# How Do the Amended Rule 605 Reporting Categories Affect Sor Logic? ▴ Question

**Published:** 2025-08-04
**Categories:** Question

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## Concept

The amended Rule 605 reporting framework represents a fundamental redesign of the data architecture available to the market. For a [Smart Order Router](https://prime.greeks.live/area/smart-order-router/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (SOR), this is not an incremental update; it is a systemic evolution. An SOR operates as a high-speed, automated decision engine, its logic entirely dependent on the quality and granularity of the data it consumes to solve a complex optimization problem which is achieving the best possible execution outcome. The amendments transform the nature of this problem by introducing new, high-fidelity data dimensions that redefine what “[best execution](https://prime.greeks.live/area/best-execution/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite)” means in a quantifiable, machine-readable format.

Historically, SOR logic was primarily engineered around a narrower set of variables, with the National Best Bid and Offer (NBBO) serving as the principal benchmark. The system’s objective was to capture the best available price, with liquidity and fill probability as secondary constraints. The data available from the previous iteration of Rule 605 supported this model, providing a retrospective, aggregated view of [execution quality](https://prime.greeks.live/area/execution-quality/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). This information was useful for high-level analysis but lacked the specificity required for real-time, dynamic routing adjustments at the level of individual [order types](https://prime.greeks.live/area/order-types/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).

The new rules dismantle this paradigm. The expansion of reporting entities to include larger broker-dealers, the inclusion of orders outside regular trading hours, and the creation of more nuanced order categories (such as those for fractional shares, odd-lots, and various immediate-or-cancel types) provide a vastly richer dataset. Most critically, the introduction of new metrics like average time to execution measured in milliseconds and [average realized spread](https://prime.greeks.live/question/what-is-the-impact-of-liquidity-fragmentation-on-the-realized-cost-of-gamma-hedging/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) calculated at multiple time intervals (50 milliseconds, 1 second, 15 seconds, etc.) provides the raw material for a far more sophisticated SOR cost function. The SOR’s logic must now evolve from a price-centric model to a multi-factor execution quality model, where speed, market impact, and [price improvement](https://prime.greeks.live/area/price-improvement/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) are weighted variables in a dynamic equation.

> The core function of a Smart Order Router is to translate a vast set of market data into a single, optimal execution decision.

This shift compels a re-architecting of the SOR’s internal calculus. The system must now be capable of ingesting and processing these new data streams, which will be provided in standardized monthly reports, and translating them into actionable routing logic. It needs to build and constantly refine venue-specific performance profiles based on these new metrics. A venue that offers superior price improvement but demonstrates consistently high post-trade reversion (as measured by the new [realized spread](https://prime.greeks.live/area/realized-spread/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) statistics) may be systematically de-prioritized for certain order types.

A different venue that shows exceptional execution speed for odd-lot orders will be prioritized for that specific flow. The SOR is no longer just hunting for the best price; it is performing a continuous, data-driven suitability analysis for every order it handles, guided by the expanded vocabulary of execution quality defined by the amended [Rule 605](https://prime.greeks.live/area/rule-605/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).

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## What Are the New Data Points for Sors?

The amended Rule 605 introduces a spectrum of new data categories that serve as direct inputs for the next generation of [SOR logic](https://prime.greeks.live/area/sor-logic/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). These inputs provide a multi-dimensional view of execution quality, moving far beyond the previous standards. The SOR must be re-engineered to parse, store, and act upon this enriched information, building a more granular and predictive model of [venue performance](https://prime.greeks.live/question/how-does-an-rfq-platform-differentiate-between-on-venue-and-off-venue-reporting-obligations/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).

- **Order Size Categorization** ▴ The logic now shifts from a simple share-based model to one based on both notional dollar value and the nature of the order. This includes specific categories for fractional shares, odd-lot orders, and round-lot orders. An SOR can now build distinct routing tables for a $500 notional odd-lot order versus a 10,000-share block, recognizing that different venues specialize in handling different order sizes with varying efficiency.

- **Expanded Order Types** ▴ The inclusion of marketable immediate-or-cancel (IOC) orders, orders with stop prices, and new non-marketable limit order types provides critical new labels for order flow. An SOR can now analyze venue performance specifically for IOCs, understanding which market centers provide the highest fill rates without information leakage, a completely different optimization problem than routing a standard marketable limit order.

- **Time-Based Execution Metrics** ▴ The requirement to report average [time to execution](https://prime.greeks.live/area/time-to-execution/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), measured in millisecond increments, is a significant architectural change. This allows an SOR to quantify the latency characteristics of each venue. For latency-sensitive strategies, the SOR can now make a data-driven decision to route to a slightly more expensive but demonstrably faster venue, optimizing the overall execution cost which includes the opportunity cost of delay.

- **Realized Spread Statistics** ▴ This is perhaps the most consequential new data set. By mandating the calculation of average realized spread at multiple time horizons after execution (e.g. 50ms, 1s, 15s, 1m, 5m), the rule provides a direct measure of adverse selection and post-trade [market impact](https://prime.greeks.live/area/market-impact/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). An SOR can use this data to identify venues where price improvement is ephemeral, quickly erased by market reversion. The system can build a “price quality” score for each venue, weighting the initial price improvement against its stability over time.

