Stock markets have always leaned in the favour of those with the most resources.
While technically the same information is publicly available to all investors, from billion-dollar Wall Street hedge funds to enthusiasts in their basements, the reality isn’t quite as simple.
It’s like those scenes from Hollywood where the high-powered, big-city law firm drops 17 truckloads of paper files on the young, just-passed-the-bar, Matt Damon-lookalike junior attorney.
The information is there, but finding it is another thing entirely.
Trying to beat the stock market has been exactly the same. Finding the relevant and valuable information amongst the sea of noise has taken vast amounts of time and money, which most retail investors don’t have.
It’s why the average retail investor achieved an annual return of 4.25% in the 20 years to 2019, when the S&P 500 achieved a return of 6.06% over that same time.
With the rapid expansion of AI investing capabilities, does this create an opportunity for startups to offer investment solutions that finally change this?
The Wall Street advantage
The difference between institutional investors and retail investors comes down to two main components. Data analysis and operations. It’s the hedge fund’s ability to throw huge amounts of cash at both of these areas that allow them to identify trends and investment opportunities faster and more frequently than the individual—and then act on them.
The data analysis edge
Data has been an edge for as long as stock markets have existed. The investors with the best, most relevant data and information are able to make more informed and, therefore, more likely accurate, decisions.
It’s the reason why insider trading laws came into effect way back in 1934. Regulators realized that the availability of information was so valuable that it needed to be policed.
It’s no different today. While staying within the regulations, institutional investors spend crazy amounts of money on ensuring that their data is as accurate and real-time as possible. There’s a reason why trading firms will spend $25,000 a year on a Bloomberg terminal for a single employee, when much of the same data can be accessed cheaper, but seconds or minutes later.
Not only do institutions have access to the best data feeds in the world, they have access to the best analyst and trading talent as well. The brightest minds from Ivy League colleges work long hours to find patterns in the data, aiming to pull insights from it that could lead to profitable trades.
When it comes to data, retail investors are rec league ballers turning up to an NBA arena to play Game 7 of the finals. They might know the rules of the game, but they’re not in the same league.
The operations edge
But the advantage doesn’t end there.
Spotting a trend or an opportunity is only one part of the investing puzzle. Acting on it can be deceptively complex. A retail investor might believe that the price of crude oil is going to fall. But how do they trade on that?
They’ll likely have to wade into the world of options and futures, shorting oil commodities themselves or potentially energy producers. That’s easier said than done. Understanding the technicalities of how to trade these sorts of complex financial instruments isn’t something that can be learned overnight.
By the time a retail investor has worked out how to practically implement their trade, the opportunity may have passed. This could mean they need to move on to the next idea, or worse, that they forge forward with the trade when they really shouldn’t.
Not only that, but the downside risk when not done properly can be effectively unlimited.
So from a purely operational standpoint, institutions also have a leg up. They have vast teams dedicated to implementing the trades in the shortest possible time and in a way that provides the most potential upside with the maximum downside risk protection.
This is not to say that mistakes don’t still happen at an institutional level. But the chances of a WallStreetBets style wipeout is highly unlikely.
Does this represent an opportunity for startups?
Since the birth of the internet, there’s been talk of how the democratization of information was going to help close this gap. There have been some tentative steps in that direction. Retail investors now have access to a much wider range of investment options, and can make trades instantaneously, all across the world.
As the data shows, retail investors still underperform. But with the emergence of AI, startups may now have the ability to deploy the equivalent of a large team of analysts to help make investments decisions for their users, with minimal actual analyst headcount.
How the Gamestop era tried (and failed)
For a little while, it looked like this balance of power was starting to ever-so-slightly shift. The euphoria that took place in early 2021 around meme stocks like Gamestop and crypto joke coins like Dogecoin, saw retail investors wield significantly more power than usual.
Some hedge funds came under pressure as retail investors banded together and moved much higher volumes than usual, as the hype on Reddit spilled into the mainstream.
While it was an exciting time for markets and an interesting case study in the power of great marketing, very little change was felt in the aftermath.
And really, like almost every major investment trend we’ve ever seen, the movement on Gamestop started off the back of data analysis. The only real difference in this case, was that the unique perspective and detailed breakdown came from a YouTuber in Massachusetts, rather than a hedge fund trader in Manhattan.
It was a rare case of a retail trader creating an information edge over the institutional players. Combined with the potluck nature of viral online content, it created the perfect tinderbox for a retail investor tidal wave.
And the spark that started it all was data analysis. With the rapid development of AI, and specifically the integration into retail investment platforms, we could be about to see the playing field become more level than it ever has been before.
