8 ms·

As an industry practitioner I disagree with this but I can see why first order thinking will lead to that conclusion. A smaller tick size does not necessarily

As an industry practitioner I disagree with this but I can see why first order thinking will lead to that conclusion. A smaller tick size does not necessarily translate into lower transaction costs for investors. Market makers' competition for queue priority will ensure that queues are over sized with liquidity when the tick size is larger, creating more adverse selection for market makers and lower transaction costs for investors. The mechanism of action is that queues remain sized with depth even when the fair price breaches the BBO because there remains a nontrivial probability that the fair price will bounce to the other side of the BBO, returning the market maker's posted size to positive expected value territory. Market makers have an incentive to do this when the tick size is large in order to preserve time priority. This mechanism doesn't exist in small tick stocks since there is no cost to pull an order, since time priority doesn't exist in the limiting case of infinitesimally small tick sizes. My experience has basically confirmed this theory. I have run market making algorithms in both small and large tick stocks and found both categories to be equally difficult. In fact it's hard to imagine it any other way, market makers will compete away any difference in edge, reducing the size of the pie to near zero in both tick size categories. My findings here only apply to tick sizes below 100 bps. I do however agree that it helps to create a speed arms race. But I see that as offset with more simplicity of larger tick sizes, order management is much easier.

dcolkitt 6y ago
You’re not considering the second order effect of smaller spreads inducing more volume in non-toxic order flow. You’re right that market makers aren’t earning economic rents. At least at the margin. Since transaction costs are just the reverse of market maker profits (plus exchange fees and commissions), this would suggest that aggregate transaction costs would remain unchanged regardless of microstructure. However this ignores the fact that trading volume is highly elastic to the price of liquidity. Moreover this is doubly true of non-toxic order flow. I.e. traders with only a very small edge are more sensitive to costs than those with a large one. In other words smaller ticks would lead to much more trading volume, the bulk of which would be high quality and non-toxic. In aggregate, market maker profits would not decrease. But they would be aggregated over a much larger pool of non-toxic flow. Thus the individual cost paid on any single trade would decrease. This isn’t just hand waving theory, it’s exactly what we witnessed when the equities converted from 1/16 ticks to decimization. In econ terminology the problem with wide ticks isn’t the capture of economic rents, but the deadweight loss from price floors in an otherwise competitor market.
- stagehn 6y ago
  What's deadweight loss? Trading is zero sum dollars (gross fees) and positive sum utility. If execution flow is paying more slippage in large tick stocks then that PnL must be going to someone's pocket (market maker or short term scalper or prop firm) I don't agree that flow execution is going to be queueing much more than hitting in larger tick stocks relative to smaller tick stocks especially in US equities where the largest tick size is 100 bps and low price stocks have larger volatility. Most of these stocks have multi tick spreads anyway so reducing the tick size does nothing but increase complexity of order management. The bid ask volume imbalance is often skewed in these stocks and you get less slippage by just lifting the entire queue (when the BBO imabalance points in your direction) and being bid-over with half of the average queue size and being front of queue even if you have a low information order you're trying to execute. I can actually make a theoretical argument that large tick stocks is actually better for flow execution as follows: if the tick size is sufficiently large then I can be bid-over with size and not get dimed. Queue position is mine and can't be effectively stolen by market maker algos. I think it's mostly a myth that execution slippage is lower when queueing versus hitting for these large tick names. The average slippage from VWAP from randomly queueing in a stock with a 20 bps tick size will be about 10 bps, roughly the same as if you're just crossing the spread with a large order. But of course this slippage can be massively reduced in both the queueing and hitting execution strategies with some simple heuristics. You can get some market data and backtest this slippage yourself.
