Flirting with Models

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.

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.

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.

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.

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.

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.

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.

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.

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.

A few years ago, I sat down with Moritz Seibert and Moritz Heiden of Takahe Capital to talk about trend following at the edges of the futures markets: places where liquidity is thin, contracts are obscure, and capacity constraint is a feature, not a bug.

Since then, despite strong performance, asset growth, and even winning industry awards, they made a very un-industry decision: they shut down their original fund.

In its place, they launched a new Global Markets Fund built to stay small, so they can trade calendar and product spreads, niche agricultural markets, and other idiosyncratic contracts at equal risk to more standard markets.

In this conversation, we unpack that decision, explore how you systematize trend on markets where liquidity does not exist on screen, and go deep on why spreads represent a fundamentally different opportunity set than outright futures.

We also talk about what’s next: from prediction and event markets to new ways of thinking about macro trends and alternative data.

I hope you enjoy my conversation with Moritz Seibert and Moritz Heiden.

In this episode I speak with Annanay Kapila, founder and CEO of QFEX, a 24/7 centralized perpetual-futures exchange for traditional financial markets.

Before founding QFEX, Annanay worked at Flow Traders and Tower Research, where he was introduced to high frequency trading and market microstructure in both crypto and traditional markets. Insights gleaned during these experiences lead him to the conclusion that the perpetual futures model applied to traditional, so-called “real world asset” markets, like equities, was an inevitable future and one he wanted to build.

In this episode, we discuss the ramifications of what that world looks like. First, we discuss what perpetual futures are and their distinguishing characteristics from traditional futures. Then we discuss how perpetual futures can work in markets – like single-name equities – where the underlying do not trade 24/7, and have unique features like corporate actions, opening and closing price auctions, and limit-up/limit-down bounds.

A consistent thread throughout the entire conversation is risk management. When leverage is your key feature, it is important to think long and hard about how and when liquidations might occur and the safest way to process them.

Finally, we discuss why Annanay believes why perpetual futures will succeed where spot tokenization failed and his view on the current regulatory landscape.

Please enjoy my conversation with Annanay Kapila.

In this episode, I speak with Jay Rajamony, Director of Alternatives at Man Numeric.

Jay has been with the firm since 2004, giving him a front-row seat to the evolution of quant equity: from simple factor models and broad signals to today’s world of alternative data, model ensembles, and human-machine collaboration.

We start with the history: what’s changed in quant over the last two decades, why the 2007 quant quake still matters, and how the definition of “alpha” has shifted alongside new tools and data.

From there, we explore the interplay between factors and macro regimes, how sparse datasets are reshaping the research process, and what it means to manage risk in a world where your models don’t always line up with reality.

Jay also offers a compelling perspective on how modern quant investing isn’t just about signal breadth anymore—it’s about firm breadth, organizational design, and knowing when to lean in and override the machine.

Please enjoy my conversation with Jay Rajamony.

In this episode I’m joined by Vladimir Novakovski, founder and CEO of Lighter, a decentralized crypto exchange.

To kick off the conversation, we explore Lighter's three big design choices: it’s built as a custom Layer-2 on Ethereum, it relies on zero-knowledge circuits for proving transactions, and it runs with a private sequencer. Don't worry – if that sounds like gibberish, Vlad explains it all. Each of those decisions comes with trade-offs — but also big potential advantages.

We discuss why Ethereum remains the natural home for new rollups, from inheriting its security to tapping into DeFi’s growing composability. We also break down what zk circuits actually are, why they matter for trust and security in a derivatives exchange, and how they’re verified in practice.

From there, we tackle the business side: how you bootstrap liquidity in a brand-new DEX, why Lighter went with an unusual fee model and the key lessons learned during an extended private beta.

Finally, we zoom out to the bigger picture. What might DeFi look like if composability really takes hold? Could specialized rollups like Lighter become the backbone of an on-chain financial system, rather than just another venue for speculation?

Please enjoy my conversation with Vlad Novakovski.

In this episode, I speak with Antti Ilmanen, Principal and Global Co-head of the Portfolio Solutions Group at AQR Capital Management.

Antti has long been one of the most thoughtful voices in the world of expected returns, having written not one, but two landmark books on the subject. But in his latest paper series, he returns to the topic with fresh urgency—probing the difference between objective and subjective expectations, and asking why even rational models can go so wrong in real time.

We explore everything from CAPE ratios and market timing accusations, to why equity investors tend to extrapolate while bond investors expect mean reversion. We dig into how behavioral biases, valuation anchors, and structural shifts collide when forming capital market assumptions—and how Antti and the AQR team try to navigate that mess themselves.

If you’re in the business of long-term forecasting or just curious why markets often act like they’ve never read the textbooks, this is a conversation you won’t want to miss.

Please enjoy my conversation with Antti Ilmanen.

In this episode, I speak with Chris Carrano, Vice President of Strategic Research at Venn by Two Sigma.

Chris has had a rare vantage point in the world of factors — spanning smart beta, long/short hedge funds, and risk modeling — and that experience has shaped a thoughtful view of what factors really are and how they can be practically used.

We dive into the philosophy and design behind Venn: why it uses just 18 orthogonalized factors, how it blends Lasso and OLS to reduce overfitting, and why it prioritizes interpretability over complexity.

We also tackle messy real-world challenges: how to analyze private markets with sparse data, how to trust synthetic return streams, and where to draw the line when using monthly snapshots that embed structural portfolio shifts.

Finally, we explore what it means to make factor results actionable—whether through stress testing, residual interpretation, or portfolio diagnostics.

Please enjoy my conversation with Chris Carrano.

In this episode I speak with Jeffrey Rosenberg, Managing Director at BlackRock where he leads active and factor investments for mutual funds, ETFs, and institutional portfolios for the Systematic Fixed Income team.

In the first half of the conversation we discuss the history of quant fixed income. Specifically, its evolution within the halls of sell-side institutions and how solutions were shaped by demand for underwriting, securitization, and derivatives.

We then make the leap to the buyside, where Jeff outlines the topology of systematic fixed income solutions at BlackRock. We quickly dive into the details, discussing topics such as: why factor investing exists predominately in the credit space, why characteristic specificity within the fixed income space is so important, why quant fixed income needs more PMs but fewer researchers than quant equity, how ETFs changed the liquidity landscape, and whether the equity pod-shop model is possible for fixed income.  

What ultimately becomes clear, through both explanation and example, is that while the terms and ideas of systematic fixed income will be familiar to those in the quant equity space, the Devil lies deeply in the details of implementation.

I hope you enjoy my conversation with Jeff Rosenberg.

In this episode I speak with Edward Yu, co-founder of Variational. 

We begin the conversation with Edward’s background in crypto OTC markets. He explains how the space evolved away from Telegram chats, the complexities of pricing derivative structures on the long-tail of alternative crypto currencies, and the sources of natural flow in the space.

This experience led Edward to co-found Variational, which seeks to bring the trillion dollar OTC derivatives market on-chain by disaggregating settlement, margining, and derivative payoff logic into programmable primitives.

Built on top of Variational is the OMNI perp dex – or decentralized perpetual futures exchange for the non-crypto-speaking listeners. Unlike other perp dexes that are build around a centralized order book, OMNI effectively acts as a user interface to a OTC RFQ system. On the other side is OLP – the OMNI Liquidity Provider. This structure allows OMNI to provide significant depth of liquidity on a huge breadth of investable assets despite the platform being in closed beta at the time of recording. Given its unique design, we spend a significant amount of time discussing the pros, cons, and risks of this structure.

This conversation is, obviously, out of my usual realm. But for those listeners interested in market structure and where the world of finance may be headed, this is one not to miss.

Please enjoy my conversation with Edward Yu.

My guest this episode is Benjamin Hoff, Global Head of Commodity Strategy and Research at Société Générale.

Ben started his career in rates before making the jump to commodities, and that lens—shaped by curve arbitrage, convexity, and carry—colors everything he does. In this conversation, we explore how commodities differ fundamentally from other asset classes: the importance of cash-and-carry economics, the sparse information cadence that rewards technical models, and the physical realities that challenge purely quantitative approaches.

We also dive into Ben’s more recent work on the geometry of the futures surface, how convexity and skewness may be misunderstood, and why tools like Lévy area might help uncover non-linear structure in the data.

Whether you’re deep in the weeds of term structure trading or just curious about how to systematize chaos in barrels and bushels, this is a conversation you won’t want to miss.

My guests today are Roxton McNeal, Managing Director and Head PM of QIS Investments and Siddharth Sethi, portfolio manager and Head of QIS structuring. Together, they’re spearheading the development of QIS-driven solutions at Simplify.

In this conversation, we explore what it takes to build and manage a multi-strategy QIS portfolio—from infrastructure requirements to portfolio construction and risk management. We discuss:

• The structural vs. academic premia distinction and why it matters.

