Digest 6 | AI in Financial Markets: A Double-Edged Sword
Waterfield Advisors
Independent Multi-Family Office and Wealth Advisory firm, providing holistic advice aligned with the investors' interest
Dear reader,
If AI can recreate art, how would it impact more quantifiable fields like the financial markets?
Earlier this month, Nvidia's stock price precipitously climbed by 14%, a rise deeply tied to the surging demand for its Blackwell AI chip. Offering up to 25 times the performance and energy efficiency of its predecessor, Blackwell has positioned Nvidia as a key player in the next phase of AI-driven technological progress. With shares already up over 150% year-to-date, analysts project Nvidia’s revenue to more than double this fiscal year, with an additional 44% growth forecasted for the following year. This reflects not only the high demand for AI infrastructure and solutions but also how financial markets respond to innovation.
Nonetheless, this growth comes with its downsides, as echoed by the IMF’s Global Financial Stability Report, which highlights how AI’s growing role in financial markets presents both opportunities and threats. While AI promises faster and more efficient trading, it could also amplify market volatility. High-frequency AI-driven trading, while advantageous in stable periods, could lead to disruptive flash crashes during market stress, as trading algorithms respond faster than markets can stabilize. Non-bank financial intermediaries, particularly hedge funds, could further benefit from this trend, potentially destabilizing capital markets.
At the same time, the EU AI Act introduces another dimension—one where regulatory oversight intersects with technological expansion. The Act, particularly its provisions around high-risk AI applications in sectors like healthcare and law enforcement, demands greater transparency and ethical compliance from AI developers. While this could mean increased compliance costs, it also presents the sector with the chance to lead in ethical AI development.
Ultimately, this story is about the broader interplay between unparalleled technological progress and the potential risks it brings. Today, we find ourselves at an unprecedented juncture where the delicate balance between innovation and risk must be carefully navigated. How this balance plays out will shape not just the future of technology but also the macroeconomic and societal landscape.
In this month’s Vault Digest, we bring to you insightful reads about AI and markets. We hope you like it.
P.S. If you enjoyed reading this newsletter or think it can be improved, let us know here.
I. This month's big story
Semiconductors Everywhere: National Security, Transportation, and AI
Imagine going through a day without booting up a laptop, sticking in a pair of wireless earbuds, or scrolling through social media.
Now consider the new everyday technologies we are starting to see: artificial intelligence-powered digital assistants, self-driving cars, and advanced health wearables such as the Apple watch. All of this everyday tech has one key element in common… an insatiable demand for semiconductors.
Semiconductors are the digital brainpower driving every major innovation we take for granted today. The surge of brainpower and money into artificial intelligence technology has ushered in an industrial revolution for chip-making/semiconductors. The Wall Street Journal reports that the global chip industry is forecasted to double in size by 2030, generating USD 1 trillion in revenue.
Key sectors of the economy including information technology, automotives, and industrials are major drivers of chip demand. As these sectors continue to grow, so do their demands from their digital infrastructure, the physical and virtual components that make up their products and on which their services run. Some of the most recognizable examples of a company’s digital infrastructure are data centers and cloud services.
A.I. doesn’t have a sweet tooth, but it does have a hankering for chips
Technology companies have been developing new applications of A.I. for their product suites. This research and development entails building new A.I. systems which require hardware that must handle a lot of processing power with high performance. The crucial components in these hardware systems are the semiconductors as processing units, a common type being graphic processing units otherwise known as GPUs; (these are the chips.) These massive hardware systems are built in data centers to create “modern A.I. factories.”
These data centers operate with the products and services of semiconductor designers and manufacturers, semiconductor material input companies, and data center cooling companies.
These niche technology industries located around the world have been spurred on as the spectacular growth of companies like Nvidia and TSMC have also led to massive growth among their input and partner companies.
Materials and Manufacturing
GPUs require sophisticated machinery and materials that are most often found from niche companies such as ex-rubber (JSR) and ex-film (Fujifilm) producers. Japanese companies have been leading the world in critical chip supplies: chemicals, packaging materials, and tools, accounting for nearly half of the world’s six crucial semiconductor materials. Toppan, a 124-year-old ex-printing company is one of Japan’s proudest semiconductor strongholds and has seen its stock price double since the start of last year due to its production for a type of packaging board for semiconductors.
In the Netherlands, ASML holds a monopoly over the advanced chip-making lithography machines necessary to advanced chip development. The development of the EUV technology the company’s machines use took billions of dollars of investment by ASML as well as Intel and TSMC and even the support of university research over the span of many years. Despite its Dutch base, the hundreds of thousands of components that are used in the manufacture of ASML’s EUV lithography machines involve over 800 global suppliers built in modules at 60 world locations before being shipped back to the Netherlands for final assembly.
Data centers housing these chips and A.I. systems create demand for greater cooling systems, (computing systems run hot). As a result, Vertiv Holdings Co, one of the most popular choices for cooling and IT infrastructure services, has seen its share price rise along with its revenue growth rate. Its business segments operate across the Americas, Asia Pacific, Europe, Middle East, and Africa.
Many countries have been fighting to be the most competitive for chip-making, often even citing national security issues to justify massive investments to develop these expensive factories. However, regardless of where these companies are based, the inputs, brainpower, and operations are always global. Even as these companies compete with each other, they also collaborate due to the nature of how tech advancements rely on building atop the work of others.
领英推荐
For an investor looking to capture this rapid industry growth within their investment portfolio, the focus isn’t where the next factory is built, but rather capturing the breadth of contributors and beneficiaries from the industry: from the specialized manufacturing equipment and materials like Vertiv and Toppan to the largest semiconductor names and A.I. companies like Nvidia and Microsoft.
II. Handpicked goodreads for you
1. Artificial Intelligence Can Make Markets More Efficient – and More Volatile
In this insightful read, the IMF explores the dual impact of AI on financial markets, highlighting its potential to enhance market efficiency while also increasing volatility. Co-authors Nassira Abbas, Charles Cohen, Dirk Jan Grolleman, and Benjamin Mosk provide insights into how the rise of AI in financial markets may shape future market dynamics.?
2. Robo-advisors are dead, long live robo-advisors
An insightful examination of why the initial wave of robo-advisors has struggled to meet expectations. It discusses the limitations that led to the perceived decline of traditional robo-advisory models, while delving into how advancements in technology and AI could redefine the role of robo-advisors in wealth management.?
3. Gen AI: Too much spend, too little benefit?
In this Goldman Sachs podcast, experts delve into the current gap between spending and tangible outcomes, debating the long-term impact on companies, industries, economies, and markets if the anticipated AI revolution materializes or falls short.
4. What banking directors should ask about AI and machine learning risks
This EY article provides insights into the growing role of AI and ML in the financial services sector, particularly in risk management, emphasising the need for financial institutions to adopt strong governance frameworks to mitigate the risks associated with AI.
5. AI for Climate, Not Convenience
In this Waterfield blog, we share a systems thinking approach to adopting Artificial Intelligence. Highlighting the need for a balanced approach where AI development prioritizes sustainability over convenience, writer Kshitij Kumar Pandey underscores the role of impact investors, global leaders, and entrepreneurs in fostering a more sustainable future for AI.
III. Data to ponder upon
Which regions will gain the most from AI?
IV. Upcoming must-attend events for UHNIs
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Very insightful!