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AI Investments Beats Broad Market Performance

Your capital is at risk if you invest. You could lose all your investment. Please see the full risk warning here.

By the end of 2023, Artificial Intelligence (“AI”) had become a powerful buzzword in the markets and for good reason: an increasing amount of corporate spending has been in incorporating AI into their operations and offering. AI-driven services are increasingly more adaptable to identifying (as well as replicating) patterns in data of multiple varieties while also potentially offering the means to automate services, thereby reducing human operator costs.

The benefits of AI have also percolated into the public sector, which usually tends to be slower on the uptake. For instance, a recent analysis by the think tank Brookings1 shows that between 2022 and 2023, the U.S.’ Federal government had spent almost $4.5 billion on AI, with nearly 90% of contract value within the Department of Defense.

Given the near-universal adoption of AI-driven services with immense growth potential, it’s no wonder that market participants have been piling up conviction into stocks with high “AI-relevant” exposure. It is entirely feasible to create a “basket” of stocks that capture most major aspects of AI adoption within a limited number of stocks.

Building an “AI” Basket

AI services aren’t just about the algorithm. Effective deployment is often predicated on an effective processor. While microchip development has increasingly centered around AI-relevant architecture, there are a few industry leaders in the present: Nvidia inc (ticker: NVDA), Advanced Micro Devices Inc (ticker: AMD), and Qualcomm Inc (ticker: QCOM) are widely considered to be running at the forefront of AI-relevant hardware design while Taiwan Semiconductor Manufacturing Company Limited (TPE ticker: 2330) is presently considered to be the world’s most prominent foundry for the manufacturing of microchips. Intel inc (ticker: INTC), meanwhile, can be considered as both designer and manufacturer – around 75% of Intel’s chips are manufactured in fabrication plants in Oregon and Arizona. Similarly, Arm Holdings (ticker: ARM) is a British semiconductor and software design company increasingly catering around an AI strategy.

On the “algorithm” side of the business, Big Tech is very prominent: Amazon Inc (ticker: AMZN), Microsoft Inc (ticker: MSFT) and Alphabet Inc (ticker: GOOGL) offer “on-demand” cloud-based computation platforms and infrastructure to corporations while Alibaba (ticker: BABA) does the same predominantly in China. Apple (ticker: AAPL) doesn’t currently have an AI offering yet, it incorporates AI extensively in its products and is expected to make some major inroads via a new “AI strategy”2 in 2024. Similarly, Meta Inc’s (ticker: META) Meta AI is working on developing various forms of artificial intelligence, developing augmented and artificial reality technologies. Another prominent (and arguably the most secretive) AI services provider is, of course, Palantir.

“Basket” Performance versus the Market

Given the price performance of many of these tickers tend to be rather extreme on many an occasion, a time-tested approach to handling this would be to weigh each of these stocks (or their American Depositary Receipts) equally. Each of these tickers – one per company – would thus have a weight of approximately 7.69%.

In the Year Till Date (YTD), the price performance of this equal-weighted “AI” basket versus the broad-market S&P 500 (ticker: SPX) and the tech-heavy Nasdaq-100 shows the former having a clear and massive lead.

Given the near-universal adoption of AI-driven services with immense growth potential, it’s no wonder that market participants have been piling up conviction into stocks with high “AI-relevant” exposure. It is entirely feasible to create a “basket” of stocks that capture most major aspects of AI adoption within a limited number of stocks.

Building an “AI” Basket

AI services aren’t just about the algorithm. Effective deployment is often predicated on an effective processor. While microchip development has increasingly centered around AI-relevant architecture, there are a few industry leaders in the present: Nvidia inc (ticker: NVDA), Advanced Micro Devices Inc (ticker: AMD), and Qualcomm Inc (ticker: QCOM) are widely considered to be running at the forefront of AI-relevant hardware design while Taiwan Semiconductor Manufacturing Company Limited (TPE ticker: 2330) is presently considered to be the world’s most prominent foundry for the manufacturing of microchips. Intel inc (ticker: INTC), meanwhile, can be considered as both designer and manufacturer – around 75% of Intel’s chips are manufactured in fabrication plants in Oregon and Arizona. Similarly, Arm Holdings (ticker: ARM) is a British semiconductor and software design company increasingly catering around an AI strategy.

On the “algorithm” side of the business, Big Tech is very prominent: Amazon Inc (ticker: AMZN), Microsoft Inc (ticker: MSFT) and Alphabet Inc (ticker: GOOGL) offer “on-demand” cloud-based computation platforms and infrastructure to corporations while Alibaba (ticker: BABA) does the same predominantly in China. Apple (ticker: AAPL) doesn’t currently have an AI offering yet, it incorporates AI extensively in its products and is expected to make some major inroads via a new “AI strategy”2 in 2024. Similarly, Meta Inc’s (ticker: META) Meta AI is working on developing various forms of artificial intelligence, developing augmented and artificial reality technologies. Another prominent (and arguably the most secretive) AI services provider is, of course, Palantir.

