The Tick-Constrained Stock Problem | Nasdaq


With the SEC looking at a more holistic review of market structure, there are a lot of problems regulators might be looking to fix. One, which others have also pointed out too, is trading in tick-constrained stocks.

What is a tick-constrained stock?

Tick-constrained stocks are stocks that almost always have a bid-offer spread that is 1 cent wide, the minimum allowed by Reg NMS rule 612, which requires decimal priced limit orders.

The diagonal orange line in Chart 1 clearly shows tick-constrained stocks are limited by the 1 cent tick, which forms a barrier along the 1 cent constraint. Moreover, dot size shows each stock’s daily volume, and the orange circles are generally larger, showing that the more liquid stocks at each price level tend to be tick constrained.

We have seen this from a different perspective in our perfect stock price research. That shows that as stocks see more liquidity, they can typically achieve tighter spreads. It also follows that, for tick-constrained stocks, if ticks could be smaller, spreads should also fall.

Chart 1: Tick-constrained stocks have spread that cannot decrease because of the 1 cent tick rules

Tick-constrained stocks have spread that cannot decrease because of the 1 cent tick rules

As a result, tick-constrained stocks have artificially wide spreads that usually lead to longer queues and more fragmentation, as traders try to find spread savings in inverted or midpoint markets. That, in turn, makes them more expensive to trade quickly and harder to work orders.

If we look at stocks that trade with an average spread of less than 1.08 cents, we see a collection of around 570 tickers. The circle size in Chart 2 again shows that some of the most liquid stocks (larger circles) are also the most tick constrained.

Chart 2: The most tick-constrained stocks at each price level have higher ADV (larger circle)

The most tick-constrained stocks at each price level have higher ADV (larger circle)

However, because the dot plot above has a log scale on the horizontal axis, it distorts the fact that most tick-constrained stocks are actually priced below $30.

If we stack the stocks into columns and re-plot the data on a normal axis, 10% of the tick-constrained stocks are priced under $3. Also, note that over 90% of tick-constrained stocks are priced below $30.

Chart 3: Most tick-constrained stocks are under $30

Most tick-constrained stocks are under $30

As prices rise, it is less likely for a stock to be tick constrained because the economic cost of the tick becomes (mathematically) smaller, as we see in this study. This reflects problems with our one-size-fits-all trading rules. For example:

  • A 1 cent tick on a $1.00 stock represents a spread cost of 1.0%.
  • A 1 cent tick on a $5.00 stock represents a spread cost of 0.2%.
  • A 1 cent tick on a $10.00 stock represents a spread cost of 0.1%.
  • A 1 cent tick on a $30.00 stock represents a spread cost of 0.03%.

We can also see this in Chart 1, where the spreads costs are shown falling in basis points as stock price rises. Market-wide, there are few stocks with enough liquidity, or low enough volatility, to be profitable for market makers with a spread of three basis points or less.

Tick-constrained stocks are harder to trade

The problem with tick-constrained stocks is that crossing the spread costs more compared to other similar stocks. The artificially higher cost makes a rational (but less urgent) trader try to save crossing spreads by:

Overall, that tends to increase routing complexity, spread and opportunity costs for investors.

To see these trends, we can plot tradability data for tick-constrained stocks vs. all others. For the charts below, we control for market capitalization by limiting our sample to S&P 500 securities. Chart 4 shows queue size (in shares and in dollars) across stock prices. We see that lower-priced, tick-constrained stocks have larger queue sizes, which also translates into higher dollar sizes at the national best bid and offer.

Chart 4: Tick-constrained stocks typically have longer queues – in shares and dollars. (Note that Chart 4b excludes odd lots on the true inside with much smaller notional)

Tick-constrained stocks typically have longer queues - in shares and dollars. (Note that Chart 4b excludes odd lots on the true inside with much smaller notional)

That, in turn, increases the time it takes to get a new order to the top of the queue, so it’s (theoretically) next in line for a fill. And this increases opportunity costs – the chance that only worse prices are available in the future.

Chart 5: Tick-constrained stocks typically have longer wait times to get to the top of the queue

Tick-constrained stocks typically have longer wait times to get to the top of the queue


We say “theoretically longer queues” because there are strategies more urgent traders can use to improve queue priority. We see that for the same stocks above, inverted venues, midpoint and off-exchange trading is higher for the tick-constrained stocks (Chart 6).

Remember, inverted venues pay a rebate to take liquidity (financed by a fee on the provider, the opposite of maker-taker pricing model). It is economically cheaper for those crossing the spread to remove inverted venues first, meaning those who are willing to pay for inverted venues are effectively paying for queue priority.

Similarly, midpoint orders are willing to forgo half the spread in order to get a fill, making them also more attractive to spread crossing orders. In the same chart, we can also see that hidden midpoint usage tends to be higher for tick-constrained stocks.

Logically, fragmenting quotes across more venues lets an order join a shorter queue.

Chart 6: Inverted and midpoint usage is higher for tick-constrained stocks

Inverted and midpoint usage is higher for tick-constrained stocks

Conclusion

Now that trading costs are so low, the 1 cent tick increment creates an artificial constraint for many stocks in the U.S. market.

That, in turn, makes trading in those stocks more complicated and more expensive. We see this through artificially wider bid-ask spreads, more inverted usage and longer queue lengths. It’s an example of where our one-size-fits-all tick size may not be optimal.

There are two ways we’ve discussed to fix this problem. Stock splits or intelligent ticks will both help to make the economic cost of spreads more appropriate for each stock, making trading cheaper and more consistent.



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