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Betterment’s trading execution methodology

Enhancing execution quality through managed trading

By Betterment Editors

Published Nov. 03, 2025

Betterment’s trading execution methodology Nov 3, 2025 3:55:00 PM Enhancing execution quality through managed trading Betterment already manages rebalancing and tax optimization at scale—but there’s another layer of value working behind the scenes: execution. This paper focuses on how Betterment improves trade execution through intelligent design and infrastructure. Our system doesn’t just serve one segment of users; it applies equally across the platform, enabling everyone to tap into scalable benefits that were once reserved for institutions. One key aspect is our use of marketable limit orders—orders placed near or slightly better than the current market price so they can execute immediately. This type of order is designed to strike a balance between speed and price control: it seeks a fast execution while placing a guardrail on how far the price can drift. For clients, this means greater protection during periods of market volatility—helping ensure that trades don’t fill at prices significantly worse than expected. Another foundational element is our use of an omnibus trading structure. Rather than executing each individual order separately, Betterment aggregates client trades allowing us to batch and route them more efficiently. This method helps us access deeper liquidity and potentially reduce overall execution costs. Through features like scheduled trade windows, omnibus aggregation, and a design that favors round-lot execution, Betterment helps minimize structural trading disadvantages, reduce exposure to adverse selection, and increase the potential for improved pricing. These execution benefits compound with scale and are embedded directly into the trading experience. The result is greater fairness, efficiency, and cost-effectiveness for every investor on the platform. The challenge in retail execution Retail trading has evolved significantly in recent years, fueled by technological innovation and increased market accessibility. However, key structural disadvantages persist for individual investors, especially when it comes to small, odd-lot orders and immediate execution strategies. Betterment’s managed execution framework—aggregating and scheduling trades throughout the day—offers a powerful and scalable alternative designed to reduce costs, mitigate execution risk, and better align with the realities of market structure. While trades are scheduled into structured windows, they are executed multiple times during the trading day to balance timeliness with the opportunity for aggregations. Betterment does not net opposing orders; each trade is routed externally to our clearing partner. Market structure and the importance of round lots In equity markets, trade size plays a critical role in determining execution quality. A round lot—currently defined as 100 shares for the majority of tickers—is the standard unit recognized by exchanges and market makers. These trades are included in the National Best Bid and Offer (NBBO), prioritized in routing decisions, and eligible for execution in institutional venues. Even mixed-lot orders that include at least one round lot (e.g., 105 shares) benefit from this visibility, often improving pricing for the entire trade. In contrast, odd lots—any order smaller than a round lot—are excluded from the NBBO and typically experience lower priority, reduced transparency, and worse pricing. These orders dominate retail investor flows and often result in less favorable execution. Legal scholar Robert P. Bartlett III analyzed more than 3 billion U.S. equity trades in his 2021 paper and found that odd-lot orders received roughly 10% less price improvement than round lots. This is due to reduced visibility, exclusion from public quotes, and lower priority by execution venues. Trades of 99 shares were particularly disadvantaged compared to trades of 100, even when both were placed simultaneously. High-volume stocks like Amazon (AMZN) illustrated this disparity clearly—Bartlett estimated that over 30% of odd-lot trades in AMZN could have received better pricing if executed as round lots. Betterment’s managed trading approach is designed to help mitigate these penalties by systematically aggregating client flows to reach round-lot thresholds, increasing the likelihood of more favorable outcomes. Quantifying the impact: price discrepancies between lot sizes A core feature of Betterment’s execution strategy is aggregating client orders to cross the round-lot threshold wherever possible. This is not just a preference; it is a response to well-documented execution disadvantages that odd-lot orders face. To illustrate what that kind of pricing difference could mean in dollar terms, consider VTI, a highly liquid security frequently traded by Betterment clients. We selected VTI because it shares characteristics with AMZN—both are heavily traded by retail investors, benefit from high liquidity, and are broadly popular. As of May 2025, VTI trades at approximately $280 per share. If an odd-lot trade receives even just 2 basis points worse pricing than a round lot, this translates to a cost penalty of approximately $0.14 per share for odd-lot executions. For a 15-share odd-lot trade: this means a $2.10 higher cost. For someone investing $5k/month, this means roughly $30 a year in higher costs. Over a 30-year period, this could equate to more than $3,400 in missed gains, assuming 8% yearly growth. The pricing examples presented in this paper are based on internally derived simulations that reflect market behavior consistent with the cited peer-reviewed research. These examples are intended for illustrative purposes only, are not meant to communicate potential performance of any investment strategy, and are not predictive of execution outcomes for any individual trade. This pricing inefficiency compounds quickly and has significant implications when managing client assets at scale. Betterment’s execution engine is designed to help reduce this cost by structurally creating opportunities to aggregate orders into round lots. In line with our regulatory obligations, we aim to achieve best execution—a regulatory standard that requires seeking the most favorable terms reasonably available under prevailing market conditions. This includes evaluating factors such as price, speed, likelihood of execution and settlement, and overall cost. Betterment does not delay trades to form round lots, but it uses a system of time-based trade windows and an omnibus aggregation strategy to opportunistically cross the round-lot threshold when client order flow naturally aligns. This allows us to systematically access the more favorable pricing conditions typically associated with round-lot trades—potentially reducing cost and improving execution outcomes for clients. While our model is designed to improve execution quality in the aggregate, individual trade outcomes may vary depending on market volatility, order size, and venue-specific factors. Trade windows as a mechanism for better execution Most retail brokers execute trades