InSight

Market InSights:

When does a Bear look like a Bull? (Pt. 2)

When will a Bear-Market Rally form a New Bull?

The market will turn around, they always do, some would argue that they are built to expand. Below are some of the elements we look for to determine if a market is turning around, or if we are looking at another Bear Rally. 

Rallies will get longer in time, and less dramatic 

The drama of a bear market is exciting and news outlets love it. The markets and the news gravitate towards those chaotic headlines. This was easily seen when during the last Bull market news outlets ran headlines and talking heads marking the top, declaring market “warnings” and finding economists that would deride the market. It’s exciting and captures eyeballs…the turnaround won’t be all that exciting. 

There won’t be a day of major capitulation, followed by a counter move to the upside. It will come with steady, long-term grinds up. It will come with the whole market moving up in a coordinated and cooperative way. Markets with a broad influence from several sectors that grind out small moves over a long time are far more attractive to investors and generate a virtuous cycle. 

The Bear Rallies of 2022 so far…

 

Days

Percent

Daily %

Bear Rally (1)

9

6.1%

0.67%

Bear Rally (2)

11

9.9%

0.90%

Bear Rally (3)

12

6.2%

.51%

Bear Rally (4)

41

14.3%

.34%

Bear Rally (5)

?

?

?

The median gain of the largest rallies that have occurred within bear markets is 11.5% over 39 days. Typically, the rallies on the low side of the median, occur early in the bear market, while those that exist on the high side are in the more mature parts of the bear market.

Additionally, there are far more rallies below the mean, than above. Meaning that we will see more false rallies that are short and volatile and only a few long-term sustainable rallies that are long with small moves.

The longer these rallies get, and the smaller the moves, the more likely an “all clear” can be declared. 

There will be broad support  

Investment professionals look for certain technical signals to be in place before confirming a reversal is underway. There are several measuring sticks that look for broad support in trading. The advance-decline line, trades above the moving average, and the McClellanOscillator are examples of technical measurements of the breath the market is moving, for how many stocks and how many sectors are participating in the move. 

“Breadth thrust” is the term for these signals, and a leading indicator if a market is transitioning from a Bear to a Bull. The duration of the move and the price gains associated with it are also important. The indicators that most reliably confirm that there is a shift into a new bull market are:

Flows into equities and out of cash in important ETFs

There are “traders” ETFs, and there are “investors” ETFs, and knowing the difference is important.

If dollars are flowing into leveraged high volatility trading products it is a signal that the market is trading for a short-term and volatile swing (read a bear rally). If money flows are going into long-term holds that cover the whole of a market in balanced and long-term ways, it’s a signal that the investment appetite is changing to a more long-term outlook and investors are building a new core of their profile. Outsized flows into SPY, QQQ, or VOO are a good sign that the broad market is healthy and investors are willing to hold the whole of the market. 

The current market is witnessing the worst first half for stocks and bonds in 50 years, the highest inflation in 40 years, and an endless barrage of bad economic data. So seeing a broad, coordinated shift from cash and cash-like funds, into broad equity will be a good sign in a change from “risk off” to diversified “risk on”.

Earrings being “better than expected” at more and more companies

There is an entire industry reporting on “beats and misses” on companies’ earnings. While individual stock stories are exciting and reported on the news, the sizes and frequency of misses vs. beats are often overlooked. 

Wall Street pros are at odds as to whether we are at an inflection point in the markets. That inflection point will be confirmed when estimates, which are increasingly bleak, are replaced by corporate earnings that are better than expected. This will take several quarters and is a laggard indicator. But is the most reliable measurement to say the companies that make up the market are in a healthy and expansionary space. This seachange in earnings will likely happen 2-3 quarters after the market has “bottomed”, so while not a great trading and timing indicator, it is a very good indicator of changes in the macroenvironment.

Company earnings are a more reliable indicator of investment health, this is not a shocking revelation. But the frequency and diversity by which these companies manage inflation pressures, and sell their product to the marketplace is a tide that raises all boats and encourages board participation in rising stock prices. 

What past Bear-Markets tell us about future ones

A peek at the history of bear markets would suggest that the “naysayers” are on the right side of history, at least for a time. In the 30 different bear markets that have occurred since 1929, the stock market registered an average decline of 29.7%. These downturns lasted have lasted for an average of 341 days. 86% of the bear markets last less than 20 months, and few last longer than one year.  

