Episoder
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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.
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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.
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Manglende episoder?
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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!
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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