Andrew Lapthorne, Global Head of Quantitative Research, Societe Generale

Today’s market landscape is defined by extremes that challenge conventional portfolio construction. A small group of mega-cap stocks now represents an unprecedented share of index weight, profit generation, and capital spending, raising important questions about valuation, diversification, and risk concentration. With this in mind, it was great to have Andrew Lapthorne, Global Head of Quantitative Research at Société Générale, back on the Alpha Exchange. Drawing on long-run valuation distributions and profitability data, Andrew examines whether today’s market qualifies as a valuation bubble, not through narratives, but through measurable historical comparisons. His analysis highlights that while headline index multiples appear defensible due to strong profits among a narrow group of companies, the average stock is more expensive than during prior bubble periods, including the late-1990s technology cycle. Our discussion also examines how passive investing and benchmark constraints have altered market behavior. With capital increasingly flowing through index vehicles, Andrew argues that valuation changes now affect entire indices rather than discrete groups of stocks, limiting opportunities for rotation into “cheap” segments. This dynamic has substantially increased tracking error for active managers and reinforced concentration, even among investors who recognize valuation risk but remain bound to benchmark exposure. I hope you enjoy this episode of the Alpha Exchange, my conversation with Andrew Lapthorne.

As I share my closing thoughts on 2025, I want to look back with an eye towards pointing out this year’s unique characteristics from a market risk perspective. I start this exercise by highlighting what I consider to be 2025’s three most interesting days from a vol and risk perspective: 1) the April 7th roller-coaster in the VIX  2) the September 10th surge in ORCL and  3) the October 21st melt-down in the GLD. Each of these helps us better understand some of the forces at work in today’s market. Next, I explore two important themes and their implications. First, the “stock up, vol up” dynamic that is increasingly common among stocks, even mega-caps. Here, the market assigns a higher implied volatility when pricing options on stocks that have often surged in value. It speaks to FOMO and a winner-take-all notion in which stocks are often treated as options. Second, I discuss the incredibly low level of both realized and implied correlation among stocks in the SPX. I consider this a risk hiding in plain sight and something that may be leading investors to underestimate the true level of risk they are taking.I thank you for being a listener this year and wish you a fantastic 2026.

It was a pleasure to welcome Ian Harnett, co-founder and Chief Investment Strategist at Absolute Strategy Research, to the Alpha Exchange. Our discussion explores how long periods of low volatility and abundant liquidity can quietly allow systemic risks to accumulate outside the traditional banking system. Drawing on lessons from the Global Financial Crisis, Ian explains why today’s financial system—now dominated by non-banks rather than banks—requires a different risk framework.  While post-GFC regulation focused on large banks and insurers, much of the system’s leverage and liquidity transformation has migrated toward pension funds, private equity, insurance companies, and private credit vehicles. In the U.S. alone, roughly three-quarters of private-sector financial assets are now controlled by non-banks, reshaping how shocks can propagate through markets. A key theme of the discussion is that systemic risk is multiplicative rather than additive. Ian argues that past crises were often triggered not by the largest institutions, but by smaller nodes in the system that proved critical once stress emerged. Today, he highlights the growing role of private-equity-backed insurers, which tend to hold riskier assets, maintain lower capital buffers, and allocate more heavily to private credit—an area that remains largely illiquid and difficult to mark to market. Ian’s work emphasizes cash flow as a central lens for assessing vulnerability. I hope you enjoy this episode of the Alpha Exchange, my conversation with Ian Harnett.

Kumaran Vijayakumar has spent his career in the equity derivatives market, first as an exotics trader and later in running large risk-taking desks in listed and OTC options. Now, the CEO of DataDock Solutions, a firm he Co-Founded in 2018, Kumaran and his team are developing analytical tools that allow sell-side flow desks to better understand the risks they take and clients they take it for. Our discussion explores the challenges inherent in evaluating client flow, and how data-centric infrastructure has changed the way risk is assessed. With the premise that “what you can measure you can manage and improve”, we discuss DataDock’s efforts to build tools capable of ingesting large-scale trade history and simulating outcomes at the most granular level. In equity derivatives, where trades move quickly and visibility is often instantaneous, desks have historically made decisions based on memory and anecdotal assessments of “good” versus “bad” flow. Kumaran describes this as a space where information is abundant, but structured insight often lags execution speed. Our discussion highlights a key theme: not all flow that loses money is detrimental, and not all flow that is profitable is necessarily strategic. Instead, Kumaran notes that client value emerges when one analyzes trade behavior across time, including delta hedge quality, volume risk transfer, roll probability, expected event-driven distribution, and the role of flow as portfolio offset rather than standalone P&L. I hope you enjoy this episode of the Alpha Exchange, my conversation with Kumaran Vijayakumar.

