Flirting with Models

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.