Right now, according to traditional economic interpretations, the U.S. could well be in a recession. We have seen two-quarters of GDP contraction. The Commerce Department reported that gross domestic product shrank by 0.9% in the second quarter of, after contracting 1.6% in the first quarter of this year. That’s it, that is the traditional definition of a recession, and the Bear market has priced that move in as a result. 

So why the “is this a recession this time” talk? Well, there has been a rash of different pro-growth data that has persisted. Wages have grown, unemployment has stayed low, and demand for freight, semiconductors, and component raw materials has been high. These would indicate that demand is still healthy. How can you have a recession with such a demand for materials? 

If the Fed can achieve the delicate balance of taming inflation by slowing the economy without tipping the country into a recession, this bear market could already be long in the tooth. If we count the correction from the November high, we will be entering the second year of the bear market next month. The one-year mark for this Bear market would come in March of 2023 (just around the corner by economic standards – meaning we are currently in the 3rd or 4th inning of the Bear Market with the most violent changes in pricing behind us. This would be an “un-recessionary bear market”

If the Fed fails in a “soft landing” in the first quarter of next year more reliable indicators of recession (falling commodity prices, major spikes in unemployment, and weakening manufacturing outlooks) are on the rise before the Fed quells inflation then we can see a more elongated bear market and a full-blown recession. 

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The Engine Room of AI: Servers, Networks, and the Cloud Infrastructure Beneath Every Model

Artificial intelligence is often discussed through the companies that design chips or develop software. Those businesses matter, but neither layer can create economic value without the infrastructure that connects them. This is Post 5 in our eight-part AI investment series, following the value chain from AI Semiconductor Supply Chain → AI Compute & Networking → AI Intelligence. The series anchor, “AI Is Bigger Than AI Stocks: The Eight-Layer Value Chain Every Investor Should Understand,” can be found in the Articles and News archive. The AI Compute & Networking layer is the engine room beneath every model. It includes servers, storage systems, networking equipment, optical components, cloud infrastructure, and the data centers that house them. Semiconductors provide the processing capability. Compute infrastructure assembles that capability into usable systems. Software and intelligence layers then run on top of it. That structure has an important investment implication: AI is a connected economic value chain. Every layer depends on the layers beneath it, and a portfolio can unintentionally count the same AI exposure multiple times. Why Compute and Networking Are Necessary A high-performance AI chip is not a complete product for a model developer or enterprise customer. It must be integrated into a server, connected to other servers, supplied with data, cooled, powered, and managed through specialized software. Training and operating large models require thousands: or, in the largest deployments, many thousands: of processors working together. The system must move data rapidly between: Individual processors inside a server Multiple servers within a rack Server racks across a data-center cluster Separate data centers and regions Compute systems and high-capacity storage This creates several infrastructure requirements. Servers package processors, memory, power delivery, cooling, and management systems into deployable units. AI-optimized servers are materially different from conventional enterprise servers because they must support high-power accelerators, specialized interconnects, and dense thermal-management systems. Networking equipment allows processors to communicate with one another. In AI workloads, network performance can directly influence how efficiently expensive compute capacity is used. A bottleneck in the network can leave processors waiting rather than calculating. Storage holds the enormous datasets used to train and fine-tune models, along with model weights, checkpoints, logs, and customer data. Training systems need both high capacity and high throughput. Storage is not simply an archival function; it is part of the performance profile of the AI cluster. Cloud infrastructure converts these physical assets into a service. Customers can access computing capacity through infrastructure-as-a-service, rather than purchasing and operating an entire data center themselves. The result is a layered system in which chips, servers, networks, storage, power, cooling, and software must operate as a coordinated whole. The direct benefit is higher utilization, better reliability, and more predictable access to compute. Demand Drivers: From Hyperscaler Capital Expenditure to Network Speed The immediate demand cycle is being driven by substantial capital expenditures from hyperscalers and other large technology companies. Amazon, Microsoft, Alphabet, Meta Platforms, and Oracle are among the major providers investing in data centers, servers, networking, power systems, and cloud capacity. The relevant question for investors is not simply whether capital expenditure is increasing. It is how that spending is allocated and whether it produces durable revenue, acceptable returns on invested capital, and recurring customer demand. Several infrastructure trends are especially important. AI-Optimized Server Demand AI servers typically contain high-value accelerators, large memory configurations, advanced cooling systems, and high-speed network interfaces. Their dollar content can be substantially higher than that of general-purpose enterprise servers. However, higher revenue does not automatically mean higher profitability. Server manufacturers face component costs, customer pricing pressure, supply-chain constraints, and rapid product refresh cycles. Investors should distinguish between reported shipment growth and sustainable margins. Higher-Speed Networking As clusters grow, the network must move more data with lower latency. The industry is transitioning through 400G and 800G Ethernet and optical connections, while 1.6-terabit technologies are beginning to appear in advanced road maps and deployments. The exact mix depends on cluster size, architecture, distance, power constraints, and whether the customer uses Ethernet, InfiniBand, or a hybrid approach. In general: 400G remains important for many server-facing and existing deployments. 800G is increasingly central to new, large-scale AI fabrics. 1.6T represents the next step in bandwidth density for the highest-performance systems. Optical transceivers, fiber, direct-attach copper cables, active cables, and related components become increasingly important as electrical signals face distance, power, and signal-integrity limits. NVIDIA’s LinkX interconnect overview provides a useful technical illustration of how cables, transceivers, InfiniBand, and Ethernet fit together within AI infrastructure. Scale-Up and Scale-Out Architectures AI infrastructure uses two complementary approaches. Scale-up connects processors within a tightly integrated system so that they can share data rapidly. This approach emphasizes memory bandwidth, low latency, and specialized interconnects. Scale-out connects many systems across a broader cluster. It emphasizes switching capacity, network topology, workload scheduling, reliability, and the ability to expand without rebuilding the entire environment. The distinction matters because different suppliers benefit from different infrastructure decisions. A company focused on servers may have limited exposure to the optical or switching components required for scale-out. Conversely, a networking supplier may benefit from cluster expansion even when individual server configurations change. Storage for Training Data Large language models and other AI systems require extensive datasets, model checkpoints, and continuous data movement. High-performance solid-state storage, storage networking, data-management software, and capacity-oriented systems all participate in this demand. Storage demand can be uneven. Customers may initially build performance storage for training and later add less expensive capacity for inference, archives, and backup. This creates opportunities across different storage categories but also introduces pricing pressure and inventory risk. Potential Investment Opportunities Across the Layer The Compute & Networking category includes several distinct business models. Representative public companies and exchange-traded funds can help investors identify areas for further research, but they are illustrative examples: not recommendations. Server OEMs and ODMs Server original equipment manufacturers and original design manufacturers assemble systems for enterprise, government, cloud, and specialized customers. Examples include Dell Technologies, Hewlett Packard Enterprise, and Super Micro Computer among branded or system-focused vendors. Quanta Computer

