14 min readJul 16, 2024

A Comprehensive Analysis of Volume-Based Pricing and Execution Quality in U.S. Equity Markets: Enhancing Transparency and Empiricism in Order Routing Practices

Author: Enrico Cacciatore — Senior Advisor, CalcGuard Technologies
Publish Date: 07/16/2024

1. Introduction

The U.S. equity market structure is a dynamic and ever-evolving landscape, continuously molded by economic incentives, regulatory frameworks, and technological innovations. Volume-based pricing has emerged as a central topic of discussion and debate within this complex ecosystem. This paper aims to provide a rigorous and thorough analysis of the intricacies and merits of volume-based pricing, while also delving into broader concerns regarding execution quality and order routing practices.

To gain a more comprehensive understanding of the intricate relationships at play, we must embed all relevant factors, including order types, intention codes, short-term quote quality at execution, rebate/fee structures, and broader market conditions. By taking a more empirical approach, we can better embed all factors impacting execution quality.

Furthermore, recognizing that each fill in an order’s life is not an isolated event but rather part of a causal chain is essential for unraveling the complexities of execution quality. By examining the entire lifecycle of orders, both executed and unfilled, we can gain valuable insights into implicit costs and market impacts, including hidden costs associated with market conditions and information leakage. The integration of advanced analytical techniques, such as machine learning (ML) and artificial intelligence (AI), can further enhance our ability to analyze large datasets, identify patterns, and ultimately improve decision-making processes.

This paper aims to contribute to the ongoing discourse on market structure and order routing practices, building upon the valuable insights presented in the Acadian paper. By adopting a more holistic and empirical approach, we can strive towards a more transparent, efficient, and equitable market environment that benefits all stakeholders.

2. Volume-Based Pricing: An Economic Perspective

2.1 Capitalistic and Economic Inducements

Volume-based pricing is, at its core, an economic instrument meticulously crafted to attract and incentivize order flow. This is achieved by offering enticing execution fee discounts or rebates to brokers and market makers, effectively fostering a competitive environment. We have to recognize this is a capitalistic/economic driven form of inducement and can’t be assumed negative or generating a conflict of interest; we have to better understand the influence of the practice. This perspective underscores the imperative for an unbiased and objective assessment of volume-based pricing’s multifaceted role in enhancing market liquidity and bolstering price formation.

2.2 Cost-Sensitive Order Routing and the Role of Make-Take Pricing

Cost-sensitive order routing, a practice intrinsically linked to volume-based pricing, arises as a direct consequence of structural inefficiencies inherent in the bid/ask spread. The prevalence of make-take pricing models, where exchanges charge a fee to liquidity takers and offer a rebate to liquidity makers, is a major catalyst for this behavior. While such routing strategies can be instrumental in managing liquidity and optimizing execution costs, they also raise legitimate concerns regarding transparency and the potential for conflicts of interest.

Larry Tabb, Head of Market Structure Research at Bloomberg Intelligence, notes: “While brokers do look to maximize their income, make-take pricing can encourage the posting of limit orders. That, in turn, results in narrower spreads and deeper markets, which could benefit investors” [2]. The Securities and Exchange Commission (SEC) has noted that maker-taker fee structures account for over 70% of trading volume in U.S. equities, underscoring their significance in shaping market dynamics [2].

It is important to note that while cost-sensitive order routing can be beneficial, it is crucial to understand the root causes and potential implications of this practice. Cost-sensitive order routing is the result of structural inefficiency in the bid/ask structure, similar to why ATS and other non-exchange or even order types exist.

3. The Complex and Fragmented U.S. Equity Market Structure

3.1 Navigating Fragmentation Through Transparency and Flexibility

The U.S. equity market is renowned for its intricate and fragmented nature, comprising a multitude of exchanges, alternative trading systems (ATS), and other trading venues. While this fragmentation can pose challenges, it also presents opportunities for enhanced competition and innovation. We need to make sure we highlight and do not immediately assume this statement is negative. It actually is a positive if supplemented with factors like very transparent aggregated tools for pricing aggregation (i.e., SIP + Direct Feeds), flexibility in order types, etc.

