Finnerty vs Chaffe DLOM Models: Which Discount Is Defensible in 2026?

Picking the right Discount for Lack of Marketability, or DLOM, is one of the toughest calls in valuing a private company.

Get it wrong, and the entire report can unravel under IRS review, in court, or during a Big 4 audit.

Two models dominate this decision: the Chaffe model and the Finnerty model. Both use option-pricing math to estimate how much value illiquidity strips away from a private share. Yet they rarely land on the same number.

This gap matters. A 10-point swing in DLOM can shift a startup’s 409A strike price, an estate’s taxable value, or a divorce settlement by hundreds of thousands of dollars. Whether you’re a founder issuing stock options, a CFO preparing an audit, or an estate attorney filing Form 706, understanding which model applies – and why – protects you from costly disputes.

This guide breaks down both models in plain language, shows the exact math behind each one, walks through a real calculation, and explains what regulators and courts expect to see in 2026. At Transaction Capital LLC, our ABV, ASA, CVA, and MRICS credentialed appraisers apply both models daily across 409A, estate, and litigation engagements – so this comes from practice, not just theory.

Key Takeaways

• DLOM measures the value lost because a private share can’t be sold quickly, unlike a public stock.
  
• The Chaffe model uses a European put option and generally produces a higher discount.
  
• The Finnerty model uses an Average Strike (Asian) put option and typically produces a more moderate discount.
  
• Neither model is officially “preferred” by the IRS, courts, or valuation standards – defensibility depends on documentation and reasoning, not the model’s name alone.
  
• Typical Finnerty-based DLOM ranges in 2026, run from roughly 12% at late-stage/pre-IPO to 45% at seed stage, driven mainly by volatility and expected holding period.
  
• DLOM is different from DLOC (Discount for Lack of Control) – the two should never be merged into one blended number.
  
• Most experienced appraisers apply multiple models and reconcile the results with empirical market data, rather than relying on a single formula.
  

The Enduring Importance of DLOM in Valuation

A Discount for Lack of Marketability captures the simple fact that a private company’s share is harder to sell than a public one. A public shareholder can exit any trading day at a known price. A private shareholder is often locked in for years, waiting for an acquisition, an IPO, or a secondary sale that may never happen.

DLOM puts a dollar figure on that waiting cost. In a 409A valuation, DLOM is applied specifically to the common stock value, since common shares sit at the bottom of the capital structure and usually carry tighter transfer restrictions than preferred shares held by institutional investors.

Getting DLOM right matters for three reasons:

1. It sets your employees’ strike prices. Too low for a DLOM, and the IRS may argue options were granted in-the-money, triggering the 20% penalty tax on recipients under Section 409A.
2. It affects deals and estate math. DLOC and DLOM discounts together can reduce a taxable gift or estate value by 20-40%, but only when properly documented and empirically supported.
3. It shifts under scrutiny. Auditors, courts, and IRS examiners increasingly expect discounts tied to real economic reasoning, not a flat “industry standard” percentage.

A quick but important distinction – DLOM is not the same as DLOC (Discount for Lack of Control). DLOC reflects the reduced value of a minority stake that can’t control company decisions. DLOM reflects illiquidity.

Both discounts can apply to the same interest, but they measure different things and should never be blended into a single, undocumented number. In most 409A engagements, the Option Pricing Model (OPM) allocation already reflects the minority nature of common stock, so DLOM is typically the only additional discount layered on top.

Because these variables differ from so much company to company, a flat “rule of thumb” discount – like a blanket of 20% – rarely holds up. Over the past two decades, the profession has shifted from relying only on empirical studies toward using structured, quantitative option-pricing models like Chaffe and Finnerty, layered with real market data.

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What Are the Three Categories of DLOM Methods?

Before comparing Chaffe and Finnerty directly, it helps to understand where they fit in the bigger picture. Appraisers generally draw on three categories of evidence when concluding a DLOM.

1. Empirical restricted stock and pre-IPO studies. These examine real transaction data – how much less investors paid for restricted shares compared to freely tradable ones.

