Quantitative investing models have been utilized for decades by money managers, but they are being aided substantially by the ongoing rise of artificial intelligence and machine learning, Financial Times reports.
Some money managers, such as Michael Kharitonov of the San Francisco-based Voleon Group, say the trend is likely to accelerate further. “The tools are complex,” he told The Financial Times, “but eventually others will have to move in this direction if they want to remain differentiated.”
Of course, machines ultimately are still run by humans, so the underlying themes that machines are programmed to find in identifying investment and asset management opportunities remain largely man-made.
But not exclusively so. “An algorithm derived from machine learning can extrapolate rules from the data itself. As a result, it learns as markets fluctuate,” Financial Times editor Robin Wigglesworth writes.
Yet, while machine learning is on the rise in financial services and asset management, its adoption is more likely to be incremental.
Kharitonov, for instance, believes “companies will need to weave machine learning into their entire process” and continue to augment it with human input.