Abstract
The current research assesses the risks commonly attributed to the presence of HFT in the context of different market structures deployed by the U.S. exchanges. In particular, we find that, by design, the so-called “normal” exchanges have the lowest market quality, including the highest proportion of limit orders cancelled, the lowest ability to detect spoofing market manipulation, the highest volatility and probability of market crashes, yet the highest liquidity. The so-called “inverted” exchanges have higher market quality, including a lower proportion of limit orders cancelled, higher ability to detect spoofing market manipulation, lower volatility and probability of market crashes, but lower liquidity levels. Finally, we show that “pro-rata” markets possess even higher market quality. We derive these results theoretically and then show that they hold empirically. We also derive the theoretical quality of markets with no-cancel ranges, and optimal order sizes in pro-rata markets.
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