Do Minimum Quantities Maximize Performance?

The three most important factors for evaluating the impact of MQ use.

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Minimum quantity (“MQ”) is a tool that allows traders to limit their orders to trading with counterparties only above a certain size.

Traditionally, market participants have used MQs as a way to profile counterparties and reduce interactions with those that could be potentially toxic. The idea was that by using orders above a certain size, they could avoid engaging with less desirable counterparties.

But is that true today?

Over the past few years, we at IEX Exchange have noticed a decrease in average trade size and an increase in odd lot-sized orders overall from our Members — not only from specific types of market participants. The drivers of this shift — including the increasing prevalence of stocks priced over $1,000 and the rise of sophisticated algorithmic traders among institutional investors — are no mystery. However, the impact of this change on the efficacy of tools like MQ has been less closely examined.

We therefore thought it might be useful to look at MQ use on IEX to evaluate whether the risks and rewards of this tool remain consistent with conventional wisdom.

In this series, we explore three important factors for evaluating the impact of MQ use:

  1. Adverse Selection: In this first part, our analysis on IEX suggests that MQ use may not be a very effective tool to prevent adverse selection, and, in some cases, high MQs can increase adverse selection. Our data demonstrates greater adverse selection in trades over 1,000 shares and finds limited benefit from restricting your trading to round-lots.
  2. Information Leakage: In the second part of the series, we find that while parent orders that execute in fewer trades overall have better performance (measured in slippage), artificially manufacturing fewer trades over the life of order by setting high MQs does not necessarily improve performance on IEX.
  3. Opportunity Cost: In the final part of the series, we found that opportunity cost on IEX disproportionally increases as MQs rise above 200, particularly during periods when a significant amount of volume traded in the market.

For more in-depth data and analysis, please refer to each individual blog post.

In conclusion, our analysis suggests that high MQs (over 100 shares) produce very little performance gain in terms of information leakage while increasing both the probability of adverse selection and opportunity cost.

A MQ of 100 seems like the best compromise in terms of minimizing information leakage and opportunity cost; however, setting a MQ of 0, or no MQ, is the only way with respect to MQ to prevent any loss of liquidity and minimize adverse selection.

Obviously, each order is different and the reason for MQ use varies, but we hope this series helps quantify some of the costs and benefits of utilizing MQs.

One final nuance worth noting is that our analysis only uses data from trades on IEX, which are not necessarily representative of the overall market. IEX’s proprietary protections, including the Speed Bump (a 350-microsecond delay designed to make sure IEX Exchange executes trades at the most up-to-date prices) and Signal (predictive technology designed to help prevent trading when the price is likely about to change), may make MQs less impactful on IEX than on other venues. In other words, because IEX already has protections in place which are designed to help prevent information leakage and adverse selection, using MQ for these purposes may not generate additional benefits. This is worth noting because it suggests this analysis is likely specific to IEX and might not be extrapolated market-wide.

We hope that you enjoy this series. Please let us know if you would like to collaborate on any bespoke analysis — we are eager to partner more closely and use our data to help improve performance!