Risk generally falls into 4 categories, monetary (Central Banks), economic (growth and profits), financial (leverage, carry and correlation) and finally, geopolitical. This last category is non-market, market risk.  And in this context, it was a pleasure to welcome Mark Rosenberg, Founder of GeoQuant and adjunct professor at UC Berkeley to the Alpha Exchange for a discussion centered on political risk as a measurable market variable.Mark’s work evaluates how governance, social instability, institutional stress, and security dynamics influence asset pricing. Tracing his path from academia to his time at Eurasia Group, he describes the gap that existed in country-risk assessment—macroeconomic indicators were abundant, yet political inputs remained qualitative, backward-looking, and infrequent. His motivation for launching GeoQuant followed the belief that political dynamics could be structured into model-based, data-driven signals rather than anecdotes, expert impressions, or slow annual indicators.GeoQuant separates political risk into governance, social, and security components, drawing from quantitative indicators, news-driven updates, and structural model frameworks. Geopolitical risk conjures referendums like Brexit, countries like Russia, China and Iran, conflicts like trade wars and actual wars. The United States does not come to mind. But looking ahead to the 2026 midterm cycle, Mark describes a US landscape defined by elevated turnover risk, the potential for policy conflict, and a political structure capable of generating prolonged uncertainty, a risk factor that may not be sufficiently priced into assets.I hope you enjoy this episode of the Alpha Exchange, my conversation with Mark Rosenberg.

Todd Rapp got his career started in equity options at Goldman Sachs in the late 1990’s, a wild time in which a bubble inflated and burst and provided critical lessons in both gamma and vega risk in the process. Now the CEO of the Fortress Multi-Manager Group, Todd leans heavily on his derivatives DNA in the areas of sourcing uncorrelated return streams, portfolio construction and both measuring and managing risk. Early training has shaped his long-term view that markets express probability through delta, option curvature, and distribution structure rather than through static price movements.Our conversation connects early risk management lessons to today’s landscape, where market concentration echoes 1999, yet correlation conditions differ meaningfully. Todd notes that unlike the prior cycle, today’s equity index shows low intra-index correlation, making dispersion, risk sizing, and factor neutrality more fundamental for return generation.We also explore how the multi-manager architecture seeks to harness uncorrelated strategies packaged with capital efficiency and leverage, producing return streams engineered to operate through dispersion. Todd highlights how understanding optionality remains central to managing equity factor shocks, beta instability, and correlation convergence events.Lastly, we touch on the human capital side of building a business. Having interviewed hundreds of risk takers over the years, Todd looks for individuals who have something to prove, suggesting that having experienced adversity is important because, “if you don’t have a significant drawdown in your past, it’s in your future.”I hope you enjoy this episode of the Alpha Exchange, my conversation with Todd Rapp.

It was a pleasure to welcome Jessica Stauth, CIO for Systematic Equities at Fidelity Investments, to the Alpha Exchange. Our discussion explores how quant investing has evolved through cycles of market stress, technological change, and today’s extraordinary concentration in the equity landscape. Reflecting on her start in markets in the aftermath of the 2007 Quant Quake and the onset of the global financial crisis, Jessica highlights the foundational lesson that markets contain far more uncertainty than models can fully capture — a theme as relevant today as investors confront narrow leadership and elevated fragility. She explains how early dislocations demonstrated the limits of traditional risk models and the dangers of crowding, especially when many quantitative strategies rely on similar signals or hedging techniques. Turning to the present, Jessica describes how her team builds equity strategies designed to function across regimes, emphasizing the need for diversified risk models, guardrails that prevent overfitting, and a clear understanding of how macro shocks can overwhelm bottom-up stock selection. She details the evolution of factor research, including the durability of broad categories such as value, momentum, and quality, while outlining how competition and data availability reshape their effectiveness over time. Lastly, she discusses the growing role of non-traditional data — from earnings-call text to machine-learning tools and LLM-driven sentiment extraction — while underscoring the importance of broad, consistent datasets that can be applied across global universes. Against the backdrop of the S&P 500’s heavy top-weighting, Jessica details how diminished breadth affects opportunity sets, investor demand for alternative approaches, and the search for alpha outside the most crowded areas of the market. I hope you enjoy this episode of the Alpha Exchange, my conversation with Jessica Stauth.

