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In this episode I am going to read Newfound’s latest research paper, LIQUIDITY CASCADES: The Coordinated Risk of Uncoordinated Market Participants. This reading will refer to a number of figures within the paper, so I urge you to go to our website, thinknewfound.com, and download the PDF so you get better follow along. This paper is unlike any research we've shared in the past. Within we dive into the circumstantial evidence surrounding the "weird" behavior many investors believe markets are exhibiting. We tackle narratives such as the impact of central bank intervention, the growing scale of passive / indexed investing, and asymmetric liquidity provisioning. Spoiler: Individually, the evidence for these narratives may be nothing more than circumstantial. In conjunction, however, they share pro-cyclical patterns that put pressure upon the same latent risk: liquidity. In the last part of the paper we discuss some ideas for how investors might try to build portfolios that can both seek to exploit these dynamics as well as remain resilient to them. I hope you enjoy.

My guest this episode is Kris Sidial, co-CIO of The Ambrus Group, a volatility arbitrage focused firm founded in 2018. Kris recently joined Ambrus after spending several years on BMO’s exotic and listed options desks. While time on these desks gave Kris the experience of managing a large derivatives book, what convinced him to take the leap to a new firm was growing confidence in a thesis that market micro-structure had undergone a regime shift. And in Kris’s view, this regime shift supports his approach to building a volatility arbitrage book. Kris’s approach is broken down into two sleeves: long and short volatility. Within long volatility, Kris plays a unique flavor of dispersion trading. Within short volatility Kris plays contango in the VIX futures curve and kurtosis trades that seek to exploit mean-reversion and overpriced volatility. With several moving pieces, we spend the back half of the episode discussing each sleeve, the underlying approach, how Kris thinks about managing risk, and how it fits into the whole. What becomes clear is that while we discuss each sleeve independently, they do not exist in isolation. The portfolio is designed to co-exist, with careful thought about how positions in one sleeve offset risk in another. From a unique fundamental outlook to the holistic approach to portfolio construction, this episode has a lot to offer. I hope you enjoy my conversation with Kris Sidial.

“Keep an open mind. But not so open your mind falls out.” My guest in this episode needs little introduction: Cliff Asness, co-founder and managing partner at AQR. Cliff has done dozens of interviews, podcasts, talks, and fireside chats over the years. He is also a prolific writer. So, my goal in this conversation was to try to find the questions he hadn’t been asked before or had not answered himself already. How did his formative experiences in the dotcom bubble shape his perception of markets? Why should we stick to factors like grim death? Which of his dozens of papers have been woefully overlooked? Where has he changed his mind over the years and what is he most confident in going forward? Cliff is fountain of knowledge of quant history, research, and practical experience and tells some fantastic stories along the way. Please enjoy my conversation with Cliff Asness.

Today I chat with Euan Sinclair, Partner at Talton Capital Management and author of the books Options Trading, Volatility Trading, and the up-coming Positional Option Trading. We begin our discussion with Euan’s experience as a market maker as I try to get a better understanding of what a market making operation really looks like from the inside and how it has changed over the last 15 years. Of particular interest to me, given how much market makers have been villianized in recent years, were Euan’s comments on misconceptions about market makers. We then turn to the buy side, where Euan has spent recent years and is largely the subject of his new book. We discuss common mistakes, sources of edge, thinking about directional versus volatility bets, and the seemingly overwhelming degrees of freedom that options trading offers. I know I walked away from our conversation with both an increased appreciation of the nuance in these topics, but also several new ideas for both edge and risk management. Please enjoy my conversation with Euan Sinclair.

Today I am speaking with Omer Cedar, CEO and co-founder of OmegaPoint. One of the significant trends in quant equity over the last decade has been the attempt to better control for unintended bets and idiosyncratic risks. At OmegaPoint, Omer comes at the problem from the opposite direction: helping fundamental managers better focus on their idiosyncratic risk and recognize the factor risks they may be unintentionally taking. We discuss how quantitative investors have impacted markets, how fundamental managers should think about factors, the low-hanging fruit for optimization, and surprising lessons Omer has learned in evaluating fundamental portfolios. The idea of embracing idiosyncratic returns is, arguably, the antithesis of traditional quant investing. But in discussing the lessons learned about unintended bets from the opposite direction, I think there are important ideas that quants can take away. I hope you enjoy my conversation with Omer Cedar.