- **Coverage of Additional Timeframes** ▴ The inclusion of certain orders submitted outside of regular trading hours that become executable after the open expands the SOR’s operational window. The router’s logic must now account for pre-market and opening auction dynamics, using the new data to inform its strategy for handling these specific order types.

![A spherical Liquidity Pool is bisected by a metallic diagonal bar, symbolizing an RFQ Protocol and its Market Microstructure. Imperfections on the bar represent Slippage challenges in High-Fidelity Execution](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-optimization-within-principals-market-microstructure-framework.jpg)

## The Sors Evolving Objective Function

The [objective function](https://prime.greeks.live/area/objective-function/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) of a Smart [Order Router](https://prime.greeks.live/question/how-does-an-rfq-router-differ-from-a-traditional-smart-order-router/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is the mathematical expression of its goal. It is a cost function that the SOR seeks to minimize with every routing decision. The amendments to Rule 605 fundamentally alter the variables within this function, transforming it from a relatively simple equation into a complex, multi-variate model.

The legacy objective function could be represented as a primary focus on price improvement, often measured as effective spread over quoted spread. The goal was to maximize this value, subject to the constraint of achieving a high fill rate.

The new objective function is substantially more complex. It integrates the new data points from amended Rule 605 as distinct variables, each with a configurable weight. A modern SOR’s objective function must now account for:

ExecutionCost = w1 (PriceImprovement) + w2 (ExecutionTime) + w3 (RealizedSpread_50ms) + w4 (RealizedSpread_1min) + w5 (FillProbability) +. 

Where ‘w’ represents the weight assigned to each factor. These weights are not static. They must be dynamically adjusted based on the specific order’s characteristics (size, type, limit price) and the client’s stated execution objectives. For a large institutional order, the weight for realized spread might be very high to minimize market impact.

For a small retail order, the weight for price improvement and fill probability might be dominant. This dynamic weighting requires a sophisticated analytical layer within the SOR, capable of translating high-level client instructions into a precise mathematical objective for each order.

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## Strategy

The strategic implication of the amended Rule 605 is the mandatory evolution of SORs from simple routing mechanisms into sophisticated execution quality engines. The availability of granular, standardized data across brokers and venues creates a new competitive landscape where execution performance can be measured and compared with unprecedented accuracy. A broker’s SOR is no longer a black box; its performance, as dictated by its underlying logic, will be indirectly visible through the firm’s enhanced 605 reports. This transparency forces a strategic pivot toward building SORs that can demonstrably optimize for the new, multi-faceted definition of best execution.

The primary strategic shift is moving from a defensive, compliance-oriented approach to an offensive, performance-driven one. Previously, SOR logic was often designed to ensure that it did not violate best execution principles, primarily by routing to the NBBO. The new strategy involves proactively using the enriched data to build a competitive advantage. This means developing a SOR that can intelligently navigate the trade-offs between price, speed, and market impact, tailored to the specific characteristics of each order.

For example, the SOR’s strategy for a 10,000-share order in an illiquid stock will be fundamentally different from its strategy for a 10-share market order in a highly liquid ETF. The former might prioritize routing to venues with low realized spreads, even at the cost of slower execution, to minimize signaling risk. The latter might prioritize speed and price improvement above all else.

> A modern SOR strategy is defined by its ability to dynamically construct and solve a unique optimization problem for every single order.

This requires a significant investment in quantitative research and technology. The strategy involves building a “feedback loop” where the monthly [Rule 605 reports](https://prime.greeks.live/area/rule-605-reports/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) from all relevant market centers are ingested, analyzed, and used to update the SOR’s internal models. This is a continuous process of learning and adaptation. The SOR’s strategy must be flexible enough to account for changes in venue performance over time.

A venue that offers excellent performance one month may see its execution quality degrade the next. A proactive SOR strategy involves detecting these changes early and adjusting routing logic accordingly.

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## From Price to a Multi-Factor Model

The most critical strategic adaptation for SOR logic is the transition from a price-centric routing model to a multi-factor one. The new Rule 605 data provides the necessary inputs for this evolution. The table below illustrates the conceptual shift in the data points driving SOR decision-making.

