Real Estate Appraiser Specializing in Commercial Industrial Residential Income Land & Single Family Residential Properties Existing or Proposed Construction Estate & Gift Tax Conservation Easements Partial Values Fractional Interests Former Senior Appraiser United States Treasury Department IRS Large Business and International Division California General Certified Real Estate Appraiser FHA Approved

Michael F. Ford #AG002512



E. Evaluation and Recommendations

DLOM Job Aid page 76

selection of valuation methods or parameters such should be looked at for the

underlying reasoning applied and the logic and flow of the judge’s thinking not for

the results that were finally reached. No two valuation assignments are identical.

Therefore, basing one’s results on the results of another assignment whether

litigated or not is a failure of proper diligence with regard to the assignment

presently at hand.

4. Sources available to IRS Valuation Analysts

It has been attempted to gather as many of the underlying studies and research

papers referenced in this job aid. Please refer to the Engineer DLOM shared

folder on the IRS intranet see Engineering Program National Shared folder for

information on mapping the network drive where these have been placed to your

computer.. See Exhibit D—DLOM Files on Shared Folder as of September 25,


DLOM online sources currently available51 are listed below. These have limited

access and have been purchased for one user—contact information is provided

at Engr BV Resources webpage.

Online databases:

FMV Restricted Stock Study

Valuation Advisors Pre-IPO database

FMV Restricted Stock Database—Analysis

The FMV Restricted Stock database of transactions is available for purchase,

and is utilized by valuators to estimate DLOM on privately-held business

interests. IRS Engineer, Tom Kelley, AVA, completed an analysis52 of the 475

transactions in the FMV Restricted Stock database in 2009. The purpose was a)

to analyze the FMV model for determining DLOM on private equity, and b) to

determine whether it is possible to develop a statistically valid regression-based

model to determine the DLOM. The conclusions drawn are:

1) FMV Opinions’ model is flawed insofar as explanation of the DLOMs on

the restricted stock transactions in their database;

2) Valuators cannot confidently rely on FMV’s model when determining

DLOMs on restricted stocks, much less on interests in private equity; and

3) Neither FMV’s model nor multivariate regression analysis can be applied

to FMV’s database to confidently determine the DLOM on private equity.

51 Resources require annual funding to maintain the license. Therefore budgetary limitations may require

that these subscriptions be canceled.

52 February 18, 2009 memo from Tom Kelley with the subject, “Update: FMV Opinion’s Model and

Database”. Copy is provided as an Exhibit to this job aid.

E. Evaluation and Recommendations

DLOM Job Aid page 77

Please refer to Exhibit A—Review FMV Restricted Stock Model in this job aid for

information on the process Tom Kelley followed in reaching his conclusions.

F. Summary

DLOM Job Aid page 78

F. Summary and Conclusions

This job aid was prepared to assist IRS valuators understand the numerous

studies and approaches used by valuation professionals to determine DLOM. We

have addressed restricted stock studies, the eldest type of study having been

developed in the early 1970’s. As the need increased to better quantify DLOM,

newer approaches are introduced, such as Liquistat (2007). While many of the

newer approaches are not currently used in professional practice, the

profession’s reliance could change in the future. In total, the job aid has

information on 23 different DLOM approaches.

DLOM has been defined as well as the factors that impact DLOM on a specific

interest. Sample IDR questions are provided. We have summarized each

approach, provided references, identified strengths and weaknesses, how the

Tax Court has ruled on the approach, and how prevalent its use in practice. In

addition, the job aid offers discussion points to use with Taxpayer appraisers to

focus on a specific method.

As is always the key, facts and circumstances surrounding the subject interest

are what determine the level of DLOM, if any. DLOM studies, methods and

models can be complex, can indicate widely diverse conclusions, and may be

appropriate in only certain limited situations. The business valuation profession

does not identify acceptable or unacceptable methods for estimating

marketability discounts, although some individual practitioners have their own

preferences and frequently disagree as to the best approach.

This job aid does not provide guidance on the best DLOM approaches, but is

meant to help the reader understand and make an informed decision about

DLOM. It is current as of the date of this writing.

For recommendations on the content included in this job aid, please contact any

of the members of the DLOM Team who were the developers.

