Primer on Market Structure III: Market Fragmentation
Best Execution, Payment for Order Flow, Internalization, Preferencing, Crossing, Dark Pools, Fragmentation, The Competition Among Markets vs Among Orders
In the previous post we looked at some ways that market participants trade and deduced based on the market impact of particular actions what reasonable regulation may look like / what they need to weigh. However, most new market microstructure regulation aim at consolidating markets rather than preventing certain abuses (the most common ones are already banned). This leads to the natural question of why markets are fragmented in the first place. The main takeaway is that market fragmentation is driven by the fact that different participants aim to solve different trading problems, and that there is an inherent tenson between the competition among orders and the competition among markets. Most of the analysis in this series are derived from the textbook Trading & Exchanges by Larry Harris.
Best Execution (Source: Bloomberg Law)
Brokers have a responsibility to provide best execution for their clients i.e. to execute orders quicky at the best available prices. However, most execution traders are aware that sourcing liquidity can sometimes taking time, and as such there is an inherent tension between the price that an order can be executed at versus how quickly it can be executed. FINRA Rule 5310(a)(1) requires broker-dealers to “use reasonable diligence to ascertain the best market for the subject security and buy or sell in such market so that the resultant price to the customer is as favorable as possible under prevailing market conditions.”
The NBBO (National Best Bid and Offer), part of the National Market System (Reg NMS), is used to determine best execution. The NBBO displays the most favorable bid and ask prices for NYSE and Nasdaq-listed securities. When brokers secure prices better than the NBBO for investors, it's called "price improvement"(Reg NMS Rule 600(b)(92)). However, it must be noted that the price assigned to the customer by the broker can be any price at or between the NBBO displayed by the SIP (Securities Information Processor, i.e. the consolidated feed) during a 1 second interval (Reg NMS Rule 600(b)(92)) for market orders.
Payment for Order Flow (Source: Bloomberg Law)
Payment for Order Flow (PFOF) is a practice where a broker receives compensation from a third party, typically a market maker, for directing customer orders to that specific market maker for execution; this is also called preferencing. This compensation can be in the form of monetary payments or other benefits. The practice was pioneered in the 1990s by Bernard Madoff, who at the time had a stellar reputation but was later convicted of financial crimes. If the broker is also a broker-dealer and fills the customer’s order by themselves, this is called internalizing. While FINRA allows brokers to internalize and preference, these arrangements must not compromise the broker's obligation to achieve best execution (FINRA Rule 5310).
One can easily note that PFOF creates a significant conflict of interest for brokers. While brokers have a duty to provide best execution for their clients' trades, PFOF arrangements give them a financial incentive to route orders to specific market makers who pay for this order flow. This can lead brokers to prioritize their own profits over their clients' best interests. The conflict arises because the market maker offering the highest payment may not necessarily provide the best execution or price for the client's trade. Indeed, it may be easier for the market maker to pay the broker if they choose to not to give the best price improvement. The mere fact that they are paying for the order flow suggests, but does not imply, that they could do better. Brokers are supposed to analyze the market maker’s fills and demand more price improvement, but this may result in market makers paying less for the orders.
The SEC has implemented regulations to address concerns surrounding PFOF. The current regulatory framework aim to increase transparency and protect retail investors by mandating specific disclosure requirements for brokers and market centers. In 2005, the SEC introduced Reg-NMS, which, among other things:
Requires market centers, including market makers, to publish monthly reports on their trade execution quality (Rule 605).
Mandates broker-dealers to provide quarterly reports on their order routing practices (Rule 606(a))
Obliges broker-dealers to disclose routing practices and relationships with execution venues upon customer request (Rule 606(b)).
Stipulates broker-dealers to inform new customers about any PFOF arrangements and the potential for price improvement beyond the NBBO (Rule 607).
These regulations collectively aim to ensure that substantial information is available to market participants regarding order routing practices, PFOF arrangements, and execution quality. This transparency is supposed to enable investors to assess whether PFOF potentially impacts the quality of order executions and helps them make informed decisions about their brokers and trading strategies.
