November 7, 2018

Keep Your Eyes on the Prize:
the All-in Cost to Trade

At last month's hotly debated SEC market data roundtable, there was passionate discussion over both the nature of competition and fees charged for market data and market access. Some around the table, including IEX, chimed in that exchanges should only charge transaction fees. Market data and connectivity services, they said, should be provided for free.

We disagree. Exchanges are integrated enterprises that bring broad value through trading and technology services, but not all clients use every exchange offering. Allowing investors to order a la carte empowers each to select the blend of services they need. By contrast, charging high transaction fees but "giving away" data and connectivity is like requiring all diners to order a prix fixe tasting menu. Importantly, the current competitive market structure allows investors both choices. While the blend of exchange revenues has shifted from purely transactional to a mix of execution and technology, the overall costs on NYSE markets remain a bargain. In fact, the All-in Cost to Trade on NYSE Group exchanges is lower than on IEX or on many dark pools.

Keep your eyes on the prize: the All-in Cost to Trade on NYSE Group exchanges is less than $0.0007 per share. For our members, compare that to the $0.0009 transaction fee per share that IEX charges for most of its trading, and to a typical ATS fee of $0.0010 per share.

In fact, NYSE's competitiveness is understated in the comparison above as 1) the NYSE group calculation includes some fees associated with multiple NYSE markets, including NYSE Options, and 2) there are still datacenter and telecom fees associated with trading on IEX and dark pools, even if they are earned by unregulated datacenter and telecom providers instead of the trading venue operators.

Some market participants have understandably asked for a full breakdown of our calculation. We are happy to oblige, and stand ready to discuss any market participant's specific All-in Cost to Trade upon request.

We calculate NYSE Group's All-in Cost to Trade per share in two steps.
  1. First, we calculate the sum of the following NYSE-related product lines to get total cost to trade:
    1. Net transaction fees (i.e., fees minus rebates)
    2. Proprietary market data fees
    3. Connectivity and co-location fees
    4. Logical order port fees
    5. Membership fees
  2. Second, we divide this sum by NYSE Group's executed volume

Applying separate fees for market data and connectivity allows members to choose the right bundle of products for their specific business. For example, members of multiple NYSE exchanges do not necessarily subscribe to the same market data products or use the same number of logical order ports on each venue. Some participants add and remove liquidity evenly, while others are skewed more toward one style of trading. Because market participants choose different trading, data and connectivity services, it's entirely possible that any given member's All-in Cost to Trade may be lower or higher than the average in our calculation.

What's your own All-in Cost to Trade?

Reach out to us at rmteam@nyse.com to find out.

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About

NYSE started this forum to share data-driven insights from our trading systems and thoughts on key market structure topics.

We welcome any and all feedback to rmteam@nyse.com.


Contributors

Michael Blaugrund

Head of Equities, NYSE


Paul Kenyon

Head of Sales and Relationship Mgmt, NYSE


Steven Poser

Director, Research, NYSE


Kevin Tyrrell

Head of Equities Strategy and Research, NYSE

OCTOBER 29, 2018

Credit to Those In the Arena:
Enhanced Quoted Spread

In today's U.S. equities markets, roughly 60% of volume executes on an exchange and 40% executes off-exchange in dark pools and other broker-dealer facilities. All activity, both on and off exchange, relies on the quoted prices from exchanges to inform transaction pricing. This makes the National Best Bid and Offer (NBBO), reflecting the best quoted prices from all exchanges, a key benchmark for all types of trading, including midpoint trading leveraged by institutional investors and price improvement offered to retail investors. We have seen that the quality and quantity of quotes contributing to the NBBO can vary dramatically between exchanges, which we can measure using a new metric called "Enhanced Quoted Spread."

Quoted Spread & Exchange Competition

The NBBO that facilitates midpoint trading and retail price improvement arises from robust competition among exchanges to provide the highest bid and lowest offers for the longest portion of the day. One standard calculation for quoting performance is the exchange's average quoted spread. Taking a simple average of quotes published by an exchange, however, can hide an important fact: many exchanges offer two-sided quotes for only a small portion of the day in many stocks. This means that an exchange's "average" quoted spread may exist for only fleeting moments of the day, and market participants looking to execute on such an exchange may frequently find the venue does not offer a competitive quote (or sometimes any quote at all).