Name POD

Mike Gregory, ASA, AVA

Engineering Territory

Manager St. Paul, MN

Sue Kurzweil, CPA, ASA

National Business Valuation

Issue Coordinator Independence, OH

Jeff Myers, ASA, AVA Engineering Team Manager Columbus, OH

Laura Goldberg, AVA Engineer Plantation, FL

Ernie DeRosa, AVA Financial Analyst New York, NY

James McCann, ASA Financial Analyst San Francisco, CA

Aberdeen Sabo Estate Tax Attorney Independence, OH

G. Bibliography

DLOM Job Aid page 79

G. Bibliography


Abbott, Ashok. “Empirical Measures of Marketability and Liquidity Discounts,

Discount for Lack of Marketability: An Empirical Analysis and DLOM – Concepts

and Models.” Presentations at Various ASA and NACVA Conferences and on the

BVR Teleconference of April 26, 2006. (available in shared folder)

Abbott, Ashok. “New Abbott Analysis Aids Valuators in Assessing Liquidity

Discounts.” Business Valuation Update. Vol. 13, No.11, Nov. 2007. (available in

shared folder)

Amihud, Yakov and Mendelson, Haim “Asset Pricing and the Bid Ask Spread”,

Journal of Financial Economics v17 (December 1986) pp. 223049. (available in

shared folder)

Bajaj, Mukesh, David J. Denis, Stephen P Ferris & Atula Sarin. Firm Value and

Marketability Discounts. Journal of Corporation Law. Vol 27, No.1. (available in

shared folder)

Barclay, Michael J., Clifford G. Holderness and Dennis P. Sheehan. “Private

Placements and Managerial Entrenchment.” Journal of Corporate Finance Vol.

13, 2007, pp. 461-484. (available in shared folder)

Cost of Flotation of Registered Issues 1971-1972. Securities and Exchange

Commission, 1974.

Dann, L.Y. and H. DeAngelo, 1988, Corporate Financial Policy and Corporate

Control: A Study of Defensive Adjustments in Asset and Ownership Structure,

Journal of Financial Economics, 20, 87-127

Edelman, Richard B. and H. Kent Baker, 1993, The Impact of Company Pre-

Listing Attributes on the Market Reaction to NYSE Listings, The Financial

Review, Vol. 28, No. 3, August 1993, 431-448

Emory, John D. Sr, F.R. Dengel, III. “Discounts for Lack of Marketability, Emory

Pre-IPO Discount Studies 1980-2000 as Adjusted October 10, 2002.” Business

Valuation Review, Vol. 21 No. 4, (December 2002). (available in shared folder)

Feldman, Stanley Jay. “Revisiting the Liquidity Discount Controversy:

Establishing a Plausible Range.” Bentley College and Axiom Valuation Solutions.

(available in shared folder)

G. Bibliography

DLOM Job Aid page 80

Finnerty, John D. “The Impact of Transfer Restrictions on Stock Prices.” Fordham

University, Presentation at the Meeting of the American Finance Association,

2003. (available in shared folder)

Frazier, William. "Non-marketable Investment Company Evaluation (NICE)."

Valuation Strategies. November/December 2006. Vol 10, No 2. (available in

shared folder)

Garland, Pamela J. and Ashley L. Reilly. “Update on the Willamette

Management Associates Pre-IPO Discount for Lack of Marketability Study”.

Available, April 30,


Gomes, Armando and Gordon Phillips. “Why Do Public Firms Issue Private and

Public Equity, Convertibles and Debt?” Presentation at the Research Seminar in

Law, Economics, and Organization, 2005. (available in shared folder)

Hall, Lance. “New Tactics Required to Prove Discount for Lack of Marketability.”

The Value Examiner, Jan-Feb 2007, pp 36-39. (available in shared folder)

Hall, Lance S. and Timothy C. Polacek, “Strategies for Obtaining the Largest

Valuation Discounts”, Estate Planning, Vol. 21 No. 1, January/February, 1994.

(available in shared folder)

Hall, Lance, 2004, “The Discount for Lack of Marketability: An Examination of Dr.

Bajaj’s Approach”, BV Update, March 2004. (available in shared folder)

Hertzel, Michael and Richard Smith. “Market Discounts and Shareholder Gains

for Placing Equity Privately.” Journal of Finance, Vol. 48, 1993, pp. 459-485.

(available in shared folder)

Keys, Phyllis and Norris Larrymore. “Integration of Private and Public Offerings.”

Presentation at the Conference of the Eastern Finance Association, 2004.

(available in shared folder)

Koeplin, John, Atulya Sarin and Alan Shapiro, 2000, “The Private Company

Discount, Journal of Applied Corporate Finance, Volume 12, Number 4, Winter

2000, 94-101. (available in shared folder)

Longstaff, Francis A. “How much Can Marketability Affect Security Values?” The

Journal of Finance, December 1995, pp. 1767-74. (available in shared folder)

Mitchell, Mark and Mary Norwalk, 2008, “Assessing and Monitoring Bajaj”,

Business Valuation Review 27-1, Spring 2008.