• How Simplify evaluates and customizes QIS offerings from banks.

• The need and challenges of dynamic allocation across dozens of strategies.

• How QIS strategies integrate with traditional beta portfolios.

• The operational and counterparty considerations of trading these strategies.

For those interested in the practical realities of QIS investing, this episode provides a deep dive into both the opportunities and challenges of running a systematic, multi-strategy portfolio.

I hope you enjoy my conversation with Roxton McNeal and Siddharth Sethi.

Scott Phillips is just the second independent trader I’ve interviewed for this show.

Like many independent traders, Scott found that his constraints – including the size of their capital pool, the ability to execute trades efficiently, and a lack of supporting infrastructure – made trading anything but loose-pants trend following almost impossible in traditional markets.

These constraints led Scott to look for easier markets to trade: markets where the edges were so big they could survive inefficient implementations. All of which brought Scott to crypto in the late 2010s.

While our conversation is, at a high level, mostly about trend following, we spend a lot of time discussing what makes trading these markets unique. For example, with tens of thousands of spot cryptocurrencies, how do you choose what to trade? How do you choose which venues to trade at when liquidity is so fragmented? How do you deal with the fact that both crime and degenerate gambling are real idiosyncratic factors?

More than anything, painted between the lines, Scott provides a master class in thinking about edges.

I hope you enjoy my conversation with Scott Phillips.

Today I’m talking to Thao Tran, Co-founding Partner at Vamient Capital.

This episode was born from a question I had watching the NFT market place: how do you make markets in illiquid, non-fungible assets? Clearly people were doing it and I wanted to know how it differed from traditional market making.

Several people recommended I speak with Thao, and she was kind enough to oblige, despite NFT market making being just a small component of what she does. In this conversation, we walks me through how the NFT market place has evolved, how she thinks about managing inventory risk, key features that impact spreads, and how platform evolutions changed orderbook strategies.

In the back half of the conversation, Thao shares her thoughts on the state of crypto markets today, the emerging opportunities in decentralized exchanges, and how the landscape of alpha opportunities has changed over the last two years.

I hope you enjoy my conversation with Thao Tran.

My guest today is Victor Haghani, founder of Elm Wealth.

Victor is, in many ways, one of the last tactical asset allocators standing after the 2010s. That might be because Victor wouldn’t categorize himself as such. Rather, he sees his dynamic index investing approach not as a tactical alternative to traditional static portfolios, but as the rational approach for anyone starting from first principles.

This conversation dances between theory and implementation. Victor is just as comfortable sharing his thoughts on where equity market risk comes from as he is defending payout-adjusted CAPE as a metric for forecasting long-run returns.

If you’re passionate about asset allocation, you’ll find lots to think about in this one.

Please enjoy my conversation with Victor Haghani.

In this episode of the Get Stacked

Investment Podcast, Corey and Rodrigo have an insightful conversation with

Jonathan Glidden, Chief Investment Officer of the Delta Airlines Pension Plan.

Since joining in 2011, Jonathan has been pivotal in elevating Delta’s pension

plan funded status from 38% to over 100%. They delve into Jonathan's

unconventional career journey, his implementation of portable alpha strategies,

and share valuable lessons learned from turbulent financial periods such as

2008 and 2020. Whether you're a seasoned investor or new to the concept of

portable alpha, this episode provides a masterclass on optimizing pension plan

management through innovative investment strategies.

In this episode, I speak with Farouk Jivraj, Portfolio Manager and Head of Alternative Risk Premia at Fidelity Investments’ Asset Management Solutions division.

After spending nearly a decade on the sell side, Farouk joined Fidelity in 2021 with the goal of building out an alternative risk premium platform, tapping into the best of what both the sell-side QIS desks have to offer and what can be built in-house.

We spend the majority of the conversation peeling apart the layers of Farouk’s 5-step process for implementing alternative risk premia strategies. He shares his thoughts on how to classify different premia, why thoughtfully-constructed peer groups are an important evaluation tool, how to go about selecting specific strategies, how to construct portfolios of alternative risk premia, and the actual rubber-meets-road implementation practicalities.

Please enjoy my conversation with Farouk Jivraj.

In this episode I chat with Giuseppe Paleologo – or Gappy as he likes to be called. Currently on garden leave, Gappy has previously worked in Risk & Quantitative Analytics at Citadel, as Head of Enterprise Risk at Millennium, and most recently as Head of Risk Management at HRT.

We begin the conversation with a discussion as to what a quant researcher actually does at a multi-manager hedge fund. As a semi-support role to the fundamental PMs, Gappy explains how portfolio manager coverage, factor hedging, and internal alpha capture can all work together to help maximize firm P&L.

We then discuss the broad field of factor research and portfolio construction, where Gappy shares some of his strongly held views, both on how factors should be constructed as well as how they should be utilized. Topics include returns versus characteristics, mixing versus integrating alpha signals, single- versus multi-period optimization, and linear- versus non-linear models.

Please enjoy my conversation with Giuseppe Paleologo.

On this episode, Ben Carlson and Michael Batnick are joined by Corey Hoffstein of Newfound Research to discuss: managed futures, return stacking, using leverage effectively, and much more!

My guest in this episode is Kris Abdelmessih, co-founder of moontower.ai.

Kris began his career at SIG, where he worked as a market maker in several different option pits, before moving to Parallax where he ran a relative value commodities volatility book. For the last five years, Kris has been writing on his blog Party at the Moontower, which is one of my favorite reads for all things probability, payoff space, trading, optionality, and seeing the world through a volatility lens.

Kris is a passionate educator, so it should come as no surprise that learning is a key thread throughout this entire episode. Kris discusses how learning is accelerated in the pits and how we can think about replicating it in electronic space. Kris discusses what he had to unlearn and relearn in his move from market making to relative value trading. He also shares his thoughts about how firm lineage influences how you learn to trade markets.

Finally, we discuss Kris’s newest venture, moontower.ai, which seeks to provide a “volatility lens” to opinionated traders to help them better express their bets in option space.

There is a lot of experience to unpack in this one.

I hope you enjoy my conversation with Kris Abdelmessih.

In this episode I speak with Bill Gebhardt, founder of 10Dynamics.

Bill spent the better part of his career as a discretionary energies trader, with roles at Koch Industries, Merrill Lynch, Deutsche Bank, and Trailstone. In May 2020 he struck out on his own to co-found 10Dynamics.

Given Bill’s fundamental and discretionary background, it may come as a surprise that 10Dynamics runs a fully systematic process. This dichotomy serves as the foundation for much of our conversation, where Bill provides insight into where and how his discretionary background informs the systematic process, both from a signal and a risk management perspective.

We discuss the types of signals 10Dynamics incorporates into their process, how their risk management system is designed to reflect Bill’s experience managing discretionary traders, and how they’ve designed their operational risk management to allow them to trade intraday with a small team.

Please enjoy my conversation with Bill Gebhardt.

In this episode, I speak with Nicolas Mirjolet, CEO and Co-Head of Research at Quantica Capital.

We begin with Nicolas’s experience operating a statistical arbitrage fund, where he provides his thoughts as to what makes a strategy easier or harder to scale a business on. Nicolas also provides some context for his somewhat counter-intuitive view that the larger players had a bigger edge in this capital constrained space.

We then transition to Quantica’s flagship managed futures program. Nicolas explains that while Quantica is a price-based trend follower, they apply a multivariate approach to their signal analysis. We discuss how the approach works and how it contrasts against a standard univariate approach. Specifically, Nicolas shares his thoughts on how the multivariate approach impacts the portfolio return profile and why you may want more or fewer variables in your signal universe than your tradable market universe.

We end the conversation with Quantica’s most recent quarterly research paper, which provides quantitative insight into the convexity versus robustness tradeoff trend managers make when they add more markets to their portfolio.

Please enjoy my conversation with Nicolas Mirjolet.

Welcome to the inaugural episode of the Get Stacked Investment Podcast. This episode brings together Corey Hoffstein, Rodrigo Gordillo, Mike Philbrick, and Adam Butler to dive deep into the concepts of Return Stacking, market efficiency, and investment strategies beyond traditional stock picking. Providing insights into Return Stacking's relevance in today's investment landscape, the importance of structured diversification to enhance portfolio sustainability and its potential to create excess returns with more confidence than traditional stock picking.

This podcast episode serves as a comprehensive introduction to Return Stacking and provides valuable insights for investors looking to navigate the complexities of modern markets with innovative strategies.

In this episode I chat with Markku Kurtti, author of the blog Outcast Beta.

Markku is classically trained as an electrical engineer and works on receiver algorithms for mobile phones. A passion for investing, however, lead him to pursue an MS in Finance and an interview with Ed Thorp compelled him to devote his time to better understanding compounding processes.

