Bringing manufacturing back to the United States, colloquially known as nearshoring, is poised to significantly reshape trucking and rail networks across North America. The push for localized supply chains promises shorter delivery times and reduced geopolitical risks, but it also brings challenges in infrastructure and logistics. The companies solving these challenges are going to be critically important and could be an investment opportunity.

Nearshoring offers two big advantages and a few smaller challenges. First, it can help companies avoid tariffs and FX headaches. Second, it can shorten lead times and improve inventory management. Trump’s original push for tariffs and COVID-19’s supply chain shock have made a strong business case for bringing manufacturing back to the United States, but the cost of manufacturing domestically is higher than manufacturing abroad. However, having confidence that your supply chain can deliver and not having to deal with political spats carries significant value. Unfortunately, the higher costs associated with manufacturing domestically generally need to be passed on to the consumer. Higher prices for some goods are tolerable, but if it’s broad-based then it can be inflationary. An additional challenge is that the United States currently faces some constraints on manufacturing. Labor is one – we addressed it last month here – and transportation is another. Put simply, we need our domestic logistics to level up to accommodate a push for more manufacturing at home.

North American Trade

Mexico has become America’s largest trade partner, recently overtaking China as the top exporter to the United States. It is well positioned geographically and broadly has lower wage costs and a greater supply of labor for factory-level jobs than the United States. U.S. companies have invested significant capital in Mexico over the past several decades and many companies send parts back and forth from the U.S. to Mexico for different parts of the manufacturing process.

Canada’s geographic proximity has also made them a critical trade partner for the U.S., but mainly in the realm of natural resources. Crude oil, liquefied natural gas, lumber, and other mined commodities consistently supply US markets.

North American trade has become increasingly interwoven and has accelerated as scrutiny on China has mounted. According to the Brookings Institution, the U.S. imported $472.5 billion of goods and services from Mexico while Canada imported $15.6 billion worth of goods. The United States also accounts for over 40% of Mexico’s imports. This partnership is bidirectional and has led to gains for both the United States and Mexico. Generally speaking, Mexican manufacturing shouldn’t be seen as a direct competitor to American manufacturing but rather as a complement. Mexican factories use parts imported from the U.S. and vice versa; corporations have allocated capital across both countries to drive manufacturing efficiencies in an attempt to remain competitive with low-cost goods from China. While investing in Mexico means navigating complicated labor laws and exposure to cartel crime, the low-cost labor makes it a necessary input for effective North American manufacturing.

The degree to which companies can nearshore and access cheap labor in Mexico is important because it impacts the mix of goods that can be effectively manufactured outside of China. High-value goods like electronics and automotive components can be manufactured and sold domestically with cheaper labor in Mexico and capitally intensive factories in the United States combining to offer a competitive product. Potential shifts in U.S. import policy, specifically with regards to tariffs on Mexico and Canada could jeopardize this balance. The ability to manufacture efficiently in the United States could actually take a hit if we make trade with Mexico and Canada more difficult.

Consequently, while we are broadly optimistic on North American manufacturing, we’d shy away from trying to pick winners or losers who might be impacted by tariffs or trade disputes. Instead, we would suggest focusing on investment opportunities in companies who facilitate trade and transport unfinished components and final goods to their points of sale. The economy is strong and nearshoring has momentum, so the space is probably worth a look.

Nothing Is More American Than Trucking

The value of U.S. freight by truck with Canada and Mexico has steadily increased since the mid-2000’s and amounts to over $70 billion as of December 2023, according to the Bureau of Transportation Statistics. With nearshoring comes shorter supply chains, and an increase in the need for valuable truck space, meaning trucking fleets need to navigate the shifting trade landscape to accommodate retailers’ just-in-time inventory approach. With trucking, the two general approaches to shipments are full truckload (FTL) and less-than-truckload (LTL) – the latter meaning a single truck carries shipments from multiple customers and the former meaning all goods in the container are destined for the same location for the same customer.

Generally, LTL shipments are more expensive on a per-unit basis but offer manufacturers greater flexibility in getting finished goods to retail customers or storage warehouses. Instead of committing and paying up for larger shipments that take up entire truckloads, companies can have goods shipped with smaller, more frequent LTL runs which allow for quick inventory adjustments. These quicker adjustments are helpful during labor strikes or supply chain disruptions. LTL shipments account for just about 10-15% of the industry’s volume today, but the rise in e-commerce and necessary shorter transit times presents a compelling investment opportunity for trucking firms down the road.

Companies like FedEx Corp. (FDX) and Old Dominion Freight Line Inc. (ODFL), who specialize in LTL shipping, dominate the market and offer solutions to small and medium-sized enterprises that don’t have the scale to fill up whole truck beds with raw materials or finished products. Conversely, the FTL industry is highly fragmented and relies heavily on brokerage firms to match shippers with small and mid-size carriers.

According to RXO Inc (RXO), the top 15 FTL carriers combine for less than 10% of total market share. More than 95% of carriers operate 10 trucks or less! Although still critically important for the food, pharmaceutical, and consumer goods industries, it’s a heavily diluted market with minimal barriers to entry.

Innovating American Trucking

Artificial intelligence and technological innovation are coming for the trucking industry. Something as simple as improving routing could lead to significant cost savings. Technology enabling the real-time tracking of vehicles, predictive maintenance, and dynamic route adjustments based on traffic or weather conditions could all lead to bottom line improvements. Better routes and more well-maintained trucks reduce fuel consumption, repairs, and idle/empty drive times. Firms with enough capital to own trucking fleets and invest in technology, like XPO Logistics (XPO), can also integrate trucking fleets with warehouse management systems to streamline order processing and reduce downtime.