Liquidity Improvement with Internalization and Preferencing
Matt Levine from Bloomberg has written in favor of PFOF in general, and Robinhood Markets in particular. The main argument given is that by separating informed order flow from noisy (i.e. retail) order flow, market makers are able to produce price improvement since they face much less adverse selection and are more likely to get balanced two-way flow. To quote Mr. Levine directly:
[The] risk of being a market maker on the public stock exchanges: Sometimes you sell 100 shares to a small retail investor and it’s random noise; other times you sell 100 shares to Fidelity and you get run over. But if a market maker can guarantee that it will only interact with retail customers—if it can filter out big orders from institutional investors—then its risk of adverse selection goes way down. The way the market maker does this is by paying retail brokers to send it their order flow, and promising those brokers that it will execute their orders better than the public markets would. It can offer a tighter spread than the public markets—and have money left over to pay the retail brokers—because it doesn’t have to worry about adverse selection. If the retail broker is, say, one designed to let young people day-trade for free on their phones, then those orders are probably particularly valuable, because they are probably particularly random.
He also dismisses the most common objection against PFOF:
[I]t is bad for investors whose orders aren’t sold to market makers, the institutional investors who instead trade on public stock exchanges. Payment for order flow fragments the markets, takes retail order flow away from the public stock exchanges, widens out spreads on those exchanges, and, by segregating retail and institutional orders, makes institutional execution worse. This objection is probably true! If you’re a hedge-fund manager, you should dislike payment for order flow, because it makes public markets worse for you.
[B]y selling its customers’ orders to market makers, Robinhood is actually stealing from two sets of “the rich”: Rich market makers [who] are paying it directly for the orders, while rich hedge-fund managers are getting worse execution on public stock exchanges so that Robinhood customers can get better executions off those exchanges. Big institutions are paying to subsidize free trades for Robinhood’s customers. It feels pretty Robin-Hood-y!
From this initial analysis, we can see that there is again a trade-off between encouraging price efficiency (by making it cheaper for informed traders to trade) and providing liquidity to utility traders (which is better done by separating order flow). It is difficult for us to guess how much the economy is hart by less price efficiency, but the savings to retail can be quantified quite easily. For example, Robinhood’s Execution Quality page tells us that they save customers around $2.77 per 100 shares on average and that execution typically happens within the middle 40% of NBBO.
It is important to note that the important question here isn’t whether PFOF improves liquidity for retail (it does), but rather if there exists some set of regulations where retail and other utility traders can benefit from even more price improvement. In addition, whether the cost of market fragmentation and reduced price efficiency is worth the extra liquidity provided to retail.
To date, to the best of my knowledge, the critics of PFOF have not relied on analysis of long-term industry-wide data. Instead, they have made arguments based on how retail orders can be exploited, a distrust of financial institutions to avoid conflicts of interests, and theoretical arguments. However, this does not mean that their case doesn’t have merit. Indeed, financial institutions do not have a great historical record of self-regulation, and arguments against PFOF shed light on how regulation can improve market structure and deliver additional value to its natural participants.
Anticompetitive Aspects of Internalization and Preferencing
Dealers and other limit order traders are more likely to offer aggressive prices when their quotes attract order flow. Internalizing and preferencing by brokers therefore divert flow again from aggressive leaders and reduces the incentives to quote aggressively. As such, it widens bid-ask spread on central exchanges beyond the effects of increased adverse selection due to a higher ratio of informed traders. This effect distort the measurement of price improvement which compares execution quality for PFOF against centralized exchange NBBO.
This practice is seen not only on financial markets, but also on consumer markets as well. For example, travel portals and retailers would often offer to meet or beat any advertised price that the consumer can find (NBBO, if you will). While this initially appears that they are competing aggressively on pricing, the actual effects of the practice is anticompetitive in the long term because they lower incentives for others to post aggressive prices, since now retailers who offer the lowest prices will not get as much order flow as they would have if price matching was banned. Consumers would, in the long run, on aggregate, benefit more if retailers attracted orders by simply offering the lowest prices instead of matching the lowest prices.
