Despite recent empirical research suggesting a positive relation between algorithmic trading (AT) and improvements to market quality, several market participants question the tangible benefits of AT. Recently, several market regulatory bodies have proposed or implemented cost recovery and fee models that charge brokers for market participation on a pro-rata basis with respect to message traffic and trading activity. For instance, IIROC (Canada) implemented the Integrated Fee Model on April 1, 2012, which involved afee structure to recover market regulatory costs based on participants’ message traffic and trading activity that allocates IIROC’s annual operating cost to two pools comprising unique costs for each of dealer regulation and market regulation. On Jan. 1, 2012, ASIC (Australia) introduced new market supervision and competition cost recovery billing arrangements for ASX and Chi-X participants proportionally allocated to each participant as follows: non-IT costs ($14.92 million) will be proportionally allocated based on the number of transactions, and IT costs ($7.89 million) will be proportionally allocated based on the number of messages. “The Impact of Message Traffic Regulatory Restrictions on Market Quality: Evidence from Chi-X Canada” (below)examines the impact of pro rata message traffic and trading activity cost recovery measures on trading activity and market quality. IIROC estimates that approximately 85% of firms will see a decrease in fees based on the new market regulation model, while 15% of firms will experience a fee increase (IIROC, 2012). The 15% that are expected to experience a fee increase are firms that contribute a greater amount of message traffic and trading activity — that is, high-frequency trading firms. This study examines the association between order-to-trade ratios (OTT), commonly used as a proxy for HFT, and broad liquidity-based market quality metrics for Chi-X Canada. Using the implementation of IIROC’s Integrated Fee Model on April 1, 2012, the study examines the impact of the regulator’s pro-rata fee model on order submission and market quality. Results have important implications for exchanges, market participants, and regulators. Using fixed effects regression analysis, high OTT strategies are linked with lower transaction costs (effective and quoted spreads) and increased depth.Across the entire sample, an increase in OTT is associated with a decrease in quoted and effective spreads and an increase in quoted depth. Furthermore, stocks with lower market capitalization exhibit a strong negative relation between OTT and spread-based liquidity measures. Larger market capitalization firms exhibit a strong positive relation between OTT and depth. The relation between OTT and spread-based liquidity measures is weaker for higher trading activity stocks; the relation between OTT and depth is stronger for higher trading activity stocks. The implementation of the IIROC Fee Model results in a decline in message traffic, trading volume, OTT, and liquidity measures. Regression analysis reveals a deterioration in the relation between OTT and market quality following the implementation of the IIROC 2012 Fee Model. These results highlight the importance of message traffic, predominantly from liquidity-supplying HFT, to market quality.