Odds on Open

Ethan Kho

Conversations with leading thinkers on trading and investing.
Hosted by Ethan Kho.
Produced by Patrick Kho.

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Today · 1 hr 32 min
Hedge Fund Manager Alix Pasquet: How Small Funds Can Outsmart Multi-Managers
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.
September 3 · 44 min
⁠Greed Makes Markets: Market Making From First Principles With an HFT Quant
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.
August 27 · 1 hr 5 min
22-Year-Old Hedge Fund Manager: “Hedge funds are the least sexy business in the world”
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.
August 21 · 1 hr 13 min
He Started a Quant Fund in His Dorm. Now He's Building the Brokerage for Everything.
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.
August 13 · 1 hr 16 min
Inside the Billionaire-Backed Prediction Markets Hedge Fund
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.
August 6 · 1 hr 14 min
World's #1 Oil Hedge Fund Manager: How I Made 200% While Everyone Lost 60%
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.
July 30 · 1 hr 22 min
The Strategy Behind Asia’s $6 Billion Quant Fund: Quantedge
Checkout Flux 4.0 here: https://www.flux.live/Suhaimi Zainul-Abidi is the CEO of Quantedge, the Singapore-based systematic hedge fund that has compounded at roughly 20% net annualized returns for 20 years — growing from $3 million raised from friends and family to over $6 billion in AUM, with close to $5 billion of that from investment gains rather than fundraising. In this episode of Odds on Open, Suhaimi breaks down Quantedge's founding thesis and why the firm's real edge isn't informational: with close to 300 distinct markets traded across equities, commodities, rates and FX, breadth and independent bets let them target ~25% annualized volatility without risk of ruin. We go deep on risk premia and factor-based market-neutral strategies, why economic rationale must come before empirical evidence in the research pipeline, why they refuse to run a black box they can't explain, and how they think about signal versus noise in alternative data, narratives and news flow. Suhaimi also gives a clear-eyed view on generative AI in portfolio management — transformational for research productivity, data cleaning and execution, but deliberately kept out of the production models.The second half is essential listening for emerging managers, allocators and anyone building an asset management business. Suhaimi explains why Quantedge turned down the obvious scaling path — a lower-vol, allocator-friendly product — and why he believes chasing capital on someone else's terms is the mistake that kills early-stage funds. He details the 2018 decision to introduce fixed-term and semi-perpetual share classes, the estimated cost of that call (he thinks they'd be a $20 billion fund without it), and the deeper insight behind it: funds rarely die from drawdowns, they die from redemptions arriving at the worst possible moment. We also cover Class Q and permanent capital as employee alignment, why Quantedge hires almost exclusively out of school rather than poaching mid-career PMs, what a broad definition of meritocracy looks like inside a quant fund, his own path from law to running the firm, capital consolidation and the rise of AI-native allocators, and the case for patience and conviction in building a 50-year compounding machine.00:00 Intro1:34 Founding thesis: $3M to a $6B quant fund6:06 Why the edge is breadth, not information10:40 A Message from ONYX11:20 Scaling to $6B without chasing allocator capital15:25 Why they refuse an allocator-friendly low-vol version18:21 No black boxes: holding conviction at 25% vol23:22 News flow, narratives, and where AI actually helps30:29 Hiring fresh grads and retaining quant talent38:51 From lawyer to CEO of a quant fund49:19 Capital consolidation and the AI-native allocator54:52 The capital trap that kills emerging managers58:54 Fixed-term lockups and why funds actually die1:04:48 Class Q, permanent capital, and employee alignment1:18:59 How to build a 50-year compounding business
July 23 · 1 hr 11 min
Ex-Balyasny PM: “Automation will increase demand for hedge fund talent.”
