How Do You Build a Defensible Best Execution File for a Bond That Has Not Traded in Years?

Concept

Constructing a defensible best execution file for a bond that has been dormant for years is an exercise in navigating a data vacuum. The absence of recent trades removes the most direct and observable measure of fair value, the market price. This situation shifts the entire burden of proof from simple price comparison to a rigorous, multi-faceted justification of value.

The core task is to create a compelling narrative, supported by qualitative and quantitative evidence, that demonstrates a fiduciary’s diligence in achieving the most advantageous terms for a client under conditions of extreme illiquidity. It is an intellectual and procedural challenge that lies at the heart of institutional responsibility.

The foundation of this process rests upon a clear understanding of regulatory obligations, such as those outlined by FINRA Rule 5310 and MSRB Rule G-18. These rules mandate that firms exercise “reasonable diligence” to ascertain the best market for a security under the prevailing circumstances. For an untraded bond, “reasonable diligence” transcends checking a screen for a quote. It becomes an active, investigative process.

The objective is to build a logical framework that a regulator or auditor can follow, demonstrating that the final execution price was fair and reasonable given the bond’s specific characteristics and the state of the market at that precise moment. The quality of the defense is directly proportional to the quality and depth of the evidentiary file.

A defensible file for an untraded bond is not a record of a transaction, but a documented proof of a valuation process.

This process is fundamentally different from executing trades in liquid securities where a National Best Bid and Offer (NBBO) might exist. The fixed-income market, particularly its less liquid segments, is fragmented and traded over-the-counter (OTC). Price discovery is not a passive act of observation but an active process of engagement with market participants. For a bond that has not traded in years, this might involve soliciting interest from a select group of dealers known to specialize in similar securities or sectors.

The challenge lies in gathering these data points without creating adverse market impact; excessive signaling of an intent to trade can move the potential price away from the seller or buyer. Therefore, the initial steps involve careful planning and a deep understanding of the instrument’s unique attributes ▴ its issuer, coupon, maturity, credit quality, call features, and any existing covenants ▴ as these will form the basis for all subsequent valuation work.

Strategy

Developing a strategy for evidencing best execution for a long-dormant bond requires a pivot from direct market evidence to indirect, model-based evidence. The strategy must be systematic, documented, and grounded in established financial principles. The primary goal is to create a “fair value” estimate that can serve as a benchmark against which the final execution price is judged. This involves a multi-pronged approach that combines quantitative models with qualitative market intelligence.

The Three Pillars of Valuation

A robust strategy relies on three core valuation techniques. The selection and weighting of these pillars will depend on the specific characteristics of the bond in question. A comprehensive best execution file will typically document the analysis performed using several of these methods to demonstrate a thorough and diligent process.

1. Comparable Bond Analysis (CBA) ▴ This is often the most persuasive method. It involves identifying a universe of “similar” securities that have traded recently. The definition of “similar” is critical and must be carefully documented. Factors for comparison include the issuer, sector, credit rating, maturity, coupon, and call features. The yields of these comparable bonds can be used to derive an appropriate yield and, consequently, a price for the subject bond. The key is to justify the selection of the comparable bonds and to account for any material differences between them and the subject bond.
2. Matrix Pricing ▴ This is a more quantitative approach that uses a grid or “matrix” to estimate the yield for a bond based on its credit quality and maturity. The matrix is built using recent trades of other bonds. For example, a 5-year, single-A rated industrial bond’s yield could be estimated by looking at the yields of other single-A industrial bonds with maturities around five years. This method provides a systematic and replicable valuation, reducing subjectivity. However, its accuracy depends on the availability of sufficient data points to construct a reliable matrix.
3. Discounted Cash Flow (DCF) Analysis ▴ This method values the bond based on the present value of its future cash flows (coupon payments and principal repayment). The critical input in a DCF model is the discount rate, which should reflect the riskiness of the bond. This rate is typically derived from a benchmark risk-free rate (like a U.S. Treasury yield) plus a credit spread. The credit spread is the most subjective component and must be justified, often by referencing the spreads on comparable bonds or credit default swap (CDS) markets.

Documenting the Search for Liquidity

Beyond valuation, the strategy must include a documented process for interacting with the market. For a highly illiquid bond, this rarely means broadcasting an order to a wide audience. Instead, it involves a targeted and discreet process.