The above effect mainly applies to market orders captured by PFOF, but limit orders are also harmed. When retail gives limit orders to their brokers, the broker can send it to the central market which often offer standing offers liquidity fees (more on the maker-taker model later). The problem is that these limit orders face serious adverse selection. They are unlikely to trade against market or marketable orders from other retail since those will be captured by a dealer engaged win PFOF; by definition they are then more likely to trade against informed flow. Put another way, limit orders sent by retail are less likely to execute if prices are going to move away from them and more likely to execute when prices are moving against them.
Market makers are supposed to compete with other limit order traders to provide liquidity; however, by engaging in preferencing and internalization, brokers shift the balance of power in this competition towards the market makers, who pay them for the privilege. It can be argued that segmentation gives a net advantage to liquidity providers which increases net trading costs for all liquidity takers even though some small retail orders may see significant price improvement.
Theoretical Equilibrium vs Reality
Brokers internalize and preference order flows to segment uninformed order flow. PFOF ensures that in perfectly competitive markets, dealers do not obtain excess profits from trading against those order flow. Benefits such as 0 commission and stock & cash bonuses that brokers must offer retail to obtain their orders in the first place ensure that brokers in a perfectly competitive market do not obtain excess profits from internalization and preferencing. Therefore, when competition is perfect, low commissions & cash incentives trade off against execution quality and net trading costs do not depend on best execution standards.
However, in no market is competition perfect. It would be unfair to call high-frequency market-making in equities / equity derivatives a monopoly, but it is an oligopoly of around half a dozen firms that handle a vast majority of retail orders. In fact, one of them proudly advertise the fact that they handle ~35% of US retail equity volume. High-frequency trading and sophisticated market-making carry both high fixed-costs (think regulatory compliance) and recurring labor costs (traders, SWEs, and researchers at major trading firms are all fairly well-paid).
The high barrier to entry, combined with winner-take-all effects (if you are a nanosecond faster you don’t just get some of the best trades, you get ALL of the best trades) makes it easy for the industry to settle into an oligopoly over time. Most of the firms who embraced HFT early in the electronification of the markets are the major players today. Because superior technology lead directly competitive advantages that captures all excess profit in a trade, barriers to entry become insurmountable over time as companies invest ever faster exchange connections and market data feeds.
The fact that today’s major market-makers came of age around the same time as the tech giants hints at their commonality. Companies like Amazon, Apple, Google, Facebook (Meta), and Microsoft have all developed platforms that facilitate transactions and interactions between different user groups i.e. they are marketplaces. By acting as intermediaries, they capture value from the transactions and interactions occurring on their platforms. This is very similar to how market makers as a collective provide the marketplace for securities. In addition, their fundamental models for growth and competitive advantage are also very similar; in particular, large amounts of data is harvested to build better models, which provides a better service, increases their market share, which allows even more data to be harvested. Your edge compounds. Competitors die. As Peter Thiel says: Competition is for losers.
We can expect dealers and brokers with market power to exploit that power and obtain excess profits from public traders, with the degree to which they can do that depending on how competitive those markets are. The level of competition is determined not only by the number and sophistication of competitors, but also by how price sensitive consumers are and to what extent consumers are able to measure best execution. How many people who has a brokerage account that you know of actually looks at trade reports? How many will request data from their brokers to run in a Jupyter Notebook? How many people even care?
Dark Pools & Order Crossing
Dark pools and order crossing are alternative trading systems that operate outside traditional public exchanges, providing a mechanism for large institutional investors to execute trades without revealing their intentions to the broader market. These systems work by matching buy and sell orders for securities directly within a private exchange, typically at prices based on the midpoint of the public market's bid-ask spread. For example, if two pension funds wanted to trade a large block of shares with each other, they could submit their orders to a dark pool where they would be matched at market mid and executed anonymously.