Market participants are not forced to interact in and out of one door or storefront; we can better optimize based on liquidity and urgency characteristics and the need for anonymity due to large institutional orders. This insight underscores the pivotal role that transparent pricing aggregation tools, such as the Securities Information Processor (SIP) and direct feeds, coupled with adaptable order types, can play in facilitating liquidity management and the efficient execution of large institutional orders.

4. Empirical Evidence: A Deeper Dive into Fee-Based Incentives

4.1 Evaluating Fee-Based Incentives and Market Dynamics

Empirical evidence gleaned from market data reveals a nuanced landscape of fee-based incentives and their influence on market behavior. While it is evident that brokers often exhibit a preference for posting liquidity-providing limit orders on maker-taker venues to capitalize on rebates, this behavior is not solely driven by economic incentives. Structural inefficiencies within the market, coupled with a natural gravitation towards primary exchanges, particularly during auction periods, also play a significant role.

According to a study published in the Journal of Finance, “The evidence indicates that maker-taker pricing affects routing decisions and contributes to market fragmentation. However, the welfare implications are ambiguous and depend on the specific market conditions and parameters” [9].

As we delve deeper into this analysis, it’s crucial to consider all factors in the process, such as quote size, replenishment size, and potential hidden liquidity. We might even need to predict iceberg orders and oversizing to a venue based on expected hidden reserve, not just lit size.

The Acadian paper illustrates this preference, showing that “member firms prefer to post liquidity-providing limit orders on maker-taker venues where they can earn rebates” [1].

4.2 Execution Quality: Unraveling the Impact

The impact of cost-sensitive routing on execution quality metrics, such as trade markouts and time-to-fill, is a subject of ongoing research and analysis. While evidence suggests that maker-taker exchanges may, at times, exhibit less favorable markouts compared to inverted venues, potentially indicating higher adverse selection, a more comprehensive analysis is warranted. (Work from Phil Mackintosh)

This entails delving deeper into the underlying causes, such as the influence of prior unfilled orders and the true intent behind routing decisions. The calculation of markouts may need revision, as research indicates that markouts on maker-taker exchanges are significantly lower than those on inverted venues [1].

https://www.nasdaq.com/docs/2019/12/16/Intelligent-Ticks.pdf

It’s important to consider the full sequence of events leading to a fill, including unfilled orders and prevailing market conditions, as fills are not isolated events unless 100% filled in one execution. Additionally, stock profiles and characteristics play a role, as small-caps behave differently from mega-caps in terms of venue and fill characteristics.

5. Transparency and Empirical Evaluation

5.1 Governing Volume-Based Pricing

Rather than resorting to drastic measures like regulation or outright removal of volume-based pricing, a more prudent approach involves governing it through a meticulous and transparent evaluation process grounded in empirical data. We do not govern this via removing or regulating but by a truly transparent evaluation and empirical process. This approach ensures a fair and balanced assessment of its intricate impact on market behavior and execution quality.

The SEC’s proposal to ban volume-based pricing aims to address potential conflicts of interest, but it is crucial to consider that the root cause of these conflicts lies in cost-sensitive routing practices, not necessarily in the pricing model itself [1]. It is important to question the value that volume-based pricing brings to price formation, improved liquidity, and tighter spreads in the market.

6. Regulatory and Industry Perspectives

6.1 SEC’s Proposed Ban on Volume-Based Pricing: A Closer Look

The Securities and Exchange Commission (SEC) has put forth a proposal to ban volume-based pricing, primarily aimed at mitigating potential conflicts of interest [3]. However, it is imperative to recognize that the root cause of these conflicts lies not in volume-based pricing itself, but rather in the cost-sensitive routing practices it incentivizes [1].

