October was a good month for financial markets, with a broad-based rally across geographies and sectors. Tech stocks and gold led the way, and the dollar finally had an up month. QuantStreet's strategies, across different risk levels, moved in line with or slightly exceeded benchmarks. More details about our performance are available here. We'll be carefully watching the dollar's seeming bounce off its 2025 lows. Should this continue, our portfolio overweights in U.S. assets should provide a boost to relative performance.
At the root of the festivities has been a strong Q3 earnings season across all S&P sectors, which coincides with a decline in talk of bubbles and impending market crashes. Though such ruminations are likely to return, it is nice to go at least a few weeks without endless reminders about how the current stock market rally is likely to end up in a cataclysmic crash. For what it's worth, QuantStreet's large selloff model--which uses a neural network to calculate the likelihood of a greater than 20% selloff over the next 12 months--continues to be sanguine.
Positives
Taking a break from our last two investor letters (here and here)--where we summarized and then argued against some of the prevailing bearish narratives--let's spend the next few minutes recounting some positive trends out there in financial markets.
First, the Fed is easing and the market expects Fed easing to continue. The CME's FedWatch tool shows that the market expects 75 basis points of rate cuts over the next year. The Fed is also reducing its quantitative tightening (QT) program, by starting to reinvest principal repayments into Treasury bills, which will provide robust support to rates at the short end of the curve. We've written in the past that markets do well when the Fed eases, and that remains our view. The provision of additional liquidity through the end of QT won't hurt matters.
Despite the oft-articulated concerns about the pace of AI buildout, the fact that parts of it are being financed via debt, and that many companies involved in the AI ecosystem enter into contracts with one another (which seems natural but nevertheless worries many), the projected demand for AI is truly astounding. McKinsey recently produced the following chart showing that the increase energy demands needed to drive AI buildout over the next five years (112 gigawatts) equals roughly three times the the entire energy generation capacity of New York state (40 gigawatts at the summer peak). McKinsey estimates that the total spend will be between $3 trln and $8 trln by 2030.
Someone is going to have to produce all the chips and power generation infrastructure needed to support this massive buildout. Looking at the percent of GDP that has been dedicated to information processing and software shows that the recent blip in investment, large as it is, is just that: a blip. The buildout that preceded the dot-com bubble of 2000 took years to materialize.
Similarly the real estate boom that preceded the Global Financial Crisis of 2007-09 took years to fully form and represented a much larger share of GDP than what we've seen so far with AI. This not to say that debt-fueled overinvestment can't lead to bad future outcomes. It certainly can. But our view is that the time horizon of the AI buildout is in years not in months, and (to use an overused analogy) we are still in the early innings.
Finally, one should keep in mind the deregulatory agenda advanced by the Trump administration. Estimates suggest that the anticipated decrease in regulatory capital requirements, to the tune of nearly $140 bln, will unleash lending capacity of $2.6 trln in the U.S. banking system, according to a recent FT article. Many on Wall Street expect a commensurate increase in the pace of M&A activity.
On top of that, corporate leverage in the U.S., when measured relative to the stock market capitalization of U.S. firms (the blue line), is at all-time lows, according to data from the St. Louis Fed's FRED website.
Even debt relative to companies' total net worth (sort of like book value of equity, but using market instead of book values for assets) looks benign. With credit spreads and Treasury yields low, an impending M&A cycles, and low corporate leverage, the economy has a clear runway for debt-fueled growth.
Risks and looking ahead
None of the above is to say there are no risks in current markets. Whether it's high levels of valuations, high government debt loads and budget deficits, potential political interference with the Fed, an incessant rise in the gold price, geopolitical uncertainty, the (mild) deterioration of the dollar's reserve currency status, AI overcapacity, and many as yet unarticulated risks, there are plenty of reasons to be concerned. As already mentioned, we've spent the last two investor letters talking about exactly these risks. But while some of these risks may be years in the future, the positives appear more imminent.
QuantStreet's portfolios underwent minor changes in in November, largely maintaining our U.S. overweights and risk positions that are consistent with long-term portfolio objectives.
When thinking about your own portfolio you should carefully weight the risks and opportunities that are currently on offer. Make sure that your portfolio is a good fit relative to your own risk and liquidity needs. Ultimately markets have a way of making any forecaster look foolish--present company included--and the best way to handle your own investment portfolio is to make sure you are not a forced seller when the inevitable market crisis arrives.
If you'd like further details about our model portfolios or help in thinking through how all of these issues impact your own investment plans, please reach out.
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Please keep in mind that all financial forecasts are fraught with risk and uncertainty. Our views may prove incorrect and market outcomes may be materially worse than we anticipate. Please see our full disclosure about the limitations of financial forecasts and the risks of investing at https://quantstreetcapital.com/terms-of-use/.
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