  - dcolkitt 6y ago
    > Trading is zero sum dollars (gross fees) and positive sum utility. If execution flow is paying more slippage in large tick stocks then that PnL must be going to someone's pocket (market maker or short term scalper or prop firm) The key is the total volume of execution flow is not fixed, but elastic to spread sizes. The total slippage captured by market makers and prop traders is higher in 2020 than it was in 1985. HFT firms make more more in aggregate than old school floor traders. Yet, I think both you and I can agree that by any reasonable measure, tradings costs are orders of magnitude lower in 2020 than 1985. You have to be careful not to confuse an aggregate amount (total industry profit) with an unit cost (average cost to trade $X). The former can rise, even while the latter is falling. When demand is elastic (as it is for liquidity), suppliers make up for lower costs with higher volumes. > being bid-over with half of the average queue size and being front of queue This is a tangent, but I don’t think that works for ordinary traders in US equities. Even if you manage to simultaneously sweep the touch at every exchange, SIP is still going to lag and show a stale NBBO. Without an ISO (which civilians don’t have) the exchange is obligated to route the order to the stale liquidity. By the time NBBO updated, an HFT would have already grabbed the queue. I could be wrong though, so let me know if I’m missing something.
lpage 6y ago
Also an industry practitioner, with an auction theory/mechanism design background. I agree with portions of what you said, but: > queues are over sized with liquidity when the tick size is larger, creating more adverse selection for market makers That's not right when it comes to price-time priority (pro rata is a different story). Consider that statement in limit; if the queue was of infinite length, there would be no trade-through, and no adverse selection. I'm talking about the price level penetration/second price dynamics that are relevant to a tick size conversation, not the more nuanced FV/winners curse stuff. To your subsequent point about bid-ask bounce, that's precisely why being towards the front of the queue on a deep bid and ask is valuable. > Market makers have an incentive to do this when the tick size is large in order to preserve time priority. > I have run market making algorithms in both small and large tick stocks and found both categories to be equally difficult.I have run market making algorithms in both small and large tick stocks and found both categories to be equally difficult. There's an efficient frontier parameterized (to first order) by the probability of a round trip (spread width or otherwise), the payout upon success, the loss upon failure, and the number of RT opportunities per trading day. As you noted there's not an easy way or a hard way given that these considerations are not orthogonal, and they're correlated with tick size. I haven't seen this mentioned yet, so I'll mention it explicitly. As it stands the 611-612 series rules pertaining to sub-penny pricing allow for average price executions; a large percentage of U.S. equities volume already trades at mid or within the spread, both principally and on venue. There are far bigger fish to fry in the market structure debate.
- dcolkitt 6y ago
  > As it stands the 611-612 series rules pertaining to sub-penny pricing allow for average price executions; a large percentage of U.S. equities volume already trades at mid or within the spread, both principally and on venue. True, but only lit decimal penny prices are protected by NBBO. Particularly when it comes to retail flow, that gives internalization pools a license to charge high prices by only having to match penny ticks. If sub-penny was protected by NMS, then lit exchange quotes could narrow the NBBO spread, forcing the internalization pools to give retail traders much better pricing. Also in general, I suspect price discovery is much less efficient when it occurs outside of lit quotes. If not just because, there’s no transparency on book pressure. But I’m definitely less confident about that assertion, and haven’t seen it quantified in any way.