My guest in this episode is Sandrine Ungari, Head of Cross-Asset Quantitative Research at SocGen. Sandrine cut her teeth in the industry as a fixed-income pricing quant, but made her way over to sell-side, investment quant research in 2006. Her early research focused on credit and macro, but since 2012 has been heavily focused on equity and alternative risk premia. Our conversation begins with equity factors and Sandrine provides insight both into how factor construction has evolved over the last decade as well as her thoughts into where the field is headed. We broaden our discussion to include alternative risk premia, and Sandrine provides a useful mental map for categorizing this broad range of strategies. We discuss the risks of crowding, latent beta risk in levered factors, and the influence of macro economic factors. More recently, Sandrine has focused her research in the application of machine learning in strategy construction. We discuss one particular example – the application of a recurrent neural network in trend following – and Sandrine shares her views as to how machine learning might affect factor investing going forward. Sandrine also shares some interesting ideas about where future risk premia might emerge from – but you’ll have to tune in to hear! Please enjoy my conversation with Sandrine Ungari.

In this episode I speak with Dr. Michael Hunstad, Head of Quantitative Strategies at Northern Trust. Our conversation centers around the four key trends Michael is seeing among institutional allocators in the factor space today. These trends are (1) the adoption of factors to manage concentration risk in market-cap weighted benchmarks, (2) a move from single- to multi-factor implementations, (3) using factors to de-risk equity exposure, and (4) a tactical tilt towards value. But Michael isn’t afraid to get in the weeds. He discusses the risks of unintended exposures at length and at one point even explains the importance of matching decay speeds of different factor signals within multi-factor implementations. For those interested both in the macro trends and the micro details of factor investing, this is not one to miss. I hope you enjoy my conversation with Dr. Michael Hunstad.

In this episode I chat with Mads Ingwar and Martin Oberhuber, co-founders of Kvasir Technologies, a systematic hedge fund powered by a full-stack application of machine learning. By full-stack I mean every layer of the process, including data ingestion, signal generation, portfolio construction, and execution, which gives us a lot to talk about. Our conversation covers topics ranging from the limitations of machine learning and hard lessons learned to how to keep up in a rapidly evolving field and thoughts about managing model risk. Given the niche knowledge in a field like machine learning, some of my favorite answers came when I asked how they might perform due diligence upon themselves or where they think other adopters of machine learning go wrong. For allocators, I think these answers are priceless. I hope you enjoy my conversation with Mads and Martin.

My guest is Eric Crittenden, founder and Chief Investment Officer of Standpoint Funds. Eric has spent his career with trend following strategies, first at BlackStar where he managed a fund-of-funds, then at Longboard, and now at Standpoint Funds. This background makes him not only a fountain of knowledge on trend following theory, but also the operational logistics and practical considerations. In this episode our conversation ranges from the source of the trend-following premium to novel concepts for stress-testing managed futures programs. We discuss the struggles the space has faced, the evolution of CTAs, how to think about dispersion among managers, and how Eric thinks about solving for client behavior. I hope you enjoy my conversation with Eric Crittenden.

In this episode I speak with Jeffrey Baird, managing partner at Merritt Point Partners. Merritt Point Partners seeks to build diversified portfolios of convexity exposure through the commodities market. With that in mind, we talk about what makes the commodities market unique, who the players are, and the types of trades that Jeff looks for. Stepping somewhat outside of the theme for this podcast, Jeff actually employs a heavily fundamentals-driven process. But what fundamental means in the commodity space is different than what it traditional means in the equity space, so Jeff walks us through how this concept applies in markets such as gold and natural gas. With so many markets and corresponding derivatives to trade, the opportunity set seems overwhelming. And so does the risk of managing a portfolio. Jeff talks us through his framework for managing risk and the seemingly backwards idea that being profitable in a position can actually introduce more risk for portfolios seeking convexity. I hope you enjoy my conversation with Jeff Baird.

