| Posted on
Regulators around the world are introducing cost recovery models, in part to curb the increasing incidence of High Frequency Trading. The question that arises is – will this make markets better? Indeed it has to because regulators are obliged by their respective mandates to ensure that all market design changes enhance the fairness and efficiency of markets.
Alexander SaccoCMCRC PhD candidate Sponsored by Chi-X A/Professor Andrew Lepone CMCRC Research Associate U. of Sydney Keywords: Capital markets, high frequency trading, regulation  
Despite recent research suggesting a positive relationship between Algorithmic Trading and market efficiency, many market participants continue to question the tangible benefits of Algorithmic Trading. Recently, market regulatory bodies have proposed or implemented cost recovery and fee models that charge brokers for market participation on a pro-rata basis, based on message traffic and trading activity. IIROC in Canada implemented such a model in April 2012 to recover market regulatory costs. Similarly, ASIC in Australia introduced similar cost recovery arrangements for ASX and Chi-X participants, proportionally allocated to transactions ($14.92 million) and messages ($7.89 million). Researcher Alexander Sacco and project leader Andrew Lepone examined the impact of this pro-rata message traffic and trading activity cost recovery measures on trading activity and market quality. Order to trade ratios (OTT), commonly used as a proxy for High Frequency Trading and broad liquidity based market quality metrics are examined for Chi-X Canada. Using the implementation of IIROC’s Integrated Fee Model, Sacco examines the impact of the regulators pro-rata fee model on order submission and market efficiency. It matters little that message taxes may have enhanced the fairness of markets if at the same time they have reduced its efficiency. Logic suggests that a market design change can’t be optimal if it reduces either the fairness or efficiency of markets. This work suggests that the message tax has led to a sub-optimal market. The implementation of IIROC’s Fee Model results in a decrease in message traffic (as expected) but a corresponding deterioration in market efficiency. These results are suggestive of the importance of message traffic, predominantly from liquidity supplying High Frequency Traders, to market efficiency. That is, high message traffic trading strategies (generally associated with HFT traders) are linked to improvements in spread and depth of markets. Perhaps HFT traders are not the bogeymen that they have been widely portrayed as or at least there are mitigating factors.
Author(s): Alexander Sacco, Andrew Lepone