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DLOM: The Auditor's Favorite Target

Why "industry standard" discounts for lack of marketability fail under scrutiny—and how to build defensible DLOM analysis using quantitative models.

The Discount for Lack of Marketability (DLOM) is the single most frequently challenged element in private company valuations. Auditors know that DLOM is where judgment lives—and where unsupported assumptions get buried. A 25% discount applied without analytical support is an invitation for extended review.

Why DLOM Attracts Scrutiny

DLOM is inherently judgmental. Unlike discount rates (which have observable market inputs) or revenue multiples (which can be verified against transaction data), DLOM represents a subjective assessment of illiquidity. This subjectivity creates audit risk.

Common audit findings include:

• "Rule of thumb" discounts applied without company-specific analysis
• Restricted stock studies cited without acknowledging their limitations
• Inconsistent application of DLOM across different valuations
• Missing documentation of how the discount was derived

The Problem with Empirical Studies

For decades, practitioners relied on two categories of empirical studies:

Restricted Stock Studies

These studies compared prices of restricted shares to freely tradable shares of the same issuer. While conceptually sound, they present problems:

• Data is dated (most studies are from 1970s-1990s)
• SEC Rule 144 changes have reduced restriction periods
• Studies show wide ranges (15-45%) with high variance
• Company-specific factors are not isolated

Pre-IPO Studies

These compare pre-IPO transaction prices to subsequent IPO prices. Their limitations:

• Survivorship bias (only successful IPOs are studied)
• Time-lag effects confound marketability with other factors
• Not applicable to companies without IPO prospects

Citing these studies without addressing their limitations invites challenge.

Quantitative Models: The Defensible Approach

Modern practice favors quantitative option-pricing models that derive DLOM from observable inputs. Three models dominate:

1. Chaffe Model (Protective Put)

Treats marketability as a put option—the cost of insuring against downside during the illiquidity period.

• Inputs: Volatility, time to liquidity, risk-free rate
• Strengths: Simple, intuitive, widely accepted
• Limitations: Tends to produce higher discounts than other models

2. Finnerty Model (Average-Strike Put)

Refines the Chaffe approach by using an average-strike put option structure.

• Inputs: Volatility, holding period
• Strengths: Addresses some limitations of Chaffe model
• Limitations: Requires volatility estimation for private companies

3. QMDM (Quantitative Marketability Discount Model)

A more comprehensive model incorporating expected growth, dividends, and holding period.

• Inputs: Expected holding period, required return differential, dividend yield
• Strengths: Captures economic substance of illiquidity
• Limitations: More inputs mean more assumptions to support

The FairvalueX Approach to DLOM

Our DLOM analysis follows a structured protocol:

Key Inputs and Their Support

Volatility

For private companies, volatility is estimated from guideline public companies. Document:

• Which guideline companies were used and why
• The lookback period for volatility calculation
• Whether you used a simple average or weighted approach
• Any adjustments for company-specific factors

Expected Holding Period

The time to expected liquidity event. Consider:

• Management's stated intentions regarding exit
• Contractual restrictions (shareholder agreements, lockups)
• Market conditions for the industry
• Historical holding periods for comparable situations

What Auditors Want to See

A defensible DLOM section includes:

• Explicit model selection rationale
• All inputs sourced and dated
• Full calculation shown (not just the result)
• Sensitivity analysis on key inputs
• Reasonableness crosscheck against empirical data
• Consistent application if multiple valuations are performed