• Request for Quote (RFQ) ▴ A trader might send a request for a quote to a small, select group of dealers known for making markets in similar or esoteric debt. The best execution file should document which dealers were contacted, why they were chosen, the quotes they provided (or if they declined to quote), and the time the quotes were received. This demonstrates a competitive process, even if limited.
• Single-Dealer Negotiation ▴ In some cases, approaching only one dealer may be the best strategy to minimize information leakage and potential market impact. If this path is chosen, the justification must be particularly strong. The file should explain why this dealer was selected (e.g. they were the original underwriter, or they have a known axe in the security) and how the negotiated price was validated against the internal fair value estimates derived from CBA, matrix pricing, or DCF.

The following table illustrates a comparison of strategic choices based on the bond’s characteristics and the firm’s objectives.

Ultimately, the strategy is about creating a mosaic of evidence. No single data point will be perfect. However, by combining multiple valuation techniques with a documented and logical approach to sourcing liquidity, a firm can build a powerful argument that it acted diligently and in the best interest of its client.

Execution

The execution phase translates the valuation strategy into a concrete, auditable record. This is where the theoretical becomes tangible. A defensible best execution file is not a single document but a curated collection of evidence, analysis, and commentary that collectively tells the story of the trade.

It must be assembled with the expectation that it will be scrutinized by regulators, auditors, and potentially legal counsel. Every step, every decision, and every piece of data must be recorded with clarity and purpose.

The Operational Playbook

Building the file is a systematic, multi-step process. Adhering to a defined operational playbook ensures consistency and completeness. The following steps represent a comprehensive workflow for constructing a best execution file for a bond that has not traded in years.

1. Pre-Trade Analysis and Benchmark Creation
   • Security Master Review ▴ The first step is to pull all known data on the subject bond from internal systems and data providers like Bloomberg or Refinitiv. This includes issuer details, coupon, maturity, credit ratings (current and historical), call schedules, and any specific covenants or features.
   • Initial Fair Value Estimation ▴ Before contacting any market participants, the trader or analyst must establish an initial, unbiased fair value benchmark. This involves running the valuation models chosen in the strategy phase (CBA, Matrix Pricing, DCF). All assumptions, inputs, and calculations must be saved. For example, if using CBA, the list of comparable bonds and the rationale for their selection must be explicitly documented.
   • Define Execution Parameters ▴ Based on the portfolio manager’s directive, the trader must document the order’s parameters. Is the primary goal to achieve a specific price, to execute a certain size, or to complete the trade within a given timeframe? These factors heavily influence the execution strategy.
2. Documented Market Interaction
   • Counterparty Selection Rationale ▴ A list of potential counterparties to approach should be created. For each, a justification for their inclusion is necessary. Examples include ▴ “Dealer X is a known market maker in this sector,” or “Dealer Y was the original underwriter of the bond.”
   • Communication Records ▴ All interactions with counterparties must be logged. This includes emails, recorded phone lines (with timestamps), and platform messages (e.g. Bloomberg IB chat). The log should detail who was contacted, when they were contacted, the nature of the inquiry, and their response. If a dealer provides a quote, it must be recorded with price/yield, size, and the time it is good until. If they decline to quote, that too is a critical piece of information to record.
   • Contemporaneous Notes ▴ The trader should keep a running commentary of their thought process and market observations throughout the execution process. These “notes to file” can provide invaluable context during a future review. For instance ▴ “Market tone is weak today following the FOMC announcement, which may impact liquidity for off-the-run credits.”
3. Post-Trade Analysis and File Assembly
   • Execution Quality Assessment ▴ Once the trade is executed, the final price must be compared against the pre-trade benchmark. The file must include a calculation of the variance and a narrative explaining any significant difference. For example ▴ “The final execution price of 98.50 was 0.25 points below our initial CBA-derived benchmark of 98.75. This is considered a reasonable outcome given the seller’s urgency and the lack of natural buyers in the market today, as evidenced by two of the four contacted dealers declining to provide a quote.”
   • Evidence Compilation ▴ All the collected documents must be assembled into a single file, either physical or electronic. This includes screenshots of market data, valuation model outputs, communication logs, the trader’s notes, and the final trade ticket.
   • Formal Review and Sign-Off ▴ A senior member of the trading desk or a compliance officer should review the completed file. This second pair of eyes ensures the file is complete, the logic is sound, and the documentation meets the firm’s policy standards. Their sign-off provides an additional layer of defense.