Technology can also help tackle regulatory complexity. Importing goods from Mexican maquiladoras, factories that import materials and export the finished goods, requires expertise in customs and border clearance. Facilitating the clearance of goods through U.S. customs and navigating documentation, duties, and inspections means third-party logistics firms like C.H. Robinson (CHRW) with integrated customs brokerage services are crucial for nearshoring to succeed.

Finally, the United States is facing an acute shortage of truckers, especially those who are interested in long haul journeys. The adoption of automated driving for semi-trucks would be huge for the industry. Regional routes often involve repetitive patterns and well-defined paths, making them ideal candidates for early implementation of autonomous driving systems. These systems can handle highway driving and reduce driver fatigue, while allowing human operators to focus on more complex urban or last-mile navigation. Currently, according to the American Journal of Transportation, the U.S. has a shortage of more than 80,000 truck drivers, a deficit expected to double by 2030. This is compounded by the composition of the trucking labor force – the average age of truck drivers exceeds the median labor force age in the U.S

Companies focusing on autonomous driving are therefore going to be crucial if nearshoring momentum is going to keep picking up. Companies like Aurora Innovation (AUR) have teamed up with technology giants like Nvidia (NVDA) to mass produce its integrated driverless systems. Furthermore, companies like Tesla have been working on Semitruck technologies for years.

Railroads Are Essential Too

There is no one-size-fits-all approach to tackling the logistics of nearshoring, and trucking is not the only solution. Intermodal transportation, the integration of tracking and rail, is set to grow substantially as trucking routes shrink and the just-in-time approach to inventory management continues to permeate American manufacturing. Intermodal transportation isn’t a novel idea, but the relationship between the two transportation methods will have to deepen to accommodate nearshoring and the current demographics of the trucking labor force. Intermodal transportation relies heavily on strategic partnerships between railroads and trucking companies to optimize the process of getting FTL shipments onto rail cars and shipped across North America. All of the big players in FTL trucking are attached to the hip with Class I railroads like BNSF Railway, Union Pacific (UP)and Norfolk Southern (NSC), so the ability to leverage scale and in-house logistics is of utmost importance.

Rail hasn’t seen the same levels of growth as trucking over the last 20 years but is still well-suited for transporting large volumes of goods over long distances, making it a cost-effective option for long transports. Although the actual volume of rail freight is less than that of trucking, rail networks are essential to shortening trucking routes and reducing congestion on highways. Investments in rail infrastructure, including expanded rail yards, upgraded tracks, and digitization of intermodal facilities are all going to be essential in the years to come. However, investing in infrastructure is expensive and scale brings advantages in safety standards and cost efficiency. We wouldn’t be surprised to see M&A activity in the space pick up as nearshoring continues.

Even if there’s no M&A, we still expect the space to have significant funding needs. Any build-out of intermodal transportation networks is going to be capital intensive. Electrification, new tracks, and new freight cars all have significant upfront costs with long payback periods. Specialized lenders and private credit shops will have opportunities to engage in asset-backed lending against those hard assets in the years ahead.

American Investors Will Make Nearshoring Possible

Nearshoring is poised to uplift the significance of both rail and trucking industries. As manufacturing moves closer to home, the demand for efficient, localized logistics will only grow, requiring substantial innovation and capital. The integration of rail and trucking through intermodal transportation will be critical to maintaining the speed and flexibility needed for just-in-time delivery systems. Meanwhile, the trucking sector will see increased demand for less-than-truckload and third-party logistics as businesses continue to seek more agile, responsive supply chains.

Technological advancements will also play a pivotal role in reducing operational costs for shippers. For investors, this evolving landscape presents opportunities in the picks and shovels needed for transporting goods from point A to point B. As nearshoring continues to gain momentum, the future of U.S. freight transportation will be defined by innovation, collaboration, and a renewed focus on North American trade, and is worth keeping a close eye on.

The second half of the 20th century saw globalization thrive. Supply chains expanded across the globe, pursuing cheap and reliable labor as shipping costs plummeted. China’s ascent flooded the market with low-cost goods and global shipping volumes exploded. However, a new era of geopolitical competition has seen globalization become less compelling. Costs abroad have risen as goods have become more complex and supply chains have become more sensitive to disruption. Furthermore, a need for manufacturing reliability in an increasingly uncertain geopolitical environment is pushing more companies to examine manufacturing closer to home.

Unfortunately, bringing manufacturing back to the United States is easier said than done. Companies looking to do it have a whole host of problems to tackle from finding suitable manufacturing sites to finding the labor to man the factories. Companies who solve those problems efficiently will be reshoring winners. However, while it’s tempting to try to pick winners and losers in the reshoring race, we prefer to look upstream with companies enabling the transition. Think picks and shovels during the gold rush. Navigating higher costs of labor and capital are the first steps in bringing manufacturing back from overseas, and challenges like labor shortages and implementing smart technologies are opportunities for enabling firms.

The Need For A Resilient Manufacturing Sector

Calls to reshore manufacturing to the United States are not new, but recent events have amplified their urgency. The Covid-19 pandemic highlighted the nation’s heavy reliance on widespread just-in-time supply chains. The ripple effects of singular components being delayed or unavailable lead to assembly lines coming to a stand still. Critical component shortages and supply chain disruptions, particularly in China, fueled historic inflation and exposed how dependent largely domestic industries were on seemingly simple or generic foreign parts. Low value components, comprising a fraction of the overall good’s value, were putting a whole manufacturing process at risk.

