AI will not help pick stocks

Although artificial intelligence (AI) might be a helpful tool for investors to retrieve and process data, it has its limitations when it comes to predict changes within complex systems that are as dynamic as stock and bond markets.
“AI trying to predict market prices is like self-piloting cars trying to read stop signs with words, shapes, and colours that differ from one day to the next. The continuous emergence of new information material to market prices is antithetical to static patterns fostering predictability,” according to Wes Crill, senior investment director at Dimensional Fund Advisors, which manages about $850 billion globally, including about $40 billion for clients in Australia and New Zealand.
He said that although active investors had long attempted to leverage the AI to gain an informational edge on markets, by applying AI tools to gauge sentiment from social media or extract information from company financial reports, these are still the tools that are best and processing and organising data to identify patterns and summarise information but are limited in their ability to predict and assess ‘less stable patterns’’.
“Material information gleaned from running AI processes is very likely a subset of the vast information set known by the market in aggregate and reflected in market prices. If new information is obtained, the process of acting on that information (buying or selling stocks/bonds) incorporates it into market prices. As more investors employ these tools, any edge from doing so should wane,” Crill noted.
However, the AI tools may be leveraged to enhance a fund manager’s process and have their role in smoothing business processes by interrogating data and helping to service clients and firms with massive data sets on their customers’ activities.
“But like any tool, you have to know how to use it. For example, if it makes interrogating data much easier, then the chances of finding results from data dredging increase. Where using AI can be very helpful is for firms with massive data sets on their customers’ activities. It can help those firms identify what their customers are more likely to buy next and advertise in a smart way,” Crill added.









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