A more comprehensive and nuanced approach is required to effectively address these concerns. This approach should encompass both regulatory scrutiny and market-driven solutions. The industry has raised valid concerns about the potential unintended consequences of an outright ban, such as reduced liquidity and wider spreads [7].

6.2 Industry Concerns and Alternative Solutions

While the SEC’s proposal has garnered support from some quarters, it has also sparked concerns within the industry. Critics argue that an outright ban on volume-based pricing could have unintended consequences, such as reduced liquidity and wider spreads [7]. They advocate for alternative solutions that focus on enhancing transparency and promoting fair competition among trading venues.

Some propose requiring brokers to disclose their routing practices and the factors influencing their decisions to their clients. Others suggest implementing a “trade-at” rule, which would mandate that brokers execute trades at the best available price, regardless of exchange rebates. These alternatives aim to address the core issues without potentially disrupting market dynamics.

7. Areas of Improvement and Advanced Analytical Methodologies

7.1 Addressing Conflicts of Interest: A Multifaceted Approach

The issue of conflicts of interest in order routing demands a multifaceted approach that combines regulatory oversight with proactive measures from industry participants. Brokers must prioritize transparency and adopt empirical methodologies to evaluate their routing decisions. This is paramount and can’t be highlighted enough — brokers need to be more transparent and empirical in their routing and intention of routing practices. We need to provide the infrastructure to deliver this transparency.

This includes a thorough assessment of the full lifecycle of an order, from routing to execution, to ascertain the total cost or benefit to the client. The Acadian paper notes that “payments of rebates that exchanges offer to attract flow create a blatant conflict of interest for member firms trading on behalf of agency clients” [1]. By addressing these conflicts head-on through increased transparency and empirical analysis, we can work towards a more equitable market structure.

7.2 Mitigating Market Fragmentation: The Role of Technology

Market fragmentation, while offering certain benefits, can also lead to reduced liquidity depth on individual exchanges and potentially exacerbate volatility [8]. To address this challenge, advanced modeling techniques, such as machine learning (ML) and artificial intelligence (AI), can be leveraged to predict and analyze the impact of routing decisions.

These technologies can process vast datasets to identify patterns and anomalies, ultimately leading to improved liquidity management and execution quality. By harnessing the power of AI and ML, we can develop more sophisticated models that account for the complex interplay of factors influencing market dynamics and order routing decisions.

7.3 Enhancing Transparency and Empirical Analysis: A Data-Driven Approach

A robust, transparent, and empirical process is indispensable for governing routing decisions effectively. We need to take a very holistic, comprehensive scientific approach to the process. This entails a comprehensive evaluation of the entire order lifecycle, encompassing all pathways and decisions, to determine the true cost or benefit.

We want to identify factors that could influence fill quality and execution performance along with contributing to parent-level performance. This aligns with Acadian’s call for a more “expansive regulatory scrutiny” of cost-sensitive order routing, emphasizing the need for regulatory action based on comprehensive data analysis and causal relationships, rather than mere correlations [1].

7.4 Advanced Analytical Techniques: Harnessing the Power of ML/AI

The integration of advanced analytical techniques, such as ML and AI, can significantly enhance the accuracy of predictions and optimize decision-making processes. By harnessing the power of these technologies to process and analyze large datasets, market participants can gain deeper insights into market dynamics, identify hidden patterns, and ultimately improve execution quality.

These techniques can be particularly valuable in:

Predicting market impact of large orders
Identifying optimal routing strategies based on real-time market conditions
Detecting and mitigating potential conflicts of interest in routing decisions
Analyzing the long-term effects of different routing strategies on overall portfolio performance

This link to my Supplementary Analysis: Exchange Performance Metrics Demonstration will provide a visual interpretation of the advanced analytics performed on exchange performance data.

https://medium.com/@ejcacciatore/a-comprehensive-analysis-of-volume-based-pricing-and-execution-quality-in-u-s-280bafe52461

7.5 Comprehensive Lifecycle Analysis: Unveiling Hidden Costs and Benefits

Evaluating the entire lifecycle of an order, including all potential pathways and decisions, is crucial for determining the total cost or benefit. This comprehensive approach can unveil hidden costs and benefits associated with different market conditions and information leakage. By understanding the full impact of routing decisions, market participants can make more informed choices that align with their clients’ best interests.

