Odds on Open

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.

Checkout Flux 4.0 here: https://www.flux.live/flux4/index.htmlCamilo Saravia is the founder of BlueWalker Capital, a systematic hedge fund trading prediction markets — and possibly the only fund dedicated exclusively to the asset class. Backed by Daniel Howard, son of Brevan Howard co-founder Alan Howard, Camilo breaks down how the fund prints alpha across taker and maker strategies, reflexive vs. proactive pricing, and why event contracts carry different adverse selection and binary risk than equities. He makes the contrarian case that insider flow is a feature, not a bug — the mechanism that makes prediction markets a money-backed source of truth — and maps where systematic edge actually comes from: proprietary order book and on-chain fill data, vertical integration, execution speed, and a team hungry enough to make unit economics work in a market Citadel and Jane Street won't touch.The back half is a blueprint for launching an emerging fund from scratch: underwriting talent, hiring quants who turn down Citadel and Wintermute offers, missionaries vs. mercenaries, and why speed is a startup fund's structural edge. Camilo details his research philosophy — collapsing internet entropy into tradable signal, mining exotic alternative data from TikTok virality to Spotify streams, and applying a venture-style lens to price what markets can't: unstructured data, operational KPIs, and execution quality. The episode closes with prediction markets 101 — order books, market microstructure, narrative risk, and why the best trades exit at 50 rather than waiting for resolution on Polymarket — plus how to build durable personal edge as AI commoditizes technical skills. Essential listening for quants, PMs, traders, allocators, and anyone tracking prediction markets as the next institutional asset class.

Checkout Flux 4.0 here: https://www.flux.live/flux4/index.htmlJosh Young (Bison Capital) on Energy Alpha, Deep Value, and Activism in Small-Cap Oil & Gas: Josh Young runs a concentrated, long-only public equities energy fund that's up 200% since inception while the energy sector is down 60% — a spread he calls a statistical impossibility. In this episode, Josh breaks down the process behind that outperformance: why he screens for large discounts to liquidation value and third-party reserve appraisals, how being chairman of a public E&P rewired his view of oil and gas as a capital allocation business, and why returns on invested capital and inflection points matter more than static free cash flow yields. He explains why he refuses to short stocks, how he sizes positions across speculative, medium, and high-conviction buckets, and why deleveraging setups — companies going from 4x debt/EBITDA to under 1x — have driven the bulk of his idiosyncratic returns. He also walks through the Abqaiq attack in real time as an example of why almost nobody has edge on short-term crude direction.The conversation goes deep on where alpha actually lives in energy markets: activist campaigns and proxy fights in small-cap E&Ps, co-investment vehicles for concentrated activist positions, the principal-agent problem that keeps allocators, endowments, and ESG-constrained institutions out of oil and gas, and the Fama-French small-cap illiquidity premium that makes an out-of-favor sector fertile ground. Josh discusses CTA and commitment-of-traders positioning as a timing input, energy's collapse to 4% of the S&P 500 versus a four-decade average above 10%, the long-cycle case for $250 oil, and why finding public-but-undisseminated data in state and provincial filings still produces real edge. He closes on the limits of AI in fundamental energy research, why oil companies bragging about AI-driven operations tend to underperform, and what most energy traders get wrong about left-tail risk, volatility, and buying the fundamentals instead of the macro. Essential viewing for hedge fund analysts, portfolio managers, commodity traders, allocators, and anyone studying deep value investing, portfolio construction, and edge in liquid markets.