Long-standing studies (including the Silber study from the 1990s) and databases maintained by firms like FMV Opinions and Pluris typically show discounts in the 15-35% range. Pre-IPO studies from firms such as Willamette Management Associates have documented discounts of 20-45% by comparing pre-IPO transaction prices to the eventual IPO price. These studies act as a real-world sanity check against quantitative models.

2. Quantitative option-pricing models. These treat illiquidity as a mathematical problem: not being able to sell a share is economically similar to giving up a put option that would otherwise protect you against a price decline. The three most-cited models in this category are Chaffe (European put), Finnerty (Average Strike/Asian put), and Longstaff (a theoretical upper-bound model sometimes used to bracket the top of a reasonable DLOM range).

3. Appraiser judgment. Even the best formula needs a human to select defensible inputs – volatility, holding period, capital structure nuances – and to weigh the quantitative output against the empirical data. This is where credentialed, experienced judgment separates a defensible report from a mechanically generated number.

Understanding the Chaffe Model

Developed by David Chaffe in the 1990s, the Chaffe model applies to the Black-Scholes option-pricing framework to estimate DLOM. It treats the discount as the theoretical cost of a put option that would protect an investor from price declines over the expected holding period.

Key inputs include:

• Expected holding period (time to liquidity)
  
• The underlying asset’s volatility
  
• The length of the transfer restriction (often tied to estimated time to liquidity)
  
• Risk-free interest rates
  
• Dividend yield (usually minimal for growth-stage companies)
  

Of these, volatility and holding period drive most of the outcome. Higher volatility or a longer wait for liquidity both push the DLOM higher, since the investor bears more risk while unable to exit.

Why appraisers like it: The Chaffe model has a strong theoretical foundation in established financial economics, and it’s relatively simple to apply. It’s frequently cited in valuation literature and used across estate and gift tax, financial reporting, and litigation engagements.

Its limitations: Chaffe assumes a single liquidity event occurs at the very end of the holding period – it doesn’t account for price movement along the way. It’s also highly sensitive to the volatility assumption used, so small changes in that input can swing the result significantly. For this reason, most appraisers pair Chaffe with empirical evidence rather than relying on it alone.

The Exact Chaffe Formula

For those who want the underlying math, the simplified Chaffe model can be expressed as:

DLOM = 1 − 2 × N (−σ × √T / 2)

Where:

• N () = the standard normal cumulative distribution function (the same function used in Black-Scholes)
  
• σ = annualized volatility of the comparable public equity
  
• T = the restriction period, expressed in years
  

Because Chaffe prices the full volatility path to a single terminal put option, it typically produces a higher DLOM than Finnerty for the same inputs – often by a meaningful margin.

The Finnerty Model: A Forward-Looking Perspective

Developed by Michael (John D.) Finnerty and published in 2012, the Finnerty model is an option-pricing approach that estimates DLOM using an Average Strike Put (ASP) option – sometimes called an Asian put option – instead of the standard European put option used in Chaffe.

The logic here is subtle but important: an investor holding a restricted security isn’t just exposed to the price on one future date. They experience the entire path of prices throughout the restriction window and are locked out of acting on any of them. Finnerty argued that pricing the discount based on the average expected price over that window, rather than a single terminal price, better reflects real investment risk.

Like Chaffe, Finnerty requires assumptions about expected holding period, volatility, risk-free rate, dividend yield, and current value of the underlying interest.

But because it smooths price movement across the full holding period, it typically produces a more moderate DLOM – especially for companies with high volatility.

Why it’s gaining traction: The Finnerty model is considered a more sophisticated framework precisely because it captures ongoing price risk rather than a single snapshot. It’s referenced directly in the AICPA Practice Aid on valuing privately held company equity securities, which gives appraisers confidence that regulators and auditors are already familiar with the approach.

The Exact Finnerty Formula

The simplified Finnerty DLOM formula is:

DLOM = 1 − 2 × N (−σ × √(T/3) / 2)

Where the variables are the same as above (N = standard normal CDF, σ = volatility, T = restriction period in years), except the time variable is divided by 3 before the square root is taken.

That single adjustment – averaging price movement across the holding period instead of pricing only the terminal outcome – is the entire mathematical difference between Finnerty and Chaffe, and it’s why Finnerty almost always produces a lower number.

