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Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by dcolkitt on Wednesday September 02, 2020 @08:30PM (#24359726)
> They find that when the relative tick size, i.e. the minimum tick size increment divided by the stock price, is larger, HFTs compete more intensely to be the first one to the front of the limit order book queue in order to supply liquidity.

Although I think the SEC has generally done a good job in terms of market microstructure (especially in terms of resisting ill-informed populist rhetoric), I really wish they'd start exploring sub-penny tick sizes, at the very least on the most liquid low-priced stocks.

Since decimalization, it's been two decades since we've had a tick size reduction in US equities. When certain stocks sit at a one penny bid-ask spread all day, that's a sign that penny ticks are too economically wide. It's consumers and ordinary investors that pay the cost in terms of higher spreads.

You can think of the bid-ask spread as the cost of liquidity. It's how much more you pay for immediate execution. The tick size therefore acts like a price floor on the cost of liquidity. Why are we imposing a price floor, one that's much higher than the free market price, on end-consumers? If we reduced tick sizes from $0.01 to $0.001, the cost of trading for most retail investors on most stocks would fall by 50% or more.

It blunts the price discovery process. It incentives HFTs to compete in an arms race of speed to capture queue position, rather than provide better prices. The only group it really benefits are the incumbent exchanges (who can avoid competing with new entrants offering better pricing), and large, active portfolios, like hedge funds, that incur high market impact costs.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by stygiansonic on Wednesday September 02, 2020 @09:41PM (#24360094)
Decreasing the tick size is not automatically a better situation. Take for example the "hide not slide" order type offered by some exchanges several years ago[1]. Due to the liquidity rebates offered by exchanges (essentially get a very small rebate for having your standing limit order get filled by a marketable order) traders "fight" to get first in line to have their limit orders filled. Due to price-time priority, that would mean having placed your limit order at a given price earlier than someone else. (The hide-not-slide rule essentially circumvented this)

The only way other way to get priority is by bettering your price. If minimum tick size is set to a very low threshold (or no threshold at all), "outbidding" someone for a better place by offering a economically insignificant price improvement (say $0.000000001 per share) would become the easiest way to get price-time priority on someone, and hence the value of placing a standing limit order would be reduced: Anyone can just outbid you for a fraction of a fraction of a penny at any time, so it becomes much more likely that if your limit order gets filled, the price will then move against you, and otherwise, your limit order will never get filled. This problem exists today but would probably be made worse by a smaller tick size - in fact I believe it's one reason why liquidity rebates are offered.

1. https://www.bloomberg.com/opinion/articles/2015-01-13/hide-n...

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by kasey_junk on Wednesday September 02, 2020 @10:18PM (#24360271)
I’m sorry I’m not sure I understand the relationship you implying between “hide not slides” and small tick sizes.

Hide not slides were used when you didn’t want to move the price at all. If you could move the price a little bit you’d get many of the benefits of a hns without the negative externalities.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by billsnow on Wednesday September 02, 2020 @08:51PM (#24359832)
Here, here.

Curiously, the commodities markets have always adjusted tick sizes for different contracts so that the dollar value is reasonably consistent (~10 dollars). These are products for which the contract size (in dollars) varies wildly and the quotes are all over the place (anywhere from 9 decimal points to no decimal points).

It makes writing your algos confusing, esp when you start doing inter-commodity spreads, but the business case is so obvious, it really makes you wonder why the equities markets haven't done more.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by ridaj on Wednesday September 02, 2020 @11:03PM (#24360458)
Off-topic: the expression of agreement is "hear, hear" not "here, here" https://www.grammarly.com/blog/here-here-vs-hear-hear/
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by smabie on Wednesday September 02, 2020 @08:57PM (#24359867)
Some dark pools had sub-penny spreads for awhile, but the SEC fined them because this is illegal. I'm not sure what material kind of harm they think took place, but whatever I guess.
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by cm2187 on Thursday September 03, 2020 @04:17AM (#24361874)
How do you settle the purchase of one share with a price of 20.0006? It’s a price. You can’t really go lower than monetary units.