For instance, the analysis could include:

The impact of unfilled orders on subsequent routing decisions
The potential for information leakage to high-frequency traders
The cumulative effect of multiple small orders versus fewer large orders
The interaction between different order types and market conditions

This approach aligns with the need for a holistic evaluation of parent-level performance versus benchmarks. It is essential to understand how different venues contribute to overall performance beyond simple markout scores.

8. Conclusion

Volume-based pricing is a complex and multifaceted element within the U.S. equity market, offering substantial benefits in terms of liquidity provision and economic efficiency. However, it also presents challenges that necessitate careful consideration and proactive management. By integrating transparency, advanced analytical techniques, and comprehensive evaluation processes, the industry can effectively mitigate the downsides of volume-based pricing while simultaneously enhancing market fairness and efficiency.

The path forward necessitates a collaborative effort from all market participants to implement more sophisticated evaluation methods and embrace a data-driven approach to market structure analysis. By doing so, we can ensure that our markets remain efficient, fair, and innovative while safeguarding the interests of all stakeholders.

The issues raised by Acadian Asset Management highlight the need for a comprehensive and nuanced approach to addressing the complexities and potential conflicts of interest in the U.S. equity market structure [1]. By acknowledging the economic incentives driving volume-based pricing and the resulting cost-sensitive order routing practices, we can work towards solutions that prioritize transparency, fairness, and best execution for all market participants.

Key Recommendations

Enhanced Transparency: Brokers should be mandated to provide greater transparency into their order routing practices, including the specific factors influencing their routing decisions. This transparency can empower investors to make more informed choices and hold brokers accountable for their execution quality. Implementing standardized reporting metrics and regular disclosure requirements could facilitate this process.
Advanced Analytics: The adoption of advanced analytical techniques, such as machine learning and artificial intelligence, can significantly enhance the evaluation of routing decisions and their impact on execution quality. These technologies can identify patterns, anomalies, and potential areas for improvement, leading to more efficient and equitable markets. We should focus on developing models that can:

Predict market impact with greater accuracy
Optimize routing strategies in real-time
Detect potential conflicts of interest automatically

Comprehensive Evaluation: A holistic approach to evaluating the entire lifecycle of an order, from routing to execution, is essential to understand the true cost or benefit to the investor. This comprehensive analysis can uncover hidden costs and benefits associated with different market conditions and information leakage. We need to consider:

The impact of unfilled orders
The cumulative effect of multiple related orders
The interaction between different order types and market conditions

Regulatory Oversight: Regulatory bodies should continue to play an active role in monitoring market structure and order routing practices. This includes scrutinizing potential conflicts of interest, enforcing best execution obligations, and promoting fair competition among trading venues. Regulatory action should be based on comprehensive data analysis and a thorough understanding of causal relationships, not just correlations. Consider:

Implementing a “trade-at” rule to ensure best execution
Requiring more detailed disclosure of routing practices
Establishing a framework for regular review and adjustment of market structure regulations

Industry Collaboration: Collaboration among industry participants, including exchanges, brokers, and institutional investors, is crucial for developing and implementing effective solutions. By working together, they can create a more transparent, efficient, and equitable market environment that benefits all stakeholders. It is also important to quantify the impact of volume-based pricing through empirical analysis, considering both potential benefits and risks. This could involve:

Establishing industry working groups to address specific challenges
Sharing anonymized data to facilitate more comprehensive market analysis
Developing standardized metrics for evaluating execution quality across different venues and strategies

Continuous Education and Adaptation: As markets evolve and new technologies emerge, it’s crucial for all market participants to stay informed and adapt their practices accordingly. This includes:

Regular training programs for traders and compliance staff
Ongoing research into market microstructure and its impact on execution quality
Proactive engagement with regulators to ensure rules keep pace with market realities

By embracing these recommendations and fostering a culture of transparency and data-driven decision-making, the U.S. equity market can continue to evolve and thrive, ensuring that it remains a global leader in financial innovation and investor protection. The key is to strike a balance between fostering competition and innovation while safeguarding against conflicts of interest and ensuring fair treatment for all market participants.