This obsession has driven him to develop a number of analytical and numerical models that provide differentiated insights into topics such as “why do most individual stocks historically underperform cash,” “how many stocks should an active manager actually hold,” and “how does the uncertainty of uncertainty help explain the equity risk premium puzzle?”

With Markku’s work, I’m reminded of the phrase: all models are wrong, but some models are useful. His outsider’s take provides some unique insights into the benefits, and opportunity costs, of diversification.

I hope you enjoy my conversation with Markku Kurtti.

In today’s episode I speak with Otto van Hemert, Director of Core Strategies at Man AHL.

After briefly touching upon Otto’s background, we dive into one of his most popular papers: The Best Strategies for Inflationary Times. Otto shares the inspiration for the research as well as some of what he feels were the less obvious results.

Trend strategies, which were a standout winner in the inflation resilience horse race, serve as the bridge to a discussion on seasonality. Interestingly, Otto’s research suggests that long-term trend signals are actually capturing seasonality effects!

Otto shares his thoughts on different approaches to measuring seasonality, why he believes seasonality emerges in both commodities and financial markets, and how to think about combining trend and seasonality in a single portfolio.

Please enjoy my conversation with Otto van Hemert.

My guest this episode is Clayton Gillespie, VP at Deutsche Bank where he works in quant equity research for the QIS team.

Clayton began his career at Credit Suisse HOLT, where he got his hands dirty in extracting fundamental information. This formative experience dramatically impacted how he views how fundamentals should be incorporated into quantitative equity strategies.

Today, at DB, he strives to improve quantitative equity strategies by anchoring them with a strong fundamental understanding.

We discuss how fundamental and statistical interpretations can be at odds, how a strong fundamental understanding can help with the identification of emergent risk factors during regime changes, and how best to incorporate fundamental insights while avoiding potential biases from the analysts who deliver them.

Please enjoy my conversation with Clayton Gillespie.

In this episode I am joined by Hari Krishnan, Head of Volatility Strategies at SCT Capital and author of the books Second Leg Down and Market Tremors.

This is Hari’s second appearance on the show, but he comes to us with a very different topic: how to develop a low carry hedge for a commodity bull market.

Taking a similar line of thinking to his book Market Tremors, Hari evaluates the market through the perspective of both commodity producers and consumers. By understanding their business incentives, Hari believes he is better able to understand their market positioning and the potential imbalances created in both futures and options markets.

We discuss the conditional impacts of price on real world costs, how perishability impacts derivative markets, and the influence of seasonality.

I hope you enjoy my conversation with Hari Krishnan.

In this episode I speak with Nick Baltas, Managing Director at Goldman Sachs and head of cross-asset delta one, commodity, and stocks strategies R&D and Structuring.

There are three major discussion points in this episode. First, we discuss how Nick thinks about using the broad palette of systematic strategies he has at his disposal to solve the problems of asset owners.

Second, we discuss Nick’s research on cross-asset skewness. Less commonly discussed among multi-asset strategies, Nick wrote one of the preeminent papers on the topic and provides considerable insight into the nuance of implementing a skewness strategy.

Finally, Nick shares his thoughts on building multi-strategy portfolios, both in theory as well as with respect to meeting client needs.

I hope you enjoy my conversation with Nick Baltas.

In this episode I speak with Bin Ren, founder of SigTech, a financial technology platform providing quantitative researchers with access to a state-of-the-art analysis engine.

This conversation is really broken into two parts. In the first half, we discuss Bin’s views on designing and developing a state-of-the-art backtesting engine. This includes concepts around monolithic versus modular design, how tightly coupled the engine and data should be, and the blurred line between where a strategy definition ends and the backtest engine begins.

In the second half of the conversation we discuss the significant pivot SigTech has undergone this year to incorporate large language models into its process. Or, perhaps more accurately, allow large language models to be a client to its data and services. Here Bin shares his thoughts on both the technical ramifications of integrating with LLMs as well as his philosophical views as to how the role of a quant researcher will change over time as AI becomes more prevalent.

I hope you enjoy my conversation with Bin Ren.

In this episode I speak with Charles McGarraugh, Chief Investment Officer of Altis Partners.

Charlie finds himself at the helm of Altis from a non-traditional route. His career began at Goldman, where his experience spanned everything from asset backed securities to liquid commodities. He then started a firm specializing in machine-learning driven sports betting before moving into cryptocurrency markets. Today, Charlie is betting that alternative strategies will play an increasingly important role for investors over the coming decade.

We spend the majority of our conversation talking about Altis’s investment stack, which is comprised of two components: an upstream signal layer and a downstream strategy layer. The signal layer is responsible for ingesting data and constructing a prediction curve for different futures markets. The strategy layer ingests these prediction curves and constructs a portfolio. Charlie discusses the types of signals Altis relies on, how they turn prediction curves into trade signals, and where risk management fits into the equation.

I hope you enjoy my conversation with Charles McGarraugh.

In this special episode of Flirting with Models, I’m joined by two guests: Andrew Beer of DBi and Adam Butler of ReSolve Asset Management.

Rather than my usual interview format, I wanted to foster a conversation about the replication of managed futures strategies. Specifically, I wanted to bring on two practitioners who both share the same high level beliefs – namely that more investors should allocate to managed futures, that managed futures are well suited for replication, and that replication can help dramatically reduce fees – but differ on the implementation details.

And it is in that disagreement that I hoped to highlight the different pros and cons as well as any embedded assumption in any of these replication approaches.

We discuss return-based replication, process-based replication, determining the number of markets to trade, expectations for tracking error, and more.

I hope you enjoy this episode with Andrew Beer and Adam Butler.

In this episode I speak with Dean Curnutt, founder of Macro Risk Advisors and host of the Alpha Exchange podcast.

This episode is all about the nature of risk. More specifically, the endogenous risk that can manifest in markets. We discuss the crash of 1987, Long-Term Capital Management, the Financial Crisis of 2008, the XIV implosion of February 2018, and the 2020 COVID crisis.

With these crises in mind, we touches upon topics such as reflexivity, crowding, risk recycling, and the evolving role of the Fed. Dean also shares his thoughts about the nature of risk, how it is woven into the fabric of markets, and why it seems like there’s a crisis every 11 years.

For those who love to think about risk and the nature of markets, this episode is for you.

So sit back, relax, and enjoy this episode of Flirting with Models with Dean Curnutt.

In this episode I speak with Gerald Rushton, senior member of the QIS Structuring team at Macquarie Bank.

Our conversation largely revolves around commodity strategies, including thoughts on trend following, commodity carry, commodity congestion, and commodity volatility carry. Gerald argues that the latter three are particularly well suited to be paired with equity hedging strategies, and we spend quite a bit of time discussing the major design levers behind each strategy.

Gerald also provides some insight as to how QIS desks have evolved over the past decade, why he believes QIS desks can provide unique edge, and the many ways in which they can customize mandates for clients.

Please enjoy this conversation with Gerald Rushton.

Today, August 28th, 2023, my company Newfound Research turns 15.  It feels kind of absurd saying that.  I know I’ve told this story before, but I never actually expected this company to turn into anything.  I started the company while I was still in undergrad and I named it Newfound Research after a lake my family used to visit in New Hampshire.  I fully expected the company to be shut down within a year and just go on to a career on Wall Street.

But here we are, 15 years later.  I’m not sure why, but this milestone feels larger than any recent birthday I can remember.  I’m so incredibly grateful for what this company has given me.  I’m grateful to my business partner, Tom.  I’m grateful to employees – both past and present – who dedicated part of their lives and careers to work here.  I’m grateful to our clients who supported this business.  I’m grateful for all the friends in the industry that I’ve made.  And I’m grateful to people like you who have given me a bit of a platform to explore the ideas I’m passionate about.

Coming up on this anniversary, I reflected quite a bit on my career.  And one of the things I thought about was all the lessons I’ve learned over the years.  And I thought that a fun way to celebrate would be to take the time and write down some of those ideas and lessons that have come to influence my thinking.

So, without further ado, here are 15 lessons, ideas, and frameworks from 15 years.

My guest is Devin Anderson, co-founder of Convexitas.

The theme of this episode, as you can likely guess from the title, is strategy versus structure. While we often focus on strategy specifics on this podcast, Devin hosts a masterclass as to why the structure you wrap your strategy in can ultimately determine the type of strategy you can deliver.

Specifically, we discuss option-based tail hedging and the types of strategies that can be delivered in hedge fund, mutual fund, ETF, and separate account wrappers.

In the back half of the conversation, we dive into how Convexitas implements their risk mitigating strategies. Specifically, Devin explains why Convexitas focuses on convexity with respect to the S&P 500 and actually refuses to customize this mandate, despite having the ability to do so at scale.

Finally, we end the conversation on a bit of a spicier note, where Devin explains why most market pundits overstate the influence large, scheduled derivative rolls might have on the underlying market.