### Table 1 ▴ Evolution of SOR Decision Inputs

| Decision Factor | Legacy SOR Logic (Pre-Amendment) | Modern SOR Logic (Post-Amendment) |
| --- | --- | --- |
| Primary Benchmark | National Best Bid and Offer (NBBO) | NBBO, plus multiple post-trade reversion metrics |
| Execution Speed | Indirectly considered, often based on historical fills or proprietary data. | Directly measured via standardized “average time to execution” reports (in ms). |
| Market Impact | Inferred from slippage analysis; difficult to standardize across venues. | Quantified via “average realized spread” at multiple time horizons (50ms, 1s, 5m etc.). |
| Order Type Specificity | Broad categories (market, limit). Limited data on IOCs or stop orders. | Granular data for marketable IOCs, stop orders, non-marketable limit orders, etc. |
| Odd-Lot Handling | Often aggregated or routed based on round-lot performance data. | Specific performance data for odd-lot and fractional share orders. |
| Data Source | Proprietary data supplemented by less granular Rule 605 reports. | Standardized, machine-readable Rule 605 and 606 reports from a wider range of entities. |

This evolution requires a strategic commitment to data science. The SOR’s effectiveness will be directly proportional to the quality of its analytical engine. The strategy must involve developing sophisticated models that can predict execution quality based on the historical data from the 605 reports, combined with real-time [market data](https://prime.greeks.live/area/market-data/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). This predictive capability allows the SOR to make forward-looking routing decisions, rather than simply reacting to past performance.

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## How Will Sor Strategies Differentiate?

As the new Rule 605 data becomes a commodity, the strategic differentiation between SORs will lie in how they interpret and act upon that data. Several key areas of strategic focus will emerge:

- **Dynamic Weighting Schemes** ▴ The most sophisticated SORs will develop dynamic weighting for their objective functions. The strategy will involve creating client-specific or even strategy-specific profiles. A quantitative hedge fund’s profile might heavily weight speed and market impact, while a retail aggregator’s profile might maximize price improvement and fill rates for small orders. The ability to customize these weights provides a significant competitive advantage.

- **Predictive Analytics and Machine Learning** ▴ A forward-thinking strategy will incorporate machine learning models to predict venue performance. These models can identify patterns in the 605 data that are not immediately obvious to human analysts. For example, a model might find that a particular venue’s performance for stop orders degrades significantly during periods of high market volatility. The SOR can then proactively re-route that order flow during such conditions.

- **Child Order Placement Strategy** ▴ For large parent orders that are broken up into smaller child orders, the SOR’s strategy becomes even more complex. The SOR must not only select the best venue for each child order but also determine the optimal size and timing of those orders. The new 605 data, particularly the realized spread metrics, will be a critical input into this process, helping the SOR to minimize the market impact of the overall parent order.

- **Integration with other Datasets** ▴ The most advanced strategies will involve integrating the Rule 605 data with other sources of information. This could include real-time market data feeds, news sentiment analysis, or proprietary signals. By combining these datasets, the SOR can build a more holistic view of the market and make more informed routing decisions. For instance, if a news event is likely to increase volatility in a particular stock, the SOR might adjust its routing strategy to favor venues that have historically performed well in high-volatility environments, a characteristic now identifiable through the enhanced reporting.

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## Execution

The execution phase of adapting a [Smart Order](https://prime.greeks.live/question/can-a-smart-order-router-effectively-blend-rfq-and-dark-pool-strategies-for-a-single-large-order/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) Router to the amended Rule 605 is a complex engineering and quantitative challenge. It requires a complete overhaul of the SOR’s data ingestion, processing, and decision-making architecture. The goal is to transform the static, monthly 605 reports into a dynamic, predictive, and actionable intelligence layer that drives every routing decision. This is not a simple software update; it is a fundamental re-engineering of the SOR’s core logic.

The process begins with the establishment of a robust data pipeline capable of systematically downloading, parsing, and standardizing the new 605 reports from every relevant market center and broker-dealer. These reports, which will be available in a machine-readable format like XML, must be ingested into a centralized database. This database becomes the foundational layer of the SOR’s new intelligence system. It must be designed to store and query terabytes of historical execution quality data across hundreds of venues and thousands of securities, categorized by the new, granular order types and sizes.

Once the data is stored, the next step is the development of a sophisticated analytics engine. This engine is responsible for transforming the raw 605 data into meaningful performance metrics. It must calculate baseline performance statistics for each venue, such as average price improvement, average execution speed, and average realized spread, for every combination of order type, order size, and security.

This creates a multi-dimensional performance matrix for the entire market. This matrix is the SOR’s map of the execution landscape.

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## The Operational Playbook

Implementing an SOR that leverages the new Rule 605 data requires a structured, multi-stage approach. The following represents an operational playbook for this process:

- **Data Architecture Construction** ▴ 

<li>**Develop a Scalable Ingestion System** ▴ Build automated scripts to download monthly Rule 605 reports from all relevant SEC-registered entities. This system must be fault-tolerant and capable of handling variations in file formats or availability.

- **Design a Granular Database Schema** ▴ The database schema must be designed to accommodate the new reporting categories. This includes fields for notional value, fractional shares, stop prices, IOC attributes, and the various realized spread time horizons.

- **Implement a Data Validation and Cleansing Layer** ▴ Incoming data must be validated for completeness and accuracy. A cleansing process should handle any inconsistencies or errors in the reported data to ensure the integrity of the analytical results.

</li>
- **Quantitative Model Development** ▴ 

<li>**Build a Multi-Factor Venue Scoring Model** ▴ This is the core quantitative task. Develop a model that assigns a composite execution quality score to each venue for different order scenarios. This model will use the data from the analytics engine and apply the dynamic weights discussed in the strategy section.