My guest in this episode is Dr. Ernest Chan, founder of QTS Capital Management. Investor, researcher, and educator, Ernie is well-known for his blog – which he has been publishing since 2006 – as well as the several books he has authored, including Quantitative Trading, Algorithmic Trading, and Machine Trading. Our conversation meets at the intersection of tail risk hedging and machine learning. Ernie has a long history with machine learning, having first applied it on Wall Street in the late 1990s. After striking out on his own in 2006, he abandoned it due to the overfitting issues he believed it suffered. In recent years, however, Ernie has re-adopted machine learning, believing that modern approaches help circumvent the overfitting problems and create robust, reliable models. Specifically, Ernie applies machine learning as a risk-management layer on QTS’s Tail Reaper program, an intraday trend-following model designed to profit in periods of crisis. We discuss why such a program can be effective as a tail hedge and how the risk management layer can potentially help reduce the premium bleed typically associated with tail programs. For listeners keen on understanding modern applications of machine learning, this is not one to miss.

In this episode I speak with Jim Masturzo, Head of Asset Allocation at Research Affiliates. In his role, Jim oversees the research and publication of the firm’s capital market assumptions as well as the implementation of those views into a suite of tactical portfolios. We begin our conversation discussing the foundational assumptions behind the capital market assumptions. Like most firms, Research Affiliates takes a long-term view on return and risk. In line with the firm’s guiding philosophy, they also introduce long-term mean reversionary effects. Not surprisingly, these assumptions have been relatively bearish on U.S. equity returns for a large part of the last decade, and we discuss how to view the dispersion between these model forecasts and realized results. We then shift our conversation to the application of tactical views. With capital market assumptions serving as the strategic backbone, Jim and his team develop a number of regime-based model portfolios that can be blended to express different tactical views. But the team does not take a purely quantitative approach. Jim proactively acknowledges and seeks out model blindness. Rather than try to force idiosyncratic fixes into the models that might bias results, however, he and his team adopt qualitative trades to adapt the portfolios. From strategic to tactical and quantitative to qualitative, this is a wide ranging conversation all about asset allocation. I hope you enjoy.

Today I am speaking with Benn Eifert, founder and CIO of QVR Advisors. Benn is my first repeat guest on the podcast, making his first appearance in Season 2. When I asked listeners who they wanted on for Season 3, he was high on the list. In this episode, we take things in a bit of a different direction. Rather than a normal interview, I use this opportunity to ask Benn about his opinion on a number of different trade ideas, from covered calls to shorting VIX ETPs. Benn walks me through the subtleties of each trade and why the PnL of what might look like a simple trade can be incredibly nuanced. Towards the end of the conversation we turn to broader market topics and discuss the general impact of structured product desks and options dealers as well as Benn’s view as to whether March 2020 will create a lasting impact on volatility markets. I hope you enjoy my conversation with Benn Eifert.

In this episode I am joined by Michael Krause, co-founder of Counterpoint Asset Management and Counterpoint Mutual Funds. Our conversation covers two major topics. In the first half, we discuss some of the nuances of high yield bond timing and the subtleties of strategy construction. In the second half, we discuss long/short equity strategies. For listeners more interested in the technical, this is where the meat and potatoes of the conversation lies. We discuss Michael’s evolution from regression to machine learning techniques, the unintended consequences of accidental exposures, and managing risk through optimization while managing the risk of optimization. I hope you enjoy my conversation with Michael Krause.

My guest today is K.C. Hamann, founder of AQIS LLC. K.C. is a Warren Buffett disciple and spent his first decade in the industry working as an analyst at discretionary, deep value long/short equity hedge funds. Which probably makes him sound like an odd guest for a podcast all about quantitative investing. K.C.’s experiences, however, lead him to identify a number of biases that he believes pollute the stock picking skills of discretionary analysts. And thinking of a hedge fund as a system whose first goal is survival, he believes that these biases are durable. For K.C., 13F filings are prospect theory in action. By modeling both the universal and idiosyncratic biases of a manager, K.C. seeks to better identify cases of true conviction which often do not correspond to position size. And it is in these high conviction ideas that K.C. believes are the best opportunities to generate excess returns. I hope you enjoy my conversation with K.C. Hamann.

My guest today is … me. But rather than interview myself, my co-portfolio manager Nathan Faber joins the podcast to take the reigns. In this episode, we talk all things rebalance timing luck. It’s been an obsession of mine for years and something we believe to be a dramatically misunderstood and outright ignored source of risk in portfolios. We discuss how we first came across the topic, some recent research into it, important implications for the industry at large, and how we can try to solve for it. I hope you enjoy the conversation.