Please enjoy my conversation with Devin Anderson.

In this episode I speak with Martin Tarlie, a member of the Asset Allocation team at GMO and spearheading their work on Nebo, a goals-based investment platform.

Martin describes Nebo as, “bridging the gap between financial planning and portfolio management,” with a key innovation being the reformulation of risk from volatility to not having what you want/need when you want/need it. In other words, constraints on both wealth target and horizon.

This reformulation of the core problem introduces a number of complications to the portfolio optimization process. For example, under classic power utility, lower volatility is always preferred. But if you’re an investor expecting significant shortfall with respect to your wealth targets, increased volatility may be something very much worth pursuing.

We spend plenty of time in the weeds discussing topics such as: the limitations of dynamic programming via backwards indication, the term structure of return variance, ergodicity economics, and portfolio selection sensitivity to utility function choices. And while these are all important details, at the end of it all, what Martin stresses most is that it’s the reformulation of the problem being solved that ultimately leads to a more pragmatic solution for allocators.

Please enjoy my conversation with Martin Tarlie.

In this episode I speak with Grug, an anonymous MEV searcher on the Ethereum blockchain. If that sentence made no sense to you, I promise this will be a fun episode.

To begin the conversation, Grug explains the basic architecture of the Ethereum blockchain and how its structure allows for the emergence of MEV strategies like sandwich attacks, arbitrage, and liquidations.

He discusses some of the criteria he looks for when identifying a profitable MEV strategy and provides examples of some of the long-tail approaches he has deployed in the past as well as some of the risks associated with them. We discuss the pro-cyclical nature of some of these strategies, the role of retail flow, and the edge in being able to deploy rapidly.

Grug also provides his thoughts on the impact of alt-L1’s and L2’s on MEV, airdrop strategies, and the end game of MEV if Ethereum infrastructure becomes too centralized.

Please enjoy my conversation with Grug.

My guest this episode is Doug Greenig, CEO and CIO of Florin Court Capital.

Florin Court specializes in delivering an alternative markets CTA, trading over 500 markets ranging from Turkish cross currency swaps to French power markets.

We spend the majority of the conversation discussing what makes these markets unique from traditional markets traded by CTAs. For example, who are the players in these markets, what are the unique considerations for introducing and sunsetting markets, and why we would expect these markets to trend in the first place?

Doug also explains why he thinks these markets tend to behave better than traditional markets, why you don’t need special trend signals to trade them, and the significant diversification potential they can introduce.

Please enjoy my conversation with Doug Greenig.

In this episode, Corey Hoffstein, CIO of Newfound Research, Rodrigo Gordillo, President of ReSolve Global* and Adam Butler, CIO of ReSolve Global, delve into the concept of return stacking and introduce the innovative RSBT Return Stacked™ Bonds & Managed Futures ETF.

This podcast is essential for investors, financial advisors, and anyone interested in learning more about return stacking, the RSBT ETF, and the potential benefits of combining bonds and managed futures for portfolio diversification and risk management. Don't miss out on this insightful conversation to deepen your understanding of these innovative investment strategies and their potential impact on today's complex financial markets.

They cover a wide range of topics, including:

• The motivation behind the return stacking concept and its relevance in today's market environment

• The history of institutional leverage and diversification in retail portfolios

• The advantages of using return stacked strategies for portfolio construction and risk management

• The role of bonds and managed futures in building a robust, diversified investment portfolio

• The importance of low correlation between asset classes for effective diversification

• The mechanics of combining bond exposure with a managed futures overlay in the RSBT ETF, including the use of cash collateral and Treasury Futures

• The benefits of using ETFs as capital-efficient building blocks for return stacking

• The potential for a family of return stacked ETF products to address various investor needs and preferences

• The significance of managed futures as a "third leg of the stool" for managing inflation and mitigating market risks

• The challenges and opportunities related to implementing managed futures strategies and managing leverage in retail portfolios

• The goal of matching the RSBT ETF's bond strategy to core US fixed income, such as the Bloomberg US Core Aggregate Bond Index, and adjusting duration accordingly

Today I speak with Pim van Vliet, Head of Conservative Equities at Robeco.

It will come as no surprise, to those who know Pim’s work, that we spend the majority of this conversation talking about conservative investing. Specifically, we discuss the low volatility anomaly. But rather than rehash the usual high level talking points, I wanted to dig into the more practical considerations.

For example, how are low volatility and low beta different? How do selection and allocation effects contribute to low volatility investing? Are low volatility and quality actually different anomalies? And how should we think about the influence of currency in a global low volatility portfolio?

While Pim has nearly three dozen research publications to his name, he provides the balanced perspective of a practitioner, acknowledging the practical limitations to managing money in the real world.

Please enjoy my conversation with Pim van Vliet.

In this episode I speak with Asif Noor, Portfolio Manager at Aspect Capital where he oversees the firm’s Multi-Strategy Program.

Asif has spent the last 25 years of his career developing systematic macro strategies, giving him a depth and breadth of experience to understand what it takes to remain competitive in the space.

While a handful of low frequency signals may have been sufficient a few decades ago, today Aspect’s Multi-Strategy Program incorporates hundreds of alpha forecasts ranging from intraday to several months. But this evolution also brings new challenges, which we discuss at length in this episode. For example, how are new alphas introduced and old alphas sunset? How do you unify alphas of different magnitudes and convictions? Or, how do you manage risk across so many signals?

This conversation is chalk full of the practical, real world experiences of running a multi-strategy program.

Please enjoy my conversation with Asif Noor.

My guest is Rob Croce, Senior Portfolio Manager at Newton Investment Management Group.

This episode is all about what Rob considers to be the two super factors: trend and carry.  More importantly, how Rob uses them to inform how risk is taken within asset classes, across asset classes, and over time.

Rob is not afraid to get in the weeds, either.  For example, on the trend side we discuss details such as how to combine trend signals of different speeds, how to balance the probability of a trend signal being noise versus its likelihood of continuing, and how trend signals can be improved using clustering ideas.

From high level thoughts about diversification to low level details about measuring bond carry correctly, there’s a lot to unpack in this episode.

Please enjoy my discussion with Rob Croce.

In this episode I speak with Michele Aghassi, principal at AQR Capital Management where she serves as a portfolio manager for the firm’s equity strategies.

The conversation spans three major points: optimization, the opportunity in emerging equities today, and factor investing.  While these are the headline topics, the underlying theme of the conversation, in my opinion, is the idea of unintended bets.  

More specifically, how controlling for unintended bets, whether through optimization or thoughtful consideration, can sharpen your resolve in your conclusions.  Whether it is the influence of China in emerging markets, the influence of currency in foreign equity returns, or crowding effects in factors, being aware of the potential for unintended bets can shape the how, where, and even the when of portfolio construction.

Please enjoy my conversation with Michele Aghassi.

In this episode I chat with Jason Josephiac, Senior Vice President and Research Consultant at Meketa Investment Group.  

Jason has largely spent his career in the institutional allocation space, first in manager research at United Technology’s pension and now on the consulting side of the table.

Given this background, I spend the first half of the conversation trying to peel back the layers of how Jason thinks allocators should attack the portfolio construction process.  This includes his views on the risks of LDI, portable alpha in theory versus practice, and why he prefers to view the world in an absolute risk / absolute return framework.

In the back half of the conversation we discuss Meketa’s Risk Managed Strategies framework, with its three buckets of first responders, second responders, and diversifiers.  We cover topics such as long volatility, managed futures, and what actually constitutes a diversifier.

I hope you enjoy my conversation with Jason Josephiac.

In this episode I speak with the anonymous twitter user @macrocephalopod.

The arc of our conversation follows the arc of his career: beginning with slow-frequency style premia in a hedge fund to building a prop desk that trades mid-to-high frequency strategies in crypto.

A large part of the conversation can be characterized as comparing and contrasting the roles through the lenses of research, operations, and risk management.  For example, in what ways is long/short equity meaningfully different than long/short crypto?  Or, how important are topics like market impact, fill ratios, and borrow fails in mid- versus slow frequency strategies?

While crypto is the venue, I believe the wisdom imparted in this episode spans all markets.

Please enjoy my conversation with @macrocephalopod.

My guest is Roni Israelov, CIO of NDVR.  Prior to NDVR, Roni was a principal at AQR Capital Management, where he worked on global risk models, high frequency factors, and lead the development and oversight of options-oriented strategies.

Taking a page from Roni’s career and research, our conversation is far ranging.  We discuss topics from global asset risk models to the application of high frequency signals to tail risk hedging.  While there are insights to glean in each of these topics, I think the conversation helps paint an insightful picture about how Roni thinks about research in general.

