How Does a Lack of Marketability Affect Private Share Value?

Concept

The value of any asset is a direct function of its convertibility to cash. For interests in privately held enterprises, this conversion mechanism is structurally impaired. Quantifying that impairment is a central challenge and a primary determinant of realized value.

The inability to rapidly execute a transaction at a predictable price with minimal cost introduces a specific, measurable form of economic friction. This friction is termed a lack of marketability, and its impact on private share value is quantified through a valuation adjustment known as the Discount for Lack of Marketability (DLOM).

A DLOM is a percentage reduction applied to a preliminary valuation of a private company interest. That initial valuation is typically derived by referencing publicly traded comparable companies or discounted cash flow models, both of which inherently assume a freely marketable, liquid security. The application of a DLOM adjusts this theoretical, marketable-equivalent value to reflect the operational reality of holding an illiquid asset.

An investor cannot simply enter an order to sell a private share on a public exchange; the process is manual, lengthy, and carries significant price uncertainty. The DLOM is the system’s method for pricing this structural disadvantage.

The core function of a Discount for Lack of Marketability is to bridge the valuation gap between a theoretical, freely traded asset and the actual, illiquid private security being appraised.

The Systemic Origins of the Discount

The requirement for a DLOM arises from several interconnected factors inherent in the structure of private capital markets. Understanding these components is essential to grasping the full impact on share value. The discount is a composite reflection of time, risk, and cost.

First, the time horizon for converting a private interest to cash is extended and uncertain. Unlike a public stock, which can be sold within days, a private holding may take months or even years to liquidate. This extended holding period exposes the investor to prolonged market and company-specific risk without the ability to exit the position.

The capital is, in effect, trapped for an unknown duration. Investors demand compensation for this loss of flexibility, and that compensation takes the form of a lower entry price, which is what the DLOM achieves.

Second, information asymmetry is a dominant feature of private markets. Public companies are subject to rigorous disclosure requirements, providing a continuous stream of audited financial data to the market. Private companies operate with significantly less transparency. An outside investor in a private entity has limited access to real-time performance data, creating a higher degree of uncertainty and perceived risk.

This information gap makes it more difficult for potential buyers to perform due diligence, which in turn limits the pool of willing purchasers and puts downward pressure on the achievable price. The DLOM partially accounts for the higher risk premium demanded by buyers to compensate for this lack of transparency.

Third, the costs associated with selling a private interest are substantial. Locating a suitable buyer, negotiating terms, and executing the legal transfer of shares is a resource-intensive process. It often involves legal fees, brokerage commissions, or advisory fees that are orders of magnitude higher than the transaction costs for public securities. These expected future costs are capitalized into the present value of the holding by applying a discount.

Marketability and Liquidity a Necessary Distinction

In this context, the terms marketability and liquidity are related but distinct. Liquidity often refers narrowly to the speed at which an asset can be converted to cash. Marketability is a broader concept, encompassing not only the speed of the transaction but also the certainty of the price and the magnitude of the associated costs.

A share might be sellable (liquid) within a few months, but if the process requires accepting a price that is substantially below an informed estimate of fair value, it lacks marketability. The DLOM therefore addresses the full spectrum of disadvantages associated with illiquid ownership, capturing the combined impact of delayed realization, price uncertainty, and high transaction costs.

Strategy

Strategically determining the appropriate DLOM involves moving from the conceptual understanding of illiquidity to its quantitative measurement. Valuation analysts employ several established frameworks to derive a supportable discount. These strategies are broadly categorized into empirical approaches, which rely on observational data from real-world transactions, and quantitative models, which use financial theory to calculate the discount. The choice of strategy depends on the available data, the specific characteristics of the subject company, and the requirements of the valuation assignment.

Empirical Approaches the Benchmark Studies

The foundation of DLOM analysis rests on empirical studies that observe the price differences between marketable and non-marketable securities. These studies provide objective, data-driven benchmarks that serve as a starting point for most valuation analyses.

Restricted Stock Studies

The most common empirical approach involves analyzing transactions of restricted stock. Restricted shares are identical to the freely traded common stock of a public company, except they are barred from sale on the open market for a specific period, typically six months to two years in the historical studies. By comparing the price at which these restricted shares are sold in private placements to the price of their publicly traded counterparts on the same day, analysts can isolate the discount attributable solely to the lack of marketability.

