Artificial Intelligence, investing and structured products


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Artificial Intelligence, investing and structured products

Artificial Intelligence (AI) is a topic that has been dominating commentator, press and investor attention for some time. We will examine developments in this area and the resulting opportunities in the structured products market.

It is nearly impossible to read any publication today without coming across some mention of AI. Since it is such an important trend it is natural that the companies in the business and investment world are scrambling to take advantage to provide solutions and avoid being left behind.

Although AI still feels in its infancy to many it has a long history of development. Automation is now deeply embedded in industry offering new possibilities and cost savings at the expense of traditional business and employment models. While politicians debate the topic of the effect of labour migration the consequences of automation are increasingly more important and are silently changing the landscape. Many industry sectors are now heavily using automated processes and sophisticated software.

The algorithmic aspects of AI have also seen explosive growth. Pattern detecting and inference making algorithms have been in use since at least the 1940s but have accelerated in scope with the power of modern computing and the ever-increasing capacity for data storage and usage.

From big data to generative AI

“Big Data” was a concept defined in the 1990s meaning ways to gain intelligence from large amounts of data available from internet searches and other methods. It was never really about the “big” but more about extracting information from data with an inherent lack of structure.

Focus has since moved on to the discipline of machine learning which harnesses data and previous patterns to predict outcomes of human behaviour and generate complex models. Machine learning is also not new but has evolved substantially in the last ten years.

The latest strand is the idea of generative AI, not simply analysing patterns of available data but using it to create significant amounts of content or solutions. The emergence of chatGPT and other resources has already had a profound effect and future development will surely only accelerate rather than plateau.

This has had ramifications in many spheres, governments and politicians have become involved. Last November the “AI Safety Summit 2023” was held in the UK and the United States has recently appointed lawyer Jonathan Mayer as its first chief AI officer.

In the tech world, Google, Microsoft and others have been scrambling over investment in AI and grabbing headlines. This has occasionally backfired such as the teething problems over Google’s recent Gemini launch.

AI's impact on investment and industry

There have been many previous themes that have caught the attention of the investment industry over the years and AI is now front and centre. At the recent SRP Europe conference held in London, there were many discussions and mentions of AI. In contrast, ESG had more or less disappeared, an initiative that was equally ubiquitous for many years but has now suffered something of a drop in interest and support.

Perhaps uniquely amongst major trends of the day, AI offers opportunities to invest in companies that are involved in AI, and to develop algorithms and propositions that themselves use AI.

AI-focused indices and ETFs

In order to generate targeted investment opportunities in firms involved in AI, new indices have been created. Not surprisingly the tech exchange and index provider Nasdaq has been at the forefront of this with its Global AI and Big Data Index and in conjunction with CTA, its Artificial Intelligence & Robotics Index. These two related indices consist of large tech companies including Nvidia, Meta, Sony and BT as well as newer entrants in this area such as Teradata, UI Path and Dürr.

ETFs have already been created linked to these indices which therefore generate interest and liquidity and the potential for options trading. All of this aids structured product activity.

AI-powered investment strategies and products

Specialist index provider MerQube has also been involved in this area with the launch of its MerQube/QueensField US AI Powered Index family. This comprises seven rules-based strategies that seek to uncover and benefit from the dynamics of investor preferences, using AI techniques.

Meanwhile Investment bank HSBC has developed an index called AI Powered US Equity Adjusted TR Index. This is an index that uses AI techniques to select stocks from 250 US companies. Usage of AI in this way is essentially an extension of traditional factor investing methods such as momentum and value. These techniques have been around for many years and AI provides data driven ways to refine them. Whether this can generate true extra value over the long term remains to be seen. It has already proven difficult for factor investing to systematically show higher returns and as more players try to seek alpha it becomes a case of chasing diminishing opportunities. A few structured products have already been issued on these indices. We can expect this sector to grow upon further adoption.

Other major investment banks have also been active. These include Credit Suisse with the Ravenpack Macro Trend JPY Index, Bank of America with the BofA Iris U.S. Sectors Index and SG Global Alpha Index.

The CS trend index has a number of components including the Credit Suisse RavenPack Artificial Intelligence Sentiment Index. The AI Sentiment index uses scoring extracted from news data by RavenPack's artificial intelligence algorithms and was launched in 2017. It was the bank's first quantitative investment strategy resulting from its collaboration with RavenPack.

The BofA Iris U.S. Sectors Index is based on a sector rotation strategy using AI technology (Natural Language Processing) to assess company executives’ sentiment around the key performance indicators and allocate accordingly with a volatility control overlay.

Finally, the SG Global Alpha Index is a long only global, multi-asset strategy that relies on a deep learning model to process market information and various financial metrics to determine optimal portfolio allocation. It also has a volatility control overlay.

AI powered indices and thematic AI indices will undoubtedly continue to increase in usage and enter mainstream investing as an important part of the technology sector.

Tags: Investment

Image courtesy of:     BoliviaInteligente / unsplash.com

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