In this episode of Odds on Open, former Balyasny Asset Management (BAM) quantamental portfolio manager and Imply founder Ying Hua breaks down how top multi-manager hedge funds synthesize quantitative discipline with discretionary analysis to extract repeatable market alpha. Ying details the mechanics of constructing a systematic quantamental framework—ranging from automating volatility-adjusted position sizing to eliminate behavioral bias, to scraping granular alternative data sets like state highway patrol records and geospatial tracking for asymmetric earnings trades. The conversation draws a sharp line between quantitative pattern matching and fundamental situational judgment, exposing how institutional investors capture edge where pure quants and traditional fundamental analysts both miss the mark.The deep dive extends into the frontier of AI in portfolio management, dissecting why off-the-shelf LLMs fall short without ticker-level financial knowledge graphs and specialized domain context. Ying analyzes how automated data workflows impact earnings print volatility, why pod shop equity trading increasingly mirrors high-stakes poker dictated by positioning dynamics rather than static valuations, and how junior analysts can identify high-alpha sectors. Tailored for hedge fund PMs, quants, equity research analysts, allocators, and MFE/MBA candidates, this episode delivers rigorous mental models on market microstructure, regime shifts, and process automation in liquid markets.00:00 Intro01:07 Positioning and position sizing in a quantamental framework02:30 Quant pattern matching vs fundamental situational edge04:47 Automating position sizing to remove emotional bias06:35 A message from ONYX07:03 Extracting alpha from alternative data: Scraped highway and disaster mapping11:54 Which parts of the fundamental investment process can AI automate?16:53 Why market automation increases earnings print volatility20:29 Structural limitations of using general LLMs for portfolio management27:32 Building ticker-level domain knowledge graphs for AI workflows30:29 Why specialized finance workflows beat commoditized AI wrappers36:48 Will AI make liquid markets more efficient?39:34 How fundamental PMs should redesign workflows for the AI era42:08 What core competencies define elite talent in modern pod shops?48:52 Why multi-manager equity trading resembles high-stakes poker52:29 How junior analysts should evaluate sector alpha and career edge58:23 Evaluating personal drawdowns, self-awareness, and P&L meritocracy01:08:51 Reconstructing market narratives from first principles
July 16 · 1 hr 6 min
~100% Returns in 2025, No Losing Year Since 2008: Erik Smolinski on Edge for Retail Trader Edge
In this episode of *Odds on Open*, hedge fund risk manager and derivatives trader Erik Smolinski deconstructs the structural mechanics of alpha generation, portfolio construction, and risk mitigation in liquid markets. Boasting a near-100% return last year and a flawless annual track record since 2008, Erik details how he transitions from profiling persistent market effects to engineering scalable profit mechanisms. The discussion explores the practical realities of the variance risk premium (VRP), sector rotation dynamics, and advanced derivatives structures—such as ratio call diagonals—designed to capture convex upside across shifting volatility regimes while minimizing exposure to tail risk and adverse market microstructure.Tailored specifically for hedge fund analysts, portfolio managers, quants, allocators, and MFE students, this episode isolates the institutional edge of book agility and systematic process execution over retail bias. Erik breaks down the microstructural nuances of navigating illiquid options chains, the mathematical frameworks behind quantitative momentum, and the strict process constraints required to prevent spectacular portfolio blowups during unexpected regime shifts. Listeners will gain a deep understanding of how to desensitize P&L tracking, align execution models with individual psychological risk profiles, and accurately price implied volatility to build a sustainable, credibility-forward trading framework.00:00 Intro00:01:26 How thematic volatility and objective execution drove triple-digit returns00:04:38 Profiling market effects to construct actionable profit mechanisms00:07:19 Sponsor break00:10:29 Identifying sector leaders and structuring ratio call diagonals00:16:42 The path from military discipline to options trading00:28:05 Formulating systematic trading plans and pricing implied volatility00:39:59 Aligning options strategy with individual psychological risk profiles00:42:57 Structural agility and liquidity capture in retail books00:55:42 Developing discretionary intuition through structured market observation01:01:12 The mechanics of spectacular portfolio blowups and scaling risks01:03:00 The macroeconomic foundations of edge and risk premia persistence
July 9 · 1 hr 27 min
Ex-Citadel PM: All Hedge Fund Failures Are Because of One Reason - Rich Falk Wallace