continuously, immediately passing orders to the market. While this appears fast and transparent, it exposes clients to harmful microstructure dynamics. High-frequency traders (HFTs), for example, exploit real-time signals to capture spread value, often at the expense of slower retail flows. Betterment mitigates this by batching trades into scheduled trade windows. These windows operate throughout the day and function similarly to frequent call auctions—a concept studied by Budish, Cramton, and Shim (2015). Their research shows that batched execution reduces the arms race in trading latency, promotes fairness, and narrows spreads. Though Betterment does not run formal batch auctions, our windows are intended to serve a similar purpose: reducing predictability, concealing intent, and improving average execution. This design also lowers market impact by consolidating demand. Liquidity providers can see larger, more regular flows instead of a noisy, fragmented stream. A single larger order is more likely to attract competitive pricing because it signals meaningful interest and is easier for liquidity providers to match against existing supply. For example, multiple clients buying SPY over the same trade window are combined into one order, reducing slippage—the difference between the expected price and the actual execution price—and improving fills, or the likelihood that the entire order will be completed promptly at a desirable price. Execution in practice: Betterment’s strategy At Betterment, trades are executed in windows throughout the day. Each window consolidates similar trades—buy or sell, same ticker—into a single order, executed through an omnibus structure. Trades are routed through Apex, our clearing and trading partner, to venues offering a competitive combination of price, liquidity, and fill reliability, with round-lot opportunities prioritized. We work to achieve best execution in all trades routed through this process. This structure introduces flexibility without sacrificing fairness. Betterment does not delay execution for the sake of creating a round lot, but we design the system to allow aggregation when practical. If immediacy is necessary—such as at day-end—we will execute whatever lots are available.1 We also monitor managed accounts for rebalancing and tax-loss harvesting (TLH) opportunities. When Betterment’s trading algorithm evaluates client accounts for tax loss harvesting and rebalancing opportunities, it generally prioritizes identifying potential tax loss harvests ahead of potential rebalancing opportunities. This activity also plays a meaningful role in how we strive to optimize outcomes alongside our execution practices. When clients’ orders align, aggregation and scheduling increase the likelihood of a favorable outcome. 1Betterment reserves the right to delay trading under certain circumstances; more information about our trading practices and policies is available in our Form ADV. To support oversight of Betterment's execution quality, Betterment has established a formal Best Execution Committee tasked with oversight of execution quality. This committee performs a regular and rigorous review of trading outcomes, assessing execution quality across market centers using key metrics such as basis point deviation from market price at placement (placement strike), routing behavior, peer comparisons, and arrival price analysis. Evaluations are made across ticker, order size, and timeframes. Aggregation in action: a comparative scenario To further illustrate how aggregation leads to better execution, consider this example where three clients submit small trades around the same time. When routed individually, these odd-lot orders are exposed to the same disadvantages outlined earlier—such as worse pricing due to exclusion from the NBBO. But when aggregated into a single round-lot trade, the order gains visibility and priority, increasing the likelihood of receiving better pricing. Client Orders Without Aggregation With Aggregation Alice: Buy 35 shares Executed at $135.02 = $4,725.70 100 shares executed at $135.00 = $13,500.00 Bob: Buy 40 shares Executed at $135.01 = $5,400.40 Carol: Buy 25 shares Executed at $135.03 = $3,375.75 Total Cost Impact Total: $13,501.85 (varied, higher prices) Total: $13,500.00 (uniform, better pricing) Illustrative purposes only. Prices shown do not reflect actual client execution results. This example reinforces the earlier point about execution quality differences between odd-lot and round-lot trades—such as the estimated 2 basis point disadvantage found in high-volume stocks like VTI. A consolidated 100-share order, like the one shown here, is more likely to attract competitive pricing from liquidity providers because it is easier to match against existing supply and signals meaningful demand. This example illustrates a core insight: retail investors are disadvantaged when fragmented. But when they act collectively—via an automated platform like Betterment—they gain access to efficiencies normally reserved for large institutional traders. Delivering institutional benefits to retail investors Betterment’s model is designed to translate institutional market advantages into a retail context. Institutional desks execute trades strategically—splitting orders, timing placements, and waiting for liquidity. These techniques aren’t usually available to individuals, but Betterment’s platform replicates many of them algorithmically. By aggregating trades to reach round lots, using structured time-based execution, and accessing liquidity intelligently, Betterment customers may benefit from pricing and execution quality similar to what’s typically associated with institutional standards. This parity is especially powerful in volatile or illiquid conditions, where fragmented execution can be costly. Conclusion and client-centric outcomes Managed trading, as implemented by Betterment, is a deliberate, research-driven strategy to overcome the inherent flaws in retail execution. We combine trade scheduling, order aggregation, and a neutral fee structure to deliver meaningful advantages to individual investors. Our model does not guarantee better execution on every trade, but in the aggregate, it enhances pricing, reduces slippage, and levels the playing field. Betterment believes that balancing immediacy and opportunity is key. Betterment may wait to aggregate trades to seek improved execution, which we believe is a rational tradeoff. Betterment clients are not sacrificing control—they’re gaining efficiency. Over time, this system is designed to create small but consistent enhancements in return, aligning with our core mission: helping clients make the most of their money. References Bartlett, R. P. III. (2021). Modernizing Odd Lot Trading. Columbia Business Law Review. Budish, E., Cramton, P., & Shim, J. (2015). The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response. Quarterly Journal of Economics. American Economic Association. Research and publications on equity market structure and trading practices. NYU Stern School of Business. Faculty research on market microstructure and fairness. Australian Centre for Financial Research (ACFR). Market design and equity structure studies.

