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 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.

This episode I chat with Toby Carlisle, a managing member at Carbon Beach Asset Management and author of popular value investing books such as Deep Value and The Acquirer’s Multiple.  Toby’s approach to value investing evolved from his observations as a corporate lawyer in Australia during the burst of the dot-com bubble.  Watching investors target cash-rich, business poor dot-com companies confused his traditional, discounted-cash flow mentality.  But after watching these activists get their hands dirty, Toby realized that even bad companies can be attractive if they’re trading at a deep discount to liquidation value.

We navigate a wide range of topics, including uses and limits of quantitative investing in the realm of special situations, how Apple can be a deep value stock, and why using the opposite of your signal to build a short book might be a bad idea.  

My guest in this episode is Adam Butler, Chief Investment Officer at ReSolve Asset Management. Adam's story is the near quintessential example of my belief that every investor's approach is colored by their experience. From nearly blowing up his firm's omnibus account at his first job, experiencing the tech wreck first hand, and going all in on the commodity and emerging market super cycle narrative, it took "three frying pans to the face" – his words, not mine – to finally rebuild his mental framework from the bottom up. The evolution of his thinking ultimately lead him to embrace what he believes is the ultimate gift: embracing uncertainty in strategy specifications as a means of exploiting the benefits of diversification.

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 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, 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.

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.

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.  

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 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.

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.

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.

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.

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 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 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.