In this episode of Odds on Open, we dissect the mechanics of institutional alpha generation with Rich Falk-Wallace, founder of Arcana and former portfolio manager at Citadel. Rich explains why the vast majority of hedge fund failures stem from flawed portfolio construction and mismanaged risk leakage rather than a lack of fundamental insights. We dive deep into how elite multi-strat platforms mathematically isolate idiosyncratic alpha by systematically neutralizing ex-ante correlation and factor exposures across trading books. For PMs, quants, and allocators looking to understand market structure, this conversation provides a rigorous framework for evaluating the cost of volatility, managing crowding, and building attribute-perfect benchmarks that keep investment teams intellectually honest.The discussion also charts the structural shifts redefining the front office, tracing how sophisticated risk architecture is migrating from the back office directly into the hands of fundamental stock pickers and concentrated long-only asset managers. Rich offers an insider’s perspective on the secular evolution of buy-side talent, explaining how artificial intelligence and mock portfolio trackers are accelerating the career progression of junior analysts into active risk-takers. Finally, we analyze the current macro regime of capital allocation, detailing the ongoing fragmentation of hedge fund capital via separately managed accounts (SMAs) and why the future of active management belongs to firms that treat factor constraints with the same diligence as single-stock theses.00:00 Intro01:10 Defining the fundamental role of a hedge fund portfolio manager02:52 How top portfolio managers isolate alpha and avoid risk leakage09:57 A message from ONYX10:25 Risk management frameworks at elite multi-manager platforms18:17 The mechanics of neutralizing factor risk in multi-strat books27:33 Why institutional allocators are adopting advanced factor modeling tools38:57 How veteran investors adapt to modern systematic risk architecture44:48 Integrating factor constraints into fundamental portfolio construction processes55:29 Decomposing idiosyncratic returns in concentrated long-only portfolios01:05:34 The secular evolution and future of buy-side junior analyst roles01:15:52 Contrarian theses on multi-manager asset aggregation and market fragmentation01:19:42 Operational pitfalls and capital allocation mistakes in scaling funds
July 2 · 1 hr 7 min
Ex-Two Sigma Quant: You Should Bet Against Bullish Analysts
Apply to Onyx’s trading event here: https://www.onyxcapitalgroup.com/uni-studentsIn this episode of Odds on Open, former Two Sigma quant Omer Cedar joins host Ethan to deconstruct how top-tier quantitative hedge funds systematically aggregate discretionary signals to isolate pure alpha. Cedar reveals the inner workings of institutional alpha capture programs, detailing how premier multi-manager pods map the information propagation curve and exploit crowded consensus sentiment to capitalize on structural mispricings. The conversation provides a rigorous, finance-native breakdown of market microstructure, analyzing the statistical deltas between asset pricing and expert variant perceptions during high-surprise macro and corporate catalysts. For portfolio managers, quantitative researchers, and buy-side analysts, this discussion offers a masterclass in data validation, situational weighting, and the mechanics of separating idiosyncratic returns from passive factor premiums.The dialogue transitions into the future of market structure, exploring how the proliferation of generative AI and autonomous digital analysts will reshape liquidity and market efficiency across equities, commodities, and secondary private markets. Cedar delivers a framework-first outlook on the scaling hedge fund ecosystem, explaining how large language models alter competitive advantage by shifting the alpha premium from commoditized data crunching to proprietary context curation. Crucially, he exposes the most persistent behavioral pitfalls observed across sophisticated institutional desks, specifically unpacking how the conservatism bias hampers optimal sizing during initial portfolio construction. Whether you are an asset allocator evaluating systematic strategies or an MFE student analyzing modern trading frameworks, this episode delivers actionable insights into balancing algorithmic risk management with human judgment.00:00 Intro00:01:14 Why systematic quant models require discretionary human judgment00:06:27 A message from Onyx00:07:06 How Two Sigma engineered an institutional alpha capture pipeline00:13:25 Why extreme consensus sentiment creates contrarian trading opportunities00:18:53 Aligning buy-side and sell-side incentives through informational edge00:25:36 How to extract alpha from the information propagation curve00:34:54 Navigating analyst mean reversion and situational weighting00:39:08 How generative AI and digital analysts reshape alpha capture00:48:13 Why a fragmented hedge fund ecosystem ensures market efficiency00:56:17 How modern LLMs accelerate data validation and market entropy01:03:47 Overcoming the conservatism bias in initial portfolio construction