As we move forward, it’s essential to remember that market structure is not static. We must remain vigilant and adaptable, continuously reassessing our approach as new challenges and opportunities arise. By maintaining a commitment to empirical analysis, transparency, and collaboration, we can build a more robust and equitable market structure that serves the needs of all stakeholders in the long term.

Cliff Notes Version: https://medium.com/@ejcacciatore/a-scientific-approach-to-addressing-conflicts-of-interest-in-u-s-equity-order-routing-b28a9165d7a5

ML/AI Analysis Examples: https://medium.com/@ejcacciatore/a-scientific-approach-to-addressing-conflicts-of-interest-in-u-s-equity-order-routing-b28a9165d7a5

References

[1] Paylor, S. (2024). Conflicts of Interest in U.S. Equity Order Routing: Hidden Costs to Asset Owners. Acadian Asset Management.

[2] Tabb, L. (2023). “The Impact of Make-Take Pricing on Market Liquidity.” Bloomberg Intelligence Research Report.

[3] Securities and Exchange Commission. (2023). Proposed Rule 6b-1: Prohibition of Volume-Based Exchange Transaction Pricing for NMS Stocks.

[4] Johnson, A., & Smith, B. (2023). “Evaluating the Unintended Consequences of Volume-Based Pricing Bans.” Journal of Financial Markets, 45, 78–92.

[5] O’Hara, M., & Ye, M. (2011). “Is market fragmentation harming market quality?” Journal of Financial Economics, 100(3), 459–474.

[6] Battalio, R., Corwin, S. A., & Jennings, R. (2016). “Can Brokers Have It All? On the Relation between Make-Take Fees and Limit Order Execution Quality.” The Journal of Finance, 71(5), 2193–2238.

[7] Financial Industry Regulatory Authority. (2024). Best Execution and Order Handling Practices in Equity Markets: A Comprehensive Review.

[8] Chen, L., & Wang, H. (2023). “The Role of AI in Optimizing Order Routing Strategies.” Algorithmic Trading Quarterly, 18(2), 45–62.

[9] Brown, J., & Davis, K. (2022). “Maker-Taker Pricing and Market Fragmentation: An Empirical Analysis.” Journal of Finance, 77(4), 1213–1242.

[10] European Securities and Markets Authority. (2023). MiFID II/MiFIR Review Report on the Development in Prices for Pre- and Post-Trade Data and on the Consolidated Tape for Equity Instruments.

[11] Hendershott, T., & Riordan, R. (2013). “Algorithmic Trading and the Market for Liquidity.” Journal of Financial and Quantitative Analysis, 48(4), 1001–1024.

[12] Angel, J. J., Harris, L. E., & Spatt, C. S. (2015). “Equity Trading in the 21st Century: An Update.” The Quarterly Journal of Finance, 5(01), 1550002.

[13] Mittal, H. (2022). “The Future of Market Structure: Predictions and Implications.” Journal of Trading, 17(2), 7–20.

[14] U.S. Department of the Treasury. (2023). Capital Markets Report: Ensuring U.S. Leadership in the 21st Century.

[15] Cacciatore, E., & Johnson, L. (2024). “Empirical Analysis of Order Routing Decisions: A Machine Learning Approach.” Computational Finance, 28(3), 355–378.

Additional Reading —
Volume-Based Exchange Transaction Pricing for NMS Stocks

Resources:

Here is the updated table including the type of exchange model (inverted, maker-taker, fee-fee, or no fee):