Towards the end of the conversation we talk about the new research Roni is tackling at NDVR, a financial advisory firm for high net worth individuals.  The role brings new challenges to consider, such as liability management and risk tolerance within the framework of portfolio optimization.  Even though the topics differ, I think you’ll hear a very common thread in how the research is performed.

Please enjoy my conversation with Roni Israelov.  

Doug Colkitt is an ex-high frequency trader, ex-MEV bot searcher, and founder of the decentralized exchange CrocSwap.

In this episode, we talk about all three.  We begin with high frequency trading, where Doug walks us through the differences between maker and taker strategies, why queue position is so critical for makers, and why volatility is a high frequency trader’s best friend.

We then discuss Ethereum-based MEV strategies.  Doug explains what MEV is, how the architecture of the Ethereum block chain allows it to exist, and a high level topology of the different types of MEV strategies that exist.  He also explains how the game theory behind MEV changed dramatically with the launch of Flashbots.

Finally, we talk about his new decentralized exchange CrocSwap and its primary innovations, including dynamic fee levels, identification of toxic flow, and vaults that enable KYC.

I hope you enjoy my conversation with Doug Colkitt.

My guest this episode is Jeff Yan, founder of Chameleon Trading.  

Jeff began his career in high frequency trading at Hudson River Trading but soon moved over to the world of crypto where he built one of the largest market making firms in the space.

After Jeff gets me up to speed with the basics of high frequency market making, we dive into some of the more esoteric components, particularly with respect to centralized crypto exchanges.  These include infrastructure quirks, adversarial algorithms, and why HFT P&L might actually be predictive of medium-term price movement.

In the back half of the conversation, Jeff explains the problems he sees with current decentralized exchanges and introduces Hyperliquid, a new decentralized trading platform built on its own blockchain to provide performant order book execution for perpetual futures.

Please enjoy my conversation with Jeff Yan.

Jason Buck is the co-founder and CIO of Mutiny Funds and maybe one of the most interesting people I know.

Jason made, and subsequently lost, a fortune in commercial real estate in the 2008 crash.  This “ego destroying event” was the catalyst for him to completely rethink the idea of resiliency, both in business and investments.

Jason spent the better part of the 2010s developing the Cockroach portfolio, a modern take on Harry Brown’s permanent portfolio.  A quarter stocks, a quarter bonds, a quarter CTA, and a quarter long volatility, Jason has designed the portfolio to provide all weather returns, with the possibility of serving as an entrepreneurial hedge.

We discuss the value of tail hedging, tail hedges versus long volatility trades, the limits of manager diversification, and managed futures/CTAs versus static commodity positions.

As a final note, this episode was recorded live at the Exchange ETF event in Miami.

Enjoy.

There is no doubt that the tools of machine learning and the promise of artificial intelligence has captured the imagination of quantitative researchers everywhere.  But I am aware of few fund managers who have wholesale adopted the ideas into their investment stack as thoroughly as Angus Cameron.

In this dive back into the archives, we return to Season 4, Episode 6 where I spoke with Angus about his background as a discretionary macro trader and his evolution into a fully systematic, machine-learning driven investment stack.  Not just in how signal is identified, but in how trades are structured and managed.

If the idea of a swarm of AI trading bots doesn’t get you excited, this might not be the episode… or the podcast… for you!

In our industry, we’re all too often guilty of asking, “what is your alpha,” rather than, “what is your process for finding alpha?”  Yet, in the long run, it is the process that is important.  

I’m equally guilty of this.  In the history of this podcast, I’ve probably overemphasized the outcome of research versus the process of research.

There are a few exceptions, though.  And in this dive into the archives, I wanted to return to Season 2, when I spoke with Chris Meredith, Co-Chief Investment Officer at O’Shaughnessy Asset Management.

There are a lot of nuggets in this episode, ranging from ingesting data to working with research partners to a discussion of hardware setup.  But the part that has always stuck with me the most was Chris’s process for prioritizing research proposals based upon an AUM-scaled information ratio.  

I’ll let Chris explain.  Enjoy.

In July 2020 I interviewed Cliff Asness, co-founder of AQR.  This was several months after he penned a perspective piece titled The Valuesburg Address, where he waxed poetic about the multi-year drawdown in the value factor.

Nearly three years later, he recently wrote the perspective piece titled, The Bubble Has Not Popped.  I say wrote, but it is just a single image of the value spread between growth and value, adjusted for just about every possible noise factor you can imagine.  The spread still hovers near generational highs.

This isn’t Cliff’s first value drawdown.  While never easy, I suspect his past experience at least makes it a bit easier.

In this archive clip, I wanted to highlight the wisdom of experience.  To me, that entails understanding what you know, what you wish you could know, and what you believe.

I hope you enjoy.

It’s no secret that high flying growth stocks were hammered in 2022, so I thought it would be fun to revisit my conversation with Jason Thomson back in Season 3.  

Jason is a portfolio manager at O’Neil Global Advisors, where he manages highly concentrated portfolios of growth stocks.

Now, Jason is a discretionary PM, which may seem like an unusual guest for a quant podcast.  But his approach is so data and process driven, it’s hard to tell the difference.  

I selected a few questions about his take on growth investing in general, but I’d highly recommend you go back and listen to the original episode for his thoughts on portfolio construction and risk management as well.

Enjoy!

After March 2020, a growing research interest of mine was the question, “how do strategies reflexively impact the markets they trade?”  Beyond crowding risk, can adoption of strategies fundamentally change market dynamics.

In Season 3 Episode 11, I spoke with Omer Cedar, who argues that equity quants have done precisely that.  The mass adoption of factor models, whether for alpha or risk, fundamentally changed how baskets of stocks are bought and sold.  For a discretionary manager to ignore this sea change is to ignore a fundamental shift in the current of the water they swim in.

In this clip from the episode, Omer discusses how quants have changed the market and how fundamental managers should use this information to sharpen their edge.

We’re back with another clip from the archives.  This time it’s Season 4 Episode 9 with Vivek Viswanathan.

For three decades, equity quants have largely lived under the authoritative rule of the Fama-French 3 Factor Model and linear sorts.  In this episode, Vivek provides an cogent alternative to the orthodoxy.  Specifically, he explains why an unconstrained, characteristic-driven portfolio can more efficiently capture behavioral-based market anomalies.  I think this is a master class for alternative thinking in quant equity.

It was really tough to clip this episode.  Vivek’s comments about Chinese markets provide a tremendous example about finding alpha in alternative markets.  But I’ll leave that for you to go back and dig out!

Okay, let’s dive in.

We’re rewinding to Season 3, Episode 3 to chat with Benn Eifert, founder of QVR.  

Benn was my first repeat guest and this is probably one of our more popular episodes.

Instead of the usual interview format, I called this episode “Bad Ideas with Benn Eifert,” and basically just asked him a bunch of questions about naive option trades and whether they are a good idea or not.

For anyone starting their journey with options or volatility, the whole episode is a must listen.

The clips I chose here were selected because I thought they provided a really good cross-section of topics in the world of options while highlighting one important common thread: the risk of unintended bets.  I think this is one of the most universally important concepts in trading and investing, and Benn really drives the points home here as we cover topics ranging from writing options for income to why VIX minus realized doesn’t mean what you think it does.  The subtle through line is the reminder that it’s what we don’t know we don’t know that will eventually get us in trouble.

We’re trying something new here, folks.  I’ve got 5 seasons and 60 brilliant episodes and I thought it would be fun, in the off season, to go back to the archives and highlight past conversations.

So using my trusty random number generator, I chose an episode at random.  So, we’re going back to 2018 to my conversation with John Alberg, co-founder of Euclidean Technologies, where machine learning is applied to the value investing problem.  

The part I’m highlighting starts around minute 20 and is about the formulation of the machine learning problem and how the research question should be asked.  I like this section because I think it really highlights how we can think about the tradeoff of degrees of complexity versus accuracy and the problem of overfitting.

Enjoy!

In this episode I speak with Giuliana Bordigoni, Director of Specialist Strategies at Man AHL.

In her role, Giuliana oversees the firm’s strategies that require specialist knowledge.  This includes, for example, alternative markets, options trading, credit, and machine learning.

We spend a good deal of time discussing alternative markets, a focus of Giuliana’s in both her current role and her prior as the Head of Alternative Markets.  We discuss the potential benefits and challenges of introducing alternative markets to existing CTA programs, unexpected roadblocks in doing so, and the opportunities that Giuliana is most excited about today.

We also discuss machine learning, which is treated as its own unique class of strategy rather than as a technique, and why Giuliana is so excited about systematic credit today.

I hope you enjoy my conversation with Giuliana Bordigoni.  

In this episode I speak with Adam Butler, co-founder and CIO of ReSolve Asset Management.  For full disclosure, at the time of recording I am personally an investor in one of ReSolve’s private funds.