Betterment already manages rebalancing and tax optimization at scale—but there’s another layer of value working behind the scenes: execution. This paper focuses on how Betterment improves trade execution through intelligent design and infrastructure. Our system doesn’t just serve one segment of users; it applies equally across the platform, enabling everyone to tap into scalable benefits that were once reserved for institutions. One key aspect is our use of marketable limit orders—orders placed near or slightly better than the current market price so they can execute immediately. This type of order is designed to strike a balance between speed and price control: it seeks a fast execution while placing a guardrail on how far the price can drift. For clients, this means greater protection during periods of market volatility—helping ensure that trades don’t fill at prices significantly worse than expected.

Another foundational element is our use of an omnibus trading structure. Rather than executing each individual order separately, Betterment aggregates client trades allowing us to batch and route them more efficiently. This method helps us access deeper liquidity and potentially reduce overall execution costs.

Through features like scheduled trade windows, omnibus aggregation, and a design that favors round-lot execution, Betterment helps minimize structural trading disadvantages, reduce exposure to adverse selection, and increase the potential for improved pricing. These execution benefits compound with scale and are embedded directly into the trading experience. The result is greater fairness, efficiency, and cost-effectiveness for every investor on the platform.

The challenge in retail execution

Retail trading has evolved significantly in recent years, fueled by technological innovation and increased market accessibility. However, key structural disadvantages persist for individual investors, especially when it comes to small, odd-lot orders and immediate execution strategies. Betterment’s managed execution framework—aggregating and scheduling trades throughout the day—offers a powerful and scalable alternative designed to reduce costs, mitigate execution risk, and better align with the realities of market structure. While trades are scheduled into structured windows, they are executed multiple times during the trading day to balance timeliness with the opportunity for aggregations. Betterment does not net opposing orders; each trade is routed externally to our clearing partner.

Market structure and the importance of round lots

In equity markets, trade size plays a critical role in determining execution quality. A round lot—currently defined as 100 shares for the majority of tickers—is the standard unit recognized by exchanges and market makers. These trades are included in the National Best Bid and Offer (NBBO), prioritized in routing decisions, and eligible for execution in institutional venues. Even mixed-lot orders that include at least one round lot (e.g., 105 shares) benefit from this visibility, often improving pricing for the entire trade. In contrast, odd lots—any order smaller than a round lot—are excluded from the NBBO and typically experience lower priority, reduced transparency, and worse pricing. These orders dominate retail investor flows and often result in less favorable execution.

