren’t like you.Some key takeaways:– How venture capital has changed in the past two decades– Why "great ideas" don’t matter without the right founders– What makes a great startup exit– The question top VCs like Guy Horowitz ask before writing a check– What NOT to say in a pitch meeting– How DTCP became a breakout fund backed by Deutsche Telekom– Why today’s job market is rigged (and how you can stand out anyway)– Whether AI will make human investors obsolete– Why most white-collar jobs are more automatable than we think– Is now a good time to start a fund? Guy’s honest take– Advice for young people unsure about their futureAlso in this episode, we discuss how to identify REAL startup talent (even if they’re mean) and what makes a great VC (beyond capital). Subscribe for more conversations with founders, builders, and leaders.#venturecapital #investing #ai 00:00 Podcast Intro 00:43 How venture capital has changed 01:55 Guy’s early career at Gemini 05:46 Lessons from being cocky too early 09:15 What makes a great VC investor 12:49 How Guy evaluates founders 18:54 What not to say in a pitch 21:38 The story behind DTCP 27:08 Fundraising success and growth 30:11 Is venture capital dead? 36:41 Raising kids in the AI age 43:44 What happens to the middle class?51:12 Advice to young people 52:42 Outro

How will AI affect education? Minh Tran has a lot to say about the future of learning in the age of large language models (LLMs) and generative AI. As the COO of GoodNotes—one of the world’s leading AI-powered note-taking apps—he’s at the forefront of how AI is changing the education system. For Minh, the future of learning is already here: “We need to rethink WHAT we teach, not just HOW we teach,” he says.Before working in edtech, Minh was the Executive Director at Education First, the global learning company. He also founded Bloom Academy in Hong Kong, literally building a K–12 school FROM SCRATCH during COVID. With experience in both traditional and startup education organizations, Minh shares why AI-first schools are better positioned to thrive, while schools that don’t adapt to AI will fall behind.Some key takeaways:– How Minh started a school from scratch during the pandemic– What today’s students *actually* need to learn in an AI-first world– Why most schools are failing to adapt to ChatGPT and generative AI tools– How Goodnotes became a tech unicorn through remote-first culture– How Goodnotes is winning the tech talent war through flexible work arrangements– The importance of mentorship– How to find a mentor– Why AI experimentation, curiosity, and play are key to raising future-ready kids– How to pivot from education to tech (and how others can break into tech from different industries)– What Gen Z can offer senior leaders at the workplaceWe also dive into Minh’s advice for young people chasing unconventional careers and the secret to building a career with impact. He emphasizes this: put in the hours, and if you’re privileged enough to follow your passion, just do it.Subscribe for more conversations with founders, builders, and leaders.

Is a finance degree still worth it if you want to become a quant? In this week’s Build to Last episode, quant researcher and YouTuber Dmitri Bianco explains why he calls his own finance undergrad “a big mistake” — and why most quant roles today demand far more math, statistics, and programming than students realize. (The short answer to that first question is: no.)Dmitri shares how he went from a misguided finance major to Head of Quantitative Research at Agora Data, a fintech company — after being rejected from top financial engineering programs and racking up $160K in student debt. He now runs a YouTube channel with nearly 60,000 subscribers, where he shares real insights on quant careers, financial engineering, and navigating the industry.breaks down how the world of finance is evolving, and how new grads can break in. A few key takeaways:— Why most finance degrees don’t prepare you for quant roles— How buy-side firms use prestige to exploit junior talent— Why the traditional finance hiring model is broken— How passion and problem-solving beat credentials in quant interviews— Practical advice for students entering quant and finance roles today— What makes a company a great place to work in quant finance— Why career satisfaction matters more than titles or payHe also shares thoughts on AI’s impact on quant careers, what it’s like being a YouTuber with a dedicated hate page (yes, really), and how to build a career you can be proud of (even in a tight job market).#QuantFinance #FinancialEngineering #financejobs Check out Dimitri's channel: https://www.youtube.com/c/dimitribianco