- **Create a Predictive Layer** ▴ Implement machine learning models (e.g. regression analysis, gradient boosting) to forecast near-term venue performance. This model will use historical 605 data along with real-time market variables (like volatility and volume) as inputs.

- **Back-testing Environment** ▴ Construct a high-fidelity back-testing environment that can simulate the performance of the new SOR logic against historical market data. This is critical for validating the model and tuning its parameters before deployment.

</li>
- **SOR Algorithm Re-Architecture** ▴ 

<li>**Integrate the Venue Scoring Model** ▴ The SOR’s core routing algorithm must be rewritten to query the new venue scoring model in real-time. For each incoming order, the SOR will request a ranked list of venues based on the order’s specific characteristics.

- **Develop Dynamic Parameterization** ▴ The SOR must be able to accept dynamic parameters that adjust the weights in the scoring model. This allows for customization based on client preferences or specific trading strategies.

- **Implement Child Order Logic** ▴ For large orders, the SOR’s “slicing” algorithm must be enhanced to use the new data. The choice of how to break down a parent order should be informed by the market impact data (realized spread) for different order sizes.

</li>
- **Monitoring and Continuous Improvement** ▴ 

<li>**Deploy Real-Time Performance Monitoring** ▴ Build dashboards that track the SOR’s performance in real-time, comparing its execution quality against market-wide benchmarks derived from the 605 data.

- **Establish a Feedback Loop** ▴ Create a formal process for reviewing the SOR’s performance each month when new 605 data is released. This process should identify areas for improvement and feed that information back into the quantitative modeling and algorithm development stages.

</li>

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## Quantitative Modeling and Data Analysis

The heart of the new SOR is its quantitative model. The following table provides a simplified example of a venue selection matrix that a re-architected SOR would use. This matrix is generated by the analytics engine based on the new Rule 605 data. The scenario is a marketable, odd-lot order with a notional value between 2,000 and $4,999 in a specific NMS stock.

### Table 2 ▴ Hypothetical SOR Veνe Selection Matrix

| Execution Veνe | Avg. Time to Exec (ms) | Avg. Price Improvement (/100sh) | Avg. Realized Spread (1s) | Fill Rate (%) | SOR Score |
| --- | --- | --- | --- | --- | --- |
| Venue A (ATS) | 5.2 | 0.08 | 0.06 | 99.5 | 92.1 |
| Venue B (SDP) | 15.8 | 0.12 | 0.04 | 98.2 | 95.5 |
| Venue C (Exchange) | 2.1 | 0.03 | 0.03 | 100.0 | 89.4 |
| Venue D (Wholesaler) | 25.4 | 0.15 | -0.02 | 100.0 | 85.7 |

In this example, the “SOR Score” is a weighted composite. For this particular client profile, the weights might be ▴ Price Improvement (40%), Realized Spread (30%), Time to Execution (20%), and Fill Rate (10%).

- **Venue B** receives the highest score. Although it is slower than Venue A and C, its combination of strong price improvement and very low post-trade reversion (a low realized spread) makes it the optimal choice under this weighting scheme.

- **Venue D**, despite offering the highest initial price improvement, scores the lowest. Its negative realized spread indicates significant adverse selection; the initial price improvement is more than erased by subsequent market movement. A legacy SOR might have chosen Venue D, but the modern SOR, armed with the new 605 data, identifies it as a suboptimal choice.

- **Venue C** is the fastest but offers minimal price improvement, resulting in a lower score for this profile. For a different profile that heavily weights speed, it might become the preferred venue.

This quantitative framework is the core of the execution process. It allows the SOR to move beyond simple, rule-based routing and into the realm of true, data-driven optimization.

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## What Is the Impact on System Architecture?

The execution of this new SOR logic has significant implications for a firm’s trading technology architecture. The system must be designed for high-throughput data processing and low-latency decision-making.

The architecture requires a clear separation between the offline analytical environment and the real-time routing engine. The offline environment is where the heavy lifting of processing the monthly 605 reports and training the predictive models occurs. The output of this environment is a set of compact, efficient models and scoring tables.

The real-time SOR engine is designed for speed. It loads the latest models from the analytical environment at the start of each trading day. When an order arrives, the SOR does not need to perform complex calculations from scratch.

Instead, it performs a series of rapid lookups in the pre-calculated scoring tables and executes the logic of the predictive model. This two-tiered architecture allows the SOR to leverage the insights from massive datasets without sacrificing the low-latency performance required for live trading.

Integration with Order Management Systems (OMS) and Execution Management Systems (EMS) is also critical. The OMS/EMS must be able to pass the necessary order attributes (client ID, strategy type) to the SOR so that it can apply the correct dynamic weights and performance models. The system must also provide a mechanism for traders to override the SOR’s automated logic when necessary, providing a crucial layer of human oversight.

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## References

- KPMG. (2024). SEC Final Amendments ▴ Rule 605 of Regulation NMS. KPMG International.

- U.S. Securities and Exchange Commission. (2024, March 6). SEC Adopts Amendments to Enhance Disclosure of Order Execution Information.

