Show Notes
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.
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David Orr returns to Odds on Open to unpack how he sustains a 50% annualized return and a 2.1 Sharpe ratio by stripping the multi-manager model down to raw alpha generation. We deconstruct his firm’s AI-driven risk architecture, detailing how proprietary factor models recalculate custom basket correlations in real-time to manage tail risk across a 400% levered portfolio. David also breaks down his personal discretionary process, explaining his strict two-hour cap on single-name equity research to eliminate sunk-cost bias, the fatal mechanics of shorting revenue growth, and why institutional pod shops structurally sacrifice top-tier returns to optimize for AUM fee harvesting.Beyond portfolio construction, we explore the unit economics of scaling a high-performance fund through unconventional talent sourcing. David explains how he evaluates pure live track records to recruit non-consensus PMs, utilizing the fund’s long/short vehicle to offer massive tax deferral advantages for incoming high-frequency traders. We also examine his structural framework for the AI trade—specifically why hyperscalers offer superior downside protection and take-or-pay ROIC compared to hardware manufacturers—and his thesis on why unplugging from consensus narrative feeds is required to isolate variant views in shifting market regimes.
Checkout Flux 4.0 here: https://www.flux.live/flux4/index.html On this episode of Odds on Open, hedge fund manager Joe Walsh joins Ethan Kho to break down how probabilistic decision-making and bankroll management from high-stakes poker translate into institutional equity outperformance. Walsh outlines his framework for game selection across liquid markets, detailing why he deliberately avoids the crowded, factor-constrained time horizons of multi-manager pod shops and indiscriminate passive ETF flows to capture mispriced fundamentals. From exploiting negative gamma events, forced de-grossing cascades, and liquidity cycle dislocations to balancing expected value against variance, this conversation explores how disciplined capital preservation and downside underwriting unlock high-compounding, low-drawdown portfolio construction.The discussion then pivots to tactical execution, asymmetric bet sizing, and the mechanics of buyside alpha generation. Walsh breaks down why he scales positions on the “right side of the V” rather than fighting price trends, his strict risk limits and borrow cost considerations on the short side, and how George Soros’s reflexivity framework dictates narrative-driven multiple expansion and terminal value compression. Bringing the framework to life, he maps out value chains and shifting profit pools across emerging asset classes—dissecting the entire AI infrastructure trade from hyperscaler CapEx sustainability and data center power grid constraints to thermal cooling bottlenecks and specialized offshore industrial monopolies. This masterclass is essential viewing for long/short equity analysts, portfolio managers, quantitative traders, and allocators seeking durable, structural edge in modern markets.
Geoffrey Williams spent more than a decade at Goldman Sachs, where he traded structured products through the 2008 financial crisis and later co-ran the CMBS trading business. In this episode of Odds on Open, he takes Ethan Kho inside the Goldman mortgage desk as Bear Stearns and Lehman collapsed. He explains how banks sold tens of billions of super senior protection on ABS CDOs for 10 basis points a year, and what it was like to trade TABX and ABS CDOs as AAA paper repriced from basis points to points upfront. He also breaks down how conduit CMBS is structured and tranched, why commercial real estate moves in cycles across malls, office, and life science, and how post-GFC capital rules pushed securitized credit risk off dealer balance sheets and onto hedge funds.Geoffrey now runs 1543 Capital LP, an opportunistic structured finance hedge fund, with a co-CIO who came from Brevan Howard. The fund focuses on end-of-life CMBS, residential solar ABS, and other dislocated credit. He walks through how he underwrites a CMBS bond loan by loan, when desktop tools like Google Earth are enough and when you need to see the property, and how he sizes positions to survive unknown unknowns while targeting mid-teens unlevered returns. The conversation also covers hedging macro tail risk from deficits, rates, and AI disruption, how populist politics and the proposed California wealth tax shape his real estate exposure, luck versus skill in finance careers, thinking in bets as an entrepreneur, and the biggest mistake structured credit PMs make: forgetting that credit markets move in step functions.
Checkout Flux 4.0 here: https://www.flux.live/flux4/index.html In this episode of Odds on Open, Alpaca Co-Founder and CEO Yoshi Yokokawa breaks down the changing microstructure of systematic trading, the democratization of quantitative R&D, and why AI agents alone will never grant you a defensible market edge. As LLMs compress strategy iteration and backtesting feedback loops, the traditional line between retail quants and institutional fund managers continues to blur. Yoshi shares high-signal data from Alpaca’s API platform—tracking a 4x explosion in active algorithmic developers—and explains why execution discipline, behavioral risk control, and operational frameworks remain the true drivers of alpha in liquid markets.The conversation dives deep into the structural economics of modern asset management, analyzing the recent surge of YC-backed AI hedge funds, the reality of competing against multi-manager scale, and why top-tier trading firms spend aggressively on compute. Drawing from his background as a former trader at Lehman Brothers and his journey building global brokerage infrastructure, Yoshi explores the rise of entity-based solopreneurs, tokenized equities, and MCP-ready financial services. Whether you are a portfolio manager, quant developer, or market allocator, this episode provides actionable frameworks for handling strategy recalibration through regime shifts and cultivating defensibility in an increasingly commoditized financial landscape.
Checkout Flux 4.0 here: https://www.flux.live/flux4/index.html Chris Camillo and Tom Costello go head-to-head on Odds on Open's first every debate episode. They answer a question every trader eventually confronts: who is actually better positioned to take risk — a concentrated retail investor with no LPs, mandates, or career risk, or an institutional hedge fund manager with a two-and-twenty product to protect? Chris, who compounded $20K into roughly $80 million over 18 years using his "social arb" strategy, argues that a 50–70% drawdown is rational inside a properly bucketed, levered, long-horizon risk account. Tom, a former Tudor, Moore, and Caxton PM who now runs a market-neutral fund targeting ~20% annual returns with a 1.4% peak drawdown, counters with the Pareto distribution of hedge fund and day-trader returns, the beta-versus-alpha logic behind institutional portfolio construction, and why allocators refuse to pay for beta they can get on margin themselves. Along the way they debate 3x leveraged S&P ETFs and the hidden roll and theta costs inside them, "too big to fail" AI concentration, the Situational Awareness blowup, crypto's 98% correlation trap, and why overfit backtests stopped landing in Tom's inbox.The second half is a live stress test of social arb as an edge: Chris walks through the Beacon Roofing hailstorm trade built on Google Trends, the Hunger Games and Stranger Things trades built on conversational data, and the e.l.f. Cosmetics trade triggered by a single Jeffree Star video that no sell-side cosmetics analyst had seen. Tom critiques it as an institutional money manager — alpha decay, crowding, discretionary-desk constraints, and whether Citadel plus LLMs will systematize TikTok sentiment before retail's information asymmetry is arbitraged away. If you care about risk management, leverage, position sizing, uncorrelated returns, alternative data, market microstructure, and where retail traders still hold a structural advantage over multi-manager pod shops, this episode is for you.