Flirting with Models – Details, episodes & analysis

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Flirting with Models

Corey Hoffstein

Business

Frequency: 1 episode/24d. Total Eps: 128

Flirting with Models is the show that aims to pull back the curtain and meet the investors who research, design, develop, and manage quantitative investment strategies. Join Corey Hoffstein, Chief Investment Officer of Newfound Research, on a journey to explore systematic investment strategies, ranging from value to momentum and merger arbitrage to managed futures. For more on Newfound Research, visit www.thinknewfound.com.

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Data updated on 13/10/2026

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Score global : 42%

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Philip & Allan Maymin – Compounding Through Risk, Not Return (S7E35)

Season 7 · Episode 35

Monday, October 12, 2026 • Duration 01:05:29

In this episode, I speak with Philip and Allan Maymin, co-Heads of Global Asset Allocation at Janus Henderson.

Philip and Allan run the asset allocation group founded at Janus Henderson by Nobel laureate Myron Scholes more than a decade ago, and they've arrived there by wonderfully different routes — Philip through LTCM, academia, and behavioral analytics; Allan through high-frequency trading, derivatives, and prop desks.

At the heart of their process is a simple but subversive idea. As Philip put it in our pre-call, "people live in an average return world, and they ought not." What matters to investors is compound growth — and they believe that the surest way to improve compounding isn't chasing higher returns, it's managing risk. Drawdowns destroy compounding and avoiding them is the more tractable lever.

They connect theory to practice through the options market. Calls and puts embed the market's collective, forward-looking view of risk, making them one of the richest sources of information available to an asset allocator. We discuss how they extract those signals and propagate them across more than 4,000 assets to build portfolios around client objectives rather than benchmarks.

Please enjoy my conversation with Philip and Allan Maymin.

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Lucas Schuermann – Swapping Out Perpetual Futures (S7E34)

Season 7 · Episode 34

Monday, September 14, 2026 • Duration 01:14:01

My guest in this episode is Lucas Schuermann, co-founder of Variational, which seeks to bring the trillion-dollar OTC derivatives market on chain.

This is my second episode on Variational. A little over a year ago I spoke with Lucas's co-founder, Edward Yu. In that time, the mission hasn't changed, but a lot else has.

We begin with a re-introduction to the business and its retail-facing platform, Omni. Unlike a central limit order book, where a crowd of competing market makers quote against unknown flow, every trade on Omni is quoted by a single, internal liquidity provider — OLP — through a request-for-quote model that segregates flow. Because OLP knows who it's trading with, it can price retail flow as non-toxic: netting offsetting positions against each other, warehousing what it chooses to keep, and hedging only the residual risk externally. It's a model that let Variational list a long tail of crypto-native assets at competitive spreads, even where on-platform open interest remained thin.

The surge in demand for real-world asset exposure on chain has pushed that model in two directions.

The first is widening where those hedges can go. Rather than trying to rebuild forty years of traditional market depth on a crypto order book, Variational has built a global network of dealer relationships to tap into it directly.

The second is questioning whether the perpetual future is even the right instrument. Perp funding is driven by where the contract trades relative to its index, which makes it volatile and hard to forecast. Variational's answer is a swap: a price-return leg plus an explicit financing leg, priced off short rates — a far more predictable cost of carry for anyone who wants to hold levered exposure for the long haul. And there's currently over a billion dollars of dealer capacity behind it.

I hope you enjoy my conversation with Lucas Schuermann.

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Stacie Mintz – Turning Qualitative Fundamentals into Quantitative Factors (S7E33)

Season 7 · Episode 33

Monday, August 3, 2026 • Duration 47:17

My guest this episode is Stacie Mintz, Managing Director and Head of Quantitative Equity at PGIM Quantitative Solutions.

Stacie has spent 33 years at PGIM, and she's been there for every defining moment of the firm's quant equity effort: a first strategy born from a client's challenge to move beyond indexing, a 1999 decision to abandon Barra and bring the risk model in-house, surviving the quant quake of August 2007, and the post-GFC realization that in a crowded-factor world, it's not enough to be a quant — you have to be a different quant.

We dig into what PGIM's "fundamental quant" label actually means in practice, from a financing factor that asks how a company funds its growth, to a factor taxonomy that includes an unfamiliar Linkages group and — unusually for a quant shop — excludes momentum entirely.

In the back half, we turn to the frontier: turning qualitative signals like board composition and innovation into systematic factors, building models that assess emergent shocks like COVID and AI in real time, and why Stacie calls LLMs "bazookas" — tools powerful enough to blow up what already works, which is exactly why you start with the insight and only then reach for the tool.