- Dechert LLP. (2024). SEC Approves Amendments to Enhance Disclosure of Order Execution Information.

- Morgan, Lewis & Bockius LLP. (2024). SEC Adopts Amendments to Modernize Disclosure of Order Execution Information.

- Barlup, R. (2024). SEC Rule 605 ▴ New Amendments. Best Execution Solutions.

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## Reflection

The assimilation of amended Rule 605 data into a Smart Order Router is a microcosm of a larger systemic shift in financial markets. It marks a transition from an environment of information asymmetry to one of radical transparency. The core challenge this presents to any trading entity is not merely technological but philosophical. The availability of this data transforms best execution from a qualitative principle into a quantifiable, auditable, and competitive discipline.

As you evaluate your own operational framework, consider the second-order effects of this change. When every major participant’s execution quality is laid bare in standardized reports, the definition of a competitive edge changes. The advantage no longer lies in proprietary access to information, but in the sophistication of the engine that interprets it. The quality of a firm’s quantitative research, the efficiency of its data architecture, and the intelligence of its algorithms become the primary differentiators.

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## How Does This Redefine the Broker-Client Relationship?

This new data paradigm also reshapes the dialogue between brokers and their institutional clients. Conversations can now be grounded in a shared, objective dataset. A client can ask pointed questions about a broker’s routing decisions, and the broker can provide data-driven answers that justify its strategy. This fosters a more collaborative and transparent relationship, where execution strategy is not a service being provided, but a partnership being forged.

Ultimately, the amended Rule 605 is an external catalyst forcing an internal evolution. It compels firms to examine the intelligence of their own systems. The task ahead is to build frameworks that not only comply with the new rules but also leverage them to create a durable, performance-based advantage in a market that is becoming more transparent, and therefore more competitive, by design.

![A futuristic apparatus visualizes high-fidelity execution for digital asset derivatives. A transparent sphere represents a private quotation or block trade, balanced on a teal Principal's operational framework, signifying capital efficiency within an RFQ protocol](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-via-prime-os.jpg)

## Glossary

<a href="https://prime.greeks.live/area/smart-order-router/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A blue speckled marble, symbolizing a precise block trade, rests centrally on a translucent bar, representing a robust RFQ protocol. This structured geometric arrangement illustrates complex market microstructure, enabling high-fidelity execution, optimal price discovery, and efficient liquidity aggregation within a principal's operational framework for institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/precision-institutional-rfq-execution-framework-optimizing-digital-asset-derivatives-liquidity-aggregation-across-complex-market-microstructure.jpg)

## Smart Order Router

Meaning ▴ A Smart Order Router (SOR) is an advanced algorithmic system designed to optimize the execution of trading orders by intelligently selecting the most advantageous venue or combination of venues across a fragmented market landscape. </a><a href="https://prime.greeks.live/area/best-execution/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Abstractly depicting an Institutional Digital Asset Derivatives ecosystem. A robust base supports intersecting conduits, symbolizing multi-leg spread execution and smart order routing](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-engine-optimization.jpg)

## Best Execution

Meaning ▴ Best Execution, in the context of cryptocurrency trading, signifies the obligation for a trading firm or platform to take all reasonable steps to obtain the most favorable terms for its clients' orders, considering a holistic range of factors beyond merely the quoted price. </a><a href="https://prime.greeks.live/area/execution-quality/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Abstract forms depict institutional liquidity aggregation and smart order routing. Intersecting dark bars symbolize RFQ protocols enabling atomic settlement for multi-leg spreads, ensuring high-fidelity execution and price discovery of digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-high-fidelity-execution-2.jpg)

## Execution Quality

Meaning ▴ Execution quality, within the framework of crypto investing and institutional options trading, refers to the overall effectiveness and favorability of how a trade order is filled. </a><a href="https://prime.greeks.live/area/order-types/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, conical precision instrument, with a vibrant mint-green tip and a robust grey base, represents the cutting-edge of institutional digital asset derivatives trading. Its sharp point signifies price discovery and best execution within complex market microstructure, powered by RFQ protocols for dark liquidity access and capital efficiency in atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-microstructure-price-discovery-optimization-prime-os-intelligence-layer.jpg)

## Order Types

Meaning ▴ Order Types are standardized instructions that traders use to specify how their buy or sell orders should be executed in financial markets, including the crypto ecosystem. </a><a href="https://prime.greeks.live/question/what-is-the-impact-of-liquidity-fragmentation-on-the-realized-cost-of-gamma-hedging/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![An abstract metallic circular interface with intricate patterns visualizes an institutional grade RFQ protocol for block trade execution. A central pivot holds a golden pointer with a transparent liquidity pool sphere and a blue pointer, depicting market microstructure optimization and high-fidelity execution for multi-leg spread price discovery](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-market-microstructure-optimization.jpg)

