Alpha Exchange

It was a pleasure to welcome Amanda Lynam, Chief Credit Strategist in Global Investment Research at Goldman Sachs, back to the podcast. Nearly three years after our first conversation, much has changed! With the extraordinary capital expenditure cycle underway in artificial intelligence, there is no shortage of questions about how the corporate credit market will finance it and what the growing supply of debt means for investors.

We begin with Amanda’s assessment of the broader credit landscape. She describes a market supported by resilient economic growth, generally solid corporate fundamentals, and powerful demand from yield-oriented investors, including insurers, pensions, and foreign buyers. These forces have kept periods of spread widening relatively brief, even as issuance has accelerated.

We then turn to the scale of the AI buildout. Amanda walks us through Goldman Sachs’ estimates for hyperscaler capital expenditures and debt issuance, along with the financing needs of data centers, chips and other businesses supporting the AI ecosystem. We discuss why companies are raising debt before an immediate funding gap appears, how much issuance the investment-grade market can absorb and why private markets may take on a larger role as the cycle progresses.

Importantly, Amanda sees little evidence so far that AI borrowing is crowding out other corporate issuers. Instead, investors appear increasingly attentive to their total exposure to the theme across equities, bonds, and private assets. That creates a renewed role for sectors such as banks, energy, healthcare and food and beverage as sources of diversification.

Lastly, we explore the risks that could challenge today’s supportive credit backdrop, particularly an increase in rates volatility that weakens yield-based demand. Amanda also discusses the evolving high-yield market, the software refinancing calendar, and the role of real assets in portfolio construction.

I hope you enjoy this episode of the Alpha Exchange, my conversation with Amanda Lynam.

Kimberly Gallant, the Global Head of QIS Structuring at CIBC, has spent nearly two decades working across quantitative investment strategies, derivatives and structuring. Our conversation is a deep dive into the evolution of QIS and the economic rationale behind these increasingly important systematic investment strategies.

We begin by exploring the origins of QIS and how ideas from academia, pension funds, commodity markets and bank trading desks ultimately converged into a cross-asset business focused on generating alternative sources of return. Kimberly explains that at its core, QIS is about identifying persistent factors, facilitating risk transfer between market participants and packaging these exposures in a transparent and efficient way.

The discussion turns to carry and volatility risk premia. Kimberly describes carry as compensation for taking a risk that another market participant needs to transfer—essentially the insurance premium of financial markets. Importantly, she explains why an attractive backtest alone is never enough. Investors must first understand the economic hypothesis behind a premium and whether the market structure supporting it is likely to persist.

Lastly, we discuss crowding, leverage and correlation. Kimberly explains how a strategy can evolve from alpha to a fairly compensated risk premium, and how crowding can initially make performance appear stronger before a market shock exposes the underlying positioning. Unexpected correlations and forced unwinds can then turn what should have been a contained event into something much larger.

I hope you enjoy this episode of the Alpha Exchange, my conversation with Kimberly Gallant.

In this discussion, I make the case for tail hedging. I communicate two main ideas. First, I lay out the concept of the “fourth type of risk off”, an episode that features instability in the back end of the US bond market. As I’ve said, nothing can really work in markets if the Treasury market does not. Count me as worried that the US fiscal issues are incredibly difficult to solve – we wouldn’t be here otherwise – and that the timeline to address them has shortened.

Second, I argue that the US economy and market are far too exposed to the AI capex trade. There are various correlations that emerge, two of which are among the companies in the value chain and between the economy and the market. The AI buildout is demanding capital that is likely putting upward pressure on real rates. A prospective homebuyer may certainly find a 7% mortgage rate restrictive. A hyperscaler chasing AI gold may not find the current cost of debt capital restrictive at all. If getting inflation to target means slowing this capex materially, leading to a meaningful decline in the equity market, there could be substantial knock-on impacts via the wealth effect and an economy which has gathered so much beta to ongoing capex.

These concerns are set against some of the lowest prices for financial market insurance we have seen in a long time. I find tremendous value in long optionality. Buckle up. The midterms are coming, monetary policy is in flux, the back end of the yield curve is wobbling, the AI trade is way too concentrated, and implied volatility is quite low.

I wish you a wonderful holiday weekend and thank you for listening.

I really enjoyed hosting this Alpha Exchange discussion with Ulrike Hoffmann-Burchardi, CIO for the Americas and Global Head of Equities at UBS Global Wealth Management. Ulrike has had a long career in markets, having spent nearly 25 years at Tudor Investment Corporation working across quantitative macro and global tactical asset allocation before joining UBS.

We begin with Ulrike’s academic background in economics, political science and financial econometrics and the path that ultimately brought her from academia to Tudor. She reflects on the culture created by Paul Tudor Jones and several lessons that stayed with her throughout her career: the importance of respecting trends, sizing positions appropriately, understanding liquidity and recognizing that while markets continually evolve, the human emotions driving them remain remarkably consistent.

We then turn to portfolio construction at UBS, where Ulrike and her team combine three distinct lenses: macro, bottom-up fundamentals and structural trends. Within that structural framework, they are focused on three transformational opportunities—artificial intelligence, power and resources, and longevity. We discuss how AI connects all three and why the enormous capital expenditure associated with its development is increasingly becoming a macro factor in its own right.

Ulrike walks us through the potential bottlenecks to the AI buildout, from electricity and grid capacity to permitting, turbines and transformers, as well as the possibility that monetization fails to keep pace with investment. We also explore opportunities across the AI value chain, including semiconductors, power, industrials, materials and healthcare.

Lastly, we discuss hidden correlations and why portfolios that appear diversified across traditional asset classes may share common underlying exposures.

I hope you enjoy this episode of the Alpha Exchange, my conversation with Ulrike Hoffmann-Burchardi.

The IMF’s Global Financial Stability Report is a twice yearly, must read. Leading the excellent research done here is Tobias Adrian, Financial Counsellor and Director of the Monetary and Capital Markets Department at the IMF. It was a pleasure to welcome Tobias to the podcast to explore the IMF’s financial stability framework, vulnerabilities in global markets, and the evolving risks shaping the financial system.

We begin with Tobias’ role and the evolution of the GFSR, which combines market intelligence, analytical research, and a framework for assessing financial vulnerabilities. He explains how the report has shifted alongside the macro backdrop, from an environment defined by low inflation and negative-yielding debt to one characterized by higher inflation, tighter financial conditions, and geopolitical uncertainty.

A central theme throughout the conversation is the distinction between forecasting shocks and identifying vulnerabilities. Tobias describes how the IMF focuses on leverage, maturity transformation, valuation, currency mismatches, and interconnectedness rather than attempting to predict the next catalyst. The discussion explores how these vulnerabilities can amplify the effects of unexpected shocks across financial markets.

We then turn to several themes from the most recent GFSR. Tobias discusses artificial intelligence as both a driver of investment and productivity while examining the financial linkages, capital spending, and interconnectedness developing across the AI ecosystem. He also outlines the IMF’s assessment of sovereign debt, rising term premiums, and the growing role of non-bank financial institutions in financing global markets.

The latter part of the discussion focuses on market plumbing, including leverage in hedge funds, Treasury basis trades, derivatives markets, and the challenges of monitoring system-wide positioning. Tobias explains how liquidity, options markets, and quantitative strategies can contribute to vulnerabilities that become apparent during periods of market stress.

I hope you enjoy this episode of the Alpha Exchange, my conversation with Tobias Adrian.