We’ve recently talked about how the market naturally determines what an optimal spread should be. In that post it was obvious that the one-cent tick could be an artificial constraint for liquid stocks at “too low” a stock price level. That, in turn, leaves spreads that are artificially wide (in basis-points).

Today we delve deeper into that phenomenon.

But before we do, we encourage you to read about Chart 3 in our V is for Volume post. Specifically, note that there is a cost vs. queue priority tradeoff when choosing between inverted or maker taker venues. (That tradeoff is also the driving force behind the Access Fee Pilot, because research has shown that queue priority saves investors money, while it’s thought that rebate capture doesn’t).

Tick-constrained stocks do most of the inverted trading

First, we look at spreads for large-cap stocks, this time in cents. Then we color each ticker based on how much they trade inverted (red is more inverted).

This highlights some interesting phenomenon:

  1. Inverted is important mostly for stocks that are tick-constrained (sitting on the horizontal axis).
  2. Stocks above $100 all trade multi-cents wide, and only rarely trade on inverted. Interestingly, the spread increases in a roughly straight line as price increases for all stocks with the same market cap (circle size).
  3. Arguably that straight line reflects the “natural spread” for the tick-constrained stocks too, and would continue below the horizontal axis if sub-penny ticks were allowed.

Chart 1: Low priced stocks that trade one-cent wide spreads trade much more inverted

Source: Nasdaq Economic Research

Low priced stocks with long queues do the most inverted trading

Our second chart focuses on point #1 (and the tick-constrained stocks in the box) above.

This chart re-plots the tick-constrained stocks by average queue length (vertical axis). Note that we see another diagonal line, with queue size increasing as the tick constraint increases.

But we also see the color-shift to red as queue size increases (top left of Chart 2). Remember these are ALL “tick-constrained stocks,” but as queues become a bigger problem to solve, smart traders use inverted venues more. They are rationally, but also dynamically, increasing likely to “buy” queue priority.

Chart 2: Inverted venues are used much more for wide spread (in %) stocks which also have longer queues

Source: Nasdaq Economic Research

Markets automatically compress tick-constrained spreads

What this also shows is that markets are pretty good at counteracting inefficiencies like sub-optimal ticks.

Consider again Chart 3 in V is for Volume.

  • A stock that trades 100% maker taker has a “true spread” of 1.6 cents
  • A stock that trades 100% inverted has a “true spread” of 0.6 cents
  • But the economic average spread of a stock that trades 50% maker taker and 50% inverted will be right in the middle, at 1.1 cents, resulting in a 50 mil economic spread compression

If we look at how that economic spread compression works out for each of our tick constrained stocks we again see a straight diagonal line develop (at least for the most liquid stocks). The market is quite efficiently compressing the spreads more, the greater the artificially wide tick constraint becomes in basis points.

Chart 3: As low priced stocks trade more inverted, their economic spread also compresses

Source: Nasdaq Economic Research

Not surprisingly, this is also what happened to Tick Pilot stocks that were forced to artificially wide spreads. The market increasingly routed to inverted venues and midpoint prices, compressing the economic spread capture back below the five-cent tick.

Why is this important?

One of the basic implications of the Battalio-Jennings study that led to the Access Fee Pilot is that investors are better off “always” in inverted venues. This data seems to show that’s probably not true, especially for investors who account correctly for all the economics of trading.

Unfortunately, institutional investors might be stuck on using a definition of “best-ex” that focuses on execution price alone and ignores all the other trading and routing economics, including commissions and opportunity costs. That is potentially distracting them from the real focus, which should be data-driven smarter algos which lower overall costs.

The fact that these charts show the market naturally reducing the economic spread when a tick is constraining also supports more intelligent ticks and rebates: Something we first mentioned in Revitalize, and more recently reiterated in our TotalMarkets blueprint.

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