Odds on Open

Lihong Wang spent his career as a discretionary options trader at IMC, one of the world's largest market makers, trading semiconductor volatility on names like Nvidia, AMD, and Broadcom. In this episode, he breaks down how a prop trading desk actually makes money: reading order flow to identify counterparties, trading against structured product hedging flows from Asian banks, warehousing benign risk instead of externalizing it, and why correlation blowups — like the DeepSeek selloff and July's deleveraging cascade — are how options market makers get hurt. He explains why the seat at a top trading firm is one of the most leveraged information positions in markets, how firms like IMC, Jane Street, SIG, and HRT train and allocate quant trader talent, and what separates market making from prediction.Now the founder of Freeport, a YC-backed perpetual futures exchange, Lihong shares his AI investing thesis: why he holds a 2x levered portfolio of 50 stocks across the entire AI and semiconductor supply chain — from TSMC and ASML to optics, connectivity, and memory names like SK Hynix — and why nearly every quant trader he knows is doing the same. We cover how narratives move from private conversations to Twitter to Bloomberg (and where the edge dies), Leopold Aschenbrenner's Situational Awareness fund, whether AI is a dot-com-style bubble, Kelly criterion leverage sizing, the future of perp DEXs like Hyperliquid, and how young people should think about risk, career moats, and personal brand in the age of AI. Essential listening for hedge fund analysts, quants, options traders, and anyone trading the AI supply chain.

Checkout Flux 4.0 here: https://www.flux.live/flux4/index.html Alix Pasquet, hedge fund manager and Managing Partner at Prime Macaya Capital, breaks down how fundamental investors build durable edge in modern markets. In this episode, Alix explains the three sources of competitive advantage in the investment business — analytical, informational, and behavioral — and why exploiting group behavior beats behavioral finance checklists. He covers what he learned inside a top quant fund (data scrubbing, transaction costs, temporal stops), how smaller hedge funds compete against multi-manager pods like Citadel and Millennium, and his full idea generation process: investor networks, 13F tracking, thematic collisions, and the customer-investor mismatch. He also makes the contrarian case for technical analysis as a behavioral tool, explains why moats and chart strength are connected, and shares why buying stocks at new highs beats bottom-fishing in a post-2022 market.Later in the conversation, Alix delivers a warning on AI in investing: why over-reliance on AI tools will produce the worst portfolio managers of the next decade, the five core analytical skills every analyst must protect (pattern recall, visualization, reading between the lines, leap of judgment, synthesis), and how to become a "bionic" investor who combines analog training with digital tools. He closes with career advice for young analysts and aspiring PMs — building a personal moat, the power pair concept, network as competitive advantage, and applying margin of safety to your personal life. Essential listening for hedge fund analysts, portfolio managers, long-short equity investors, and anyone pursuing a career in active management, stock picking, or the hedge fund industry.

How does market making actually work? In this lecture, former high-frequency trader Annanay Kapila (Flow Traders, Tower Research Capital; founder & CEO of QFEX) breaks down the mechanics of market making from first principles. He maps the systematic trading landscape—prop trading vs hedge funds, HFT vs mid-frequency—and explains why market making sits in the high-Sharpe, proprietary quadrant. You'll learn how a central limit order book (CLOB) works, how arbitrage-free pricing pins down fair value (theo), and why the mid-price between best bid and best ask is the market's best estimate of a stock's true price.From there, the lecture gets into the real edge mechanics: quoting around fair value, edge per share, queue priority, and adverse selection—the hidden cost that punishes market makers when their fair value model is wrong. Annanay walks through how competition between market makers compresses the bid-offer spread, why thick books (large-cap US equities trading $10B+ a day) offer lower transaction costs than thin books, and how quant firms size their quotes based on confidence in their fair value models. Essential viewing for aspiring quants, traders, MFE students, and anyone who wants to understand market microstructure, liquidity provision, and how high-frequency trading firms actually make money.

Checkout Flux 4.0 here: https://www.flux.live/flux4/index.html Noah Kann is 22, running his third firm, and managing capital raised from some of the wealthiest families in America. On this episode of Odds on Open, Ethan Kho sits down with the co-CEO of Venari Asset Management to unpack what a 22-year-old hedge fund manager knows that 20-year Wall Street veterans miss: why running a hedge fund is the least sexy business in finance, why compliance and a well-written PPM are an emerging manager's competitive advantage, and why complacency, not inexperience, is the real driver of alpha decay. Noah walks through his path from buying HCA at $15 during the COVID drawdown at 16, to a leveraged crypto trading firm at 17, to launching SageTech Capital at 19, and explains how behavioral finance and studying past cycles like the Great Depression substitute for market reps he hasn't lived through.The conversation then moves into Venari's macro discretionary playbook: trading government intervention and defense spending, a top-down process that turns a geopolitical thesis into a position, non-consensus indicators like data-center HVAC suppliers, and how the firm handles crowded trades and momentum with hard stops, max drawdown limits, and disciplined profit-taking. Noah breaks down the multi-strategy structure across long/short equity, LEAPS options, and ETF baskets, explains why mindfulness is the single most important risk control for a discretionary macro fund, and shares what family offices actually diligence when an emerging manager raises capital — stewardship, lockups, and the next generation. The episode closes on what people miss about Jane Street, SIG, and WorldQuant, hiring for rate of improvement over credentials, pod-shop culture, and why differentiated inputs produce differentiated returns. Essential listening for hedge fund analysts, PMs, quants, allocators, emerging managers, and MFE and MBA students building an edge in liquid markets.

Checkout Flux 4.0 here: https://www.flux.live/flux4/index.html Lucas Schuermann started a market-neutral quant fund in his Columbia dorm room, trading stat arb across FX and early crypto markets, before dropping out to scale it into Q Capital. In this episode of Odds on Open, he breaks down how he electronified Genesis Trading's OTC desk as VP of Engineering — taking a phone-and-Telegram trading operation to a fully electronic market-making system with HFT execution — and why flow, capital, and trust are the real moats in market making, not speed. He explains the biggest misconception about HFT firms and market makers like Jane Street, Jump, and Citadel Securities, and why having flow and economies of scale matters more than latency.Lucas then dives into building Variational, first as a crypto prop shop trading DeFi and OTC derivatives, and now as one of the largest on-chain perps trading platforms — a broker-like model with zero-fee trading, aggregated liquidity, and a new swaps instrument that fixes the funding rate problem with perpetual futures. We cover perps vs swaps vs spot mechanics, total return swaps, internal vs external market makers, RWA perps, and why he believes the cypherpunks already won. Plus: how to identify trends worth riding using growth-curve data, why asset prices are uncorrelated with industry durability, how to build expertise in a technical domain fast, and the role of hubris in career differentiation for young quants, traders, and founders.