Francis Breedon, Louisa Chen, Angelo Ranaldo and Nicholas Vause
Most academic studies find that algorithmic trading improves the quality of financial markets in normal times by boosting market liquidity (so larger trades can be executed more quickly at lower cost) and enhancing price efficiency (so market prices better reflect all value-relevant information). But what about in times of market stress? In a recent paper looking at the removal of the Swiss franc cap, we find that algorithmic trading provided less liquidity than usual, at worse prices, and that its contribution to efficient pricing dropped to near zero. Market quality benefits from a diversity of participants pursuing different trading strategies, but it seems this was undermined in this episode by commonalities in the way algorithms responded.
It’s been a while now since high-frequency-trading (HFT) made its debut in the financial market landscape. Initially, little was known about it and regulators and market participants alike were naturally concerned about its potential impact on markets. Nevertheless, over the past few years we have learned quite a bit more about HFT. So what’s the deal with HFT? This short blog post briefly describes the evolution of HFT, summarizes the current understanding of the impact of HFT on market quality and highlights some aspects of HFT activity that are still contentious. Regardless, I believe, the inescapable conclusion that so far emerges is that HFT has mostly had a positive impact on market functioning.