Flirting with Models

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.