How AI could level the playing field
AI has become a buzzword that’s an apparent mandatory inclusion on every SaaS landing page or investor deck. We’ve seen the trend happening for a while, but the release of the simple ChatGPT interface has really accelerated the mainstream awareness of the tech.
When it comes down to it, AI’s key strengths are its ability to process and analyze huge amounts of data in a short space of time, and with machine learning, find trends and patterns within that data.
As well as that, it can be designed to execute programs or strategies that have been programmed into the system.
In short, AI excels at data analysis and technical operations. You can see where I’m going with this.
AI investment apps and platforms have the potential to reduce the edge for institutional investors. Where it might take a team of analysts days or weeks to comb through newly released earnings or economic data looking for trends and opportunities, AI could do the same thing in a matter of hours or minutes.
Where shorting Japanese automakers (for example) might require specialized and technical knowledge on complex foreign financial instruments, AI and natural language processing could be used to identify and implement the trades almost immediately.
“Hey Siri, short Toyota but make sure it doesn’t send me broke.”
Obviously I’m getting ahead of myself, we’re a long way from that level of sophistication. But the reality is that AI is already being used to provide retail investors access to trading strategies that have previously only been available through Wall Street hedge funds.
Retail investor empowerment 2.0
So what does this really look like for retail investors? Many of them will have been burned badly in the post-meme market. Late 2020 into early 2021 saw a rush of retail inflows and often huge gains in a very short space of time. By the summer of 2021 the shine had started to come off, and into 2022 things got very ugly.
Many investors gave up all their gains, and then some. As an introduction for first timers into the markets, it was a stark lesson of the highs and lows that can punctuate long term returns.
The concern has been whether this experience would encourage long term investing in younger generations, or turn them off forever.
If you spend a bit of time lurking on Reddit subforums like the original r/WallStreetBets or its offshoot r/Superstonk, the overwhelming sense from the members is that they got ripped off by the establishment during the GME craze.
With that as a backdrop, it’s a tough sell to get them to wade back into markets without a new weapon on their side.
The answer may lie within AI, which has the potential to provide retail investors with capabilities they didn’t have last time they sent their stimulus check to a trading app. It could provide investors with the sense that they have another ‘pair of eyes’ watching their money, rather than being on their own in their journey to make gains.
For investors who are wary of being burned by the markets again, having AI capabilities in their corner may provide the confidence they need to dip their toes back in. This is particularly true for younger, tech savvy Millennials and Gen Z, who place less trust in traditional institutions and those in positions of power.
It’s something I’ve seen first hand. Over 80% of our investors opt for AI managed portfolios, rather than DIY options.
The challenge from the investment providers perspective will be to ensure that their technology is providing real capability and value that allows retail investors to compete with institutions, rather than simply some great marketing that provides the perception of it.
Where is the alpha?
So if AI can allow everyone to be special, then no one is special, right? That’s partly true. As AI technology continues to advance, we’ll see smaller and smaller advantages on offer from data analytics, technical arbitrage and operational efficiencies.
But not everyone can win. There’s always another buyer or seller on the opposite side of every trade.
Just as AI continues to disrupt across many, many different industries, the key ingredient that will produce above average results will come down to a single, uniquely human trait.
Creativity.
While economists and analysts work very hard to make the study of finance appear to be a hard science, it’s not one. You don’t find physicists debating the expected level of gravitational pull for 2023.
The ability to predict long-term economic themes and where our society and the world might be heading, is likely to be one of the most valuable sources of alpha in the age of AI. The fundamental concept of AI is that it can only use historical data to provide predictions on future results.
If ChatGPT was around in 1980, you couldn’t have asked it what lay ahead for the future of the internet. It didn’t exist yet. Yet savvy entrepreneurs were able to see the potential, see the trend and build fortunes off the back of it.
It’s not to say that institutions will lose all the advantages they have over retail investors. At the end of the day they will still have more money and more time to spend on finding alpha. But as time goes on and the gap narrows, we could see far more Keith Gill’s in the spotlight, and hopefully, improvements in the average retail investors returns.
What about you?
At its core, despite all of the advances in technology and the proliferation of trading apps and data providers, the fundamentals of good investing haven’t changed, and they probably never will.
You need to know what you’re investing for, the objectives behind your portfolio and to understand exactly what it is you’re trying to achieve. This, combined with having a clear investment time horizon and a realistic view of the worst case scenario, means you’ll be in the box seat for returns above the average retail investor—AI or no AI.
Jason Mountford is a Forbes contributor covering markets, tech and business.
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