Odds on Open

Roger Ehrenberg ran DB Advisors, Deutsche Bank’s $6 billion multi-manager hedge fund platform, overseeing around 20 trading teams across statistical arbitrage, high-frequency trading, CTA, and special situations. He went on to found IA Ventures and now runs Game Changers Ventures. In this episode of Odds on Open, Ethan Kho and Roger get into how risk was allocated across pods before the Millennium and Citadel era, and why correlations go to one in a crisis. They also cover the LTCM lesson on time-horizon diversification and how to size positions when semiconductor volatility is running far above historical norms. They debate whether small, nimble managers or scaled multi-manager platforms capture the alpha from AI, and why the best small funds look like high-Sharpe volatility market makers that can’t scale.The second half moves into venture capital through the lens of a former hedge fund risk manager. Topics include Cliff Asness’s “volatility laundering” critique, right to win in a market where VC money is all chasing AI momentum, slugging percentage versus hit rate, portfolio concentration with 25 shots on goal, follow-on and pro rata discipline, and when to sell secondaries. Roger explains where venture process errors come from and the founder pattern behind his biggest winners. He also makes the contrarian case for investing outside the crowded AI infrastructure trade, compares today’s interconnected AI capex to 2007–08 rather than the dot-com bubble, and gives career advice for students and junior analysts whose skills are being commoditized by AI. If you care about hedge funds, quant trading, portfolio construction, risk management, or early-stage investing, this one is for you.

Former Goldman Sachs head of natural gas trading John Knorring delivers a lecture on commodities trading from first principles, adapted from the one he gives to Princeton financial engineering students. Starting from one equation, supply minus demand equals the change in inventory, he explains how storage constraints drive price, why crude oil went negative in 2020, and why US natural gas is so volatile. Topics include Henry Hub futures, physical delivery and arbitrage, basis risk, the storability of coal, oil, gas, and power, and how weather shocks can double nat gas prices in a week. Essential viewing for energy traders and quants.Knorring then covers the shale revolution and Aubrey McClendon, how low prices built demand through power burn, LNG exports, and AI data centers, and the Goldman trading framework: idea generation, trade expression, execution, and money management. He walks through his bullish silver trade, from the structural deficit and gold-silver ratio to buying futures and cheap upside calls, and what he got wrong at $120. The episode closes with market trends, including position sizing lessons from Amaranth, the solar duck curve, the US LNG export wave, and why physical gas traders will outlast automated derivatives desks, plus timeless career advice for Wall Street.

Former Goldman Sachs oil derivatives trader and GSR Head of DeFi Simranjeet Singh breaks down market microstructure, liquidity provision, and risk management across traditional commodities and crypto assets. Simran recounts navigating the historic April 2020 WTI crude collapse to -$37.63, detailing how desks adapted option pricing models when log-normality broke under 400% annualized volatility, shifted margining frameworks, and managed balance sheet risk across massive sovereign hedging flows like Mexico’s Hacienda Hedge. He breaks down how sell-side dealers monetize flow, warehouse basis risk on bespoke structured products such as producer three-way collars, and coordinate with credit and CVA desks when sharp market drawdowns trigger counterparty liquidity shocks.Transitioning from sell-side commodity derivatives to systematic buy-side trading at GSR, Simran explains why all trading strategies ultimately reduce to momentum or mean reversion. He unpacks the mechanics of delta-neutral perpetual futures funding rate arbitrage, navigating liquidity and market impact as a taker, and the operational risk lessons learned from a $3.1M single-day drawdown. Exploring current market regimes, Simran details where macro alpha is shifting—highlighting the opaque, emerging OTC complex around power, electricity, and AI compute—and outlines the market design thesis behind Monaco Exchange to disintermediate perpetual future listings and democratize 24/7 global market access.

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.