The Enhanced Quoted Spread (EQS) measure addresses this by replacing any missing quotes with the value of the Limit Up Limit Down (LULD) band.1 If an exchange has a one-sided quote, or no quote at all, we assign that exchange the LULD band price rather than drop the observation. With this method, exchanges with occasional or periodic quotes incur a penalty for their lack of displayed liquidity rather than misrepresenting a tight but infrequent displayed market as narrow on average.

The Cost of Not Showing Up

For many exchanges, the EQS calculation is similar to the average quoted spread calculation, especially in active stocks. For example, in active NYSE names, NYSE, NYSE Arca, and Nasdaq have nearly equal quoted spread and EQS calculations. However, exchanges with low market share and/or dark-oriented trading models fare worse under the EQS approach in both active and less-active stocks. For example, three venues exhibit EQS metrics of several times their standard quoted spread results, indicating they frequently have no displayed quote in the market.

So What?

As many investors have focused more attention on off-exchange trading, the exchange contribution to price formation has become frequently overlooked or even derided, even though off-exchange trades rely on exchange quotes to set prices. As the Enhanced Quoted Spread shows, contributions to price formation vary widely among exchanges. Maker/taker venues consistently outperform other venue types in both average quoted spread and in the EQS measure, suggesting that under today's market construct pricing incentives contribute positively to both the quality and reliability of displayed quotations.

1 The NYSE wishes to thank David Weisberger, who gave us the idea for this calculation.

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OCTOBER 1, 2018

Product Innovation:
NYSE Arca Official Closing Price Calculation

New Closing Price Logic

The price of a closing auction on the primary listing exchange determines the official closing price for most liquid corporate stocks and exchange-traded products (ETPs). However, many less-liquid securities do not receive sufficient closing-price interest to generate an auction. In such cases, the official closing price is based on the consolidated last sale price before the end of trading. This presents a distinct problem for less-liquid ETPs: if the underlying index/underlying fund holdings and corresponding market maker quotes have changed, but there have not been any consolidated last sales in the closing minutes of the market, the consolidated last sale value will not reflect current market pricing. This will then cause a greater disparity between the market price and its underlying net asset value (NAV). Around two-thirds of listed ETPs fit into this category.

To address this issue, in June, NYSE Arca introduced a process for setting an official closing price for its listed ETPs that better reflects the true value for ETPs that do not end trading with a closing auction. The new Arca Official Closing Price (AOCP) methodology for NYSE Arca-listed ETPs applies when an ETP does not have a closing auction, or the closing auction is an odd lot. Previously, the AOCP for ETPs without an eligible closing auction was the consolidated last sale, regardless of when the last sale occurred - be that days, weeks or even months prior.

The new AOCP methodology uses both consolidated last sale and National Best Bid and Offer (NBBO) inputs. NYSE Arca tracks the time-weighted average midpoint price (TWAP) of the NBBO over the last five minutes of the trading day. The TWAP and the consolidated last sale are blended based on the last sale time to determine the AOCP, according to the following schedule:

AOCPs derived solely from quoting activity account for 44% of total closing prices, while AOCPs reflecting a mix of trade and quote activity account for 5% of the total.

Performance Assessment

To assess the new logic's performance, we compared the difference between the AOCP and NAV Price before the logic took effect (May 1st 2018 - June 1st 2018) and after the logic was implemented (June 4th 2018 - June 30th 2018). We measured the average difference between the AOCP and NAV Price (at close) by product for each time period for products without auctions and then compared them across the before and after periods. As expected, the average difference between the AOCP and NAV tightened dramatically with the new logic.