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The investment opportunity in semiconductors

Microchips, more commonly known as computer chips or integrated circuits, have become an integral part of our lives. They are present in everything from our smartphones and laptops to our cars and household appliances. In recent years, the importance of microchips has grown exponentially, particularly with the rise of artificial intelligence (AI) and machine learning. At their core, microchips are essentially tiny electronic circuits etched onto a small piece of semiconducting material. They contain transistors, which are essentially tiny switches that can be turned on and off to perform calculations and process information. The number of transistors on a chip has been increasing rapidly over the past few decades, following Moore’s Law, which states that the number of transistors on a chip doubles approximately every two years. The increasing number of transistors on a chip has led to the development of more powerful and efficient processors, which are the backbone of computing power. The more transistors on a chip, the more calculations can be performed simultaneously, and the faster and more efficient the processing power becomes. This has allowed for the development of faster and more sophisticated computing systems, from supercomputers to smartphones. However, the significance of microchips extends beyond just computing power. With the rise of AI and machine learning, microchips have become the cornerstone for the development of these technologies. AI relies on large amounts of data and complex algorithms to make decisions and predictions, which require immense computing power and the ability to process vast amounts of data quickly. This is where microchips come in, providing the necessary processing power and efficiency to support these complex algorithms and enable the development of AI and machine learning systems. As AI continues to evolve and become more advanced, the demand for more powerful and efficient microchips will only increase. Companies that specialize in the design and manufacture of microchips, such as Intel, AMD, NVIDIA, and Qualcomm, are at the forefront of this rapidly growing industry. Investing in these companies can be a smart move for those interested in the potential growth of the microchip industry and the continued development of AI and machine learning technologies. Microchips are a revolution right now, the backbone of modern computing, and are crucial for the development of AI and machine learning. The increasing number of transistors on a chip has led to more powerful and efficient processors, which have enabled the development of faster and more sophisticated computing systems. As AI continues to evolve and become more advanced, the demand for more powerful and efficient microchips will only increase, making them a crucial investment opportunity for those interested in the future of technology.