Said another way, the Covid-19 supply chain disruptions were a wake-up call. Of particular concern are goods that are essential to national security like semiconductors or components for power generation. Understanding the critical nature of some of these components, the Federal Government has been enticing companies to bring more manufacturing home. This has been done both with incentives, and by putting tariff pressure on goods manufactured abroad. In particular, programs like the CHIPS and Science Act and the Inflation Reduction Act use subsidies, grants, and tax credits to promote manufacturing and R&D in areas critical to domestic security.

Semiconductors in particular are worth calling out. With semiconductors being essential components for advanced weapon systems, quantum computing, and artificial intelligence, manufacturing domestically means the U.S. can better protect supply chains and intellectual property. Semiconductors are the backbone of the technology economy; the United States can’t be the global technological powerhouse and be dependent on foreign chips over any significant time frame. Manufacturing at home is essential to protect intellectual property from reverse engineering and ensure we build critical human capital in the sector. Furthermore, while nobody wants to think about war with China as being a realistic possibility, being too reliant on Taiwanese or South Korean manufacturing would critically expose the US if any conflict were to occur.

Incoming President Donald Trump is likely to continue pushing for manufacturing to come home. In his first term, he introduced sweeping tariffs on Chinese goods, and he’s likely to ratchet those tariffs higher when he takes office in 2025. It’s important to note that tariffs on Chinese goods are not necessarily a partisan policy – most of Trump’s tariffs on China were maintained during Biden’s presidency, particularly on semiconductors, steel, and electrical appliances. The government as a whole has a broad pro-US stance when it comes to manufacturing, especially manufacturing goods critical to national security. However, while rhetoric and pro-US trade policies are encouraging, there are other issues that companies looking to manufacture in the US have to reckon with.

Navigating The Labor Shortage In Manufacturing

Promoting U.S. manufacturing is appealing, but there’s an inherent conflict with the current limited labor supply. On the manufacturing front, estimates from Deloitte and the Manufacturing Institute point to 3.8 million new jobs being created by 2033 and more than half of those going unfilled if labor gaps don’t get solved. Half of those jobs will be created because of retirements in the manufacturing industry, not because of new manufacturing growth. Just sustaining the industry is going to require an influx of new labor, and any expansion will require even more skilled workers. Attracting and retaining talent has become a significant business challenge.

And the shortage of labor isn’t just for factory jobs – the U.S. Chamber of Commerce reported that we currently have 8 million job openings in the U.S., and only 6.8 million unemployed workers. Even if every single unemployed worker found a job, we’d still have openings that need to get filled. Poaching workers from other industries just won’t be an option for manufacturers. That’s where immigration comes into play. Legal immigration programs are going to be critical for companies to grow their operations. That doesn’t mean companies shouldn’t look to hire and train domestic talent – they absolutely should – but we will need legal immigration as well. This need for labor is going to be even more acute if President Trump’s deportation efforts end up being far reaching. Illegal immigrants are a meaningful part of the current domestic workforce and it’s not clear where labor to replace the current illegal workforce would come from.

A temporary solution to some staffing problems may be for manufacturers to try to retain experienced workers in the field longer. Unfortunately, this is at best a temporary measure. Furthermore, while retaining experienced employees may be beneficial over the short term, the new era of manufacturing is going to require new sets of skills. Companies who wish to bring manufacturing back to the US are going to need to build educational pipelines and on the job training programs for people entering the industry. Non-traditional education programs and on the job training will also become important for existing employees as jobs become more automated and technologically productive. It’s essential that the U.S. invest in these training programs. Automation is essential to productive modern manufacturing. It’s imperative that automation shouldn’t be seen as a threat to manufacturing but rather as an opportunity. Shifting to automation should give workers opportunity to learn new skills, become more valuable to their operation, and for everyone within the manufacturing community to prosper.

Manufacturing With Capital Or Labor?

The current labor situation in the United States may demand capital intensive businesses with lower labor requirements, but that doesn’t mean setting up a factory is easy. Rather, factories with automation and robots woven into their operations have huge upfront costs and are inherently riskier than operations where labor is the primary expense. If something goes wrong with a labor oriented factory, there are layoffs and cost cuts. In a capital intensive model with significant up front expenses, those cost cuts are harder to come by as a majority of the expense is on equipment and other fixed expenses. Furthermore, the labor for a modern factory is also more expensive. These capital-intensive models need skilled operators, technicians, and engineers who take longer to train and will demand higher wages.

Lenders and capital providers with long time frames and a deep understanding of the markets they’re dealing in will be required to make the capital-intensive, automated models work. Manufacturers will need to access private credit markets to secure loans backed by hard assets and partner up with firms offering deep expertise in their respective industries. Larger corporations can access syndicated bank loans, but the average U.S. manufacturing business is substantially smaller and will need more help. The average U.S. manufacturing business generates just $5.4 million in annual revenue according to the U.S. Small Business Administration — a far cry from Big Tech’s revenue levels. There are about 600,000 small manufacturers in the United States that will need the capital to innovate and improve upon their operations in the coming years as they look to upgrade to modern manufacturing processes or expand their operations to accommodate orders that used to be sent overseas. These capital demands suggest there will be a large opportunity for specialized lenders in the mid market space.