This approach offers several benefits to clients, including reduced market impact for large trades, potential price improvements, lower trading costs, and anonymity. However, it also comes with drawbacks such as a lack of transparency, potential conflicts of interest (dark pools are often run by broker-dealers), fragmented liquidity, and regulatory concerns. While dark pools and order crossing can significantly benefit institutional investors by allowing them to execute large trades efficiently, the opacity of these systems has raised questions about market fairness and efficiency.
Fragmentation & The Competition Among Markets vs Among Orders
At the core of market fragmentation is the diverse nature of market participants. Retail investors seek liquidity and ease of execution. Institutional investors need to execute large trades with minimal market impact. Broker-dealers seek to profit from uninformed flow while avoiding informed flow. To address these varied needs, broker-dealers have developed segmented order flow systems, routing different types of orders to different venues. This segmentation, while beneficial for certain uninformed traders, creates challenges for informed traders who rely on price efficiency to capitalize on their information advantage. As order flow is divided among various alternative trading venues it becomes more difficult for informed traders to effectively execute their strategies. This fragmentation can potentially reduce overall market efficiency, as the price discovery process becomes less centralized and transparent.
The proliferation of alternative trading venues can be viewed as a form of competition among markets, offering varied execution options to different trader types. However, this competition among markets inherently conflicts with the competition among orders that is crucial for maintaining efficient central markets. When orders are dispersed across multiple venues, the central market's ability to aggregate information and determine the most accurate price is diminished.
This situation highlights the fundamental tension between market efficiency and liquidity. While alternative trading venues can enhance liquidity for certain trader segments, they may do so at the cost of overall market efficiency. The central market is most price efficient when there is robust competition among orders, allowing for the most accurate price discovery. The competition among markets undermine this order-level competition.
Moreover, note that the efficiency and liquidity of wholesale markets is very much dependent on central markets since the dealer’s only obligation is to offer price improve to NBBO, which widens as a result of internalization and preferencing. Similarly, dark pool orders are often pegged relative to the prices displayed by central markets; their very existence is the product of the positive externality of informative pricing provided by central markets. Over the long run, it is not at all clear that high levels of market fragmentation will produce net benefits to the economy. In the proposal of Regulation NMS, the SEC describes this concern:
[The] competition among multiple markets trading the same stocks can detract from the most vigorous competition among orders in an individual stock, thereby impeding efficient price discovery for orders of all sizes. The importance of competition among orders has long been recognized. Indeed, when Congress mandated the establishment of an NMS, it well stated this basic principle: “Investors must be assured that they are participants in a system which maximizes the opportunities for the most willing seller to meet the most willing buyer.” To the extent that competition among orders is lessened, the quality of price discovery for all sizes of orders can be compromised. Impaired price discovery could cause market prices to deviate from fundamental values, reduce market depth and liquidity, and create excessive short-term volatility that is harmful to long-term investors and listed companies. More broadly, when market prices do not reflect fundamental values, resources will be misallocated within the economy and economic efficiency—as well as market efficiency—will be impaired.
Recap
Economies of scale have made entrenched market makers more efficient, and almost impossible for new entrants to enter and compete aggressively in the wholesale order flow market. In addition, the more convoluted a market system is, the less efficient we can expect it to be in reality, outside of the economist’s models. By taking orders away from common market mechanisms, internalization, preferencing, and internal order cross can make it more difficult for natural buyers and sellers to find each other; central markets are also weakened when incentive to quote aggressively is reduced. The benefits to small retail orders and very large block orders can be substantial, but this comes at a cost to the combination of all liquidity takers.
Food for Thought
What would the impact be if the SEC imposed a cap on payment for order flow?
What are some ways that broker-dealers can take advantage of block orders sitting in their dark pools? How difficult would it be for regulators to discover any potential abuses?
Whose interests should the financial markets serve?
Next Up
Efforts at consolidation in financial markets have emerged as a response to the fragmentation caused by the proliferation of alternative trading venues. These consolidation initiatives aim to address the challenges of market fragmentation while preserving the benefits of competition and specialized trading venues. We will explore these efforts at consolidation and associated mechanisms made possible by it.
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