🎯 Market Signals for 2026 According to Goldman
📊 Introduction: Finding the Signal in the Noise As the year draws to a close, investors and curious readers are inundated with a flood of forecasts, predictions, and market commentary. The sheer volume of information can be overwhelming, making it difficult to distinguish between fleeting daily noise and the significant, structural trends that will actually shape the economic landscape in the year to come. This post aims to cut through that noise. We've distilled recent global market analysis to identify five of the most surprising and impactful signals that may be flying under the radar. These aren't just fleeting headlines—they're underlying shifts in data credibility, investment strategy, geopolitical cohesion, monetary policy, and financial infrastructure. 🚨 Five Surprising Signals for the Year Ahead 1️⃣ The Speedometer is Off: A Credibility Crisis in US Inflation Data A recent US Consumer Price Index (CPI) report appeared to be an impressive miss on inflation at first glance, but a closer look revealed that the positive result was achieved through "extraordinary omissions and smoothing choices." This has drawn criticism of the methodology used by the Bureau of Labor Statistics (BLS), specifically for its apparent assumption that rent and Owners' Equivalent Rent (OER) were zero for the month of October. 📌 As noted in a comment retweeted by WSJ's Nick Timiraos: "This is totally inexcusable. The BLS just assumed rent/OER were zero for October. I am sure they have a good technical explanation for this, but the only way you get a two-month average for rent of 0.06% and OER at 0.135% is assuming October was zero. There is just no world in which this was a good idea, but here we are." Why this matters: This raises critical questions about the accuracy of the tools used to measure the economy's health. After all, one way to let an economy "run it hot" is to effectively remove the speedometer. 🌡️ 2️⃣ The AI "Space Race" Isn't About Who's Spending the Most 🚀 The massive investment cycle in Artificial Intelligence is increasingly being viewed as a modern-day "space race." However, the counter-intuitive takeaway is that the companies spending the greatest quantum of investment dollars to "win" this race face highly uncertain returns on that capital for the foreseeable future.