June 25 · 1 hr
Ex-Citadel Quant on Trading the Most Asymmetric Market - Neel Somani
Apply to Onyx’s Junior Tech Graduate Scheme here: https://verichain.io/apply/0aa1debe-ac6c-452f-9421-da6cbf4a3e8cIn this episode of Odds on Open, former Citadel quant researcher Neel Somani breaks down the opaque market structure and alpha generation mechanisms driving institutional power and natural gas trading. Neel explores the foundations of competitive edge within power markets, detailing how transmission line congestion, binding physical grid constraints, and localized supply-demand dynamics create highly asymmetric, high-skew assets. The conversation dives into the operational reality of central research desks within multi-manager commodity platforms, focusing on how quants model weather variance, fuel costs, and thermal generation outages to inform relative-value basis trades. Neel also provides a masterclass on institutional risk management and portfolio construction during extreme tail-risk events, using the 2021 Texas freeze to illustrate how top PMs navigate position sizing and delta-neutral execution when illiquid power grids face catastrophic supply shocks.Shifting from liquid macro markets to the frontier of technology, Neel analyzes the massive infrastructure constraints and power demand scaling driven by AI data centers, outlining the site selection economics and temporary generation plays dictating the space. He evaluates the structural career opportunity cost of entering quantitative finance today relative to the AI paradigm shift, challenging junior talent and MFE students to build defensible technical moats in hardware and GPU kernel optimization. Finally, the discussion delivers a sharp variant view on venture capital valuation models, predicting a severe compressed pricing event for digital assets and software companies as low-switching-cost agentic architectures fundamentally disrupt traditional growth economics, customer retention metrics, and customer acquisition costs (CAC).00:00 Intro00:01:12 Quant researcher execution models within multi-manager hedge funds00:06:17 A message from ONYX00:07:35 How transmission line congestion drives alpha in power markets00:13:24 Capital intensity and managing risk profiles of high-skew assets00:19:19 Why commodity desks prefer domestic power over geopolitical oil risk00:22:55 Portfolio construction and risk mitigation during tail-risk freeze events00:31:36 Capitalizing on the physical infrastructure constraints of AI data centers00:36:25 How agentic architecture redefines software engineering and technical moats00:43:04 Quant career opportunity cost relative to the AI paradigm shift00:56:15 Variant views on venture multiples and agentic customer acquisition economics
June 20 · 1 hr 11 min
LTCM Co-founder Victor Hagani: “Taking Risk Is Always a Negative.”
Apply to Onyx’s Junior Tech Graduate Scheme here: https://verichain.io/apply/0aa1debe-ac6c-452f-9421-da6cbf4a3e8cIn this episode of Odds on Open, we sit down with Victor Haghani, co-founder of Long-Term Capital Management (LTCM) and founder of Elm Wealth, to dissect why institutional alpha frequently breaks down during the position sizing phase. While standard market commentary focuses heavily on asset selection, Haghani establishes that optimizing your risk-adjusted return is an independent, non-zero-sum discipline that dictates long-term survival. We explore the structural friction between expected value and compound return, the misapplication of the Kelly criterion by sophisticated Wall Street portfolio managers, and how treating variance as an internal financial fee reshapes quantitative portfolio construction and risk management.The discussion shifts to edge verification through Haghani’s famous "Crystal Ball" experiment, analyzing how elite macro traders and advanced LLMs process information asymmetry against historical market regimes. Designed for hedge fund analysts, quants, allocators, and advanced finance students, this section provides a rigorous framework for isolating compensated systematic risk from uncompensated idiosyncratic risk. We close with an actionable breakdown of how practitioners should mathematically model and discount their own human capital, offering a definitive blueprint for maximizing lifetime smooth capital accumulation without succumbing to high-volatility ruin.00:00 Intro01:27 LTCM: Why sizing matters more than selection03:00 Expected value vs. risk-adjusted value in portfolios05:15 Why sophisticated investors struggle with sizing bets08:20 The zero-sum reality of beating the market09:30 A message from Onyx10:35 Why most firms lack a risk-adjusted return rubric12:55 Risk as an internal "fee" in portfolio construction16:30 The math of sizing concentrated stock positions20:50 The hidden danger of high-volatility wealth22:20 "How to become a billionaire" is the wrong question27:25 Testing the "Crystal Ball" hypothesis with Wall Street Journal data34:55 How LLMs perform at macro trading games40:35 Can individual investors generate alpha sustainably?47:40 Solving for optimal sizing at Elm Wealth50:25 Risk limits for young investors and human capital57:55 How to estimate the value of your human capital1:02:45 Why changing minds on investing is nearly impossible1:07:35 The most critical factor for a stable wealth curve