A note on inputs: Since private companies don’t have observable market volatility, appraisers typically derive σ from a basket of comparable public companies in the same industry and stage, using a historical lookback period that roughly matches the expected restriction period. Typical volatility inputs for venture-backed companies range from roughly 55% to 120%, depending on industry and stage – the same volatility figure often used in the OPM allocation itself.

Worked Example: Calculating DLOM for a Growth-Stage Startup

To make this concrete, here’s a simplified walkthrough for a hypothetical Series B fintech company, 20 months post-round, with no active exit process underway.

Step	Calculation	Result
1. Select volatility (σ)	Median of comparable public fintech peers	σ = 65%
2. Set restriction period (T)	Series B, no active exit process	T = 2.5 years
3. Compute Finnerty core term	0.65 × √(2.5/3) / 2	≈ 0.2967
4. Apply N()	N(−0.2967)	≈ 0.3834
5. Finnerty DLOM	1 − 2 × 0.3834	≈ 23.3%
6. Compute Chaffe core term (for comparison)	0.65 × √2.5 / 2	≈ 0.5140
7. Chaffe DLOM	1 − 2 × N(−0.5140)	≈ 39.5%
8. Apply Finnerty result to common stock	$5.10/share × (1 − 0.233)	≈ $3.91/share

Cross-checking against restricted stock study ranges of roughly 20-35% for a company at this stage confirms the Finnerty output of 23.3% falls within a reasonable, defensible band. The Chaffe result of roughly 39.5% sits meaningfully higher – illustrating exactly why the model choice matters and why many appraisers present both figures alongside empirical data rather than picking one in isolation.

Comparative Analysis: Finnerty vs Chaffe in 2026

Both models are grounded in option-pricing theory and aim to quantify the economic cost of illiquidity. Where they diverge is in how each one models the path of marketability risk – and that difference shows directly in the final discount.

Chaffe prices a hypothetical European put option, assuming the investor is only protected at the very end of the holding period. Finnerty prices an Average Strike Put option, recognizing that price swings throughout the restriction window also matter.

The practical result: Chaffe generally produces higher DLOM estimates, especially for volatile companies or long expected holding periods. Finnerty tends to produce more moderate discounts by smoothing out short-term price swings.

Factor	Chaffe Model	Finnerty Model
Option Type	European Put	Average Strike (Asian) Put
Volatility Treatment	End-of-period only	Averaged over the full holding period
Formula	DLOM = 1 − 2N(−σ√T/2)	DLOM = 1 − 2N(−σ√(T/3)/2)
Complexity	Moderate	Higher
Typical DLOM Output	Generally higher	Generally moderate
Best Suited For	Traditional, single-event valuations	Complex or highly volatile businesses

Neither model is universally “better.” The right choice depends on the facts of the engagement, the reliability of available inputs, and the valuation purpose. Many appraisers run both models side by side, compare the spread, and reconcile the results with empirical market evidence before reaching a conclusion – exactly as shown in the worked example above.

Typical DLOM Ranges by Funding Stage in 2026

Founders and CFOs often ask what DLOM range is “normal” for a company on their stage. While every engagement is fact-specific, the following ranges reflect common outputs seen in 2026 practice, driven mainly by expected time to liquidity and comparable-company volatility.

Stage	Typical DLOM Range	Key Drivers
Pre-Revenue / Seed	30-45%	Longest expected holding period (3-5 years), highest peer volatility
Series A	22-35%	Demonstrated product-market fit, but exit still years away
Series B / C	15-25%	Cleaner exit path, more operating history, shorter expected holding period
Late-Stage / Pre-IPO	10-20%	Short restriction period tied to lockup, IPO probability weighting

A company assuming a DLOM far outside these bands – for example, a pre-revenue seed startup claiming a 10% discount – should expect that assumption to draw scrutiny from auditors or the IRS unless it’s backed by unusually strong documentation.

Practical Application: When Should Each Model Be Used?

Choosing between Finnerty and Chaffe comes down to the facts of the valuation, not a blanket preference for one method.

Chaffe tends to work well when a straightforward option-pricing approach is sufficient, and both the expected holding period and volatility can be reasonably estimated. Its simplicity and long track record make it a practical fit for many estate and gift tax valuations, shareholder transactions, and financial reporting engagements.