If you round it, you create a risk free arbitrage opportunity.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by egwor on Thursday September 03, 2020 @06:50AM (#24362706)
How's this different from in FX where someone buys EURUSD in USD quantity? Venues trade EURUSD not USDEUR. So they want to trade 1000 dollars. Current fx rate is 1.18162. So that's 846.2957634434 euros. Minimum settlement in euros is 1 cent, so what is done with the 0.57 of a euro cent or what happens to the difference between 1000 USD and 999.9931898? I think the answer to this is bankers rounding.
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by cm2187 on Thursday September 03, 2020 @06:56AM (#24362742)
It's called an "FX Rate" not an "FX price". You apply a rounding as part of the transaction. The amount settled is not a rate, it is a monetary amount.

The price quoted on the market is the amount settled for one share. If it is not, then it is not really the price of one share.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by dm3 on Thursday September 03, 2020 @06:42AM (#24362660)
There are already contracts trading at fractional cent prices. For an example see treasury bonds listed on CME. According to CME document[1] margin and option premium calculations round the amount to nearest cent. I suppose the same happens at settlement.

[1] https://www.cmegroup.com/trading/interest-rates/files/Treasu...

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by cm2187 on Thursday September 03, 2020 @06:57AM (#24362752)
But then you can arbitrage it. Buy 10,000 times 1 share, sell 10,000 shares. You can't really do that in the bond market, but you can in the equity market.
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by dm3 on Thursday September 03, 2020 @08:21AM (#24363267)
I think practically this would have to be solved by the equity brokers. All the intermediary accounting done in fractions and only rounded once cash leaves the broker.
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by jedberg on Wednesday September 02, 2020 @08:45PM (#24359804)
I agree with you, but there is an interesting though experiment. What if we made tick sizes $.000000000000001?

At what point do we get a diminishing return? At what point is it so small that it blows up the algorithms?

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by pierrealexandre on Wednesday September 02, 2020 @09:09PM (#24359937)
There is some interesting research regarding the optimal tick size (by instrument), eg https://arxiv.org/abs/1207.6325
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by vii on Wednesday September 02, 2020 @09:08PM (#24359934)
Well it might blow up some software not expecting these tiny tick sizes but there is an economic motive for larger tick sizes.

Traders can compete on

- price

- queue position

Small ticks mean they compete on price and big ticks mean they compete on queue position - to trade they need to have an order on the book, offering to trade at the current tick, that is ahead of other orders.

It's easy to see how the market benefits if people compete on price. However, it also benefits if people show how much they are willing to buy and sell. No sophisticated trader wants to reveal that as they will be taken advantage of when they are wrong. By having bigger tick sizes you incentivise people to try to get into the queue at these artificially better prices - it pulls liquidity into the open.

The tick size pilot that concluded in 2019 shows how this balance isn't easy to strike https://www.finra.org/rules-guidance/key-topics/tick-size-pi...

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by rytill on Thursday September 03, 2020 @01:45AM (#24361091)
Thank you for this simple explanation.

Lowering tick size helps price discovery, but hurts open liquidity.

Is there some ideal constant average number of ticks between the bid and ask which optimizes this tradeoff given a desired state of liquidity and price discovery?

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by ah- on Wednesday September 02, 2020 @08:54PM (#24359846)
They wouldn't blow up, but if the tick size is too small there's no point in displaying orders on the book and you end up with less liquidity.
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by anonu on Wednesday September 02, 2020 @09:24PM (#24360024)
Actually they went the other way with nickel wide spreads.

Plus you can trade at sub penny all day long. You just can't quote. So I don't think that hinders price discovery one bit, even on SPY trading at $350

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by hervature on Wednesday September 02, 2020 @08:49PM (#24359822)
Can you give an example of a "most liquid low-priced stocks" that "sit at a one penny bid-ask spread all day"? Correct me if I'm wrong, but you mean that it's the same penny bid-ask spread right? Like, 10.49-10.50 for 6.5 hours as opposed to a tight spread that moves.

Can you source this:

> If we reduced tick sizes from $0.01 to $0.001, the cost of trading for most retail investors on most stocks would fall by 50% or more.