Investing In Manufacturing 4.0

The intersection of automation and industrial labor is set to continue making massive strides, especially as technology investment becomes a larger and larger part of operating budgets. Rockwell Automation published its 9th annual State of Smart Manufacturing report, with over 1,500 global manufacturers, showing technology investment up 30% in 2024 from the year before. These capital expenditures can serve to expand and improve upon quality management systems, automate assembly, and even manage energy usage across a firm’s manufacturing plants. We are in the midst of the fourth industrial revolution, and production processes will inevitably be taken over by or supplemented with smart technology. We believe the companies enabling streamlined production processes are where the investment opportunity is at, regardless of whether or not the factories in a specific industry end up hitting the jackpot.

Take inventory management for example – identifying and storing goods coming into a plant each day is critical to ensuring customers receive shipments correctly and on time and can be easily outsourced to integrated robot systems. Similarly industrial robot applications, originally adopted by automotive companies, are another technology that is being scaled down to be more available to smaller factories. Their deployment across smaller factories across the US will mean workers can be reallocated to more value-added roles in organizations. Firms like Rockwell Automation (ROK) and Teradyne (TER) are at the forefront of industrial automation and aiding the transition to smart factories, while bringing solutions to markets that help factory employees coexist with new automations.

Similarly, smart devices implemented across factory operations are collecting an immense amount of data that needs to be harnessed into actionable insights across all levels of the organization. Major players like General Electric (GE) and Honeywell International Inc (HON) are leading the charge in integrating sensors to monitor equipment health and safety of facilities. Think about industrial IoT sensors that help to monitor changes in the physical environment for ultra-sensitive manufacturing processes, or pressure and vibration sensors used to ensure machinery is operating optimally. Being able to predict when machines likely will need maintenance with these sensors helps to minimize downtime and improve product quality over time. The data from these sensors is even used to produce digital twins of factories to enable manufacturers to simulate and optimize their operations in real time, in turn enhancing product quality for the end consumer.

Above the factory level there will be opportunities for companies to help factories streamline their labor processes. For example, firms like Workday (WDAY) use AI to help human resources departments make sure new hires will have the right skills necessary to make an impact on day one. Efficient allocation of resources starts with making sure you have the right resources to work with in the first place! Ultimately, think beyond just the actual manufacturers – enabling firms that offer the picks and shovels have substantial long-term tailwinds from reshoring’s effect on manufacturing processes.

Look Beyond The Manufacturers

Reshoring manufacturing to the United States presents a complex yet promising opportunity for economic growth and further expansion of our nation’s manufacturing output. While the challenges of labor shortages and initial investments in smart technologies are significant, they are well worth the upfront costs to boost the security of our nation’s manufacturing sector and to protect against future foreign disruption. Automation and advanced technologies will play a critical role in bridging these gaps, enabling factories to operate more efficiently and with higher productivity. We believe investors should explore how technology will supplement the industrial labor force and why automation is essential for continued GDP growth. Ultimately, investment opportunities are immense with companies that are positioned upstream of the actual manufacturers and can benefit from the retooling of the U.S. workforce.

Bitcoin and the broader cryptocurrency market have seen a resurgence since Trump’s election victory became clear. An industry formerly on the fringe of finance has drawn in institutional interest, interest from young investors, and interest from those interested in disrupting the current financial system.

The recent shift in the political environment is likely to lead to a change in the regulatory perspective on the industry, and recent financial innovations have made cryptocurrencies more accessible than ever. Furthermore, various interest groups associated with the industry lobbied the Trump campaign heavily and have touted his victory as a major win for the ecosystem

Following the election, crypto assets and equities associated with the industry, such as crypto exchanges, have seen significant appreciation. The recent performance, breadth of the market, and the potential for a shift in the regulatory environment necessitates a discussion around whether or not crypto deserves to be viewed as an independent asset class in a broader diversified portfolio. In particular, advocates for the asset class have touted its value as ‘digital gold’, as a potential payments platform, and as a disruptive component of the modern financial industry. Skeptics have pointed to its lack of utility, substantial volatility, and speculative nature.

Can You Use Crypto As a Payment System?

One of the primary arguments for crypto to investors is that it offers a cleaner and faster way to transact payments. But from where we stand today, crypto’s volatility undermines its utility in any payments ecosystem. The price swings for most large crypto instruments are dramatic: Bitcoin, the largest crypto asset, went from being below $1,000 in 2017 to reaching $69,000 in 2021, followed by a crash to $30,000 within months. You need an iron stomach to block out the noise that comes with owning an asset like that. Such volatility is almost unprecedented compared to other stable currencies like the Dollar or the Euro. Rather, that volatility even stands above that seen in far more speculative equity markets or bond markets. The ability to use Bitcoin for peer-to-peer transactions is significantly undercut by its price swings. Reliability and price stability is essential for a payments network.

Real world evidence supports this perspective. Crypto generally isn’t used for transactions in a place where a stable currency is available. According to the Federal Reserve, only 7 percent of U.S. households held or used cryptocurrency in 2023, down 8 percent from 2021. That number encompasses the broad crypto ecosystem with more than 10,000 different cryptocurrencies – no single asset has any sort of significant payment volume, even if some assets like Bitcoin have seen dramatic price increases in the past few months. Furthermore, when crypto is used in payment it’s often not for the kinds of purchases an ecosystem wants to be proud of. Crypto assets like Bitcoin are the preferred route for dark web transactions, ransomware attacks, and illegal gambling sites even though it’s estimated that less than 1% of Bitcoin transactions are criminal.