Finnerty tends to work better where marketability risk is expected to shift over the restriction period – particularly for companies with higher volatility or uncertain liquidity timing. By incorporating average price behavior across the holding window, it often produces a more refined estimate of the true economic cost of illiquidity.

Regardless of which model an appraiser selects, professional judgment remains the deciding factor. The reliability of any DLOM conclusion depends far more on the quality of the underlying assumptions – expected holding period, volatility source, liquidity expectations – than on which formula name appears in the report.

Many valuation professionals use both models together as part of a broader framework, reconciling results with empirical evidence, company-specific characteristics, and the purpose of the engagement before finalizing a conclusion.

What Are the Most Common Mistakes in DLOM Calculations?

Even with the right model selected, several recurring errors can make a DLOM conclusion vulnerable to challenge:

• Using an unrealistically short holding period. Assuming a 12-month exit for a Series A company with no specific plans in place will artificially shrink the DLOM – and IRS examiners are familiar with this tactic.
  
• Applying the discount at the wrong stage of the analysis. DLOM belongs to the post-allocation common stock value – after an OPM or PWERM has already split total equity value between share classes – not on total enterprise value beforehand.
  
• Relying on a single model with no cross-check. A DLOM based purely on Finnerty or Chaffe, without comparison to restricted stock or pre-IPO study data, can be mathematically sound yet still fall outside a range of regulators to consider reasonable.
  
• Leaving out the documentation. Under Treasury Regulations Section 1.409A-1(b)(5)(iv), the chosen DLOM method, its specific inputs, and the reasoning behind them must all be spelled out in the written report. An undocumented number, however accurate, does not satisfy the independent appraisal safe harbor standard.
  
• Blending DLOM and DLOC into one number. As noted earlier, these are separate adjustments addressing separate risks. Merging them into a single combined discount typically understates the true value impact of each.
  

Regulatory and Judicial Trends in 2026

Neither the Finnerty nor the Chaffe model is officially prescribed by valuation standards, tax authorities, or the courts as the “preferred” DLOM methodology. What matters instead is whether the chosen approach fits the specific facts of the engagement and rests on reasonable, well-documented assumptions.

Courts and regulators generally expect appraisers to explain their methodology, justify every key input, and reconcile their conclusion with available market evidence. A model applied mechanically, without adequate support, is far more likely to draw a challenge than a well-reasoned analysis built on any one method.

In short: the credibility of a DLOM conclusion rests less on which model name appears in the report, and more on the depth of the supporting analysis, documentation, and professional judgment behind it.

Why Professional Judgment Matters

Analytical models give appraisers a valuable structure for estimating DLOM, but no formula replaces experienced professional judgment. The reliability of any marketability discount ultimately comes down to the reasonableness of the underlying assumptions, the quality of available data, and the appraiser’s ability to interpret results in context.

At Transaction Capital LLC, we don’t believe DLOM should ever come from a single model or a preset percentage. Our analyses combine option-pricing models, empirical market evidence, and company-specific factors to reach conclusions that are economically sound, transparent, and defensible.

Every engagement follows USPAP, AICPA SSVS No. 1, IVS, and other applicable professional standards.

Led by Dr. Gaurav B. (ABV, ASA, CVA, MRICS), our team has completed more than 2,500 valuation engagements across startups, privately held businesses, complex financial instruments, and intangible assets – delivering independent opinions for tax, financial reporting, litigation, and transaction purposes across 50+ industries.

Best Practices for Defensible DLOM Conclusions in 2026

Regardless of which model you use, a well-supported DLOM should rest on sound assumptions, reliable data, and documented professional judgment. The following practices strengthen the credibility of any DLOM conclusion:

• Select models based on the characteristics of the subject of interest, not a default habit.
  
• Document every input, data source, and adjustment rationale in detail.
  
• Run sensitivity and scenario analyses to demonstrate the result holds under different assumptions.
  
• Reconcile results across multiple methods and empirical studies rather than relying on one number.
  
• Factor in qualitative considerations that affect real-world marketability.
  
• Engage independent, credentialed experts to preserve objectivity and credibility.
  