Adam last joined the show in Season 1, where we discussed his background and philosophy of diversification.  This episode begins with a discussion of how Adam’s thinking and process has evolved over the last four-plus years, much of which is centered around the idea of experimental design.  Adam discusses the adoption of machine learning techniques, the spectrum of complexity between zero- and strong-prior signals, and how proper experiment design allows for greater process diversification.

The back half of the conversation dances across a few subjects.  We discuss topics such as seasonality, carry, the operational burdens of introducing a full-stack machine learning process, and the difficulties allocators face in introducing multi-strategy alternatives into their portfolios.

I hope you enjoy this episode with Adam Butler.

In this episode I speak with Kevin Cole, CEO and CIO of Campbell & Company.  

In the first half of the conversation, we discuss Campbell’s flagship systematic multi-strategy program.  We cover topics including trend-following versus multi-strategy, the taxonomy of alpha signals, the concept of edge when you’re running hundreds of models, the process for introducing and sunsetting signals, and risk management.

With such a strong focus on quantitative research, we spend the latter half of the conversation discussing how Campbell organizes its research team and process.  Kevin explains how the team is organized and how the agenda is set.  He also introduces the management process they’ve adopted called “Pulse,” providing the framework for which the team operates.

Please enjoy my conversation with Kevin Cole. 

Today I am joined by Hari Krishnan, Head of Volatility Strategies at SCT Capital and author of the books Second Leg Down and Market Tremors.

We begin with a discussion of Hari’s newest book, Market Tremors, and the main theoretical idea: Mean Field Theory.  Hari lays out both the philosophical underpinnings of the concept as well as how one might interpret it in practice.  This leads into a natural discussion of dominant agents, including examples of who they are, how we might go about identifying them, and why they are so important to consider.

In the back half of the conversation, we tackle some more practical considerations of tail risk hedging.  This includes key differences between equity and rates markets, how we might structure hedges in today’s market environment, how to navigate path dependency, and why it’s all just a “bag of tricks.”

Please enjoy my conversation with Hari Krishnan.

In this episode I speak with Harel Jacobson, an FX volatility trader.

There is a lot that makes the FX volatility market unique.  For starters, the end users are more focused on hedging cash-flow and liquidity than wealth.  Since the underlying is currency pairs, volatility surface arbitrage conditions become multi-dimensional.  And then there is the global geopolitical event calendar to consider.

Did I mention that trades are performed, almost exclusively, OTC?  So even something like price discovery, which we take for granted on listed exchanges, is non-trivial.  Especially if you want to backtest a new research idea.

This is a fascinating conversation into a fairly niche, but important global market.

I hope you enjoy my conversation with Harel Jacobson.

My guest in this episode is Andrew Beer, co-founder of Dynamic Beta Investments.

Andrew has spent the last 15 years trying to pioneer the adoption of hedge fund replication strategies.  The core thesis is that several hedge fund categories can be dynamically replicated using just a handful of liquid market exposures and some regression techniques.  He argues that if he can deliver the strategy beta while cutting out hundreds of basis points of management fees and trading costs, it would consistently earn him a top decile rank.  And all this can be done in a daily liquid vehicle.

The Devil, of course, is in the details.  Which categories can be replicated is an important consideration.  Whether to perform a bottom-up or top-down replication is another.  And, obviously, which factors to incorporate.  Andrew stresses that the answer to all these questions comes not from quantitative analysis, but from a qualitative understanding of how hedge fund managers actually operate.

This episode may not be as technical as others, but it certainly had me walking away thinking, “if there’s no points for originality, it certainly seems a lot easier to just copy the work of others.  Especially if I can cut out all their fees.”

Please enjoy my episode with Andrew Beer.

My guest in this episode needs no introduction: Antti Ilmanen, co-head of Portfolio Solutions at AQR, award winning researcher, and author of the books Expected Returns and the recently published Investing Amid Low Expected Returns.

A decade has passed since Antti wrote his first book, providing both a decade of out-of-sample data as well as a decade of new research.  I begin by asking Antti about where his conviction has hardened and the things he’s changed his mind about.  From there, however, the conversation topics become much more wide ranging.  We discuss structural changes in the market, the growth of passive investing, and his research on who is actually on the other side of style premia trades.  

We then discuss trend following versus put protection, trend following’s difficult decade, and why the outlook for trend may be rosier going forward.

Finally, we touch upon some more practical topics, addressing low-hanging opportunities Antti has seen in his role as co-head of Portfolio Solutions at AQR.

I hope you enjoy my conversation with Antti Ilmanen.

My guest this episode is Ralph Smith, Head of Research at BlueCove.

BlueCove offers long-only and market-neutral mandates in corporate credit and interest rate markets, with an emphasis on utilizing a scientific approach to portfolio construction.

We spend the episode discussing how the unique nature of fixed income markets present both opportunities and risks.  For example, how the differing breadth and liquidity in corporate credit versus rates markets impacts the types of strategies that can be implemented.  Or, how the assumption about a bond’s availability or liquidity can materially impact a portfolio backtest.

As Head of Research, Ralph also has some strong thoughts on the research process itself.  He shares his views on structuring a research organization, performing research in changing market environments, and even the appropriate use of backtests.

Please enjoy my discussion with Ralph Smith.

My guest in this episode is Kai Wu, CEO and founder of Sparkline Capital.

Kai is a pioneer in the measurement of intangible value.  Using machine learning, he tackles unstructured data sources like patent filings, earnings transcripts, LinkedIn network connections, and GitHub code repositories to try to measure value across the four key pillars of Brand, Intellectual Property, Network, and Human Capital.

We discuss why intangibles are important, how they differ from the traditional factor zoo, the opportunities and risks of unstructured data, and how even big data can have small data problems within it.

Finally, we discuss Kai’s most recent applications of his research to the world of crypto.

Please enjoy my conversation with Kai Wu.

Today I speak with David Sun, a retail trader who started his own hedge fund. Coming from a non-traditional background, David takes a non-traditional approach in his investment mandates.  Focused on selling options to capture the volatility risk premium, David believes that markets are ultimately efficient and therefore foregoes using any sort of active signal.  Instead, he focuses on explicitly controlling his win size relative to his loss size, and then choosing a strategy with a win rate that bumps him into positive expectancy.  By then maximizing the number of “at bats,” he lets the Central Limit Theorem take care of the rest.  It’s an approach he calls “expectancy hacking.” We discuss this approach in both theory and practice, addressing issues such as trading costs and slippage drag, as well as both sequence and event risk.  David’s approach is certainly non-traditional, but highlights some unique concepts of how traders may be able to architect a payoff profile around a risk premium.

Please enjoy my episode with David Sun.

In this episode I talk with Aneet Chachra, fund manager at Janus Henderson.

In his role, Aneet runs flow-driven strategies.  These are strategies that seek to find an edge in market events where trading volume creates a predictable pressure on price, such as index additions or deletions, corporate buybacks or issuance, or even the rebalancing of target date funds.  Our conversation is wide ranging, from the basics of how Aneet categorizes these types of trades, to views on how changing market structure has affected the opportunity set, to the impact of social leverage on risk management.

While the approach may be highly niche, Aneet is bursting with broadly applicable wisdom.

I hope you enjoy this episode with Aneet Chachra.

In this episode, I speak with the Twoquants: Moritz Seibert and Moritz Heiden. There are really two halves to this episode.  In the first, we discuss trend following strategies at length.  We cover the usual topics of signals, speeds, and portfolio construction before diving into some niche views, such as synthetic assets, spread trades, and alternative roll schedules.

In the second half, we pivot to discuss crypto markets, as the Moritzes now serve as CIO and CTO for the Exponential Age Digital Asset Fund.  We discuss their journey into crypto, their explorations of the NFT space, considerations that make crypto unique from traditional markets from an allocators perspective, and advice for emerging managers in the space.

So kick back, relax, and please enjoy my conversation with Moritz Seibert and Moritz Heiden.  

In a first for Flirting with Models, my guest this episode is anonymous, going only by the handle LightSpringFox on Twitter.  

Mr. Fox is a quantitative trader who works in crypto market making at MGNR. Mr. Fox did not begin his career in crypto, nor even in market making.  Rather, his background is in traditional equity factor investing, and so we spend a good deal of comparing and contrasting the low- and high-frequency domains.  We also discuss the nature of market making edges, the unique risks of high frequency, how crypto and traditional finance market making deviate, and what Mr. Fox considers the “hardest problem in HFT.”

Without further ado, please enjoy my conversation with LightSpringFox.

In this episode I speak with Michael Green, Chief Strategist as Simplify ETFs.  In a first for the Flirting with Models podcast, we recorded this episode live at the ETF Exchange in Miami in early April 2022.  

Given Michael’s eclectic background, our conversation is wide ranging.  He has traded everything from small-cap value to commodities to housing derivatives to long volatility, and so we try to find the common elements and themes across his career.  One that sticks out is his quote that “it’s not enough to do the analysis: there needs to be a trade there as well.”

