Professional Judgment
Market-based evidence and quantitative models support the valuation process, but they do not replace informed professional judgment.
AbbottModelDLOM provides an auditable framework for evaluating the marketability of a closely held interest using quarter-specific public-market evidence. The platform identifies a reference cohort, evaluates financial and operating performance, estimates liquidity and volatility measures, and develops model-based DLOM indications.
These outputs are analytical evidence rather than an automatic valuation conclusion. The analyst remains responsible for determining whether the evidence is relevant, how it should be interpreted, and how it supports the final opinion.
Role of Professional Judgment
Professional judgment enters the analysis at several stages, including:
- Defining the subject interest and applicable valuation date
- Selecting the relevant market and industry classification
- Evaluating the comparability of the public-company reference cohort
- Assessing the subject company’s financial and operating characteristics
- Determining the applicable restriction and liquidation periods
- Evaluating the information available to prospective buyers and sellers
- Selecting the appropriate DLOM model or range of model indications
- Considering Mandelbaum factors and other assignment-specific evidence
- Identifying potentially overlapping adjustments
- Reconciling the quantitative results with the facts of the assignment
- Developing and documenting the final DLOM conclusion
The platform organizes the evidence and applies the stated calculations consistently. It does not determine the relative importance of every fact in a particular assignment.
Appropriate Use
AbbottModelDLOM is designed to assist valuation professionals and other qualified analysts in developing and documenting DLOM analyses for closely held interests.
Appropriate uses may include:
- Developing market-based evidence for a DLOM analysis
- Identifying a quarter-specific public-company reference cohort
- Comparing a subject company with the selected cohort
- Evaluating observed volatility and trading liquidity
- Estimating a supported liquidation horizon
- Evaluating alternative information conditions
- Developing option-model DLOM indications
- Organizing Mandelbaum-factor considerations
- Testing the sensitivity of results to supportable assumptions
- Documenting the relationship among inputs, calculations, and conclusions
- Supporting an independently reasoned valuation opinion
The platform should be used as part of a broader valuation process that considers the subject interest, assignment purpose, applicable standard of value, valuation date, legal rights, transaction circumstances, and all other relevant information.
Evaluating the Reference Cohort
The platform forms a public-company reference cohort using the selected market, valuation quarter, industry classification, and locked size decile.
The resulting cohort provides a market-based frame of reference. It does not establish that every selected public company is directly comparable to the subject company in all respects.
The analyst should consider whether the cohort is relevant in light of factors such as:
- Business activities
- Industry exposure
- Company size
- Profitability
- Growth characteristics
- Financial condition
- Capital structure
- Operating risk
- Geographic exposure
- Stage of development
- Public float
- Trading characteristics
- Extraordinary company or market events
Additive cohort expansion improves the number of observations when a narrowly defined industry cohort is insufficient. It may also introduce companies with broader operating characteristics. The analyst should evaluate whether that broader evidence remains informative for the subject interest.
A statistically sufficient cohort is not necessarily an economically persuasive cohort. Conversely, a cohort containing meaningful variation may still provide useful distributional evidence when the differences are recognized and explained.
Subject-Interest Considerations
Public-market evidence describes the selected reference companies. The final DLOM conclusion applies to a specific subject interest.
The analyst should evaluate characteristics of that interest that may not be captured fully by the public-company data, including:
- Legal or contractual transfer restrictions
- Expected duration of the restriction
- Size of the ownership block
- Voting and governance rights
- Distribution rights
- Redemption or repurchase provisions
- Shareholder agreements
- Rights of first refusal
- Registration rights
- Access to company information
- Concentration of ownership
- Expected holding period
- Prospects for a negotiated sale
- Availability of potential buyers
- Anticipated liquidity events
- Seller execution strategy
The relevance and effect of these characteristics depend on the facts of the assignment. They should not be converted automatically into standardized premiums or discounts.
Selecting the Liquidation Horizon
The estimated liquidation horizon is a model input, not a predetermined fact.
The platform provides market-based liquidity and block-liquidation evidence from the selected public-company cohort. The analyst should determine whether that evidence reasonably represents the expected disposition of the subject interest.
For a restricted interest, total delay may include:
- The period before unrestricted disposition is legally or contractually permitted
- The additional period required to liquidate the block after the restriction ends
For an unrestricted block, the relevant horizon may consist only of the estimated block-liquidation period.
The analyst should consider whether an orderly market sale is a reasonable disposition assumption or whether the facts suggest a negotiated transaction, issuer repurchase, strategic sale, staged disposition, or another liquidity path.
A longer estimated horizon generally increases exposure to price uncertainty and delayed access to cash. It does not, by itself, prescribe a particular discount.
Professional Judgment in Model Selection
The appropriate model depends partly on the information conditions applicable to the transaction.
The selected reference companies are publicly traded securities. Their prices and trading activity therefore provide observable public-market evidence consistent with the public-information conditions underlying the Margrabe framework.
The Margrabe model may be relevant when public information is available to both parties but material private information remains asymmetrically held.
The Asian Average model reflects a progression toward fuller information symmetry when sufficient due diligence provides the buyer with relevant private information.
The analyst should consider:
- Information available to the seller
- Public information available to market participants
- Private information available to the buyer
- Scope and quality of due diligence
- Reliability of management information
- Cost of obtaining and validating additional information
- Whether the transaction process reduces material information asymmetry
The costly due-diligence framework can help the analyst evaluate whether the economic benefit of improved information supports moving from the Margrabe condition toward the Asian Average condition.
Due-diligence cost is a model-selection consideration. It is not an additional discount to be added mechanically to the selected option-model result.