## Average Realized Spread

Liquidity fragmentation elevates gamma hedging to a systems engineering challenge, focused on minimizing impact costs across a distributed network. </a><a href="https://prime.greeks.live/area/price-improvement/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Precision system for institutional digital asset derivatives. Translucent elements denote multi-leg spread structures and RFQ protocols](https://options.greeks.live/wp-content/uploads/2025/07/precision-execution-infrastructure-for-institutional-digital-asset-derivatives-request-for-quote-protocol-optimization.jpg)

## Price Improvement

Meaning ▴ Price Improvement, within the context of institutional crypto trading and Request for Quote (RFQ) systems, refers to the execution of an order at a price more favorable than the prevailing National Best Bid and Offer (NBBO) or the initially quoted price. </a><a href="https://prime.greeks.live/area/realized-spread/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Two abstract, segmented forms intersect, representing dynamic RFQ protocol interactions and price discovery mechanisms. The layered structures symbolize liquidity aggregation across multi-leg spreads within complex market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-microstructure.jpg)

## Realized Spread

Meaning ▴ Realized Spread, within the analytical framework of crypto RFQ and institutional smart trading, is a precise measure of effective transaction costs, quantifying the profit or loss incurred by a liquidity provider on a trade after accounting for post-trade price discovery. </a><a href="https://prime.greeks.live/area/rule-605/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, black and beige institutional-grade device, featuring a prominent optical lens for real-time market microstructure analysis and an open modular port. This RFQ protocol engine facilitates high-fidelity execution of multi-leg spreads, optimizing price discovery for digital asset derivatives and accessing latent liquidity](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-rfq-execution-engine-for-high-fidelity-price-discovery-and-latent-liquidity-aggregation-across-multi-leg-spreads.jpg)

## Rule 605

Meaning ▴ Rule 605 of the U. </a><a href="https://prime.greeks.live/question/how-does-an-rfq-platform-differentiate-between-on-venue-and-off-venue-reporting-obligations/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Polished concentric metallic and glass components represent an advanced Prime RFQ for institutional digital asset derivatives. It visualizes high-fidelity execution, price discovery, and order book dynamics within market microstructure, enabling efficient RFQ protocols for block trades](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-prime-os-precision.jpg)

## Venue Performance

An RFQ platform differentiates reporting by codifying MiFIR's hierarchy, assigning on-venue reports to the venue and off-venue reports to the correct counterparty based on SI status. </a><a href="https://prime.greeks.live/area/sor-logic/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Precision-engineered modular components display a central control, data input panel, and numerical values on cylindrical elements. This signifies an institutional Prime RFQ for digital asset derivatives, enabling RFQ protocol aggregation, high-fidelity execution, algorithmic price discovery, and volatility surface calibration for portfolio margin](https://options.greeks.live/wp-content/uploads/2025/07/firm-fx-options-rfq-trade-system-key-microstructure-data-flow-core-engine.jpg)

## Sor Logic

Meaning ▴ SOR Logic, or Smart Order Router Logic, is the algorithmic intelligence within a trading system that determines the optimal venue and method for executing a financial order. </a><a href="https://prime.greeks.live/area/time-to-execution/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A prominent domed optic with a teal-blue ring and gold bezel. This visual metaphor represents an institutional digital asset derivatives RFQ interface, providing high-fidelity execution for price discovery within market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/precision-optic-interface-for-institutional-digital-asset-derivatives-rfq-protocol-execution-and-high-fidelity-price-discovery.jpg)

## Time to Execution

Meaning ▴ 'Time to Execution' refers to the duration elapsed between the initiation of a trade order by a participant and its final completion in the market. </a><a href="https://prime.greeks.live/area/market-impact/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precision probe, symbolizing Smart Order Routing, penetrates a multi-faceted teal crystal, representing Digital Asset Derivatives multi-leg spreads and volatility surface. Mounted on a Prime RFQ base, it illustrates RFQ protocols for high-fidelity execution within market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-rfq-digital-asset-derivatives-high-fidelity-execution-probe.jpg)

## Market Impact

Meaning ▴ Market impact, in the context of crypto investing and institutional options trading, quantifies the adverse price movement caused by an investor's own trade execution. </a><a href="https://prime.greeks.live/area/objective-function/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A translucent institutional-grade platform reveals its RFQ execution engine with radiating intelligence layer pathways. Central price discovery mechanisms and liquidity pool access points are flanked by pre-trade analytics modules for digital asset derivatives and multi-leg spreads, ensuring high-fidelity execution](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-core-platform.jpg)

## Objective Function

Meaning ▴ An Objective Function, in the domain of quantitative investing and smart trading within the crypto space, is a mathematical expression that precisely quantifies the goal or desired outcome to be optimized by an algorithmic system or decision model. </a><a href="https://prime.greeks.live/question/how-does-an-rfq-router-differ-from-a-traditional-smart-order-router/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A multi-faceted crystalline star, symbolizing the intricate Prime RFQ architecture, rests on a reflective dark surface. Its sharp angles represent precise algorithmic trading for institutional digital asset derivatives, enabling high-fidelity execution and price discovery](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-high-fidelity-execution-market-microstructure-optimization-for-prime-os-alpha-generation.jpg)

