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How dynamic, risk-managed investment solutions are performing in the current market environment

2nd Quarter | 2024

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Current market environment performance of dynamic, risk-managed investment solutions.

By David Wismer

It seems like every third email in my inbox, whether a market update, newsletter, or webinar invitation, mentions artificial intelligence (AI).

This is not a new topic—we first discussed transformative technologies, including AI, in Proactive Advisor Magazine in 2017.

Since then, we have looked at a variety of AI-related topics, including AI’s increasingly important role in financial planning and the accelerating development of AI-enabled investment management technology.

However, the constant stream of AI news can be overwhelming. For me, it’s like continually peeling an onion to get to the next layer. And that next layer, and the layers beneath, are in constant flux.

I thought it would be a good idea to take a step back and attempt to connect some dots surrounding the “AI revolution.”

How does AI itself define the AI revolution?

Microsoft CoPilot offers a compelling definition:

“The AI revolution refers to the extraordinary changes in technology brought about by artificial intelligence (AI). Unlike previous waves of technology, AI has the unique ability to unleash new powers and transform existing power structures. Here are some key aspects of the AI revolution:

  1. “Proliferation of Power: Unlike earlier technologies, AI is not limited to a small elite or national governments. It’s becoming more powerful and radically cheaper by the month. What was computationally impossible or prohibitively expensive a few years ago is now widespread.
  2. “Doing, Not Just Broadcasting: While the internet era focused on broadcasting information, the AI revolution is about doing. AIs can manage tasks, develop business strategies, design drugs, and even plan invasions. The pace of change is unprecedented.
  3. “Neural Networks and AI Chips: The driving force behind this revolution includes neural networks, GPT [generative pre-trained transformer] architectures, and specialized AI chips. These technologies enable AI systems to perform tasks we once thought only humans could do.

“In summary, the AI revolution is reshaping our world, unlocking new possibilities, and redistributing power on an unprecedented scale.”

It is pretty telling that this definition was largely derived from two third-party articles. It reminds us that the current consumer applications of AI, and most applications in general, are sophisticated, iterative, and algorithm-based processes built on preexisting data and knowledge bases. That is not necessarily a bad thing, but it introduces the risk of bias, intentional or not.

A related piece from CoPilot explores ethical concerns related to AI, including bias and fairness; reliability of source data; data privacy and protection; accountability; and impacts on the environment, society, and the workforce.

Concerns about the unchecked power of AI have existed for decades. For early consumer exposure to AI, you can look to Stanley Kubrick’s 1968 classic film, “2001: A Space Odyssey,” which explored themes related to human evolution, technology, artificial intelligence, and the possibility of extraterrestrial life.

Carrying the movie reference one step further, a 2024 outlook survey conducted among institutional investors framed AI opportunities and concerns in the context of several popular movies:

“On the one hand, 75% believe AI will unlock investment opportunity that was otherwise undetectable. On the other, almost four in ten (38%) worry that AI poses an existential threat to civilization as we know it. …

“Half of those surveyed say their view on AI is best captured by the film Moneyball, telling us AI is nothing more than a tool analyzing data to find hidden opportunity. …

“… Just 6% worry about the machines taking over as the dystopian future of The Terminator. Few (10%) see it as being a boon to humanity either… like the title character in Disney’s Wall-E.

“Most telling of institutional concerns about AI are the 35% who likened it to the 1983 film War Games, in which a teenage hacker unwittingly sets off a nuclear war protocol thinking it was nothing more than a video game.”

Coming to grips with the broader structure of AI and its market impact

The impact of AI-leading companies, especially Nvidia (NVDA), on the recent earnings picture has been impressive—along with how they have dominated S&P 500 returns this year.

Bespoke Investment Group recently calculated that the S&P 500 Index would be about 20% lower without the impact of gains made by companies in its basket of 30 AI-oriented stocks. Before a recent pullback, MarketWatch asserted that Nvidia alone “has driven 34.5% of the S&P 500’s advance so far in 2024 [through June 14].”

AI’s influence has not been limited to companies directly related to AI technology or platforms. FactSet notes that 199 S&P 500 companies mentioned AI in earnings conference calls during the March–May 2024 period.

Where do the key players fit into the AI infrastructure? The following Capital Group schematic presents a clear view of what it calls the “AI stack”—technology that enables AI to operate. The illustration includes companies that lead market share in each segment.

But that is just one snapshot of the current AI environment. Looking ahead, a thought-provoking article in Proactive Advisor Magazine explores the broader technology revolution, with many of the new trends impacted by AI. The article’s author, Martha Stokes, notes,

“In 1985, the emergence of personal computers, software, semiconductor materials, integrated circuits, telecommunication, and internet technology fueled the great bull market that peaked in 2000.

“Today, several technological advancements are close to being introduced to the market or achieving widespread acceptance, including the following:

•  “Digital and crypto technologies: advanced phases of distributed ledger technology (DLT) that could support the decentralization of industry, finance, and monetary systems.

•  “Robotics and automation: assembly lines, robots replacing human workers, and business hyperautomation.

•  “Sensing and AI innovations: sensors, image sensor technologies, integrated artificial intelligence, advanced machine learning, voice user interface (VUI), machine vision, facial recognition, advanced language and audio interpretation, scent recognition, and pressure recognition.

•  “Data and connectivity: advanced dark data mining, enhanced connectivity technologies, 5G, personalization internet technologies, and the Internet of Behaviors (IoB).

•  “Virtual and augmented realities: the metaverse and extended reality (XR).

•  “Health and biotechnologies: personalized health care, humanoid robots for health care, and integrated wearables like smart clothing and implants.

•  “Sustainable and advanced materials: integrated solar technologies and second-phase nanotechnology.

•  “Logistics and transportation innovations: supply-chain reinvention and platooning.”

What does this all mean from an investment perspective?

Investors certainly want exposure to the upside potential presented by what might be the next great secular bull market—one driven by technology.

Stokes notes, “With just a few of the 20-plus new technologies now in the mass market phase, there should be substantial fundamental support for further growth in new streams of corporate revenues and operating efficiencies across many industry sectors.”

However, some analysts believe a major tech shakeout, similar to the early 2000s, might be on the horizon, with a highly concentrated stock market ripe for a major correction.

Investors should consider a disciplined, rules-based strategic approach, such as that advocated by Flexible Plan Investments (FPI). This approach aims to mitigate the risk of large market drawdowns while seeking opportunities and growth in highly rated sectors and favorable market environments.

In fact, FPI’s research group has incorporated methodologies founded in artificial intelligence into its strategic development process. Certain FPI strategies can “learn from their experiences” and rapidly adapt to changing market conditions in real-time. FPI uses a walk-forward optimization approach, which involves testing a strategy by finding its optimal trading parameters in a past segment of market data and then checking the performance of those parameters by testing them over subsequent time periods. FPI also applies this framework in its backtesting—a process that tests strategies using historical data to evaluate their potential performance—to reduce biases and provide more realistic performance expectations.

If, as Stokes suggests, this young secular bull market “has the potential for many years of growth,” well-diversified investors should be able to capitalize on it through a blend of quantitatively-based strategies that can be customized for investors all along the risk spectrum.



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