Please enjoy my conversation with Stacie Mintz.

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Ben Wellington – Complex Feature Engineering at Two Sigma (S7E32)

Season 7 · Episode 32

Monday, July 6, 2026 • Duration 56:39

My guest this episode is Ben Wellington, Head of Complex Feature Engines at Two Sigma.

In a modern quant process, one might argue that edge can live in three places: the data you can get your hands on, what you do with that data, and how you forecast from it. Ben lives squarely in the middle layer — feature generation — which also happens to be the place AI is reshaping fastest.

So that's where we spend our time. We start with what a "feature" even is, and why, as raw data gets commoditized, the edge increasingly comes from what you build out of it. Then we follow the thread running through the whole conversation: large language models. Ben has a line I keep coming back to — that anything can be language now — and we trace what that unlocks, and whether making feature creation this cheap just democratizes the edge away.

We close on what a quant starting out today should be building toward, and which skills compound most in a career where AI is the dominant tool.

Please enjoy my conversation with Ben Wellington.

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Peter Hecht – Portable Alpha: Solving the Funding Problem of Alternatives (S7E31)

Season 7 · Episode 31

Monday, June 29, 2026 • Duration 01:06:49

My guest this episode is Peter Hecht, co-head of the North America Portfolio Solutions Group at AQR.

Portable alpha is drawing serious attention right now. Long the province of large institutions, it's now being wrapped into mutual funds and ETFs — which means, for the first time, advisors and the individual investors they serve get a seat at the table. So I wanted to sit down with someone who's been thinking about the idea for almost two decades.

We start with the basics — what portable alpha actually is, and why Peter insists the core concept is funding, not leverage. From there we work through the real risks, the cautionary tale of 2008, and the design space: how you organize the alpha and the beta, which overlays to choose, and how to combine them without smuggling in hidden tail correlation.

Then we turn to what matters most for this new audience — sizing, lifecycle, rebalancing inside a daily-liquid wrapper, and the gap between the line-item experience and the actual portfolio impact.

Please enjoy my conversation with Peter Hecht.

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John Gu – Crypto Market Making & The Cold Start Problem (S7E30)

Season 7 · Episode 30

Monday, May 11, 2026 • Duration 01:09:42

My guest today is John Gu, founder and CEO of Caladan, one of the most active market makers in crypto and a firm that has provided liquidity to more than 200 token launches. John's path runs through MIT, AlphaSimplex, Citadel's principal strategies group, and Tower Research before landing in Singapore at the dawn of the ICO era — where what started as a trade on the kimchi premium became the foundation for one of the most active liquidity providers in digital assets.

The thesis of our conversation is what I'll call the cold start problem. In traditional markets, every newly listed stock arrives with scaffolding already in place — a designated market maker, a reference price, a universe of comparables, and decades of regulatory infrastructure. Crypto inverts that. A new token can launch with no orderbook, no comparables, and no clear demand curve. Someone has to quote a two-sided market into that void, and how they do it shapes whether the asset becomes a real, tradable thing — or a graveyard of wide spreads and stranded liquidity.

John and I dig into how you bootstrap liquidity from zero, how the quoting playbook evolves as a market matures, the economics of token market making contracts, and how that same infrastructure now bridges into structured products and treasury solutions for token foundations.

Please enjoy my conversation with John Gu.

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Faheem Osman – Commodity QIS: An Under-Appreciated Source of Systematic Returns? (S7E29)

Season 7 · Episode 29

Monday, April 6, 2026 • Duration 01:06:56

In this episode I speak with Faheem Osman, Managing Director and Global Head of QIS Structuring at Macquarie Group.

Faheem has spent nearly two decades inside major investment banks — first at Citi, where he spent about ten years on the commodities trading and structuring side, and now at Macquarie, where he's built out their cross-asset QIS business. Commodities, though, remain firmly in the DNA of what Macquarie does, and it's where Faheem cuts his teeth.

We spend the bulk of our conversation exploring commodity QIS as a distinct and, in Faheem's view, underappreciated source of systematic returns. Faheem walks us through strategies like curve carry and index congestion, explains why commodities have historically delivered some of the highest risk-adjusted returns of any asset class in QIS, and makes the case for why these premiums haven't simply been arbitraged away. We also dig into commodity volatility selling, the shift toward weekly options, and close with a timely discussion on what the explosion of 0DTE options means for the vol risk premium more broadly.