## Order Router

An RFQ router sources liquidity via discreet, bilateral negotiations, while a smart order router uses automated logic to find liquidity across fragmented public markets. </a><a href="https://prime.greeks.live/area/rule-605-reports/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A polished metallic needle, crowned with a faceted blue gem, precisely inserted into the central spindle of a reflective digital storage platter. This visually represents the high-fidelity execution of institutional digital asset derivatives via RFQ protocols, enabling atomic settlement and liquidity aggregation through a sophisticated Prime RFQ intelligence layer for optimal price discovery and alpha generation](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-optimization-for-high-fidelity-execution-and-liquidity-aggregation-via-prime-os-intelligence-layer.jpg)

## Rule 605 Reports

Meaning ▴ Rule 605 Reports refer to standardized monthly reports mandated by the U. </a><a href="https://prime.greeks.live/area/market-data/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A multi-layered electronic system, centered on a precise circular module, visually embodies an institutional-grade Crypto Derivatives OS. It represents the intricate market microstructure enabling high-fidelity execution via RFQ protocols for digital asset derivatives, driven by an intelligence layer facilitating algorithmic trading and optimal price discovery](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine-facilitating-high-fidelity-execution-and-optimal-price-discovery.jpg)

## Market Data

Meaning ▴ Market data in crypto investing refers to the real-time or historical information regarding prices, volumes, order book depth, and other relevant metrics across various digital asset trading venues. </a><a href="https://prime.greeks.live/question/can-a-smart-order-router-effectively-blend-rfq-and-dark-pool-strategies-for-a-single-large-order/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Intersecting translucent aqua blades, etched with algorithmic logic, symbolize multi-leg spread strategies and high-fidelity execution. Positioned over a reflective disk representing a deep liquidity pool, this illustrates advanced RFQ protocols driving precise price discovery within institutional digital asset derivatives market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-optimized-algorithmic-execution-microstructure-for-price-discovery.jpg)

## Smart Order

A Smart Order Router systematically blends dark pool anonymity with RFQ certainty to minimize impact and secure liquidity for large orders. </a>

**Tags:** [Algorithmic Trading](https://options.greeks.live/area/algorithmic-trading/), [Rule 605](https://options.greeks.live/area/rule-605/), [Realized Spread](https://options.greeks.live/area/realized-spread/), [Market Data](https://options.greeks.live/area/market-data/), [Smart Order Router](https://options.greeks.live/area/smart-order-router/), [Execution Quality](https://options.greeks.live/area/execution-quality/)	

## Discover More

- 
### [Under What Circumstances Can an Investment Firm Be Deemed to Have Met Its Best Execution Obligation?](https://options.greeks.live/question/under-what-circumstances-can-an-investment-firm-be-deemed-to-have-met-its-best-execution-obligation/)
![Close-up of intricate mechanical components symbolizing a robust Prime RFQ for institutional digital asset derivatives. These precision parts reflect market microstructure and high-fidelity execution within an RFQ protocol framework, ensuring capital efficiency and optimal price discovery for Bitcoin options.](https://options.greeks.live/wp-content/uploads/2025/07/engineered-core-systems-driving-institutional-digital-asset-derivatives-rfq-protocol-execution.jpg)

A firm meets its best execution obligation by operating a demonstrable, data-driven system designed to secure optimal client outcomes.

- 
### [How Can a Firm’s Best Execution Policy Evolve with Changing Market Structures and Technology?](https://options.greeks.live/question/how-can-a-firms-best-execution-policy-evolve-with-changing-market-structures-and-technology/)
![Stacked, glossy modular components depict an institutional-grade Digital Asset Derivatives platform. Layers signify RFQ protocol orchestration, high-fidelity execution, and liquidity aggregation. This Prime RFQ architecture manages market microstructure, enabling price discovery and atomic settlement.](https://options.greeks.live/wp-content/uploads/2025/07/layered-digital-asset-derivatives-rfq-protocol-stack-for-prime-brokerage.jpg)

A firm's best execution policy evolves by integrating advanced data analytics and a flexible technology stack into a dynamic governance framework.

- 
### [How Does Market Fragmentation Affect Best Execution Obligations for Asset Managers?](https://options.greeks.live/question/how-does-market-fragmentation-affect-best-execution-obligations-for-asset-managers/)
![Sleek, modular infrastructure for institutional digital asset derivatives trading. Its intersecting elements symbolize integrated RFQ protocols, facilitating high-fidelity execution and precise price discovery across complex multi-leg spreads. This represents a Prime RFQ intelligence layer for optimal capital efficiency and reduced slippage in volatile markets.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-system-optimizing-high-fidelity-block-trade-liquidity-and-multi-leg-spread-precision.jpg)

Market fragmentation mandates an asset manager to engineer a dynamic execution system that transforms dispersed liquidity into a verifiable edge.