June 4 · 1 hr 15 min
Quant Hedge Fund Partner: Raising Capital Is Harder Than Generating Returns
Apply to Onyx’s Junior Tech Graduate Scheme here: https://verichain.io/apply/0aa1debe-ac6c-452f-9421-da6cbf4a3e8cDeWayne Louis (Versor Investments) returns to break down the part of the business almost no one explains: not generating returns, but raising the capital to scale them. After Versor pulled in half a billion dollars for an event-driven strategy with just two and a half years of track record, DeWayne walks through exactly how allocations from multi-managers and managed-account platforms actually get done — and why he argues raising capital is harder than making money.We get into the screening hurdles multi-strats apply (Sharpe thresholds, team, factor orthogonality), how to pitch a secretive pod without knowing its book, and the systematic, data-driven machine Versa built to quantify merger arb across 26 years of catalyst events. Then the conversation turns to the capital-raising playbook itself: external vs internal allocations, fee structures, fund-of-funds vs pods, and why branding and storytelling — not buzzwords like "uncorrelated," "quantamental," or "AI" — are what move an allocator from apathy to conviction.A sharp, tactical episode for emerging and mid-sized managers, allocators, and anyone trying to understand how capital really flows through the multi-manager ecosystem.00:00 Intro01:22 Sourcing capital from multi-strategy managed accounts06:45 Pitching alpha relative to common hedge fund factor exposures09:21 A message from Onyx09:55 Designing systematic models for fundamental event-driven catalysts14:25 The multi-manager due diligence and verification process20:14 Structural mechanics of internal versus external balance sheet allocations28:28 Portfolio transparency differences: Multi-managers versus fund of funds31:55 Why institutional branding is harder than generating returns37:01 Strategic branding mistakes made by emerging fund managers46:46 Applying systematic data frameworks to the capital raising process53:33 Quantifying risk profiles to match multi-manager attributes58:03 Why separately managed accounts dominate institutional allocations01:06:12 Operational skill sets that build robust asset management firms01:12:23 Retaining institutional capital through transparent variance communication
May 28 · 1 hr 4 min
Ex-WorldQuant Head of Data Strategy: Quants “Don’t Care About the Stock Market”
In this episode of Odds on Open, we deconstruct the evolution of alternative data and alpha generation with Matt Ober, former Head of Data Strategy at WorldQuant and Chief Data Scientist at Third Point. We dive deep into the institutional framework required to scale systematic trading strategies, the cultural friction of implementing quantamental processes within long-short equity pods, and the specific mechanisms used by portfolio managers to extract a variant view from massive datasets. From the factory-floor automation of PhD-led quant shops to the high-stakes risk management of activist fundamental funds, Matt reveals how market microstructure and data-driven edge define success in liquid markets.Explore the shift toward the "degenerate economy" and the rising institutional utility of prediction markets like Kalshi and Polymarket for hedging structured KPIs. We analyze the future of decision intelligence through the lens of LLMs and MCPs (Model Context Protocol), discussing how traders, analysts, and allocators can maintain differentiation in a regime of rapid alpha erosion. Whether you are optimizing portfolio construction, refining factor exposure, or seeking a competitive advantage in venture capital, this conversation provides a masterclass in leveraging social networks and information symmetry to secure uncorrelated returns.00:00 Intro01:18 The WorldQuant thesis: Mining alternative data for systematic alpha05:06 Integrating finance expertise into PhD-heavy quant factory pipelines07:00 Scaling the quant factory: Automation and the researcher pipeline09:46 Monitoring dataset performance: Risk controls and alpha decay11:07 A message from ONYX16:38 Quantamental shifts: Transitioning data strategy to fundamental funds22:29 Institutionalizing "Old Guard" firms via top-down data buy-in26:38 Networking for quants: Comparing Tulchinsky and Loeb’s sources of edge32:44 The Degenerate Economy: Prediction markets and the volatility of attention39:42 Non-consensus career bets: Why selling beta is a stickier strategy45:01 Sourcing venture alpha: Identifying exceptional founders and GTM wedges52:30 Institutionalizing prediction markets via structured KPI hedging01:00:39 How MCPs and LLMs democratize decision intelligence01:03:08 The single source of edge: Leveraging social network information