However, while a significant payment ecosystem has yet to mature, digital currency technology continues to advance. Large players like Visa and Mastercard are excited by blockchain technology and there are a lot of start ups and small companies working on building blockchain systems explicitly for payments.

Is Crypto Digital Gold?

So, if your average Joe isn’t going to use crypto to transact, then where’s the value?

Many advocates have pointed to the potential for Bitcoin and other crypto assets to be a hedge against inflation and normal market volatility. Bitcoin in particular draws attention as its total future supply is capped at 21 million coins. This artificial scarcity sets it apart from fiat currencies, where central banks have control over how much to print into circulation. In an era of rising inflation and unprecedented monetary stimulus, Bitcoin evangelists see it as a potential hedge against the devaluation of traditional currencies and bet on its recognition as a store of value worldwide. An advocate’s perspective is not that Bitcoin is a replacement for stocks, but rather an insurance contract for a fiat currency meltdown – similar to the argument used to push for gold.

Gold has served this function for investors for a long time – nobody uses gold to transact, yet many investors still incorporate it into their portfolios, thereby giving it value. Outside of its few industrial applications, gold bugs use the metal as a hedge against volatility and inflation even though imagining a situation where we barter with gold bars is pure fantasy. The argument for Bitcoin to still be worth something while not being a particularly useful asset may lead it down a path similar to the metal’s – a speculative asset devoid of intrinsic value and entirely dependent on sentiment.

Are Crypto Ecosystems Disrupting or Conforming?

Crypto has gone mainstream over the past few years through a combination of consistent promotion from the exchanges, outsized returns, and some dramatic collapses. The collapse of exchanges like FTX and the subsequent pushes to regulate the industry have made crypto feel less like a disruptive new wave of finance, and more like another part of the broader financial system. Rather than pioneer new ways to run the financial system, crypto assets have actually come closer to traditional finance. In particular, the introductions of ETFs to allow investors easier access to crypto assets like Bitcoin is noteworthy. Institutional offerings like ETFs bring ease of access to the previously esoteric market.

The introduction of regulated access points allows retail investors and institutions alike to start thinking about crypto as a potential asset class, rather than needing to focus solely on the risks associated with a frontier market. The broader financial system has regulations and systems in place to deter and prevent fraud and mismanagement like what we saw with FTX, and the financial system is similarly used to the risks associated with leverage and counterparty risk like what happened with crypto hedge fund Three Arrows. Having ETFs from established financial institutions like Blackrock may allow investors to start looking past systemic problems with the ecosystem.

It’s also important to note that while the push for crypto in developed economies has been towards regulation, it is acting as a disruptive technology in less developed economies. In places with less stable currencies crypto has become a way for people to move wealth outside of the traditional financial system and to hedge against hyperinflation and local currency instability. Peer-to-peer trading platforms are much more prevalent outside of the G7 countries and in many cases this allows crypto to be more well received.

Investing Upstream

While investing in crypto assets is fraught with risk, there are other ways to tap into the growth of the ecosystem and still have some exposure. One area we see talked about a lot right now is with the miners whose stock prices generally follow the price of bitcoin but give investors upstream exposure. Companies like Marathon Digital Holdings (MARA) or MicroStrategy (MSTR) are directly involved in the business of mining and owning crypto assets. However, while the idea of investing in a miner may be attractive, they are essentially leveraged bets on the crypto assets they’re holding. Small changes in the price of the asset they’re working with have outsized impacts on the price of the stock.

If we ignore miners and break down the essential inputs needed for crypto more broadly, we come away with two sectors with substantially stronger tailwinds. Semiconductors and power. These two spaces benefit not only from tailwinds in crypto, but are also exposed to the broader acceleration in AI and technology more broadly. Chip behemoths like Nvidia (NVDA) and Advanced Micro Devices (AMD) not only get to develop chips used for crypto, but also have huge opportunities in the AI data center market.

Similarly, utilities providing energy to both miners and AI hyperscalers will stand to benefit from the ever-increasing competition – whether that be in nuclear with companies like Talen Energy (TLN) and Constellation Energy Corp. (CEG) or broader renewables like NextEra Energy (NEE). The bitcoin mining community is already receptive to renewables with over 50% of its energy consumption powered by renewable sources. Even companies like Tesla (TSLA) are exposed to the renewable space through their sales of their solar panels, battery packs, and energy management systems to power data centers or crypto mining operations that need uninterrupted power.

Final Thoughts

Crypto assets have gone more mainstream by integrating with the rest of the financial system, but we believe they still fall short of being considered an essential asset class. The absence of intrinsic value and exceptional volatility are major obstacles. While the price increases can be exciting, that volatility can go both ways and losses can accrue just as quickly. Despite the significant increase in institutional adoption in 2024, we believe there are other more reliable ways to participate in the market. We prefer looking at the energy consumption or semiconductor suppliers as opposed to the crypto assets themselves.

There are numerous ways to invest in the Artificial Intelligence (AI) boom. Some high flying chip stocks like Nvidia have captured the spotlight, but there are more ways to invest in a broad wave of AI adoption than just semiconductor chips. Chips are essential, but without the infrastructure to support them they’re useless. Investors should also consider the sector powering the data centers needed for AI development.

