Algorithms that buy and sell stocks based on specific criteria have come to stay.
That their popularity is increasing, especially when markets are under pressure or a headline for a market collapse, which is so powerful that it is attributed to “the Algos”.
Meant are algorithmic trading systems that are programmed to trade people like stocks. These methods, which use artificial intelligence, are so widespread that they have become part of the overall structure of the stock market.
Take the sell-off in February 2018: At that time, the Dow Jones lost more points in one day than ever before. The extent was also so intense because automated trading systems, such as volatility targeting, are programmed to reduce the allocation of funds to equities when the market becomes unstable.
Put simply, if machines are programmed to sell because a lot is being sold, it will result in a negative feedback loop like the one in February 2018.
But the growing popularity of trading strategies driven by data and algorithms also has advantages. Emotional impulses that can lead to wild price fluctuations are excluded.
According to Marko Kolanovic, JPMorgan’s Global Head of Quantitative and Derivative Research, they provide a degree of market stability on a daily basis.
What has changed when investing – and what has remained the same
When investigating the influence of Artificial Intelligence on the industry, it is important that investors do not lose sight of how things worked before complex technologies were used.
The fundamental process of investing has not changed over time, says Barry Hurewitz, international head of UBS Evidence Lab, a major provider of large data sets. Investing will continue to be an information processing business that requires analyzing competing points of view – from analysts, investors and corporations – and drawing sound conclusions based on them. “The core of the work you have to do to make investment decisions has not changed,” Hurewitz told Business Insider.
He added, “What is changing is the amount of data that needs to be processed and the availability of that data.” Just as the data and AI technology that has been developed to process it has boomed , Wall Street’s interest in it has grown.
According to Hurewitz, this has the disadvantage that some investors use the strategies of successful quant companies without being able to apply the technologies appropriately. Another danger, according to the expert, is that trendy buzzwords distract investors from the strategies that have been tested and found to be good.
Ultimately, having data at your fingertips is not enough, said Ruggero Gramatica, founder and CEO of Yewno, a provider of datasets accumulated using AI technologies. It’s more important how artificial intelligence is used than simply having access to information.
Yewno is one of many companies that use Artificial Intelligence to provide an alternative to the traditional stock picking process.
Ruggero Gramatica also highlighted the boom in investment products and so-called Robo-Advisors, which allow people to invest in automated investments. This disruptive trend will further reduce the cost of the investment, he said. It is a challenge for traditional stock pickers, but it is an opportunity for companies to be the first to use these new technologies.
AI in the real world: Invest selectively without stock pickers
Gramatic’s company Yewna has co-originated a handful of indices – including two with Nasdaq – which use artificial intelligence to track global companies in fallow, and the Stoxx Global AI Index. In addition, she has effectively used artificial intelligence to create three cannabis indices for Nasdaq.
What’s a better way to invest in ETFs from AI companies than with their own technology? Yewno has used a knowledge graph to collect heaps of data from the AI industry, identifying the key trends and linking them to the companies that drive them.
The yields of the indices show that the enthusiasm of the investors for artificial intelligence is great. Both the Stoxx Global AI Index, the Nasdaq Yewno Global and the Big Data Index gained 19 percent this year on July 11. The S & P 500 gained 20 percent and the Nasdaq Composite 25 percent.
According to Gramatica, the use of Knowledge Graphs in investing – which was developed to do so – is scattered