Flirting with Models – Détails, épisodes et analyse

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.