According to the Electric Power Research Institute, data centers are forecasted to consume up to 9% of US electricity generation per year by 2030, up from 4% in 2023. That doesn’t sound like much, but between replacing old power generation and turning on new power arrays, the step up is significant. The reason is AI. The energy needs for AI computing are immense. To put the energy consumption into perspective, AI queries – just asking ChatGPT to clean up that email to your boss – can require approximately ten times the electricity of traditional internet searches. Training new models and running more complicated queries suck even more power.

The need for more power generation is so intense that it’s actually becoming the primary obstacle for companies looking to innovate in AI. The ideas are there, the computational chips are expensive, but they’re there, but you need to figure out how to meet the energy needs for the data center to function.

As this space continues to play out, we think it’s worth exploring opportunities within energy generation where investors can benefit from partnerships between both the upstream and downstream players in the AI market.

Data Centers Need Electricity…and lots of It

To explore the first-phase beneficiaries providing key inputs for AI advancements, it’s worth breaking down what data centers are used for when it comes to artificial intelligence. Data centers are the backbone of this AI boom as they store the hardware necessary to train AI models. As modern technology companies have grown larger and larger, and the amount of equipment needed to maintain operations and cloud services has skyrocketed, the energy demand from hyperscalers has followed suit.

Hyperscalers – companies that operate cloud computing infrastructure – provide the storage and compute power necessary to train AI and are faced with the difficult task of deciding where to source the energy needed for their daily operations. Major players within this space include Amazon Web Services, Microsoft Azure, and Google Cloud, all of which are forming partnerships with local utilities and power providers to ensure their energy demand is met.

With the sweeping transition to cloud data storage, electricity demand has turned into the biggest problem facing the industry. Hyperscalers providing infrastructure and platform services just can’t get enough of it, and the world of institutional finance is taking advantage of the opportunity. As we’ve seen recently, Blackrock teamed up with Microsoft (MSFT) and MGX (an AI fund out of The United Arab Emirates) to announce the launch of a $30 billion AI infrastructure investment fund focusing on building out data centers and energy infrastructure. While this may seem like a massive investment initially, it pales in comparison to the total investment in AI from the top 5 hyperscalers over the next few years. For context, current projections indicate the investment levels will reach a combined $1 trillion in 2027 according to S&P Global Market Intelligence.

Straight to the Source

The way power is generated and sold to large hyperscale consumers is going to change. Whereas in the past many data centers may have tapped into local electrical grids, the future of data center electrification involves dedicated power construction and long-term power purchase agreements (PPAs).

Hyperscalers prefer PPAs over market spot pricing since they’re able to guarantee stable energy prices for an extended period, typically over ten years. This level of certainty provides a hedge against unwanted price fluctuations that would affect hyperscalers’ bottom line and put upward pressure on already substantial model training costs. Perhaps more important though is the desirability of long-term contracts for developers and investors. PPAs from cash flush hyperscalers give developers the ability to secure financing for rapid construction of new power generation facilities. Knowing you have a reliable counter party allows for better profit forecasting! Furthermore, many of the power generation projects are dedicated solely to the data center and disconnected from the broader grid – a contract stipulating a minimum rate of return is essential for a project that takes years to break even and only has a single customer.

Finally, it’s worth pointing out that while renewables like wind and solar are the preferred long term source of power for the data centers, the demand right now is high enough that other options are on the table too. Nuclear power is back in the spotlight and natural gas turbines offer rapid deployment. Each power source comes with pros and cons – some are more flexible and some are harder to ramp up and down with data center demand. There will be a wide variety of solutions to the power conundrum over the next several years and many solutions that start off as off grid or dedicated power supplies may eventually end up becoming part of the larger power system.

Opportunities in Renewables

The long term demand for electricity is an opportunity to accelerate the build out of clean energy solutions. The top hyperscalers have set ambitious goals to reduce their carbon footprints – renewable power is a must for them over longer time frames. Among the top names, Google is targeting to operate its data centers on carbon-free energy by 2030, and Microsoft and Amazon both hope to shift to 100% renewable energy by 2025.

The massive undertaking is already underway as Microsoft (MSFT) and Brookfield Renewable Partners (BEP) signed the biggest-ever clean power deal this year for their data centers in the US and Europe, effectively penciling in 10.5 gigawatts of renewable energy capacity starting in 2026 and estimated to cost more than $10 billion. Keep in mind that 10.5 gigawatts is 3 times larger than the amount of electricity consumed by all data centers in Northern Virginia – commonly known as the data center capital of the world due to its favorable state tax incentives and best in-class access to power and internet connectivity.

With the steadfast increase in renewable energy demand due to corporate mandates, there are several ways to invest. We’ve already touched on the financing side where groups like Blackrock or Brookfield are raising capital to fund the construction of new power projects. Then there’s the manufacturing side, companies that make solar panels or electrical components, or companies who build wind turbines like GE Vernova (GEV). Finally, there are the utilities who want to own and operate the power generation facitlities over the next several decades, companies like NextEra Energy (NEE) or Constellation Energy Corp. (CEG).

Finally, there are cutting edge innovations in the power space that are less proven. As an example, innovative nuclear technology, like small modular reactors, is progressing rapidly and has received extensive backing from the US Department of Energy. These new reactors, built by firms such as NuScale Power (SMR), are smaller than traditional reactors and don’t have to be custom-built on-site. The process of generating electricity through nuclear fission is the same, but the benefits include reduced construction time, enhanced passive safety features, greater flexibility in deployment, and more efficient fuel usage. For broad adoption with data centers in the US, we’ll need to see continued investment in generation capacity and regulatory compliance, so patience is key.