Please enjoy my conversation with Faheem Osman.

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Richard Craib - Crowd-Sourced Alpha with Numerai (S7E28)

Season 7 · Episode 28

Monday, February 23, 2026 • Duration 55:59

Today, I’m speaking with Richard Craib, the CEO and founder of Numerai.

If you’ve heard of Numerai before and thought of it as an interesting experiment at the intersection of data science and crypto, it’s worth updating that mental model. Over the last few years, Numerai has quietly grown from roughly $60 million in assets to over $600 million. JPMorgan has invested and secured $500 million of capacity, and Numerai recently raised a Series C at a $500 million valuation led by top university endowments. This is no longer a toy project. It is a real, institutional-scale market-neutral hedge fund with a very unconventional engine.

In this conversation, we go deep into how Numerai actually works. Richard walks through the core insight behind Numerai’s design: that crowd-sourced alpha only works if incentives are aligned, not just participation. Simply opening up data and ranking models creates incentives to game the system, not to produce durable signals. That realization led to the introduction of the Numeraire token. By forcing researchers to stake real capital behind their predictions, Numerai shifts from a leaderboard-driven experiment to a capital-weighted signal engine. Instead of rewarding activity, the system rewards conviction, accountability, and uniqueness, creating a self-filtering model that naturally reduces noise and discourages the behaviors that caused earlier crowd-sourced platforms to fail.

We also talk about portfolio construction and risk management, including how Numerai neutralizes common factor exposures, what went wrong during the 2023 drawdown, and how those lessons reshaped their approach to diversification and concentration. Finally, we look forward, covering the limits of crowd-sourced modeling, the next frontier for Numerai’s research ecosystem, and how Richard sees AI agents reshaping model development.

Please enjoy my conversation with Richard Craib.

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Ruslan Fakhrutdinov – Extended Exchange and Vault Tokenization (S7E27)

Season 7 · Episode 27

Tuesday, February 17, 2026 • Duration 58:01

Today, I’m speaking with Ruslan Fakhrutdinov, the founder of Extended, a decentralized perpetual futures exchange.

Ruslan is the fifth perpetual futures exchange founder I’ve had on the podcast, and that’s very intentional. Flow continues to move toward these platforms, and while trading perps can feel familiar to anyone coming from centralized or traditional exchanges, the way risk is absorbed and resolved under the hood for decentralized exchanges can be very different.

In this episode, we go deep on the design of perp DEX vaults and the role they play as a liquidity and risk backstop for the entire exchange. Ruslan walks through how platforms choose between protecting system solvency, safeguarding vault depositor capital, and managing trader losses, particularly during stress events. We also discuss how settlement finality, governance intervention, and liquidation design determine where losses ultimately land.

We spend time on Extended’s introduction of vault shares as collateral, why that design can be powerful, and the new risks it introduces if boundaries aren’t explicit. Ruslan lays out the risk-management waterfall: when the vault steps in as a counterparty, when it refuses additional exposure, and when traders are pushed into forced deleveraging or auto-deleveraging instead.

We close by connecting this framework to Extended’s next phase, expanding cross-asset margin, and what it takes to design a system that still behaves predictably when markets break.

Please enjoy my conversation with Ruslan Fakhrutdinov.

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Angana Jacob - Data as the True Competitive Moat (S7E26)

Season 7 · Episode 26

Monday, February 9, 2026 • Duration 57:22

Today, I am speaking with Angana Jacob, Head of the Research Data group within the Enterprise Data business at Bloomberg.

We talk about Angana’s career path through quantitative research and data platforms, and how the industry has evolved from a world dominated by bespoke models and backtests to one where many models have become increasingly commoditized. A central theme of our conversation is the idea that while models are easier than ever to replicate, data — how it’s sourced, cleaned, standardized, linked, and delivered — has become the true competitive moat.

We discuss what it means to “do data correctly,” how Bloomberg decides which datasets to build or sunset, how modern quants think about their data pipelines and tech stacks, and why aligning research data with production and back-office systems matters more than most people realize. Throughout the episode, we focus on Bloomberg’s goal of shortening a client’s time to alpha, and what that looks like in practice.

At its core, this episode is about a simple but powerful idea: when everyone has access to similar models, durable edge increasingly comes from the data beneath them.

Please enjoy my episode with Angana Jacob.

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Flirting with Models – Details, episodes & analysis

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Flirting with Models – Details, episodes & analysis

Podcast details

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Apple Podcasts

Spotify

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Latest published episodes

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Apple Podcasts

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