“Basket” Performance versus the Market

Given the price performance of many of these tickers tend to be rather extreme on many an occasion, a time-tested approach to handling this would be to weigh each of these stocks (or their American Depositary Receipts) equally. Each of these tickers – one per company – would thus have a weight of approximately 7.69%.

In the Year Till Date (YTD), the price performance of this equal-weighted “AI” basket versus the broad-market S&P 500 (ticker: SPX) and the tech-heavy Nasdaq-100 shows the former having a clear and massive lead.

Source: Leverage Shares analysis

It didn’t take long for the “basket” to begin its massive outperformance: after 8 days where markets were open for trading, the basket goes from largely following the indices to piling on performance that far outstrips them. Both crests and troughs in the market indices tend to be highly amplified in the “basket”, which is the first indicator as to how heavy market convictions are in “AI-relevant” technology.

For a better sense of conviction, one can also consider constituent-weighted Price to Earnings (PE) Ratios that would be the “effective” PE Ratio for each of these three instruments. An examination of trends here add further nuance to the evolution of investor conviction.

Source: Leverage Shares analysis

On balance, the “basket” tended to underperform relative to the market indices through all of January. The piling of conviction – as shown by the rising PE Ratio performance – begins in earnest after the 7th of February when Arm shoots up on the back of an upbeat earnings release. While Arm’s PE Ratio performance has tended to subside during troughs, they continue to be held when conviction in other constituents of the “basket” rise.

A Basket Ready to Go

The idea of an equal-weighted “AI» basket underpins two of London Stock Exchange’s hottest new Exchange-Traded Products (ETPs). The 3X Long Artificial Intelligence ETP (ticker: GPT3) takes the basket and amplifies its daily returns on the upside by 3 times. For the downside, there’s the -3x Short Artificial Intelligence ETP (GPTS). The basket itself is estimated via the Solactive Artificial Intelligence Index (BBG Ticker: SOLUAI) wherein the constituents are rebalanced on a quarterly basis to provide consistent and rationalized performance.

Given that the basket has amplified crests and troughs relative to broad indices, professional investors will find ample opportunities to capitalise on market convictions in either direction on a tactical basis. Over the course of this year, these ETPs will likely prove to bring some very interesting performance profiles to investors’ profiles. The fact that any potential loss in either of these products is limited only to amount invested and no further (unlike many other products/strategies) certainly helps too.


Footnotes:

  1. «The evolution of artificial intelligence (AI) spending by the U.S. government», Brookings, 26 March 2024
  2. «Apple announces its big annual conference, where it could reveal its AI strategy», CNBC, 26 March 2024

Your capital is at risk if you invest. You could lose all your investment. Please see the full risk warning here.

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Violeta Todorova

Senior Research

Violeta se unió a Leverage Shares en septiembre de 2022. Ella gestiona la realización de análisis técnicos, investigación macroeconómica y de acciones, y ofrece información valiosa que ayuda a la definición de estrategias de inversión para los clientes.

Antes de unirse a LS, Violeta trabajó en varias empresas de inversión de alto perfil en Australia, como Tollhurst y Morgans Financial, donde pasó los últimos 12 años de su carrera.

Violeta es una técnica de mercado certificada de la Asociación Australiana de Analistas Técnicos y tiene un Diploma de Postgrado en Finanzas e Inversiones Aplicadas de Kaplan Professional (FINSIA), Australia, donde fue profesora durante varios años.

Julian Manoilov

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Julián se unió a Leverage Shares en 2018 como parte de la principal expansión de la compañía en Europa del Este. Él es responsable de diseñar estrategias de marketing y promover el conocimiento de la marca.

Oktay Kavrak

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Oktay se incorporó en Laverage Shares a fines de 2019. Él es responsable de impulsar el crecimiento del negocio al mantener relaciones clave y desarrollar la actividad de ventas en los mercados de habla inglesa.

Él vino de UniCredit, donde fue gerente de relaciones corporativas para empresas multinacionales. Su experiencia previa es en finanzas corporativas y administración de fondos en empresas como IBM Bulgaria y DeGiro / FundShare.

Oktay tiene una licenciatura en Finanzas y Contabilidad y un certificado de posgrado en formación empresarial de Babson College. También es titular de una certificado CFA (Chartered Financial Analyst).

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Investigación

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Sandeep tiene una maestría en Finanzas, así como un MBA del Illinois Institute of Technology de Chicago.

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