dcolkitt 6y ago

You’re not considering the second order effect of smaller spreads inducing more volume in non-toxic order flow. You’re right that market makers aren’t earning economic rents. At least at the margin. Since transaction costs are just the reverse of market maker profits (plus exchange fees and commissions), this would suggest that aggregate transaction costs would remain unchanged regardless of microstructure. However this ignores the fact that trading volume is highly elastic to the price of liquidity. Moreover this is doubly true of non-toxic order flow. I.e. traders with only a very small edge are more sensitive to costs than those with a large one. In other words smaller ticks would lead to much more trading volume, the bulk of which would be high quality and non-toxic. In aggregate, market maker profits would not decrease. But they would be aggregated over a much larger pool of non-toxic flow. Thus the individual cost paid on any single trade would decrease. This isn’t just hand waving theory, it’s exactly what we witnessed when the equities converted from 1/16 ticks to decimization. In econ terminology the problem with wide ticks isn’t the capture of economic rents, but the deadweight loss from price floors in an otherwise competitor market.

stagehn 6y ago
What's deadweight loss? Trading is zero sum dollars (gross fees) and positive sum utility. If execution flow is paying more slippage in large tick stocks then that PnL must be going to someone's pocket (market maker or short term scalper or prop firm) I don't agree that flow execution is going to be queueing much more than hitting in larger tick stocks relative to smaller tick stocks especially in US equities where the largest tick size is 100 bps and low price stocks have larger volatility. Most of these stocks have multi tick spreads anyway so reducing the tick size does nothing but increase complexity of order management. The bid ask volume imbalance is often skewed in these stocks and you get less slippage by just lifting the entire queue (when the BBO imabalance points in your direction) and being bid-over with half of the average queue size and being front of queue even if you have a low information order you're trying to execute. I can actually make a theoretical argument that large tick stocks is actually better for flow execution as follows: if the tick size is sufficiently large then I can be bid-over with size and not get dimed. Queue position is mine and can't be effectively stolen by market maker algos. I think it's mostly a myth that execution slippage is lower when queueing versus hitting for these large tick names. The average slippage from VWAP from randomly queueing in a stock with a 20 bps tick size will be about 10 bps, roughly the same as if you're just crossing the spread with a large order. But of course this slippage can be massively reduced in both the queueing and hitting execution strategies with some simple heuristics. You can get some market data and backtest this slippage yourself.
- dcolkitt 6y ago
  > Trading is zero sum dollars (gross fees) and positive sum utility. If execution flow is paying more slippage in large tick stocks then that PnL must be going to someone's pocket (market maker or short term scalper or prop firm) The key is the total volume of execution flow is not fixed, but elastic to spread sizes. The total slippage captured by market makers and prop traders is higher in 2020 than it was in 1985. HFT firms make more more in aggregate than old school floor traders. Yet, I think both you and I can agree that by any reasonable measure, tradings costs are orders of magnitude lower in 2020 than 1985. You have to be careful not to confuse an aggregate amount (total industry profit) with an unit cost (average cost to trade $X). The former can rise, even while the latter is falling. When demand is elastic (as it is for liquidity), suppliers make up for lower costs with higher volumes. > being bid-over with half of the average queue size and being front of queue This is a tangent, but I don’t think that works for ordinary traders in US equities. Even if you manage to simultaneously sweep the touch at every exchange, SIP is still going to lag and show a stale NBBO. Without an ISO (which civilians don’t have) the exchange is obligated to route the order to the stale liquidity. By the time NBBO updated, an HFT would have already grabbed the queue. I could be wrong though, so let me know if I’m missing something.

lpage 6y ago

Also an industry practitioner, with an auction theory/mechanism design background. I agree with portions of what you said, but: > queues are over sized with liquidity when the tick size is larger, creating more adverse selection for market makers That's not right when it comes to price-time priority (pro rata is a different story). Consider that statement in limit; if the queue was of infinite length, there would be no trade-through, and no adverse selection. I'm talking about the price level penetration/second price dynamics that are relevant to a tick size conversation, not the more nuanced FV/winners curse stuff. To your subsequent point about bid-ask bounce, that's precisely why being towards the front of the queue on a deep bid and ask is valuable. > Market makers have an incentive to do this when the tick size is large in order to preserve time priority. > I have run market making algorithms in both small and large tick stocks and found both categories to be equally difficult.I have run market making algorithms in both small and large tick stocks and found both categories to be equally difficult. There's an efficient frontier parameterized (to first order) by the probability of a round trip (spread width or otherwise), the payout upon success, the loss upon failure, and the number of RT opportunities per trading day. As you noted there's not an easy way or a hard way given that these considerations are not orthogonal, and they're correlated with tick size. I haven't seen this mentioned yet, so I'll mention it explicitly. As it stands the 611-612 series rules pertaining to sub-penny pricing allow for average price executions; a large percentage of U.S. equities volume already trades at mid or within the spread, both principally and on venue. There are far bigger fish to fry in the market structure debate.

dcolkitt 6y ago
> As it stands the 611-612 series rules pertaining to sub-penny pricing allow for average price executions; a large percentage of U.S. equities volume already trades at mid or within the spread, both principally and on venue. True, but only lit decimal penny prices are protected by NBBO. Particularly when it comes to retail flow, that gives internalization pools a license to charge high prices by only having to match penny ticks. If sub-penny was protected by NMS, then lit exchange quotes could narrow the NBBO spread, forcing the internalization pools to give retail traders much better pricing. Also in general, I suspect price discovery is much less efficient when it occurs outside of lit quotes. If not just because, there’s no transparency on book pressure. But I’m definitely less confident about that assertion, and haven’t seen it quantified in any way.