My guest in this episode is Daniel Grioli.  Daniel cut his teeth in the industry at Deutsche Bank in London, where he was responsible for valuing structured equity and hedge fund of fund products targeted at continental Europe.  His timing of joining Deutsche, while perhaps somewhat unfortunate for him, proves fortunate for us as he retells a few war stories and lessons learned from the desk leading into 2008. During the crisis, Daniel found himself back in Australia working for a pension fund, where he made a career in manager evaluation, selection, and combination.  That makes Daniel somewhat unique among prior podcast guests, as he provides us some insight into the decision making of capital allocators on the other side of the table. The breadth of managers evaluated gave Daniel some unique insights that he shares with us around where he believes the limits of quantitative and discretionary management lie.  He also shares his framework for manager selection, which he calls Via Negativa.   Presently, Daniel is leveraging this experience to build what he calls a “best ideas” portfolio, exploiting 13F reporting data to create a high conviction equity portf   olio for his clients. Finally, we talk about the i3 podcast that Daniel hosts and some of the most interesting guests he has interviewed. Without further ado, my conversation with Daniel Grioli.

In this episode I am joined by Katherine Glass-Hardenbergh, Associate Portfolio Manager at Acadian Asset Management.   In her role, Katherine focuses heavily on the application of alternative data in Acadian’s fundamentally-driven, systematic investment process.   Purported as being one of the leading frontiers of quant finance, there is plenty of hype around alternative data.  Katherine brings refreshing transparency to our conversation, speaking just as candidly about the hurdles in alternative data as the opportunities. We discuss everything from what alternative data is, where it comes from, interesting examples in the ever-expanding landscape, some of the practical challenges of working with alternative data, and the many potential applications for use within the investment industry. Katherine provides insight into the world of alternative data that only someone deep in the weeds could.  If you’ve ever been curious as to the real-world application of alternative data, this is definitely the episode for you. I hope you enjoy our conversation.

Chris Meredith is co-Chief Investment Officer and Director of Research at O’Shaughnessy Asset Management.  In this episode, we focus on the latter title and talk all about what it means to develop a strong research program. Our conversation centers around what Chris considers to be the three key pillars: data, tools, and people.   Chris provides insight into how data sets have changed since the beginning of his career, starting with highly structured price and fundamental data to so-called “pointy,” highly specific data sets and now completely unstructured blobs of information.  He offers his thoughts into how this growing information set represents both an opportunity for researchers as well as a risk, requiring careful forethought into how it is going to be attacked. Our discussion of tools covers both the digital and the physical.  We talk about the influence of open-source software, the growing role of machine learning, and the operational benefits of treating each researcher’s laptop like a stand-alone research sandbox.  It is easy to tell that while Chris has a passion for the data and tools, he truly believes that they are for naught without the right people and he shares some of his ideas on how to maximize the potential of his team.  Chris also sheds light on the OSAM research partners program, which grants 3rd party researchers access to the OSAM data platform.  This new initiative is a highly unusual approach for a traditionally secretive industry, but early papers coming from their collaborations suggest it may bear significant fruit. Please enjoy my conversation with Chris Meredith.

In this episode I am joined by Liqian Ren, Director of Modern Alpha at WisdomTree. After receiving her degree in Computer Science, Liqian came to the United States to pursue her Masters in Economics.  Liqian then did a quick stint at the Federal Bank of Chicago as an associate economist, before returning back to academia to pursue her PhD at the University of Chicago. In 2007, Liqian joined Vanguard’s Investment Strategy Group, where she leveraged her background to perform economic and capital market forecasts, studies on asset allocation, and research into topics such as retirement income and investor behavior. Liqian eventually transitioned to Vanguard’s Quantitative Equity group, where research efforts were focused on deep, stock-level signals analysis and portfolio construction.  Becoming one of the first to act in a dual capacity research / portfolio manager role, Liqian developed a deep appreciation for implementation-aware research. We spend much of our conversation talking about factors in both theory and practice.  We hit subjects such as the risks of delayed implementation, mixed versus integrated portfolio construction, opportunities for factor timing, active versus indexed implementations, and how factors fit within a glide path. Finally, we discuss Liqian’s new role at WisdomTree and new areas of research she is excited to pursue. I hope you enjoy our conversation.