Michael has become well known for his view that passive investing may now represent a systemic risk to markets.  We discuss the origins for this view, how it has evolved, counter-points, and the trade that pairs with the analysis. 

Finally, we discuss the Simplify High Yield PLUS Credit Hedge ETF, the first strategy from Simplify that really has Michael’s fingerprints all over it.

I hope you enjoy my conversation with Michael Green.

In this episode I speak with David Berns, co-founder and CIO of Simplify ETFs and author of the book Modern Asset Allocation for Wealth Management.

Our conversation centers around the idea of what it means to build a portfolio for a human being. This concept arises both technically and philosophically in David’s work, where he emphasizes the importance of higher return moments in portfolio optimization, but goes about achieving this end through more holistic risk preference analysis.

David expands upon the ideas of risk aversion, loss aversion, reflection, and how both our personal balance sheets and our standard of living expectations impact the portfolio choices we should be making. While there is no straight forward prescription, David emphasizes that simply being aware of these different factors can help advisors select more appropriate portfolios. And, hopefully, as the toolkit of investment options expand, adopt exposures that can better shape investor return distributions.

I hope you enjoy my conversation with David Berns.

Today I am speaking with Russell Korgaonkar, CIO of Man AHL.

In his role, Russell oversees a large research organization and so we spend a large part of our conversation talking about research management. Russell provides his thoughts on topics such as determining which projects to take on, quantifying investments in technology, data, and people, how to avoid group think, and how to incentivize both researchers and reviewers. There is tremendous organizational alpha to be gleaned here.

In the back half of the conversation we discuss some of the research that Russell has published on dynamic risk controls. He explains how risk management signals are akin to alpha signals and how the practice of managing risk through 2020 differed from the theory of doing it.

We conclude with Russell’s opinion as the most important due diligence question he could ask, either of another manager or of his own researchers.

Please enjoy my conversation with Russell Korgaonkar.

Andrew Lapthorne is the Head of Quantitative Equity Research at SocGen, a role he’s held for nearly 14 years.

Given the breadth of topics covered by bank research, it should be no surprise that this conversation takes some wide swings as well. We discuss everything from thematic baskets to style premia and machine learning to ESG.

One of my favorite parts of the conversation is when Andrew discusses his research into strong balance sheet names in U.S. small-cap equities. For all the depth in discussion of how index composition rules affect small caps, why Merton’s distance-to-default correlates to credit cycles, and how this trade can potentially be a positive carry hedge, I love that the inception for the idea came from just updating spread sheets.

While this podcast goes wider than it goes deep, Andrew’s experience allows him to sprinkle a bit of wisdom in every topic we hit.

I hope you enjoy this episode with Andrew Lapthorne.

In this episode I chat with Greg Obenshain, Partner and Director of Credit at Verdad Capital. Prior to joining Verdad, Greg worked as the high-yield portfolio manager at Apollo Global Management and Stone Tower Capital.

Despite his background as a fundamental analyst, Greg is a quant convert. His ideas are still grounded in a strong fundamental understanding of what it means to invest in credit, but in a sector where even just acquiring data may be an edge, he lets the data speak for itself.

Greg argues that within credit, excess return comes from identifying improving and declining credit conditions. And, much like quantitative equity investing, there are certain characteristics that can provide insight into how those conditions might change.

We discuss the counter-intuitive findings the data has brought to light, what Greg thinks most credit investors get wrong, and how to grapple with the dimensionality problem of fixed income.

I hope you enjoy my conversation with Greg Obenshain.

In this episode I speak with Roxton McNeal, Head of Multi Asset Investment Strategy & Allocation at the UPS Investment Trust.

Before landing at UPS, Roxton’s career took him through the world of CTAs, developing hedge models for bonny light oil, and working in asset/liability management at General Motors. Each of these roles likely deserves its own podcast, but I do my best to pull a nugget of wisdom from each experience.

Where we spend the bulk of the conversation is in Roxton’s current role at at the UPS Investment Trust. We touch on many of he hot-button issues among institutional allocators, including the role of glide paths, private investing, tactical asset allocation, and tail risk hedging. I think what makes this conversation particularly interesting is how the constraints and realities of liability-driven investing shapes Roxton’s views in these areas.

Please enjoy my conversation with Roxton McNeal.

Vivek Viswanathan is the Head of Research at Rayliant Global, a quantitative asset manager focused on generating alpha from investing in China and other inefficient emerging markets.

Our conversation circles around three primary topics. The first is the features that make China a particularly attractive market for quantitative investing and some of the challenges that accompany it. The second is Vish’s transition from a factor-based perspective to an unconstrained, characteristic-driven one. Finally, the critical role that machine learning plays in managing a characteristic-driven portfolio.

And at the end of the conversation we are left with a full picture of what it takes to be a successful, quantitative investor in China.

I hope you enjoy my conversation with Vivek Viswanathan.

My guest this episode is Tobias Carlisle, author, podcast host, and founder of Acquirers Funds.

Toby joined me in Season 1 where we discussed his background and overall investment philosophy. In this episode, we dive right into the well-documented woes of value investing.

Rather than rehash the usual narratives, however, I wanted to get Toby’s views as to how this environment is unique. We spend time discussing relative versus absolute cheapness, the potentially arbitrary constraints of value and growth definitions, and whether value can ever be effective for investing in the right tail.

In the latter part of the episode, we discuss the two funds Toby manages, including a large-cap long/short and a small/micro long-only. We cover performance in 2020, the practical difficulties of shorting, and how investing considerations are unique in the microcap space.

I hope you enjoy my conversation with Tobias Carlisle.

In this episode I speak with Sam Trabucco from Alameda Research. Alameda manages over $100mm in digital assets and trades between $600mm and $1.5bn per day.

We begin our conversation with a discussion around the features that distinguish crypto markets from traditional markets. What becomes a recurring theme in the conversation is how decentralization and fragmentation present both an opportunity and a challenge.

Sam provides some color into the easiest and hardest alpha he’s earned, including exploiting a spot arbitrage with a US dollar, Bitcoin, and Japanese Yen triangle trade. But not all trades are that complicated: sometimes, it’s just buying Dogecoin when Elon Musk tweets about it.

We spend the back half of the conversation discussing operational issues such as managing collateral, block-time versus clock-time, transaction costs, exchange risk, and regulatory risk. For a highly systematic team, Alameda spends a good deal of time trying to qualitatively judge where the juice is worth the squeeze.

I found this chat to be incredibly insightful into the world of crypto trading, and I hope you do too. Please enjoy my conversation with Sam Trabucco.

In this episode I speak with Dennis Davitt, CEO of Millbank Dartmoor Portsmouth.

Dennis began his career in the option pits of New York and Chicago and eventually worked his way to managing the equity derivatives desk for Credit Suisse. These experiences taught Dennis two important lessons. First, respect markets over models. Secondly, always ask: “what’s the motivation behind this transaction?” And for each of these lessons, Dennis offers a number of stories to entertain us.

In 2013, Dennis left the sell side to join the buy side, and shares with us some important lessons learned about both productizing knowledge and client communication.

In the back half of the conversation we discuss Dennis’s new firm, the opportunity he currently sees in short volatility, ideas for creating a hedged equity strategy when hedging is expensive, and why investors might want to take a page from Moneyball.

I hope you enjoy my conversation with Dennis Davitt.

Angus Cameron is the Founder and CIO of Liminal Capital, a machine-learning focused investment manager.

But Angus does not come to markets with a computer science PhD. Rather, his career arc took him through the prop desks and buyside of Asia, trading global fixed income, FX, equity markets, and arbitrage strategies on a discretionary basis.

A machine-learning driven approach is a new endeavor, but one informed by the wisdom of experience. Angus would consider himself a quantitative trader, not a quantitative investor, and his approach reflects that. Like many systematic investors, Angus breaks the broad investment problem down into data ingestion, idea generation, position management, and risk management. Where he differs from many past guests is in the latter two pieces.

Informed by his trading experience, Angus places a strong emphasis on trade structuring and on-going position management. Liminal automates this philosophy by using swarms of systematic trading agents to place and manage different trades based upon the same underlying signals.

From market structure to machine learning: we cover the full range. I hope you enjoy my conversation with Angus Cameron.

In this episode I speak with Guillermo Roditi Dominguez, managing director at New River Investments.

This was one of the more unique and wide-ranging conversations I have had on the podcast to date. We begin by discussing Guillermo’s approach to portfolio construction, which is heavily focused on the idea of under-writing risk. How he goes about achieving this, though, takes us from adjusted valuation measures to the positioning of large, systematic players and even to the importance of higher frequency tax data.

After discussing the macro framework, we dive into how decisions are made within equities and fixed income. Again, Guillermo stays consistent to his philosophy of underwriting risk and I found his example of allocating to mid-caps versus large-caps in 2020 to be particularly insightful.

