As reported by The Atlantic’s Daniel Indiviglio, the crazy market swings we saw last week were largely blamed on so-called high frequency trading. That’s when computer bots are programmed to automatically buy or sell stocks based on a set of criteria that quantitative traders establish. Critics of this practice say that volatility is worsened by robot traders, which cause momentum to build quicker through lightening-speed trading and cannot as easily exercise restraint. But a new study finds that these bots actually make the market less volatile. Is this plausible, given what actually occurred last week?
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The idea, simply, behind last week’s volatility is that positive or negative news caused stocks to rise or fall more than usual, and as momentum built, triggers within trading algorithms were hit, causing bots to push price movements even farther. This, in turn, led to even more momentum and bigger increases or declines in prices. This sounds reasonable enough, but maybe it has the role played by bots all wrong.
In the Wall Street Journal, Michelle Price reports on a new study that presents an alternate theory of how robot traders affect volatility. The study is by Australia-based Capital Markets Cooperative Research Centre. Alex Frino, professor of finance and chief executive of the group explains:
Part of this function is the way (high-frequency trading) algorithms identify trading opportunities–they’re built to recognize when prices are abnormally high or low, and their response to this naturally pushes prices back towards equilibrium.
Certainly, well-designed algorithms would lead bots to take advantage of under- and over-priced stocks by
buying or selling when broader market conditions also dictate doing so. So this assertion makes sense. Any algorithm that senses momentum building in one direction or another may also respond accordingly by making sure that it doesn’t endure big losses or miss prime buying opportunities. This would increase volatility.
The jury is still out on the effect high-frequency trading has on volatility.