Alpha Exchange

With one of the largest repricings in fixed income in decades underway, Brij joins me for a wide-ranging conversation on monetary policy, inflation, the wealth effect and where he sees opportunity across global bond markets.

We begin with a provocative question: what if interest rates have become more effective at influencing financial markets than the real economy? Here, Brij argues that the traditional relationship between rates and business investment has weakened considerably. Ultra-low and negative real rates did not necessarily generate the productive investment policymakers hoped for. Instead, they helped encourage greater financialization, from household leverage and corporate stock buybacks to private equity activity and, more recently, government borrowing.

That leads us to inflation and Brij's argument that today's remaining price pressures are increasingly connected to wealth rather than wages. With an enormous amount of household wealth tied to equities, particularly among older generations, we explore how asset-price appreciation can support spending in areas like housing, healthcare, restaurants and travel even as labor-market demand cools.

We then turn to the Fed and the dramatic repricing underway across developed-market yield curves. Brij explains why the front end remains closely tied to expectations for monetary policy, while longer-dated yields incorporate a much broader debate around nominal growth, term premium and the economic consequences of the AI investment boom.

AI itself becomes an important part of the discussion. We examine whether extraordinary capital spending and borrowing by hyperscalers are contributing to higher bond yields, changing the traditional stock-bond relationship and potentially crowding out other borrowers.

I hope you enjoy this episode of the Alpha Exchange, my conversation with Brij Khurana.

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.