Far from Being Over

The rapid expansion of artificial intelligence and pursuing energy demand are creating significant opportunities in the energy sector. As hyperscalers like Amazon, Google, and Microsoft ramp up their AI infrastructure, the need for massive amounts of electricity will drive investments in both traditional and renewable energy sources. While fossil fuels may provide immediate solutions due to existing infrastructure, the long-term focus is shifting toward renewables, such as wind, solar, and even nuclear power to meet sustainability goals.

Well-established and innovative companies in the energy sector, especially those forming strategic partnerships with hyperscalers can offer an alternative method to invest in the AI market besides buying chip companies or hyperscalers directly, even if the full societal benefits of investment end up taking years to play out. The ongoing collaboration between energy and AI firms will be crucial for supporting AI adoption and addressing challenges that lie ahead. Regardless of any short-term uncertainties, the unrelenting demand for energy remains far from being satisfied, and investors should continue to monitor the space for opportunities.

 

Everyone knows how Amazon started as a simple book store or how Meta began in a dorm room. At some point all of today’s great companies were just a passion project, a great idea in need of capital, employees, and the first real customer. While some ideas grow to become companies organically without outside investors, most companies need help. They need capital, they need expertise, they need connections and support.

Venture capital investing is the process by which these great ideas get funded and become dynamic companies capable of scaling and growing profitable. The return profiles for successful companies can be huge, but it’s an incredibly nuanced and risky part of the investing world and not suitable for everyone. Nonetheless, it’s where the best ideas are tried, tested, and eventually brought to fruition.

Investing in Venture Markets

You can’t invest in the venture space without recognizing that failure is an essential part of the creative process. Venture companies are dreaming big – and not every moonshot works out. In fact, most small companies end up failing and shutting the doors. Investing in the space successfully hinges on one or two ventures succeeding within a much broader portfolio. The companies that make it often hit escape velocity – they can hyperscale and the the returns can be exponential. The returns on a single venture investment could be enough to justify dozens of failures.

The complexity of the market is further complicated by the lack of transparency and minimal reporting requirements. The environment is rife with fraud and exaggeration. A great idea may be nothing more than an idea and may have no substance or practical marketability. Successfully navigating the venture space consequently requires a nuanced understanding of how businesses are run and an astute approach to avoid falling prey to exploitation. Subject matter expertise is also essential to see through the sales pitch and understand the substance of the idea.

Finally, we have to take a moment to discuss how hyperscale growth can be risky even when it succeeds. Unlike mature companies who are kicking off cash to investors, most venture investments are purely growth oriented. That growth can be awesome, but can also lead to long investing time frames – venture investing is not for those who need liquidity, even if they can handle the risk.

However, for those with the risk appetite, the time, and the expertise, the venture space can be incredibly rewarding. Diversified and done properly, a venture capital fund can be a vehicle for cutting edge ideas to become wonderful portfolio investments experiencing exponential growth over time.

Timing The Economic Cycle

This already exciting space is even more intriguing because of where we are in the market cycle. Smaller companies are typically the most exposed to the broader economic cycles and the venture space is no exception. The past two years are a great example. Inflation and interest rate hikes put a damper on the economy and small companies took it on the chin. Exuberance in 2021 turned into austerity in 2022; it’s hard to overstate the monumental shift in perspective. Think about some public market companies with established user bases and real products – companies like Teladoc or Zoom or PayPal. In 2021 their valuations were extended, and in 2022 and 2023 those valuations came tumbling downwards.

The same thing happened in private markets and in venture capital markets. In many cases it was actually worse in venture markets as the underlying products were far less tried and tested. The stress on the venture space was further exacerbated as soaring interest rates and a crisis of confidence caused the collapse of the venture-oriented bank SVB. Consequently, raising funds in venture markets today has become much more difficult. Many ventures have shut their doors and those still standing are fighting to raise capital at any valuation. Rather than looking for growth and appreciation, founders are looking at flat fundraising rounds as a victory.

This is also reflected in the IPO market. Many successful venture companies have delayed their public market debuts and have opted to stay private until capital markets start to open back up. The lack of activity in the last year or two stands in stark contrast to the successful listings of companies like Snowflake or Doordash when markets were less troubled.

However, companies resilient enough to weather downturns tend to flourish when market conditions improve. Difficult market conditions make it essential to not only have a good idea, but to become a good operator. Conserving cash, focusing on profitability, finding ways to efficiently acquire customers – these are lessons that companies learn during downturns. Taking that expertise to the broader market when capital markets start to unlock can lead to rapid growth both in terms of profitability, and in terms of the valuation of the firm.

Read the full article in Forbes.


Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!

Artificial intelligence (AI) has been a hot topic of discussion for many years now, and for good reason. AI has the potential to revolutionize many industries and aspects of our lives. Recently, the pace of AI innovation has accelerated sharply and easy to use AI tools have started to become readily available to the broader population. Recent breakthroughs have the potential to impact workflows across industries and may have significant impacts on investment portfolios.

AI – What Is It:

There are a lot of different kinds of AI tools being developed as our skill at building new machine learning models increases. In particular, deep learning and large language models have made rapid advancements. Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Neural networks are inspired by the human brain, and they are able to learn complex patterns from data that would be difficult or impossible for traditional machine learning algorithms to learn.