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Cash Is a Trap: Why Waiting Could Cost You in 2025

The Short Version – What you need to know: Cash is offering yields that are unusually high and unsustainable. Stick with it too long, and you risk missing better opportunities. Here’s why (the long Version): There is no denying it — cash has been king lately. After years of getting pennies on your savings, it finally feels like the tables have turned. Money market funds are paying 4-5%, Treasury bills are delivering solid, predictable returns, and even your once-neglected savings account is earning something that resembles real money. For the first time in over a decade, savers are winning — or at least it feels that way. If you’ve been parking your money in “safe” places, collecting interest without risk, it’s been a breath of fresh air. No volatility. No headlines to stress over. Just quiet, steady yield. And for many, that’s been a welcome change. But here’s the problem: that feeling of safety is blinding. Because the moment rates start to fall — and they will — the music stops. And by the time most investors realize the opportunity has moved on… it already has. There are a pair of market forces looking to see the interest rates on cash to get cut, the first is President Trump’s constant pressure on the Fed to cut rates, a message that dates back to the first term, and likely his long-held belief from a background in real estate that unnaturally low rates drive asset values up. And he’s right, on that side of the ledger, equity assets will go up in an environment where cash has low intrinsic value. The second element is the slowing economy, for fear of a deterioration in consumer confidence under the new weight of tariffs on imports, the consumer will see a pair of financial pressures: 1) that the costs of goods continue to rise, and 2) taxes and wages are likely flat for the year to come. But here’s the warning no one likes to hear: Cash is a trap. And by the time rates fall, it will be too late to move. The Fed’s current interest rate — just over 4.25% — has created the illusion that holding cash is a viable long-term strategy. But history tells a different story. This window won’t stay open much longer. When the Fed Cuts, Yields Vanish Let’s take a step back and look at the broader pattern behind rising cash yields. When the Fed raises interest rates, it’s typically doing so because the economy is running hot; inflation is climbing, jobs are strong, and markets are roaring. This sounds a lot like 2024 to us. In that kind of environment, it makes sense that cash starts paying again. It’s a signal that the Fed is leaning into strength, cooling off excess demand, and trying to engineer a “soft landing.” A condition we saw engineered masterfully in 2023/2024 by Jerome Powell and the FOMC. Inflation is already making its way through the economy — and the first wave is hitting the Producer Price Index (PPI), which tracks what upstream industrial producers pay for inputs. This month, it jumped 21% month-over-month, largely due to the impact of new tariffs. This marks the first tangible sign of tariffs driving real economic consequences. But here’s what most investors miss: those rising yields are the last breath of the boom. And when the tide turns, the shift is fast and often violent. Look at the Fed’s past behavior, every time it hikes even moderately and over several quarters, it eventually pivots twice as fast: After peaking at 6.5% in November 2000, the Fed cut rates to under 2% by February 2022, as the dot-com crash began unraveling. In 2006, rates hovered at 5.25%, but by the end of 2008, we were at zero, as the financial crisis hit with full force. In 2018, the Fed started easing again within months of its last hike as trade tensions and growth fears crept in, before COVID even surfaced, and then COVID short-circuited the recovery that began in 2015. With COVID in the rear-view mirror, the Fed continued that work, successfully raising rates in the most ambitious clip ever from 2022 to Sept 2023, where we are hovering now…and it is now VERY unlikely the next move is higher. This isn’t a coincidence. The Fed hikes gradually, cautiously, data-dependent, often telegraphed months in advance. But when does it cut? It cuts decisively. Because by that point, the damage has already begun. So what does this mean for cash investors? It means that the window to benefit from +4-5% yields is narrow and shrinking. And more importantly, if you wait until the Fed actually begins cutting, you’ve already missed the market’s reaction. Bond prices have risen. Equities have started their climb. And your “safe” money is now chasing yesterday’s opportunities. Why Waiting to “See What Happens” Doesn’t Work Here’s the trap: You hold cash at 5% because it feels safe. The Fed cuts once, then twice, and suddenly your yield is 3.5% or lower. You decide it’s time to buy bonds… but they’ve already gone up in price. You look at equities… and they’re already rallying because the market saw this coming. In short: you’re chasing returns with worse timing, less yield, and more risk. You Only Get One Shot at Today’s Yields Cash works “right now”, but it doesn’t scale and cannot last. Your bank teller getting you to “buy a CD for +5%” is the calm before the collapse. Those 6 months of “teaser” rates get your capital off the sidelines and lets the bank buy longer term duration debt, they pay you the +5% they collect from other longer term assets for the first 6 months (the duration of the CD), then if and when rates drop they are left with a long term asset still paying the +5% yield and offer you the new CD at prevailing rates at 3% or less…the bank profits on the spread by letting you lend

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