If that's true, it would seem to imply that trading costs are so low that it doesn't matter.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by pierrealexandre on Wednesday September 02, 2020 @09:07PM (#24359930)
No, it does not sit at the same 1-tick spread all day. Typically for these tickers the 1-tick spread transitions very quickly to the 1-tick spread above or below (each individual market is going to be 2-tick wide for a very small amount of time at each tick transition, much less than 1 second).
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by sesuximo on Wednesday September 02, 2020 @11:40PM (#24360605)
They could just reverse split if it’s such a big deal
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by boulos on Wednesday September 02, 2020 @10:43PM (#24360370)
The other option that Matt Levine has been writing about more lately is no longer having integer number of shares (jedberg’s precision question is similar).

Amusingly, there are folks who take the other side of this argument, and very drastically like Scott Kupor at Andreessen Horowitz [1]

> How did this happen? Because decimalization reduced the “tick size,” the minimum increment in which stock prices can trade, to a penny (from its previous level of 25 cents). Thus, a trader who previously might have purchased a block of small-cap shares knowing that a $0.25 tick size likely represented his minimum profit potential on a trade now found his minimum profit potential reduced to a penny. Facing this uneconomic situation, small-cap traders simply abandoned the market, killing liquidity for these stocks.

More recently, that was testimony to the SEC [2]. It’s certainly true that small-cap / illiquid stocks are illiquid. But it seems like the argument is “we should intentionally have market inefficiency for market makers to collect so that we have more liquidity”. Maybe someone here knows more about the tick size pilot mentioned?

[1] https://blog.pmarca.com/2013/03/26/unshackle-the-middle-clas...

[2] https://a16z.com/2019/06/20/capital-formation-smaller-compan...

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by smabie on Thursday September 03, 2020 @02:29AM (#24361308)
Before decimilization, the minimum increment was 1/16th, not 25 cents or 1/4th.
Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by PhantomGremlin on Thursday September 03, 2020 @06:20AM (#24362570)
Before decimilization, the minimum increment was 1/16th

Perhaps in theory, but not in practice. It took a $910 million class-action settlement to help change the collusion.

https://www.economist.com/finance-and-economics/1998/01/15/c...

Also in practice I remember the spreads being much wider, e.g. $56 bid, $57 offer.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by stagehn on Thursday September 03, 2020 @12:14AM (#24360744)
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.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by lpage on Thursday September 03, 2020 @01:03AM (#24360936)
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.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by dcolkitt on Thursday September 03, 2020 @01:36AM (#24361050)
> 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.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by stagehn on Thursday September 03, 2020 @12:24PM (#24365639)
> Consider that statement in limit; if the queue was of infinite length, there would be no trade-through, and no adverse selection.

E[PnL | is_filled_very_soon] and P(is_filled_very_soon) both decline monotonically in queue size assuming we remain at the back of the queue. E[PnL | is_filled_very_soon] starts off negative and gets more negative monotonically. P(is_filled_very_soon) starts high and asymptotes to 0 (but never reaches it assuming queue size remains finite).

I will elaborate on the mechanisms behind queues being over-sized in large tick names:

- I have estimation error in my theoretical fair value combined with an opportunity cost of pulling my order, so even if I think my order is negative EV I want to leave it in the queue unless that negative EV exceeds the opportunity cost. In small tick names I don't care about this estimation error because there's little to no opportunity cost of pulling an order, so I am much quicker to remove liquidity which incentives a sparse book.

- Even if I get filled in a large tick name there's often resting size behind me that lets me scratch out, especially if in the market I'm trading I get the ack before the print shows in the public market data (in this case I am only competing with firms that have canary orders and I'm not sure how common that is outside futures arb).

I personally see the biggest problem of large ticks being that it gives an advantage to prop firms that can pre-queue multiple levels in advance especially with GTC orders which gives them an advantage. I see the biggest problem of small ticks being that prop firms can dime genuine liquidity which is a form of front-running, again giving them a big advantage. Not sure exactly how this will net off in terms of rents collected.

> 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.

Agreed. Either way it's not very consequential. I'm 100% in favour of leaving it as-is in US equities though. I'm looking at the orderbooks now of cheap stocks with 50 bps tick sizes and the spreads are multi-ticks wide, so reducing that would achieve nothing except added complexity.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by dcolkitt on Thursday September 03, 2020 @12:35AM (#24360828)
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.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by stagehn on Thursday September 03, 2020 @12:59AM (#24360919)
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.

Re:Staff Report on Algorithmic Trading in U.S. Capital Marke... by dcolkitt on Thursday September 03, 2020 @01:26AM (#24361009)
> 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.