The US Federal Reserve That Doesn’t Stand Still
What happened last week?
Last week, the S&P 500 and Nasdaq jumped by 1.58% and 3.24%, respectively, while the Dow slid by -0.54%.
This week, investors will take in the latest on retail sales, industrial production, jobless claims, building permits and housing starts. The data should collectively point to an economy that is growing modestly while labor conditions cool down a bit.
3 Things to Know
The Fed Plays Defense
Under questioning, Fed Chair Jerome Powell noted that Federal Open Market Committee (FOMC) participants were given the chance to alter their forecasts on Wednesday morning after seeing the new CPI data.
Pushed further, his response was “most people don’t.” In essence, observers are splitting hairs over minor deviations in data subject to significant “randomness,” sample-based errors, and yes, the limitations of human forecasters.
Is 2.6% measured inflation really different from 2.8%? If you understand the survey samples and data construction process, we think you’ll agree with us: it’s virtually nothing.
More materially, as detailed in last week’s CIO Bulletin and Data Watch, readings on the economy are now unusually conflicting. The gap between employment growth reported over the past 12 months in the survey of employers and the survey of households is at a record.
Despite month/month volatility, we think evidence suggests a slowing in US employment growth is underway. In contrast, US monetary policy has done nothing but tighten in the past two.
Asked why the Fed would consider easing monetary policy, Powell explained that the current level of US interest rates is restrictive, meaning that “the economy would weaken without cuts.
Many observers have difficulty understanding why the Fed doesn’t just set US interest rates at levels it believes can be sustained for the longer run. Instead, the Fed deliberately sets monetary policy at “accommodative” or “restrictive” levels to sway inflation and employment. These settings are, by definition, not meant to be stable.
And Is Deliberately Cautious
Central banks can target 2% inflation, but when they “miss,” there isn’t a working strategy to make up for it with a below-2% target.
The Fed, for one, won’t sustain a deflationary monetary policy after taking responsibility for the Great Depression of the 1930s. While data for the month of May showed a strong gain for employment at US establishments, one risk Powell noted was that “The labor market has the tendency sometimes to weaken quickly. So, waiting for that to happen is not what we’re doing.”
In conclusion, we believe that once the Fed decides inflation risks are clear, it will begin a process of cutting rates, perhaps routinely by 25 basis points. This is in line with its history of sustaining increases and cuts over a span of many meetings.
Barring an economic catastrophe, the Fed is very unlikely to bring rates back to zero. But there is good space to cut from 5.25%-5.5% — the current policy range — and what the Fed views as “longer-term normal.” With an update, the Fed’s new projection of this is 2.8%.
We sense this estimate is still a bit too low. But unlike the 0.2% differences in inflation readings we mentioned, the gap between 3% and 5.5% for the Fed’s policy rate is far from trivial.
AI Is an Energy Transformer
The potential applications of AI are vast and include faster drug discovery, precise medical diagnoses, personalized learning, disaster prediction and response, streamlined supply chains, increased agricultural yields, and improved customer service.
AI’s ability to optimize processes, accurately predict demand, and make data-driven decisions can also enhance society’s efficiency in managing energy, food, water, and waste.
Applying AI-powered innovation to address societal challenges has the potential to maximize economic value while minimizing ecological footprint.
Currently the AI revolution has the character of a gold rush and we see one way to invest in the space remains in mega-tech leaders, AI infrastructure, and to a lesser extent AI end users.
In addition, we believe a compelling subset of potential opportunities in our ongoing AI-propelled digitization unstoppable trend include companies that are creating and/or employing strategies for sustainability challenges.
There is a class of problems that have been too costly or labor intensive for companies to address. These challenges tend to be less glamourous and are frequently neglected because the cost of solving them exceeds the value generated. For example, identifying individual strawberry plants with pests for hyper-localized and low waste insecticide application, or distinguishing which items in a generic stream of rubbish have enough copper that they’re worth salvaging at today’s market price.
Addressing these problems often requires analyzing large, diverse, and unstructured visual datasets while making frequent, incremental decisions. The era when specialized strategies were painstakingly developed for specific contexts, often at a considerable cost, is behind us.
Today, AI can create strategies for generic problems and adapt to shifting inputs at an unprecedented rate. As a result, these challenges are increasingly resembling avenues to boost profitability while maintaining competitive pricing.
See our weekly CIO Strategy Bulletin for more details