AI and quant trading strategies are nothing without solid fundamentals. As quantamental investing continues to gain traction, Elsen founder and CEO Zac Sheffer considers why human intervention will always be necessary.
- The unpredictability of markets demonstrates a perpetual need for at least some human intervention.
- AI has a big role in the future of the investment industry, but even a good quant trading strategy needs solid fundamentals behind it.
- Webinar will show how artificial intelligence can empower the investment process and support traditional human research.
Investments are continuing to flow into funds that use Artificial Intelligence (AI) to make trading decisions, but in the past few months we’ve seen just how important it is to still have human involvement and good fundamental reasoning behind these strategies.
In February, hedge funds that use AI in their trading processes experienced their worst month ever — or at least since Eurekahedge created its AI Index to track the market in 2011.
Overall it was a poor month for returns with the broader Hedge Fund Research Index falling 2.4 percent. But it was even worse for the AI Index, which dropped 7.3 percent.
These results led JPMorgan to conclude that AI-based funds “likely played a big role in February’s correction by being forced to de-risk given an unprecedented 7.3 percent loss.“
AI is here to stay
Despite these recent challenges, it’s tough to deny that AI will eventually play a central role in the investment world because it’s already seeping into our everyday lives.
While most people may not think about it — or just may not realize it — AI is no longer the realm of science fiction or limited to publicity stunts by technology companies trying to show off the cutting edge.
We’ve come a long way from when IBM’s Deep Blue squared off against chess master Garry Kasparov in 1997, or when Watson took down Jeopardy’s two biggest all-time champions in 2011.
Today, AI is already powering virtual assistants like Siri that you carry in your pocket everywhere, and picking the music you like to listen to on Spotify.
It’s helping to streamline and bring efficiency into our everyday lives, and is catching the attention of business leaders for the same reasons.
In fact, AI has even dethroned “big data” as a favorite talking point for public company executives during earnings calls.
In 2017, mentions of AI spiked after being barely mentioned at all only a few years earlier, according to an analysis of earnings call transcripts by CB Insights.
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Heavy spending on AI
Companies across industries are beefing up their usage of, and spending on AI.
And which sector is McKinsey Global Institute forecasting to increase spending the most? It’s not the technology industry, as many might think; it’s financial services.
Granted, this spending encompasses many potential applications of AI, ranging from how it can be used for marketing purposes, to its ability to streamline credit checks.
But there’s no doubt that investment groups will continue spending heavily to figure out ways that AI can give them an edge.
Fundamentals of a good quant trading strategy
We’re still in the early innings of using AI to make trading decisions, and there’s clearly a lot to learn.
But as Elsen’s Andrew Breton said when talking about the money flowing into quantitative strategies, “when algorithms are managing this money, who manages the algorithms?”.
Volatility based on unpredictable events will always be present — especially if the global political climate continues on the path it’s been on recently.
But it’s not just politics — there are scores of unpredictable circumstances, from natural disasters to technical innovation that will impact markets.
We might get close to coding algorithms or creating self-learning systems that react appropriately to any market condition. But even the smartest computer can’t see the future.
In other words, AI is no silver bullet for guaranteeing the right investment decisions.
Letting a computer pick your music on Spotify is one thing, but picking stocks that impact trillion dollar markets is quite another.
With Spotify, you can simply click “next” if it plays a song you don’t like; the stakes for AI-based investments are infinitely higher.
Whether or not we’ll ever reach a place where algorithms pick investments autonomously without any human involvement is hard to say.
But based on the results we’ve seen so far, the unpredictability of markets has demonstrated that a perpetual need for at least some human intervention is a much more likely scenario.
And that’s why it’s important to make technology easier to use and more accessible to all professional investors.
AI will certainly play a big role in the future of the investment industry, but even a good quant trading strategy needs solid fundamentals behind it. One path forward is to combine the best of quantitative and fundamental strategies into a quantamental investing future.
Asset management webinar
To see how artificial intelligence can empower the investment process and efficiently support traditional human research, view the on-demand recording of the webinar “Next Generation Asset Management: Powered by Artificial Intelligence, Designed by Humans”.
In the webinar, I joined Global Head of Quant and Feeds, Austin Burkett, and CEO and founder of Evovest, Carl Dussault, to talk about Evovest’s successful AI-based techniques and strategies.
Discover more about QA Point, a cloud-based platform for backtesting systematic investment models