Numerous studies conducted over several decades have consistently documented significant discounts, with median discounts often ranging from 13% to 45%. The key insight from these studies is that the market demonstrably and consistently prices in a discount for the temporary loss of marketability.

Empirical data from restricted stock transactions provides direct evidence that the inability to trade freely has a direct, negative, and quantifiable impact on share price.

Pre-IPO Studies

A second source of empirical data comes from pre-initial public offering (pre-IPO) studies. These analyses compare the price of a company’s shares in private transactions occurring shortly before its IPO to the public trading price immediately following the IPO. The price appreciation observed from the final private round to the IPO price is used as a proxy for the marketability discount, under the assumption that the primary change in the intervening period was the creation of a public market for the shares.

These studies have often indicated higher average discounts than restricted stock studies, sometimes ranging from 21% to 66%. However, this method is subject to potential sample selection bias, as it only includes data from successful IPOs and may also capture elements of value creation or market sentiment unrelated to pure marketability.

The strategic application of these studies requires the analyst to select the most comparable data set. A valuation professional will consider the similarities between the subject private company and the companies included in the benchmark studies, looking at factors like industry, size, and profitability, to select a relevant baseline discount.

Quantitative Modeling the Option Pricing Framework

A more theoretical yet powerful strategy for quantifying the DLOM is the use of option pricing models. This approach frames the lack of marketability as a problem of lost opportunity. The holder of a non-marketable share is deprived of the ability to sell the share at will. This is economically equivalent to having written a put option on the share; the holder is forced to hold the asset and cannot sell it to protect against a decline in value.

The most well-known of these is the Chaffe Protective Put Method. This model calculates the DLOM as the cost of a European put option with a strike price equal to the current stock value and a term equal to the expected time to a liquidity event (e.g. an IPO or sale of the company). The value of this theoretical put option, expressed as a percentage of the stock’s value, represents the economic cost of being unable to sell. The key inputs for this model are:

• Stock Price ▴ The marketable value of the share before the discount.
• Term of Restriction ▴ The estimated time until the shares become marketable.
• Stock Volatility ▴ The expected volatility of the stock over the restriction period. Higher volatility implies a higher risk of value loss, thus increasing the value of the protective put and the DLOM.
• Risk-Free Rate ▴ The rate of return on a risk-free asset, used for discounting.
• Dividend Yield ▴ Expected dividends reduce the net cost of holding the stock, which can decrease the DLOM.

The primary advantage of this strategy is its ability to tailor the discount to the specific risk characteristics of the subject company, particularly its volatility and the expected holding period. It provides a more dynamic and company-specific result than simply applying an average discount from a historical study.

Which Factors Influence the Size of the Discount?

Regardless of the primary method used, the final strategic step is to adjust the indicated DLOM based on a set of specific factors related to the company and the ownership interest being valued. The benchmark studies themselves show that discounts vary widely, and this variance is explained by underlying characteristics. A thorough analysis requires a qualitative and quantitative assessment of these drivers.

A comprehensive valuation strategy integrates these approaches. An analyst might begin with a range of discounts from restricted stock studies, then use an option pricing model to generate a company-specific estimate, and finally, use the qualitative factor analysis to select and support a definitive DLOM within the indicated range. This multi-pronged approach provides a robust and defensible conclusion about the impact of illiquidity on private share value.

Execution

The execution of a DLOM calculation is a rigorous, multi-step process that demands analytical precision and sound judgment. It is where the strategic frameworks are translated into a definitive, defensible number. The process moves from a high-level, marketable valuation to a final, discounted value that reflects the specific constraints of the private share block in question. A failure in execution can lead to significant valuation errors and disputes, particularly in contexts like shareholder litigation, estate and gift taxation, and financial reporting.

The Valuation Analyst’s Workflow a Procedural Guide

A systematic workflow is critical to ensure that all relevant factors are considered and that the final conclusion is well-documented and supportable. This process can be broken down into a logical sequence of analytical steps.