Quantitative Modeling and Data Analysis

The quantitative portion of the file provides the objective backbone for the qualitative narrative. It demonstrates that the valuation was not based on guesswork but on established financial models. The following tables showcase examples of the kind of data analysis that should be included in the file.

The first table demonstrates a Comparable Bond Analysis. The goal is to select a handful of bonds that are as close as possible to the subject bond and use their market-observed yields to derive an implied yield for the untraded security.

Based on the analysis above, the file would contain a note like ▴ “The average spread for A- rated comparables with similar maturities (Comp 1 & 2) is +148.5 bps. Adjusting for the slightly older issue of the subject bond, a spread of +150 bps is deemed appropriate. This implies a target yield of 5.70% and a price of approximately 91.50.”

A well-documented quantitative model transforms a subjective opinion into a defensible analytical conclusion.

The second table shows a simplified Discounted Cash Flow model. This provides an alternative, intrinsic valuation to corroborate the market-based CBA.

The notes for this model would need to rigorously defend the choice of discount rate ▴ “A discount rate of 5.70% was used. This was derived from the current 10-year US Treasury yield of 4.20% plus a credit spread of 150 basis points, which is consistent with our Comparable Bond Analysis.”

Predictive Scenario Analysis

To truly understand the application of these principles, consider the case of a mid-sized asset manager, “Stonebridge Capital,” tasked with selling a position in the “Northwood Water District 4.00% Revenue Bond due 2039.” The bond was part of a portfolio acquired in a merger and has not traded in over seven years. The portfolio manager, Clara, needs to liquidate the $5 million par value position to reallocate capital to a new strategic initiative. The trader, Ben, is responsible for executing the trade and building the best execution file.

Ben begins his process on a Tuesday morning. His first action is not to call dealers, but to open his valuation toolkit. He pulls the bond’s CUSIP and finds its last recorded trade was in 2018. The rating from Moody’s is A1, but he notes it hasn’t been updated since 2020.

His first task is to build a pre-trade benchmark. He identifies five other California water district bonds with similar A1/A+ ratings and maturities between 2038 and 2041. He plots their yields, noting they trade at spreads between 85 and 100 basis points over the relevant Treasury benchmark. He makes a specific note that the Northwood bond is a smaller, less-known district, which likely warrants a liquidity premium.

He establishes a preliminary fair value spread of +105 bps, leading to a target price of around 98.75. He saves a screenshot of his comparable bond screen and a detailed note on his spread adjustment logic. He also runs a DCF model using this derived yield, which confirms the price. This entire process is completed and documented before a single external communication is initiated.

Next, Ben considers his execution strategy. Broadcasting a $5 million block of a sleepy muni bond is a recipe for disaster. He decides on a targeted RFQ to four specific dealers. His rationale, which he types into the “Strategy” section of his electronic file, is as follows ▴ Dealer A is a major national player in the municipal market.

Dealer B is a regional firm in California with deep knowledge of local water districts. Dealer C has shown an axe to buy similar bonds in the past month, according to his market intelligence. Dealer D is the original underwriter of the Northwood bond. This documented rationale shows his decision-making was not random but strategic.

At 10:30 AM, Ben initiates secure chats with the traders at the four dealers. He sends a carefully worded message ▴ “Seeking a market on Northwood Water 4s of ’39. Can show $5mm.” Within fifteen minutes, the responses come in. Dealer A bids 98.25.

Dealer B bids 98.40. Dealer C passes, stating they are “full up on California paper for now.” Dealer D, the original underwriter, comes back with a question ▴ “Is this all you have? We might have a home for a larger block.” Ben responds that $5mm is the full size. After another ten minutes, Dealer D bids 98.50.

Ben logs every single message, including the pass from Dealer C, into his file with timestamps. The pass is just as important as the bids, as it provides evidence of limited liquidity.

Ben now has a range of bids from 98.25 to 98.50. His pre-trade benchmark was 98.75. He now has to make a decision and justify it. He could press Dealer D for a better price, but the question about a larger block suggests their interest might be specific to one client and could be fleeting.

Pushing too hard might cause the bid to evaporate. He assesses the top bid of 98.50 from Dealer D. It is a quarter-point, or $12,500 on the block, below his initial estimate. He writes a contemporaneous note ▴ “The bid from Dealer D at 98.50 is the highest received. It is 0.25 below my pre-trade estimate, however, this is a reasonable variance given the lack of recent trading history and the pass from a major market participant (Dealer C).