As expected, this performance improvement relative to NAV is most pronounced in the least-active products. For ETPs trading under 10,000 shares per day, the median difference between the AOCP and NAV decreased from 60 basis points previously to 10.6 basis points using the new logic. Because the AOCP sets the reference price for the 'Limit Up Limit Down' (LULD) mechanism on the next trading day, an AOCP more closely aligned with the NAV will reduce the potential for an LULD trading pause to be triggered. LULD is invoked during times of volatility and sets a percentage level above and below which a security can move within a five-minute period. A security is automatically halted if the price would move outside the set percentage levels. An incorrect reference price is likely to lead to more LULD trading pauses because it does not reflect the value of the security.

Summary

As these results demonstrate, the new AOCP logic produces closing prices closer to NAV for the nearly two-thirds of ETPs that close without an auction each day. In addition to helping fix hard-to-explain premiums/discounts due to stale data, a more accurate official closing price also helps provide market protection with better reference prices to LULD. Furthermore, since ETPs report market price returns versus returns on NAV, stale closing prices can inaccurately skew performance data. This is of particular concern on month-end, quarter-end, and year-end dates.

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July 10, 2018

Fee Pilot Round 2

Our previous post highlighted how end investors could potentially bear increased costs as a result of the SEC's proposed Transaction Fee Pilot. As we expected, the post triggered a significant amount of public debate, as well as discussion between the Exchange and members of the buy and sell-side. This is an important topic worthy of discussion.

This follow-up post provides additional detail of our original calculations. We have also prepared a sensitivity analysis highlighting that substantial costs would remain for investors even if our reasonable assumptions prove, in practice, to be either too aggressive or conservative. Finally, in the interest of inviting parties to reach their own conclusions, we have created an interactive model that enables readers to input their own assumptions related to venue and liquidity type distributions. By providing their own data, readers can see the resulting estimated impact.

Key Points of the Original Analysis

  • The original analysis considered the fee pilot's impact on liquidity-taking flow because:
    • Institutional and retail investors take liquidity more than they provide liquidity;
    • These investors generally pay fixed commissions and likely will not receive the benefit of lower exchange fees and, therefore, will bear the cost of wider spreads; and
    • Investors providing liquidity may benefit from the wider spread by (1) posting at less aggressive prices if they join the (now wider) NBBO, or (2) seizing opportunities to set a tighter NBBO with less competition from market makers. In either case, we anticipate these are relatively weak effects, and it’s important to note they are in conflict with one another.

  • We assume that a reduction in access fees would result in a corresponding reduction in rebates.

  • Rather than attempt to quantify the impact of the pilot for each bucket, we used a weighted average fee/rebate reduction based on the total number of stocks that would be impacted by the pilot.
    • This approach yields an average fee/rebate reduction of 8.2 mills across all stocks.
    • The fee/rebate reduction across just the 3,000 pilot securities will be substantially higher, but given that we do not know which securities will be included it is appropriate to apply the lower average reduction across the broader universe.

  • We then use this value to 1) estimate the change in spreads, and 2) estimate the additional cost borne by liquidity-taking flow.

  • We assume that the change in spreads applies market-wide, including to non-maker/taker venues on the basis that maker/taker exchanges drive the inside quote far more frequently than taker/maker or flat fee exchanges

  • The cost calculation measures the change in cost to take liquidity, using the midpoint of the spread as the benchmark price.
    • The calculation charges 100% of the higher spread cost to the (conservatively) estimated share of agency-taking volume.
      • Our assumptions in this scenario are as follows:
        • Agency Share (based on NYSE Arca taking volume) is 49%
        • Maker/Taker Venue Share is 52%
        • Market average daily volume ("ADV") is 7.2 billion shares; average notional value is $368.7 billion
        • Change in spread is 0.32bps
    • Principal taking volume is charged the higher spread cost, less the reduction in access fees.
      • Agency Cost:
        Change in Spread*1/2 * Market Notional Value * Agency Share
      • Principal Cost:
        [Change in Spread*1/2 * Market Notional Value * Principal Share] - [Fee Reduction * Market Volume * Principal Share * Maker/Taker Venue Share]

Sensitivity Analysis

  • Our volume assumption used a year-to-date ADV at the time of the analysis.

