The lure of technology
But facts such as these seem to have no effect on the investing public. When unit trusts displayed their failings in the early years of the current century, investors turned to ETFs.
As these also disappointed, ‘smart beta’ took over, and now one of the largest investment houses of all is putting its faith in artificial intelligence.
As the FT recently reported: “Last year, Larry Fink finally threw his lot in with the machines. On 28 March, BlackRock unveiled a secret project code-named ‘Monarch’, a radical restructuring of its equities unit that is still reverberating across the industry.
“The chief executive took an axe to BlackRock’s underperforming stock-picking business, sacking seven fund managers and shifting billions of dollars they used to manage to a little-known arm of the asset manager’s sprawling $6trn [£4.5bn] empire based in San Francisco, called Systematic Active Equities [SAE].
“When BlackRock, in 2009, swooped for Barclays Global Investors, the crown jewel was the iShares ETF business, the biggest player in a growing industry that recently smashed past $5trn of assets under management. But some at BlackRock now reckon that the simultaneous acquisition of SAE – a $100bn computer-powered ‘quantitative’ investment unit – could turn out to be an even bigger deal than the imperious iShares business.”
Faster is not always better
SAE is much older than BlackRock. It was originally an index-tracking firm called Scientific Active Equities, set up by Wells Fargo Bank in 1971 in an attempt to throw off the ‘Hicksville’ image of west coast banks at that time.
Fifteen years later it pioneered smart beta tactics, based on research which indicated that investors could beat the market by ‘tilting’ towards certain stock characteristics such as cheapness.
As the FT also reports: “One of the biggest trends in the money management industry is the explosion of interest in quantitative investing, using high-powered computers and artificial intelligence to scour markets and gargantuan data sets for patterns that can be exploited by trading algorithms.”
But this means that costs are high, and the benefits are quickly lost. Although SAE was the first into this field, it has certainly not proved that commercially successful. That is because, in the end, technology is being used to trade faster and more cleverly than the opposition, rather than to concentrate on what investment is about – buying stable, safe and growing income streams.
Guessing the future
Data sets are just that – an account of the past but with no appreciation of the future. However good and accurate, and however much we would prefer otherwise, the past cannot and does not predict the future. That remains unknown, and needs human imagination – and guesswork – to identify possibilities, though never probabilities.