- 
### [What Are the Data Requirements for the SEC’s Proposed Quarterly Execution Reviews?](https://options.greeks.live/question/what-are-the-data-requirements-for-the-secs-proposed-quarterly-execution-reviews/)
![Internal hard drive mechanics, with a read/write head poised over a data platter, symbolize the precise, low-latency execution and high-fidelity data access vital for institutional digital asset derivatives. This embodies a Principal OS architecture supporting robust RFQ protocols, enabling atomic settlement and optimized liquidity aggregation within complex market microstructure.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-precision-execution-system-microstructure.jpg)

The SEC's new rule mandates granular, millisecond-level data reporting to create a transparent execution quality marketplace.

- 
### [How Does Market Data Fragmentation Impact Best Execution for Institutional Investors?](https://options.greeks.live/question/how-does-market-data-fragmentation-impact-best-execution-for-institutional-investors/)
![Intersecting structural elements form an 'X' around a central pivot, symbolizing dynamic RFQ protocols and multi-leg spread strategies. Luminous quadrants represent price discovery and latent liquidity within an institutional-grade Prime RFQ, enabling high-fidelity execution for digital asset derivatives.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-enabling-high-fidelity-execution-across-disparate-liquidity-pools.jpg)

Market data fragmentation reframes best execution as a data engineering discipline, rewarding firms with superior operational architecture for integrating disparate liquidity pools.

- 
### [How Does Anonymized Market Data Affect Best Execution Obligations under MiFID II?](https://options.greeks.live/question/how-does-anonymized-market-data-affect-best-execution-obligations-under-mifid-ii/)
![A sophisticated dark-hued institutional-grade digital asset derivatives platform interface, featuring a glowing aperture symbolizing active RFQ price discovery and high-fidelity execution. The integrated intelligence layer facilitates atomic settlement and multi-leg spread processing, optimizing market microstructure for prime brokerage operations and capital efficiency. This represents a robust crypto derivatives OS.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-crypto-derivatives-rfq-engine-intelligence-layer.jpg)

Anonymized data requires firms to evolve beyond simple price matching, using advanced data analytics to prove superior execution under MiFID II.

- 
### [How Should a Firm’s Technology Architecture Evolve to Support an Adaptive Best Execution Framework?](https://options.greeks.live/question/how-should-a-firms-technology-architecture-evolve-to-support-an-adaptive-best-execution-framework/)
![Intersecting metallic structures symbolize RFQ protocol pathways for institutional digital asset derivatives. They represent high-fidelity execution of multi-leg spreads across diverse liquidity pools. Spheres denote aggregated inquiry and price discovery within a robust Prime RFQ, optimizing capital efficiency and mitigating systemic risk.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-framework-optimizing-multi-leg-spreads-and-liquidity-aggregation-for-best-execution.jpg)

An adaptive execution architecture transforms technology from a static utility into a dynamic, alpha-generating system.

- 
### [How Can a Firm’s Best Execution Committee Use Tca Data to Drive Performance?](https://options.greeks.live/question/how-can-a-firms-best-execution-committee-use-tca-data-to-drive-performance/)
![A multi-faceted crystalline form with sharp, radiating elements centers on a dark sphere, symbolizing complex market microstructure. This represents sophisticated RFQ protocols, aggregated inquiry, and high-fidelity execution across diverse liquidity pools, optimizing capital efficiency for institutional digital asset derivatives within a Prime RFQ.](https://options.greeks.live/wp-content/uploads/2025/07/rfq-protocols-for-institutional-digital-asset-derivatives-price-discovery.jpg)

A firm's Best Execution Committee uses TCA data to transform regulatory compliance into a strategic advantage by systematically analyzing and optimizing every facet of the trade lifecycle, thereby minimizing cost leakage and directly enhancing portfolio returns.

- 
### [How Does the Integration of Execution Pathways Affect Best Execution Compliance and Reporting?](https://options.greeks.live/question/how-does-the-integration-of-execution-pathways-affect-best-execution-compliance-and-reporting/)
![Prime RFQ visualizes institutional digital asset derivatives RFQ protocol and high-fidelity execution. Glowing liquidity streams converge at intelligent routing nodes, aggregating market microstructure for atomic settlement, mitigating counterparty risk within dark liquidity.](https://options.greeks.live/wp-content/uploads/2025/08/prime-os-high-fidelity-digital-asset-derivatives-rfq-protocol.jpg)

The integration of execution pathways transforms best execution from a compliance task into a data engineering challenge of unifying disparate data streams to prove and enhance performance.

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                "text": "The amended Rule 605 introduces a spectrum of new data categories that serve as direct inputs for the next generation of SOR logic. These inputs provide a multi-dimensional view of execution quality, moving far beyond the previous standards. The SOR must be re-engineered to parse, store, and act upon this enriched information, building a more granular and predictive model of venue performance."
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                "text": "This new data paradigm also reshapes the dialogue between brokers and their institutional clients. Conversations can now be grounded in a shared, objective dataset. A client can ask pointed questions about a broker's routing decisions, and the broker can provide data-driven answers that justify its strategy. This fosters a more collaborative and transparent relationship, where execution strategy is not a service being provided, but a partnership being forged."
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---

**Original URL:** https://options.greeks.live/question/how-do-the-amended-rule-605-reporting-categories-affect-sor-logic/
