The research by CMCRC PhD candidate Tony Zhang and Dr Vito Mollica from the Macquarie Graduate School of Management showed that companies can influence the level of algorithmic trading in their own stocks, should they want to do so, by adjusting their share price level.
“Our data suggests that firms with higher relative tick sizes attract less HFT, perhaps due to the increased marginal cost of getting ahead in the order book,” Dr Mollica said.
“We analysed data from 2009-2012 and found that when companies undergo reverse stock splits which lower their relative tick size, algorithmic trading increased and remained elevated,” he said.
“The reverse was true for stock splits.”
Researchers compared the data to stock splits and consolidations from 1996-2004, before algorithmic trading had reached appreciable levels, and did not find the same effects.
“This confirmed for us the conclusion that algorithmic traders were finding more reward in trading stock with lower tick sizes.”
Institutional investors have been vocal in recent years in condemning the complexity and speed of contemporary equity markets, saying that algorithmic trading and high frequency trading were filling order books with the ‘noise’ of excessive messaging traffic and cancellations.
Many have called for higher regulated tick sizes which they say would favour long-term investors and encourage investor confidence.
Dr Mollica said companies themselves have complained about the volatility of their stocks, and while it is debatable whether algorithmic trading can be blamed for that, there are certainly actions that companies can take to reduce the level of this type of trading in their stocks should they wish to.