Displaying more than one model indication does not require the analyst to average them. The selected model, range, or weighting should be supported by the information conditions and facts of the assignment.
Use of Financial Performance Evidence
The performance analysis compares the subject company with the same quarter-specific public-company cohort used elsewhere in the platform.
Profitability, financial condition, capital structure, and operating performance may affect investor perceptions and the marketability of the subject interest. These measures provide context for professional judgment.
They do not produce an automatic increase or decrease in DLOM.
The analyst should consider whether an observed difference:
- Reflects a persistent operating characteristic
- Results from temporary or cyclical conditions
- Is typical for the industry
- Reflects financial distress
- Results from investment in future growth
- Is already incorporated into the subject-company valuation
- Affects marketability independently of enterprise value
A factor already reflected in the underlying valuation should not be counted again automatically through DLOM.
Use of Mandelbaum Factors
The Mandelbaum analysis provides a structured framework for considering qualitative and quantitative factors associated with marketability.
The factors should be evaluated in relation to the subject interest and the supporting evidence. They should not be treated as independent numerical discounts or combined through an unsupported scoring formula.
The Mandelbaum analysis may assist the analyst in:
- Identifying relevant marketability considerations
- Comparing the subject company with public-market evidence
- Explaining the direction of professional judgment
- Evaluating whether the model indications are reasonable
- Documenting assignment-specific considerations
The factors inform the conclusion. They do not replace the option-model analysis or prescribe a particular percentage.
Avoiding Mechanical Adjustments
A DLOM conclusion should not be constructed by adding every unfavorable observation as a separate discount.
Several platform measures describe connected aspects of the same underlying economic process. For example:
- Lambda, the volume-weighted average liquidation period, and the estimated block-liquidation period describe related liquidity evidence.
- Liquidity evidence may already be incorporated through the liquidation horizon used in the DLOM model.
- Volatility is already a direct option-model input.
- Financial distress may already affect the underlying enterprise or equity value.
- Information asymmetry informs model selection.
- Due diligence may reduce information asymmetry rather than create a separate discount.
- Mandelbaum factors may explain or contextualize the model result without constituting additive adjustments.
The analyst should identify how each factor enters the analysis and confirm that the same economic effect has not been counted more than once.
Professional Judgment in Interpreting Model Results
Model-generated DLOM indications are conditional estimates. They depend on the selected inputs, measurement conventions, information assumptions, and model structure.
The analyst should evaluate:
- Quality and completeness of the underlying data
- Number of valid cohort observations
- Dispersion within the cohort
- Relevance of the cohort to the subject company
- Reliability of the volatility estimate
- Support for the restriction and liquidation periods
- Applicability of the model’s information conditions
- Sensitivity of the result to reasonable alternative assumptions
- Consistency with other assignment evidence
A cohort median is not automatically the correct subject-company input. A model result is not automatically the final DLOM. The final conclusion may be a point estimate or a range, depending on the evidence and requirements of the assignment.
Any departure from the central cohort evidence should be supported and documented.
Data and Model Limitations
Public-market data are historical observations. They may be affected by limited trading, unusual market events, corporate actions, reporting differences, missing information, or data-provider revisions.
Historical trading evidence does not guarantee:
- The timing of an actual sale
- The volume available at quoted prices
- The execution price for a particular block
- The availability of a specific buyer
- The success of a negotiated transaction
- Future volatility or liquidity
- The occurrence of a future liquidity event
Models necessarily simplify economic conditions. Their results should be interpreted as structured estimates rather than transaction guarantees.
The analyst should investigate unusual observations, material data limitations, and results that appear inconsistent with the subject interest or known market conditions.
Documentation of the Conclusion
An auditable DLOM analysis should distinguish among:
- Observed market data
- Platform-derived measures
- User-supplied assumptions
- Model-generated indications
- Analyst-selected inputs
- Qualitative considerations
- Professional-judgment adjustments
- Final conclusion
The valuation report should explain, as applicable:
- Why the selected cohort is relevant
- How the restriction and liquidation periods were determined
- Which volatility evidence was used
- Which model was selected and why
- How information asymmetry and due diligence were considered
- How financial performance and Mandelbaum factors informed the analysis
- Whether alternative assumptions were evaluated
- How potential double counting was avoided
- How the final DLOM was reconciled with the supporting evidence
Documentation should be sufficient for another qualified reviewer to trace the material inputs, calculations, assumptions, and judgments supporting the conclusion.
Inappropriate Use
AbbottModelDLOM should not be used:
- As a substitute for a complete valuation analysis
- To produce a DLOM without evaluating the subject interest
- To accept a cohort median or model result mechanically
- To combine related liquidity measures as separate discounts
- To add Mandelbaum factors as unsupported numerical adjustments
- To treat due-diligence cost as an additional DLOM item
- To assume that historical liquidity guarantees an actual sale timetable
- To apply evidence from one valuation quarter without considering the applicable valuation date
- To rely on unavailable information as though it were an observed zero
- To support a conclusion that the analyst cannot independently explain and defend
- To provide legal, tax, accounting, or investment advice
The platform should not be used beyond the user’s professional competence or without considering the applicable valuation standards, professional requirements, and assignment conditions.
Analyst Responsibility
AbbottModelDLOM supports a disciplined, market-informed, transparent, and auditable valuation process.
The platform provides the analytical structure. The analyst provides the assignment-specific interpretation.
Accordingly, AbbottModelDLOM should be used as a transparent decision-support framework. Its market evidence and model indications inform professional judgment, while the valuation professional retains responsibility for selecting supportable inputs, reconciling the evidence, avoiding double counting, and developing and documenting the final DLOM conclusion.