• Stay current with emerging data sources, IRS guidance, and judicial trends.
  

Conclusion

The Finnerty and Chaffe models remain two of the most widely recognized approaches for estimating a Discount for Lack of Marketability. Both are grounded in option-pricing theory, yet they treat marketability risk differently and can produce meaningfully different results under the exact same assumptions.

There’s no universally “correct” model. The right approach depends on the characteristics of the subject of interest, the purpose of the valuation, the quality of available data, and how reasonable the underlying assumptions are.

In many engagements, applying multiple methodologies side by side – as shown in the worked example above – and reconciling the results produces a more balanced, defensible conclusion.

Ultimately, a credible DLOM comes down to the quality of the analysis and the judgment behind it, not the formula name. By pairing analytical models with empirical data and company-specific insight, valuation professionals can build marketability discounts that are held under scrutiny from auditors, tax authorities, courts, and other stakeholders.

Transaction Capital LLC applies exactly this reconciled approach across every 409A, estate and gift tax, and litigation valuation engagement – backed by flat-fee pricing starting at $500, 3-5 business day turnaround, and our Pay After Draft Review guarantee.

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Frequently Asked Questions

1. What is a Discount for Lack of Marketability (DLOM)?

A DLOM reflects the reduction in value of an ownership interest because it can’t be readily sold in an active market. It compensates investors for the added risk, time, and uncertainty of holding an illiquid investment.

2. What is the primary difference between the Finnerty and Chaffe models?

Chaffe values a hypothetical European option. Finnerty uses an Average Strike Put option that accounts for price movement throughout the expected holding period.

3. Which model generally produces a higher DLOM?

Under similar assumptions, Chaffe usually produces a higher DLOM because it’s more sensitive to volatility. The exact result always depends on the specific inputs used.

4. Which model is more widely accepted?

Both are well-recognized in the valuation profession and supported by option-pricing theory. Neither is considered universally superior to the other.

5. Should a valuation rely on only one DLOM model?

Not necessarily. Many appraisers evaluate multiple methods, compare results against empirical market evidence, and apply professional judgment before finalizing a conclusion.

6. What factors have the greatest impact on DLOM?

Key factors include expected holding period, asset volatility, transfer restrictions, anticipated liquidity events, dividend policy, and overall market conditions.

7. Can DLOM vary for companies in the same industry?

Yes. Companies in the same industry can warrant different DLOMs due to differences in size, financial performance, governance, liquidity prospects, and shareholder rights.

8. Are empirical studies still relevant?

Yes. Restricted stock and pre-IPO studies continue to offer valuable market evidence and are typically used alongside option-pricing models to support a final DLOM conclusion.

9. Does higher company risk automatically mean a higher DLOM?

Not always. Higher volatility can raise the DLOM under option-pricing models, but the final discount should reflect all relevant company- and market-specific factors, not one variable alone.

10. Which model is better for startup valuations?

There’s no single answer. The right model depends on the startup’s expected liquidity timeline, volatility, financing stage, and the purpose of the valuation.

11. Can auditors or tax authorities reject a DLOM analysis?

Yes. A DLOM can be challenged if the methodology, assumptions, or documentation aren’t adequately justified. A well-reasoned analysis generally matters more than which model was used.

12. Why is professional judgment important in estimating DLOM?

Models provide structure, but they can’t capture every company-specific circumstance. Judgment is essential for selecting appropriate assumptions, interpreting results, and reaching a defensible discount.

13. What is a typical DLOM range for a seed-stage startup?

Seed-stage companies typically fall in the 30-45% range, driven by long expected holding periods and high comparable-company volatility. A DLOM well below this range usually needs strong supporting justification.

14. Is DLOM the same as DLOC (Discount for Lack of Control)?

No. DLOM reflects illiquidity, while DLOC reflects the reduced value of a minority, non-controlling interest. Both may apply to the same interest, but they should be documented and applied as separate adjustments.

15. How does volatility affect the Finnerty DLOM calculation?

Higher volatility increases the calculated DLOM. Because volatility is averaged over the holding period in the Finnerty formula, the effect is more moderate than in the Chaffe model, where volatility is applied to a single terminal price.

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