Odds on Open

Yoshi Yokokawa, Alpaca co-founder and CEO and a former Lehman Brothers trader, explores how AI is reshaping quantitative research without creating a lasting trading edge. They discuss execution discipline, behavioral risk, the fading line between retail and institutional markets, the rise of solo quant firms, competition with scaled trading giants, and Alpaca’s vision for open, programmable financial infrastructure.

Chris Camillo, investor and social-arbitrage pioneer, faces Tom Costello, a former Tudor, Moore, and Caxton portfolio manager. They debate retail freedom versus institutional risk controls, rational drawdowns, leverage, and concentrated bets. The conversation explores 3x ETFs, crypto correlation, AI concentration, cultural signals, alternative data, and whether hedge funds can automate the social edge.

Lihong Wang, a former IMC semiconductor options trader and founder of YC-backed Freeport, reveals how market makers read order flow, trade structured-product hedging, and survive correlation blowups. He shares his bullish, leveraged view of the AI supply chain, explores AI agents for event-driven trading, and debates whether foundation models can beat the S&P 500. Career strategy, perp exchanges, and risk-taking round out the conversation.

Alix Pasquet, hedge fund manager and Managing Partner at Prime Macaya Capital, explores how investors build durable advantages. He discusses competing with multi-manager funds, network-driven idea generation, technical analysis as behavioral intelligence, and the risks of overusing AI. He also examines the human skills analysts must protect, becoming a “bionic” investor, and building a personal moat in markets and life.

Annanay Jain, former high-frequency trader at Flow Traders and Tower Research Capital and founder of QFEX, offers a first-principles tour of market making. He maps systematic trading, opens up the central limit order book, and explores fair value, spreads, queue priority, adverse selection, inventory risk, and competition. A sharp look at how quantitative firms provide liquidity in modern markets.

Noah Kann, a 22-year-old co-CEO of Venari Asset Management who launched multiple early funds, recounts his rapid path from teenage trader to running institutional capital. He discusses why hedge funds are unglamorous, how compliance and PPMs become competitive edges, Venari’s macro discretionary, multi-strategy playbook, trading government and defense themes, non-consensus indicators, and risk controls like hard stops and drawdown limits.

Lucas Schuermann, a quant-founder who launched a market-neutral fund in college and built electronic OTC systems at Genesis, discusses electronifying trading desks and why flow, capital, and trust beat raw speed. He walks through building Variational, a broker-like on-chain derivatives platform with zero-fee perps and swap fixes for funding. Short takes on DeFi fragility, spotting multi-year trends, and using hubris to build technical expertise.

Camilo Saravia, founder of BlueWalker Capital and builder of a systematic fund for prediction markets. He explains taker vs maker strategies, how event contracts differ from equities, and why insider flow can speed truth discovery. He describes where edge comes from — proprietary data, speed, and team — and lays out how to recruit, build infrastructure, and research in this emerging asset class.

Josh Young, founder of Bison Capital known for activist, value-driven small-cap oil and gas investing. He explains screening for deep discounts to liquidation value, why chairing an E&P changed his capital-allocation lens, and how deleveraging setups produced outsized returns. Topics include activist tactics, sizing conviction buckets, timing limits on short-term oil moves, and the realistic role of AI in energy research.

Suhaimi Zainul-Abidi, CEO of Quantedge and builder of a multi-billion systematic hedge fund, explains their founding thesis and why breadth across ~300 markets is the real edge. He discusses risk premia, factor-based market-neutral strategies, insisting on economic rationale over black boxes, and keeping generative AI out of production models. He also covers scaling choices, fixed-term share classes, and hiring mostly graduates to preserve culture.