Deep learning has been used to achieve state-of-the-art results in a variety of tasks, including image recognition, speech recognition, and natural language processing.

A similar process is used in the development of large language models (LLMs). These models are able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. These models have recently burst onto the scene as they are easy to work with and highly interactive. They have many uses for day to day productivity, and show promise in assisting with a broad variety of content generation ranging from helping write code to generating articles or other creative content.

AI Constraints:

There are two primary inputs that act as limitations on the development of new AI models; data and processing power. Both resources are crucial. Data without processing power won’t yield a very accurate model, and processing power with low quality data will yield an AI tool full of biases or inaccuracies.

Processing power is the more straightforward of the two constraints. Bigger data sets or more complex AI set ups require more processing power, which means more chips and more electricity. Not all chips are made equal though – AI computing is substantially more efficient when done on graphics cards like those made by Nvidia, rather than on standard computational processors like those that currently dominate most servers across the world. Nvidia’s recent sharp stock price rise is almost entirely due to their raising guidance around expected graphics card revenues for use in AI computing. While Nvidia is currently the top player in the space, Microsoft has committed billions of dollars to help AMD design better chips for AI, and several other companies like Apple, Meta, and Alphabet all have internal chip design programs that will likely focus on AI chips as demand in that sector grows.

Data is the trickier constraint that AI models face. While processing power is primarily a question of cost versus quality, data set availability is more nuanced. The internet as a whole is a great database, but it’s very generalized and the quality is often questionable. More specialized data sets may be harder to access or may face privacy concerns. Furthermore, there are broad concerns around how data is presented when training an AI tool – will the data or the training parameters end up with the AI having a bias or tilt or blind spot. For instance, think about the difference in political perspective if the AI was sampling news from Fox News verses MSNBC. Similarly, what if it’s an automated driving AI and it’s trained without sufficient data for severe weather – the output will only be as good as the data input.

Read the full article in Forbes.


Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!

While the latest electric vehicle tax credits help auto manufacturers, it will take much more to save the industry from recent challenges. The automotive industry is at a tipping point, with a growing focus on sustainability and the need to reduce carbon emissions. Electric vehicles (EVs) have emerged as a preferred solution to combat climate change, and governments worldwide are taking steps to incentivize their production and adoption. Companies are responding by pivoting their production lines to focus on EVs – Tesla has become one of the largest companies in the world producing electric cars and domestic stalwarts like GM have announced a total conversion to EVs in their business plans. Government subsidies and tax credits are a significant driver of this strong company pivot.

Subsidies, or financial incentives provided by governments, are a key driving force behind EV production. Subsidies can take various forms, such as direct payments, grants, or discounts on purchase prices; they are designed to make EVs more affordable and competitive compared to traditional gas powered vehicles. In particular, the new tax credits that took effect on April 18th, 2023, are focused on reducing the cost for the end consumer to drive EV demand.

The new electric vehicle tax credits offer up to $7,500 to consumers who purchase a new eligible EVs. Unfortunately for consumers, the range of EVs meeting the regulatory criteria for the credit is narrow. Only a handful of models currently comply with the regulations around where the batteries and parts are sourced. Furthermore, a majority of the vehicles receiving credits are both expensive and in limited supply. The irony is that the funding for these tax credits comes from the Inflation Reduction Act. Rather than helping the inflation-impacted consumer, these subsidies for EVs are more likely to stimulate spending, making it harder for the Fed to reign in the economy. Furthermore, given the prices of the EVs right now, the subsidies will mostly be utilized by individuals with above average incomes – the population least impacted by inflation.

Read the full article in Forbes.


Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!

Recently, you may have seen the headlines regarding Silicon Valley Bank collapse, creating implications for the financial system as a whole. If you looked at the performance of the financial sector over the past week or two you’d be excused for feeling a bit of panic. The deterioration in share prices slowly accelerated into a crushing run on two banks in two days. Given the way markets have been fluctuating over the past 18 months and the pressure the Fed has been putting on the market, we can understand how some people might jump to conclusions and think the financial system is finally cracking under the pressure of rate hikes and inflation.

We’re going to dive into this deeper, but lets start this reaction piece off by pressing pause on any panic you might be feeling.

Why Is The Financial Sector Under Pressure with Silicon Valley Bank Collapse

The financial sector has been under pressure as rate hike expectations have come back into focus. While we’ve had plenty of speculation around rate hikes over the past 18 months, the past week or two has seen the 2s – 10s spread expand rapidly. The 2s-10s spread is the gap between 2 year treasury yields and 10 year treasury yields. In normal markets conditions, longer maturity yields are typically higher than short maturity yields – governments or companies who issue debt have to pay more for investors to feel comfortable locking their money up for longer periods of time. However, in the current environment where rapid rate hikes are expected to be temporary, the yield of treasury bonds with shorter maturities is higher than the yield on treasuries with longer maturities.

This spread is important because the spread between long term and short term maturities can have a significant impact on bank profitability. Banks fundamentally operate in the business of borrowing short term money and lending it out to people for longer term projects. The most extreme example taking a customer deposit for say, $500,000, and then turning around and giving another customer a loan for $500,000. The bank has borrowed short term money from the depositor, and lent it out for much longer – for the sake of this example, lets say 10 years. The interest they make on the 10 year loan is used to pay for the bank’s operational costs, drive value for bank shareholders, and of course, pay the customer some interest on their savings account.

Read the full article in Forbes.


Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!