May 24 · 1 hr 9 min
The Secret to Uncorrelated Alpha in Crypto - Leigh Drogen on Starkiller Capital’s Sharpe Ratio of 4
Apply to Onyx’s Junior Tech Graduate Scheme here: https://verichain.io/apply/0aa1debe-ac6c-452f-9421-da6cbf4a3e8cLeigh Drogen, CIO of Starkiller Capital, joins the podcast to dissect the mechanics of a market neutral DeFi strategy currently operating at a 4 Sharpe ratio. We move past surface-level crypto narratives to analyze the quantitative scoring of protocol risk, code provenance, and the identification of incentivized spreads in carry trades. Drogen outlines a rigorous framework for position sizing based on a 1% max-loss rule and explains how Starkiller modulates risk across market regimes to extract uncorrelated alpha while avoiding the pitfalls of unsustainable yield and "fuckery risk" in liquid digital asset markets.The discussion shifts to the persistent alpha of cross-sectional momentum and why Starkiller views block space as a commoditized asset, drawing parallels to the fiber optic glut of the late 90s. From the market structure of token unlock schedules to the evolution of prediction markets like Estimize and Polymarket, we explore the intersection of regulatory arbitrage and table selection. This episode provides institutional-grade insights into portfolio construction, trend following, and the risk management frameworks required to navigate the liquidity and volatility of the modern crypto regime.00:00 Intro01:09 Mechanics of a 4 Sharpe market neutral DeFi strategy03:24 Quantifying protocol risk and code provenance06:40 Case study: Exploiting incentivized spreads in carry trades09:51 A message from ONYX10:53 Three primary sources of alpha in liquid crypto markets14:28 Capacity constraints and institutional yield compression18:54 Position sizing via the 1% max loss rule21:38 Pro-cyclical returns and the risk modulation framework26:44 Compounding capital through trend following and cross-sectional momentum33:35 Why momentum is the only persistent behavioral alpha38:52 Why block space is worthless: The fiber optic analogy42:30 Mitigating "fuckery risk" and vampire attacks in shorts48:39 Extracting alpha from token unlock schedules and market structure51:20 Lessons from building Estimize and the SEC/ForceRank fight55:00 The Polymarket origin story: Arbitraging regulatory hurdles01:01:45 Career risk premia and the value of "eating shit"01:05:34 Table selection: Positioning your career on the right macro curve
May 14 · 1 hr 7 min
“Market Crashes Are Good for My Strategy” - One-Man Hedge Fund PM George Livadas
Apply here: https://onyxcapitalgroup.com/uni-studentsGeorge Livadas, Portfolio Manager and founder of Peregrine Capital, joins the show to break down the mechanics of running a concentrated, defensive long/short strategy as a solo PM. We explore how George generates alpha by systematically avoiding "hedge fund hotel" crowding, focusing instead on microstructure edges within niche sectors like non-bank financials and packaging to maintain a variant view. George details his portfolio construction framework—balancing core quality compounders with tactical value—and explains the math behind delivering equity-like returns while maintaining a beta-adjusted net exposure of approximately 35%.The conversation shifts to the evolving market regime, specifically how the dominance of multi-manager pods has created liquidity opportunities for patient, independent traders to exploit short-term data noise. George shares his technical survival guide for short selling, from managing volatility in "fraud and fad" names to recalibrating his process following the 2021 SPAC boom. We conclude with a deep dive into macro risk management, discussing how to insulate a portfolio against geopolitical tail risks and the psychological discipline required to develop a professional PM skill set without a traditional institutional pedigree.How do you stay independent in a market dominated by pods?00:00 Intro01:18 Selection criteria and sizing for defensive longs06:04 Sponsor break: Onyx Capital Group anniversary event06:42 Portfolio construction: Balancing quality and value factors09:13 How the SPAC boom changed short-side portfolio construction13:42 Why nimbleness and independent thinking generate alpha20:06 Capitalizing on the short-termism of multi-manager pods28:18 Managing macro tail risks without being wrong-footed38:26 Why defensive strategies offer an "inverse pod" return stream42:04 How to develop a professional PM skill set54:37 Circle of competence: Identifying disastrous longs and shorts
May 7 · 1 hr 15 min
“If it is easy and obvious, there is no edge in it” - TD Quant Matt Schrager