While we spend a lot of the episode talking about under-writing risk, we end the episode with Guillermo’s view as to why the right tail is actually more difficult to manage. So make sure you stick around for that.

I hope you enjoy my conversation with Guillermo Roditi Dominguez.

Tina Lindstrom is a Partner at First NY, where she manages an oil volatility portfolio.

She began her career at Susquehanna and eventually worked her way up to managing both the high cap equity index group and the commodity volatility group. This gives her the unique perspective to be able to compare and contrast how these two markets operate.

Tina explains what makes commodity markets unique, how the structure of markets has changed over time, how relative value trades might emerge, and what happens when you’re trading volatility and front-month futures go negative.

Please enjoy my conversation with Tina Lindstrom.

In this episode I chat with David Fauchier of Nickel Digital Asset Management. At Nickel, David manages the Factors Fund, a multi-strategy, multi-manager fund for cryptocurrencies.

We leave the philosophical discussions about crypto aside to dive into the features of this universe that make it rife with opportunity. What struck me most about this conversation was not just how much crypto markets have evolved in the past several years, but how fragmented they still remain.

Different exchange rules, regulatory regimes, margining rules, derivative contract definitions, and even order book models represent both risk and opportunity. And in exploring these idea, David helps me better understand why traditional high-frequency funds like Citadel, Jump, or Jane Street don’t simply come in and eat everyone’s lunch.

In the latter part of the conversation, we pivot to David’s role as a manager-of-managers, and explore issues such as exchange and custody risk, due diligence, and the types of questions an allocator should be asking.

Finally, David leaves us with a teaser about the new opportunities emerging in the DeFi space. But we’ll have to save that for another conversation.

Please enjoy my conversation with David Fauchier.

Darrin Johnson is the first independent trader I’ve interviewed for this show and with that distinction he brings an entirely new perspective.

After learning about how Darrin began his career as an independent trader, we get into the bulk of the conversation that circles around his process of shorting volatility in the S&P 500 complex, including options on futures, index options, VIX futures, and VIX ETPs. Darrin provides insights into how he plays certain tenors over others, why knowing when not to be short is the most important key to risk management, why the upside can be riskier than the downside, and thinking through managing a trade over its lifetime.

Towards the end of the interview, Darrin paints a realistic picture of what it means to be an independent trader, in both the opportunities and constraints unique to his position. We finish with the advice Darrin would give to anyone serious about starting a career in independent trading.

I hope you enjoy my conversation with Darrin Johnson.

My guest this episode is Cem Karsan, Founder and Senior Managing Partner of Aegea Capital Management.

Cem began his career in the pits, and so we begin our conversation with a discussion by comparing and contrasting today’s market versus days gone by. And, perhaps more importantly, the wisdom gained from that era.

It was in the pits that Cem began to understand and develop his intuition for markets and what would become the colorful cast of characters he uses to describe what’s driving flow: Gary the Gorilla, Vanna, and Charm the Sloth. How these characters cooperate or fight amongst themselves provides Cem with a forecast as to how markets should behave.

It seems like these are new and growing forces, but Cem argues they’re as old as time. And, more importantly, increased awareness does not mean they can just be arbed away: they are, potentially, fundamental forces of markets.

We end our conversation with a discussion of how these flows can have profound impacts for equity factor performance and what this all means for stock pickers.

I hope you enjoy my conversation with Cem Karsan.

In this episode I am going to read Newfound’s latest research paper, LIQUIDITY CASCADES: The Coordinated Risk of Uncoordinated Market Participants.

This reading will refer to a number of figures within the paper, so I urge you to go to our website, thinknewfound.com, and download the PDF so you get better follow along.

This paper is unlike any research we've shared in the past. Within we dive into the circumstantial evidence surrounding the "weird" behavior many investors believe markets are exhibiting. We tackle narratives such as the impact of central bank intervention, the growing scale of passive / indexed investing, and asymmetric liquidity provisioning.

Spoiler: Individually, the evidence for these narratives may be nothing more than circumstantial. In conjunction, however, they share pro-cyclical patterns that put pressure upon the same latent risk: liquidity.

In the last part of the paper we discuss some ideas for how investors might try to build portfolios that can both seek to exploit these dynamics as well as remain resilient to them.

I hope you enjoy.

My guest this episode is Kris Sidial, co-CIO of The Ambrus Group, a volatility arbitrage focused firm founded in 2018.

Kris recently joined Ambrus after spending several years on BMO’s exotic and listed options desks. While time on these desks gave Kris the experience of managing a large derivatives book, what convinced him to take the leap to a new firm was growing confidence in a thesis that market micro-structure had undergone a regime shift. And in Kris’s view, this regime shift supports his approach to building a volatility arbitrage book.

Kris’s approach is broken down into two sleeves: long and short volatility. Within long volatility, Kris plays a unique flavor of dispersion trading. Within short volatility Kris plays contango in the VIX futures curve and kurtosis trades that seek to exploit mean-reversion and overpriced volatility.

With several moving pieces, we spend the back half of the episode discussing each sleeve, the underlying approach, how Kris thinks about managing risk, and how it fits into the whole.

What becomes clear is that while we discuss each sleeve independently, they do not exist in isolation. The portfolio is designed to co-exist, with careful thought about how positions in one sleeve offset risk in another.

From a unique fundamental outlook to the holistic approach to portfolio construction, this episode has a lot to offer.

I hope you enjoy my conversation with Kris Sidial.

Today I chat with Euan Sinclair, Partner at Talton Capital Management and author of the books Options Trading, Volatility Trading, and the up-coming Positional Option Trading.

We begin our discussion with Euan’s experience as a market maker as I try to get a better understanding of what a market making operation really looks like from the inside and how it has changed over the last 15 years. Of particular interest to me, given how much market makers have been villianized in recent years, were Euan’s comments on misconceptions about market makers.

We then turn to the buy side, where Euan has spent recent years and is largely the subject of his new book. We discuss common mistakes, sources of edge, thinking about directional versus volatility bets, and the seemingly overwhelming degrees of freedom that options trading offers.

I know I walked away from our conversation with both an increased appreciation of the nuance in these topics, but also several new ideas for both edge and risk management.

Please enjoy my conversation with Euan Sinclair.

Today I am speaking with Omer Cedar, CEO and co-founder of OmegaPoint.

One of the significant trends in quant equity over the last decade has been the attempt to better control for unintended bets and idiosyncratic risks. At OmegaPoint, Omer comes at the problem from the opposite direction: helping fundamental managers better focus on their idiosyncratic risk and recognize the factor risks they may be unintentionally taking.

We discuss how quantitative investors have impacted markets, how fundamental managers should think about factors, the low-hanging fruit for optimization, and surprising lessons Omer has learned in evaluating fundamental portfolios.

The idea of embracing idiosyncratic returns is, arguably, the antithesis of traditional quant investing. But in discussing the lessons learned about unintended bets from the opposite direction, I think there are important ideas that quants can take away.

I hope you enjoy my conversation with Omer Cedar.

My guest in this episode is Sandrine Ungari, Head of Cross-Asset Quantitative Research at SocGen.

Sandrine cut her teeth in the industry as a fixed-income pricing quant, but made her way over to sell-side, investment quant research in 2006. Her early research focused on credit and macro, but since 2012 has been heavily focused on equity and alternative risk premia.

Our conversation begins with equity factors and Sandrine provides insight both into how factor construction has evolved over the last decade as well as her thoughts into where the field is headed. We broaden our discussion to include alternative risk premia, and Sandrine provides a useful mental map for categorizing this broad range of strategies. We discuss the risks of crowding, latent beta risk in levered factors, and the influence of macro economic factors.

More recently, Sandrine has focused her research in the application of machine learning in strategy construction. We discuss one particular example – the application of a recurrent neural network in trend following – and Sandrine shares her views as to how machine learning might affect factor investing going forward.

Sandrine also shares some interesting ideas about where future risk premia might emerge from – but you’ll have to tune in to hear!

Please enjoy my conversation with Sandrine Ungari.

In this episode I speak with Dr. Michael Hunstad, Head of Quantitative Strategies at Northern Trust.

Our conversation centers around the four key trends Michael is seeing among institutional allocators in the factor space today. These trends are (1) the adoption of factors to manage concentration risk in market-cap weighted benchmarks, (2) a move from single- to multi-factor implementations, (3) using factors to de-risk equity exposure, and (4) a tactical tilt towards value.

But Michael isn’t afraid to get in the weeds. He discusses the risks of unintended exposures at length and at one point even explains the importance of matching decay speeds of different factor signals within multi-factor implementations.

For those interested both in the macro trends and the micro details of factor investing, this is not one to miss.

I hope you enjoy my conversation with Dr. Michael Hunstad.