They say there’s always a bull market somewhere and a chart on doom commentary has surely been up and to the right. Perhaps it’s been the joint decline in the equity and crypto markets. NVDA is down 10% in November and Bitcoin is down almost twice that. Perhaps it’s been that there wasn’t a hard and fast enough of a catalyst to point to…no trade war, Powell presser, CPI surprise or earnings shortfall. These would have at least left us with plausible drivers, satisfying our need for markets to make sense. But when price operates as the only fundamental, sell-offs in asset prices take on much greater meaning.If there’s one idea that best captures my own curiosity about markets it lies in studying our presence in them. And here’s where the Soros theory of reflexivity is so relevant, especially to modern day risk-taking. Reflexivity is a brilliant concept and price is central to it. Price is surely an outcome that results from changes in economic data, corporate profits and adjustments in the stance of monetary policy. Today, price is more properly thought of as a driver of wealth, which in turn, allows it to drive investment behavior and also narratives. In the process, it can actually shape fundamentals.Through this lens, I share some of my recent thinking on the risk structure of the equity and crypto markets. I hope you find this interesting and useful. I wish you a wonderful, relaxing and highly caloric Thanksgiving holiday.

Welcome back to the Alpha Exchange. In today’s episode, I am joined by Megan Miller, Senior Portfolio Manager and Head of the Options Solutions team at Allspring Global Investments. Her career spans the extremes of market volatility—from learning options trading during the GFC to now overseeing option-based strategies across a $600 billion platform. The conversation centers on how her team uses a GARCH-like modeling framework as part of a systematic approach to forecast future realized volatility. From this, signals emerge as to which options are over or underpriced.Megan explains how the democratization of options has reshaped implementation. While call overwriting may appear simple, doing it efficiently at scale requires advanced technology, rule-based construction, and close attention to liquidity across both U.S. and global underlyings. She outlines how index-option overlays can deliver income, preserve stock-specific alpha from the underlying equities, and manage beta more deliberately—an especially relevant point as today’s markets continue to show wide dispersion between single-stock moves and index-level volatility.As client demand shifts with the market cycle, Megan highlights growing interest in income-oriented solutions, alongside renewed attention on hedging amid concerns around rates, AI-driven valuations, and geopolitical risk. She also underscores the rising importance of customization—whether for tax management, factor tilts, or exposure constraints.Megan closes with insights on mentorship, learning, and the value of embracing every stage of a career.I hope you enjoy this episode of the Alpha Exchange, my conversation with Megan Miller.

On this episode of the Alpha Exchange, I’m pleased to welcome back Jordi Visser, CEO of Visser Labs and Head of AI Macro Research at 22V. Our conversation centers on one of the most consequential themes in markets today: the intersection of artificial intelligence, exponential innovation, and market structure. With Nvidia’s historic rise as a backdrop and AI’s increasing integration into every sector, Jordi pushes back on the tendency to label this cycle a “bubble,” arguing that AI is more akin to electricity — an enabling technology whose applications will permeate everyday life. Demand for compute remains effectively infinite, he notes, and the supply shortfalls in GPUs, data centers, and power capacity shape how investors should think about the buildout phase.Jordi also lays out a framework for navigating volatility in sectors tied to AI buildout — including how to handle 20–30% drawdowns — and why estimate revisions matter more than multiple expansion from here. Beyond markets, we explore the labor dynamics of exponential technology: the K-shaped economy, margin pressure at retailers, and why he believes labor participation will keep drifting lower even without mass layoffs.Finally, we examine the policy environment. Here Jordi asserts that the Fed’s framework is backward looking and misses how humanoids, robotaxis, and accelerated drug discovery may drive deflationary pressures.I hope you enjoy this episode of the Alpha Exchange, my conversation with Jordi Visser.