In this episode of Odds on Open, TD Quant Matt Schrager discusses the microstructure of municipal bond market making and the technical challenges of extracting alpha from illiquid fixed income instruments. We analyze the shift from low-latency HFT frameworks to the probabilistic modeling and statistical pricing required for securities with fragmented liquidity. Matt details the mechanics of systematic inventory management, risk-adjusted P&L optimization, and the cultural integration of elite proprietary trading teams within institutional balance sheets.Schrager outlines a variant view on finding edge in "ugly," inefficient markets, focusing on the structural opacity of private credit and the electronification of commodities. The discussion covers the evolution of market efficiency, the role of LLMs in credit due diligence, and recruiting strategies for resilient quantitative talent. This episode provides actionable insights for hedge fund analysts, quants, and PMs on the relentless process required to maintain a competitive advantage in evolving market regimes.00:00 Intro00:01:29 Announcing OOO's Newest Sponsor00:02:20 Liquidity and latency differentials in the municipal bond market00:06:37 Probabilistic modeling and statistical pricing for low-frequency instruments00:10:50 Adapting HFT simulation and backtesting to illiquid fixed income00:20:33 Systematic inventory management and risk-adjusted P&L optimization00:27:36 Transitioning proprietary trading culture into a global bank infrastructure00:34:10 Scaling electronic market making into commodities and investment-grade credit00:41:24 Identifying edge in gnarly and inefficient corners of the market00:45:23 Structural opacity and the liquidity evolution in private credit00:56:21 Why elite trading organizations prioritize relentless process over magic01:04:16 Recruiting for resilience and the velocity of fundamental improvement01:11:02 How AI-native skillsets redefine talent in liquid market regimes
April 30 · 1 hr 15 min
Ex-Tudor Quant PM: “There Hasn't Been a New Idea in Trading for 15 Years”
In this episode of Odds on Open, we go deep into the mechanics of edge, credibility, and the structural evolution of the hedge fund industry. Host Ethan sits down with Tom, a veteran Quant PM formerly of Tudor Investment Corp and Moore Capital, to deconstruct what separates the top-tier "pod shops" from the bottom 40% of funds that fail to preserve capital.Tom challenges the common perception of market randomness, arguing instead for a deterministic view of market structure where alpha is captured by modeling participant incentives rather than just price action. We discuss the "Unified Field Theory of Finance," the operational reality of running a billion-dollar book, and why the most dangerous trap for a PM is the "gamma trap"—trading steady returns for catastrophic tail risk.00:00 Intro01:18 Building institutional credibility for early-stage managers03:01 The Pareto distribution of hedge fund returns04:25 Applying the Unified Field Theory of Finance to fair value08:14 Trading against human incentives in a deterministic market13:54 Why allocators don’t steal alpha from prospective PMs18:26 Organizational advantages and risk management in pod shops25:16 Evaluating career edge in quantitative finance for 202630:48 Paul Tudor Jones and the art of game selection33:42 Analyzing the economic viability of starting a new fund35:16 Identifying common retail pitfalls: Mean reversion and arbitrage38:55 Why there hasn't been a new trading idea in 15 years43:22 Case study: Building NLP systems and managing strategy decay50:33 Managing tail risk: Physics vs. deterministic financial distributions55:33 Identifying the gamma trap in short-volatility strategies59:10 Career pathing for PMs after a fund blow-up1:07:53 SBF and FTX: Credibility vs. the "Founder-Genius" archetype1:13:44 Establishing proof-of-concept through audited multi-year returns
April 23 · 1 hr 9 min
“Concentrated Strategies Will Do Extremely Well” - Sean Emory on Outperforming the Index
Sean Emory of Avery discusses the evolution of edge in liquid markets, specifically how to leverage alternative data—from App Store analytics to digital exhaust—to identify fundamental inflection points before they are reflected in the price. We dive deep into Sean’s underwriting process, exploring how institutional investors can use granular data sets to track thesis confirmation and identify a margin of safety in real-time. This conversation provides a technical breakdown of how to separate signal from noise in a market regime increasingly dominated by ultra-short-term microstructure and passive flows. Sean also breaks down his approach to portfolio construction, comparing the risk-return profiles of highly concentrated strategies versus diversified books. He explains why his firm prioritizes "the Six Ms" over standard volatility metrics to mitigate the risk of permanent capital impairment, offering a variant view on traditional risk management. The discussion concludes with the operational realities of the active ETF landscape, the impact of generative AI on market efficiency, and the psychological discipline required to maintain alpha when storytelling and euphoria distort traditional valuation frameworks.

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