  • We tested the model by increasing and decreasing the volume figure by up to 20%.
    • This accommodates the observation that some market activity may not be directly impacted by wider spreads, such as auction volume and midpoint volume.

  • Decreasing the volume assumption by 20% results in a cost of ~$0.86 billion, compared to the ~$1.08 billion original estimate.

  • The impact estimate is more sensitive to spread changes than volume changes:
    • If we over-estimated the spread increase by 20%, our cost estimate would be $0.79 billion compared to the ~$1.08 billion original estimate.
    • Conversely, if spreads widen more than we anticipate, costs will increase.

  • While we feel that our agency share of volume was appropriately conservative, the impact estimate shows relatively little sensitivity to this metric.

Interactive Model

As noted in our introduction, we are providing a spreadsheet that enables users to input their own assumptions so they can arrive at an estimated annual impact from their firm's own data. The model includes a robust set of venue and liquidity action variables, enabling users to customize volume mixes for variables such as add/take, standard/inverted/dark venues, etc. We also include a Yes/No variable for cost-plus or pass-through pricing models. Many of the questions generated by our initial post related to volume and activity assumptions, and we expect that this model will enable readers to review their own activity distribution and see the resulting impact estimate.

Download the Interactive Model

Conclusion

We consider the substantial debate around our original post a welcome outcome. We achieved our goal of encouraging discussion of the possible impacts of the SEC's proposed Transaction Fee Pilot. We hope that future commentators will attempt to include substantive and quantifiable data in support of their stance, as we have tried to do here. We welcome feedback and continue to believe that the proposal will result in increased costs to investors due to wider spreads. We agree with the general view of many who have commented that no one can precisely predict the future and that several assumptions are required to model the possible results of the pilot. In our view, we believe that costs for end investors to take liquidity will rise.

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May 25, 2018

Transaction Fee Pilot: An Impact Assessment

After much anticipation, the SEC has proposed a “Transaction Fee Pilot,” which would impose additional price controls on exchange access fees and rebates. As proposed, all equity exchanges (but not alternative trading systems (“ATS”) or other over-the-counter (“OTC”) trading venues) would be required to reduce access fees and/or reduce or eliminate rebates on 3,000 stocks for a period of up to two years. While some commentators equate a lower access fee with a better trade price, we have seen little analysis of the Proposal’s actual cost or benefit to investors. To fill this void, we are presenting two approaches that attempt to roughly quantify the Proposal’s potential impact on investors.

The analysis involves numerous assumptions, and we welcome any and all feedback. First, we assume that a reduction in access fees will result in a reduction in rebates. Second, we assume that with a lower rebate, spreads will widen.

The widening of spreads is generally accepted as a cost to investors because of the related increased transactions costs, particularly for agency liquidity-seeking order flow. Importantly, a wider spread will result in higher trading costs for this type of flow regardless of whether the order trades on an exchange or an off-exchange venue that derives prices from exchanges.

As demonstrated in the chart below, we find that as access fees decline, the cost to investors will increase by at least $1bn, increasing to nearly $4bn should such changes be applied to the entire market. While all investors would absorb the costs of wider spreads, the benefits from the proposed reduction in access fees would accrue primarily to sell-side brokers and proprietary traders

Top-Down Assessment of Fee Pilot Proposal

We first estimated costs using a top-down approach, which applies the proposed Fee Pilot changes to current average market-wide statistics. We assumed that rebates on trades in securities in each proposed Trade Groups would fall by the same amount as access fees would fall. For Group 3 (the “no-rebate” group) we assumed that market forces would reduce the access fee to $0.0002. We expect Group 3 to settle at a rate below Group 2’s $0.0005 cap as there is no rebate allowed on the other side of the trade; we also note that flat-fee venues which charge both sides of a trade today are generally priced between $0.0000 and $0.0003. As shown in the following table, this yields a blended access fee reduction of $0.00082 per share.