Legal scholar Robert P. Bartlett III analyzed more than 3 billion U.S. equity trades in his 2021 paper and found that odd-lot orders received roughly 10% less price improvement than round lots. This is due to reduced visibility, exclusion from public quotes, and lower priority by execution venues. Trades of 99 shares were particularly disadvantaged compared to trades of 100, even when both were placed simultaneously. High-volume stocks like Amazon (AMZN) illustrated this disparity clearly—Bartlett estimated that over 30% of odd-lot trades in AMZN could have received better pricing if executed as round lots.

Betterment’s managed trading approach is designed to help mitigate these penalties by systematically aggregating client flows to reach round-lot thresholds, increasing the likelihood of more favorable outcomes.

Quantifying the impact: price discrepancies between lot sizes

A core feature of Betterment’s execution strategy is aggregating client orders to cross the round-lot threshold wherever possible. This is not just a preference; it is a response to well-documented execution disadvantages that odd-lot orders face.

To illustrate what that kind of pricing difference could mean in dollar terms, consider VTI, a highly liquid security frequently traded by Betterment clients. We selected VTI because it shares characteristics with AMZN—both are heavily traded by retail investors, benefit from high liquidity, and are broadly popular. As of May 2025, VTI trades at approximately $280 per share. If an odd-lot trade receives even just 2 basis points worse pricing than a round lot, this translates to a cost penalty of approximately $0.14 per share for odd-lot executions.

For a 15-share odd-lot trade: this means a $2.10 higher cost.
For someone investing $5k/month, this means roughly $30 a year in higher costs. Over a 30-year period, this could equate to more than $3,400 in missed gains, assuming 8% yearly growth.

The pricing examples presented in this paper are based on internally derived simulations that reflect market behavior consistent with the cited peer-reviewed research. These examples are intended for illustrative purposes only, are not meant to communicate potential performance of any investment strategy, and are not predictive of execution outcomes for any individual trade.

This pricing inefficiency compounds quickly and has significant implications when managing client assets at scale. Betterment’s execution engine is designed to help reduce this cost by structurally creating opportunities to aggregate orders into round lots. In line with our regulatory obligations, we aim to achieve best execution—a regulatory standard that requires seeking the most favorable terms reasonably available under prevailing market conditions. This includes evaluating factors such as price, speed, likelihood of execution and settlement, and overall cost.

Betterment does not delay trades to form round lots, but it uses a system of time-based trade windows and an omnibus aggregation strategy to opportunistically cross the round-lot threshold when client order flow naturally aligns. This allows us to systematically access the more favorable pricing conditions typically associated with round-lot trades—potentially reducing cost and improving execution outcomes for clients.

While our model is designed to improve execution quality in the aggregate, individual trade outcomes may vary depending on market volatility, order size, and venue-specific factors.

Trade windows as a mechanism for better execution

Most retail brokers execute trades continuously, immediately passing orders to the market. While this appears fast and transparent, it exposes clients to harmful microstructure dynamics. High-frequency traders (HFTs), for example, exploit real-time signals to capture spread value, often at the expense of slower retail flows.

Betterment mitigates this by batching trades into scheduled trade windows. These windows operate throughout the day and function similarly to frequent call auctions—a concept studied by Budish, Cramton, and Shim (2015). Their research shows that batched execution reduces the arms race in trading latency, promotes fairness, and narrows spreads. Though Betterment does not run formal batch auctions, our windows are intended to serve a similar purpose: reducing predictability, concealing intent, and improving average execution.

This design also lowers market impact by consolidating demand. Liquidity providers can see larger, more regular flows instead of a noisy, fragmented stream. A single larger order is more likely to attract competitive pricing because it signals meaningful interest and is easier for liquidity providers to match against existing supply. For example, multiple clients buying SPY over the same trade window are combined into one order, reducing slippage—the difference between the expected price and the actual execution price—and improving fills, or the likelihood that the entire order will be completed promptly at a desirable price.

Execution in practice: Betterment’s strategy

At Betterment, trades are executed in windows throughout the day. Each window consolidates similar trades—buy or sell, same ticker—into a single order, executed through an omnibus structure. Trades are routed through Apex, our clearing and trading partner, to venues offering a competitive combination of price, liquidity, and fill reliability, with round-lot opportunities prioritized. We work to achieve best execution in all trades routed through this process.