1. Establish a Preliminary Value ▴ The starting point is always a base valuation of the equity on a marketable, minority interest basis. This is typically derived using standard valuation methodologies such as the Guideline Public Company Method, the Guideline Transaction Method, or a Discounted Cash Flow (DCF) analysis. This figure represents the theoretical value of the interest if it were freely tradable on a public exchange.
2. Analyze Company-Specific Risk Profile ▴ The next step is a deep dive into the subject company’s specific characteristics. This involves a thorough review of its financial health, management team, competitive position, and industry outlook. The goal is to assess the underlying volatility and risk associated with holding the asset over a prolonged period.
3. Evaluate the Liquidity Horizon ▴ The analyst must form a reasonable expectation for the likely holding period. This involves assessing management’s intentions, the likelihood of an IPO or strategic sale, and any shareholder agreements that might dictate a future liquidity event. A longer expected holding period will systematically increase the DLOM.
4. Select Primary and Corroborative Methods ▴ Based on the available data and the nature of the company, the analyst selects the primary valuation methods for the DLOM. For example, for a mature, stable company, benchmark studies might be most appropriate. For a high-growth, volatile technology company, an option pricing model may provide a more precise indication of the discount. It is common practice to use one method as the primary indicator and another as a check or corroborating evidence.
5. Derive an Initial DLOM Range ▴ The selected methods are used to calculate a preliminary range for the discount. This might be a 20-30% range based on restricted stock studies for companies in a similar industry, or a calculated 35% based on a protective put model.
6. Refine the DLOM with Company-Specific Factors ▴ This is a critical adjustment step. The analyst systematically compares the subject company’s attributes to the factors known to influence the DLOM. A formal analysis, often presented in a table, will score the company on various dimensions to justify moving to the high or low end of the preliminary range, or even outside of it.
7. Conclude and Apply the Discount ▴ The analyst concludes on a specific DLOM percentage, supported by the detailed analysis from the preceding steps. This percentage is then applied to the preliminary marketable value to arrive at the final, non-marketable value of the private shares.

Quantitative Modeling in Practice a Data Driven Example

To illustrate the execution, consider a hypothetical private software company, “SynthCo.” A preliminary DCF analysis has established a marketable minority interest value of $100 per share. The analyst must now determine the appropriate DLOM.

Step 1 ▴ Company-Specific Factor Analysis

The analyst first scores SynthCo on the key factors that influence the DLOM to provide a qualitative anchor for the quantitative models.

The overall qualitative assessment suggests that SynthCo should have a DLOM that is average to slightly above average compared to general market studies, primarily driven by its high volatility and lack of dividends.

Step 2 ▴ Applying the Chaffe Protective Put Model

The analyst decides to use the Chaffe model to get a more precise, company-specific estimate. The required inputs are determined as follows:

• Value of Share (Marketable) ▴ $100.00
• Time to Liquidity ▴ 2.5 years (based on management’s IPO discussion).
• Risk-Free Rate ▴ 3.0% (based on the 2.5-year Treasury yield).
• Dividend Yield ▴ 0.0% (as per company policy).
• Volatility ▴ 50% (estimated based on the volatility of a peer group of publicly traded software companies).

Using a Black-Scholes option pricing model with these inputs to value the at-the-money put option yields a value of approximately $32.40. When this cost of protection is divided by the marketable share price, the result is a DLOM.

Calculated DLOM = ($32.40 / $100.00) = 32.4%

How Does the Final Conclusion Get Formed?

The analyst now has several data points. Restricted stock studies might suggest a broad range of 20-40%. The factor analysis for SynthCo points towards a higher-than-average discount. The quantitative option model provides a specific estimate of 32.4%.

Given this confluence of evidence, the analyst can confidently conclude a DLOM of 32.5%. The final, non-marketable value of a SynthCo share is therefore calculated as $100.00 (1 – 0.325) = $67.50. This final value is not an arbitrary number; it is the output of a systematic process that quantifies and prices the very real economic constraints imposed by the lack of marketability.

Reflection

The analytical frameworks for quantifying a lack of marketability provide a necessary structure for valuation. They translate the abstract concept of illiquidity into a concrete financial adjustment. The true execution, however, moves beyond the models and into the realm of systemic judgment. The process forces a deep, fundamental analysis of an enterprise, not as a collection of discounted cash flows, but as an operational system with specific risks, opportunities, and structural constraints.

Reflecting on this process reveals the core tension in all valuation ▴ the intersection of objective data and subjective interpretation. The empirical studies provide the data; the quantitative models provide the logic. Yet, the selection of the right study, the right volatility input, or the right liquidity horizon remains an act of professional judgment. How does your own operational framework for capital allocation account for this?

Is liquidity risk treated as a static, average discount, or is it a dynamic input that is continuously reassessed based on the specific architecture of each investment and the evolving state of the market? The tools for its measurement are established; the strategic advantage lies in their masterful application.