In order to find the expected new average spread, we identified the following calculation to apply the impact of the rebate reduction to consolidated spreads:

New Consolidated Spread = Current Consolidated Spread + Rebate Reduction * 2

The Current Consolidated Spread is the median market-wide bid-ask spread, and the Rebate Reduction is the $0.00082 blended average fee change. The Rebate Reduction is multiplied by 2 as we anticipate market makers will adjust both their bids and offers to account for the new pricing structure. This calculation results in a 1.1% increase in average spreads, to 28.1 basis points (bps).

As noted by the SEC in its proposal, brokers that are subject to exchange fees and rebates generally do not pass those costs/credits to their customer. We therefore assess principal and agency flow differently as principal flow is impacted by both explicit exchange fees and spread costs, while the ultimate customer behind an agency order incurs spread costs but usually does not pay explicit exchange fees. We also assume that the principal flow benefit from the fee reduction applies to maker/taker activity, but the higher spread cost applies to all principal and agency flow in the market.

Our cost to investors is found by calculating the cost to cross the new, wider spread; our cost to principal traders is found by calculating the cost to cross the new, wider spread netted against the benefit from lower access fees. Spread costs here are considered to be ½ the quoted spread for liquidity-taking flow, per standard transaction cost analysis measurement of performance against arrival price.

Our results show, on net, an estimated cost of $1.08bn to the industry, of which $721MM would be incurred by agency flow.

We believe that this result is somewhat conservative, primarily due to the assumptions of 1) no change in quote size despite the wider spread, 2) no shift in venue market share, and 3) applying the NYSE and NYSE Arca principal/agency ratio despite the fact that the market-wide agency taking share is much higher. This second assumption likely limits our estimated cost substantially, as a quick glance at major retail brokerage firms’ 606 reports indicates that nearly all held market orders are executed OTC. These conservative assumptions are offset by the exclusion of taker/maker (i.e., rebate to take and fee to add) venues’ impact on principal flow, the assumption that all agency flow does not pay explicit exchange fees, and by not assigning any benefit to liquidity-providing agency flow from a wider spread. We also assume a representative amount of volume in each of the pilot groups, which could be incorrect in either direction.

The below chart shows the distribution of the spread cost increase and the access fee decrease for the proposal’s three groups compared to the current market average. This again assumes an even distribution of liquidity characteristics across stocks. The access fee paid by brokers is small relative to spread costs in today’s world, and could fall as much as 93% for Group 3 stocks.

Bottom-Up Assessment of Rebate Elimination

We also estimated changes from eliminating rebates across the market as a whole. We used a “bottom-up” approach that looked at the difference in quoted spreads for each stock trading on Cboe EDGX Exchange, Inc. (“EDGX”, which is a maker-taker venue) and Cboe EDGA Exchange, Inc. (“EDGA,” which is a flat-fee venue). EDGA and EDGX are very similar in that neither is a listing market, and both operate on the same technology in the same location. Accordingly, any differences in spreads between the two markets could be due to the different pricing models available on each exchange.

In aggregate, the EDGA average spread is roughly twice that of EDGX, but there is substantial variation by symbol. To account for this variation, we applied the difference in spread to the current consolidated spread for each symbol, capped that difference to 25%, and then further limited the maximum spread difference to the ratio of the primary exchange spread to the EDGX spread (these limitations were to account for the variance between venues and the fact that we are modeling a world with narrower differences in exchange pricing). The chart below shows the differences in average quoted spread between these two venues, the primary market and the consolidated quote.

We believe that eliminating rebates would widen spreads, as demonstrated by EDGA’s wider spreads relative to EDGX. Accordingly, applying this wider spread to current trading activity of all NMS securities on all equity exchanges would result in an impact of roughly $3.8bn per year, once again born largely by agency liquidity-taking flow. We also checked this result by setting all stocks to group 3 in the first model; our result in that case was a similar $3.7bn impact.

To recap, we have used two different models to assess the impact of reduced fees and rebates on liquidity-seeking flow. We find a $1bn cost from the proposed Transaction Fee Pilot, rising to $3.8bn should such limitations be applied across the market. As stated, any such analysis requires numerous assumptions, and we encourage input from market participants on how we could further refine this assessment of investor cost.

- Kevin Tyrrell and Steven Poser


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