This structure introduces flexibility without sacrificing fairness. Betterment does not delay execution for the sake of creating a round lot, but we design the system to allow aggregation when practical. If immediacy is necessary—such as at day-end—we will execute whatever lots are available.¹ We also monitor managed accounts for rebalancing and tax-loss harvesting (TLH) opportunities. When Betterment’s trading algorithm evaluates client accounts for tax loss harvesting and rebalancing opportunities, it generally prioritizes identifying potential tax loss harvests ahead of potential rebalancing opportunities. This activity also plays a meaningful role in how we strive to optimize outcomes alongside our execution practices. When clients’ orders align, aggregation and scheduling increase the likelihood of a favorable outcome.

¹Betterment reserves the right to delay trading under certain circumstances; more information about our trading practices and policies is available in our Form ADV.

To support oversight of Betterment's execution quality, Betterment has established a formal Best Execution Committee tasked with oversight of execution quality. This committee performs a regular and rigorous review of trading outcomes, assessing execution quality across market centers using key metrics such as basis point deviation from market price at placement (placement strike), routing behavior, peer comparisons, and arrival price analysis. Evaluations are made across ticker, order size, and timeframes.

Aggregation in action: a comparative scenario

To further illustrate how aggregation leads to better execution, consider this example where three clients submit small trades around the same time. When routed individually, these odd-lot orders are exposed to the same disadvantages outlined earlier—such as worse pricing due to exclusion from the NBBO. But when aggregated into a single round-lot trade, the order gains visibility and priority, increasing the likelihood of receiving better pricing.

Client Orders	Without Aggregation	With Aggregation
Alice: Buy 35 shares	Executed at $135.02 = $4,725.70	100 shares executed at $135.00 = $13,500.00
Bob: Buy 40 shares	Executed at $135.01 = $5,400.40
Carol: Buy 25 shares	Executed at $135.03 = $3,375.75
Total Cost Impact	Total: $13,501.85 (varied, higher prices)	Total: $13,500.00 (uniform, better pricing)

Illustrative purposes only. Prices shown do not reflect actual client execution results.

This example reinforces the earlier point about execution quality differences between odd-lot and round-lot trades—such as the estimated 2 basis point disadvantage found in high-volume stocks like VTI. A consolidated 100-share order, like the one shown here, is more likely to attract competitive pricing from liquidity providers because it is easier to match against existing supply and signals meaningful demand.

This example illustrates a core insight: retail investors are disadvantaged when fragmented. But when they act collectively—via an automated platform like Betterment—they gain access to efficiencies normally reserved for large institutional traders.

Delivering institutional benefits to retail investors

Betterment’s model is designed to translate institutional market advantages into a retail context. Institutional desks execute trades strategically—splitting orders, timing placements, and waiting for liquidity. These techniques aren’t usually available to individuals, but Betterment’s platform replicates many of them algorithmically.

By aggregating trades to reach round lots, using structured time-based execution, and accessing liquidity intelligently, Betterment customers may benefit from pricing and execution quality similar to what’s typically associated with institutional standards. This parity is especially powerful in volatile or illiquid conditions, where fragmented execution can be costly.

Conclusion and client-centric outcomes

Managed trading, as implemented by Betterment, is a deliberate, research-driven strategy to overcome the inherent flaws in retail execution. We combine trade scheduling, order aggregation, and a neutral fee structure to deliver meaningful advantages to individual investors. Our model does not guarantee better execution on every trade, but in the aggregate, it enhances pricing, reduces slippage, and levels the playing field.

Betterment believes that balancing immediacy and opportunity is key. Betterment may wait to aggregate trades to seek improved execution, which we believe is a rational tradeoff. Betterment clients are not sacrificing control—they’re gaining efficiency. Over time, this system is designed to create small but consistent enhancements in return, aligning with our core mission: helping clients make the most of their money.

References

Bartlett, R. P. III. (2021). Modernizing Odd Lot Trading. Columbia Business Law Review.
Budish, E., Cramton, P., & Shim, J. (2015). The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response. Quarterly Journal of Economics.
American Economic Association. Research and publications on equity market structure and trading practices.
NYU Stern School of Business. Faculty research on market microstructure and fairness.
Australian Centre for Financial Research (ACFR). Market design and equity structure studies.