Dealer D’s position as the original underwriter gives them unique insight. I recommend executing at this level.”

He communicates this recommendation to Clara, the PM, who agrees. At 11:15 AM, he executes the trade with Dealer D at 98.50. He immediately saves the trade confirmation. The final step is to assemble the file.

He creates a single PDF document containing ▴ 1) The initial security master data. 2) His pre-trade valuation analysis with the list of comps and the DCF model. 3) His documented execution strategy and rationale for dealer selection. 4) The complete, timestamped chat logs with all four dealers.

5) His final analysis comparing the execution price to the benchmark. 6) The formal trade confirmation. He titles the file “BestEx_Northwood_2039_YYYYMMDD” and submits it to his firm’s compliance portal for review. The file tells a complete story, from valuation to inquiry to execution, providing a robust defense against any future questions about the trade’s fairness.

System Integration and Technological Architecture

A robust best execution process for illiquid bonds is not solely a human endeavor; it is supported by a sophisticated technological architecture. The goal of this architecture is to streamline data collection, enforce compliance workflows, and create an unassailable audit trail. The system must integrate various components to provide the trader with the necessary tools while ensuring every action is captured.

At the core of this framework is the firm’s Order Management System (OMS) and/or Execution Management System (EMS). Modern systems are designed to be the central hub for the entire lifecycle of a trade.

• Pre-Trade Data Integration ▴ The OMS must have real-time or near-real-time data feeds from multiple vendors (e.g. Bloomberg, Refinitiv, ICE Data Services). When a trader looks up the untraded bond, the system should automatically pull in all available descriptive data, historical ratings, and any available evaluated pricing. Crucially, the system should allow the trader to attach their own pre-trade analysis, such as a spreadsheet with the CBA or DCF model, directly to the order ticket. This creates a single, unified pre-trade record.
• Compliance Rule Engine ▴ The OMS should have a built-in compliance module. Before an order can even be worked, the system can check for basic restrictions. For an illiquid bond, specific rules can be configured. For example, a rule could require that a “Fair Value Benchmark” field must be filled out by the trader before the order becomes active. Another rule could trigger an alert if a trader attempts to execute a trade more than a certain percentage away from this benchmark without providing a written justification.
• Communication and RFQ Integration ▴ Leading EMS platforms offer integrated RFQ capabilities. A trader can build a list of dealers within the system and send out the RFQ to all of them simultaneously. The platform then captures all responses ▴ bids, offers, and passes ▴ and logs them automatically against the order. This is far superior to manual chat logs, as it removes the risk of human error and provides a clean, machine-readable audit trail. For voice trades, the system should allow for manual entry of quote details, with fields for counterparty, price, size, and time. Integration with recorded phone line systems can provide an additional layer of verification.
• Audit Trail and File Creation ▴ This is the most critical technological component. Every single action taken on the order must be logged with a timestamp and user ID. This includes every modification to the order, every quote received, every note entered by the trader, and the final execution details. At the end of the process, the system should be able to automatically collate all of this information ▴ the pre-trade data, the benchmark analysis, the communication logs, the trader’s notes, and the trade confirmation ▴ into a single, comprehensive “best execution file.” This file can then be automatically routed to a compliance workflow for review and stored in a secure, immutable archive for regulatory purposes.

The technological architecture serves to systematize what can otherwise be a chaotic process. It enforces discipline, reduces operational risk, and provides the raw data needed to build a truly defensible best execution file.

Reflection

From Justification to Intelligence

The construction of a best execution file for a dormant bond, while a procedural necessity, offers a deeper institutional opportunity. It forces a shift from passive price-taking to active value-seeking. The discipline required to build this defense ▴ the rigorous pre-trade analysis, the strategic market soundings, the meticulous documentation ▴ is not merely a compliance exercise. It is the development of a core competency in navigating market opacity.

Each file becomes a permanent record of a specific market condition, a snapshot of liquidity for a particular type of credit at a moment in time. When aggregated, these individual files cease to be just audit protection; they transform into a proprietary database of market intelligence. The process of justifying a single trade builds the infrastructure for making smarter decisions on all future trades.

It cultivates a mindset where every execution is an opportunity to learn, to refine valuation models, and to deepen the firm’s understanding of the hidden corners of the fixed-income universe. The ultimate goal is not just to have a defensible file, but to build an organization that rarely needs to defend itself because its process is inherently sound.