G. Bibliography

DLOM Job Aid page 81

Pratt, Shannon , 2004, “The McCord Case and the Bajaj Method”, Unpublished

Conference Call Pre-Read. (available in shared folder)

Pratt, Shannon , Chris Mercer, Lance Hall and Rob Oliver, 2004, “DLOM: A

Critique of the Bajaj Approach”, BVR Teleconference April 2004

Pratt, Shannon, 2004, “Defending Discounts for Lack of Marketability”, ACTEC

Journal 2004, 276. (available in shared folder)

Pratt, Shannon, 2003, “Discounts for Lack of Marketability: Documentation,

Critique and Defense”, American Society of Appraisers International Appraisal

Conference, July 2003

Reilly, Robert. “Update on Study of Discount for Lack of Marketability”. American

Bankruptcy Institute Journal, June 2005, Value and Cents

Reilly, Robert and Aaron Rotkowski, “Discount for Lack of Marketability: Update

on Current Studies and Analysis of Current Controversies”. Fall 2007, Tax

Lawyer, Vol 61, No. 1. (available in shared folder)

Ritter, Jay R. “The Costs of Going Public.” Journal of Financial Economics, Vol.

19, No. 2 (December 1987), pp. 269-81. (available in shared folder)

Robak, Espen. “Discounts for Illiquid Shares and Warrants: The LiquiStat

Database of Transactions on the Restricted Securities Trading Network.” Pluris

Valuation Advisors White Paper, January 2007. (available in shared folder)

Robak, Espen. Liquidity and Levels of Value: A New Theoretical Framework.”

BV Update, October, 2004. (available in shared folder)

Paschall, Michael A. Discounts for Lack of Marketability: A Review of Studies and

Factors to be Considered. Fair Value, September 1994.

Sanger, Gary C. and John J. McConnell, “Stock Exchange Listings, Firm Value,

and Security Market Efficiency: The Impact of NASDAQ”. The Journal of

Financial and Quantitative Analysis, Volume 21, Issue 1, March 1986, 1-25

Saunders, Philip. “Marketability Discounts and Risk in Transactions Prior to Initial

Public Offerings”. Business Valuation Review. Volume 19, No. 4, December

2000, pp 186-195. (available in shared folder)

Seaman, Ronald M. “Minimum Marketability Discounts—2nd Edition.” Business

Valuation Review. June 2005, pp. 58-64.

G. Bibliography

DLOM Job Aid page 82

Seaman, Ronald M. “Minimum Marketability Discounts—3rd Edition.” September

2007. Available at August 18, 2009. (available in

shared folder)

Seaman, Ronald M. “Minimum Marketability Discounts—4th Edition, A Study of

Discounts for Lack of Marketability Based on LEAPS Put Options in November

2008.” September 2007. Available at August 18, 2009.

(available in shared folder)

Silber, William, 1991, “Discounts on Restricted Stock: The Impact of Illiquidity on

Stock Prices”, Financial Analysis Journal, 47, 60-64. (available in shared


Tabak, David. “A CAPM-Based Approach to Calculating Illiquidity Discounts.”

Available , November 11, 2002.

Trout, Robert R. “Minimum Marketability Discounts.” Business Valuation Review.

September 2003, pp. 124-126. (available in shared folder)

Trout, Robert R. “Estimation of the Discount Associated with the Transfer of

Restricted Securities.” Taxes. June, 1997, pp. 381-384. (available in shared


Wruck, Karen Hopper. “Equity Ownership Concentration and Firm Value:

Evidence from Private Equity Financings.” Journal of Financial Economics Vol.

23, 1989, pp. 3-28. (available in shared folder)


Kasper, Larry J. Business Valuations: Advanced Topics. Greenwood Publishing

Group. 1997. Chapter 5 Premium and Discounts.

Mercer, Z. Christopher, Quantifying Marketability Discounts: Developing &

Supporting Marketability Discounts in the Appraisal of Closely Held Business

Interests, Peabody Publishing, LP, 1997.

Mergerstat Review, FactSet Mergerstat, LLC, 2006.

Pratt, Shannon P., Robert F. Reilly, Robert P, Schweihs. Valuing A Business.

The Analysis and Appraisal of Closely Held Companies, 5th ed. New York:

McGraw-Hill, 2008.

Pratt, Shannon P. Business Valuation Discounts and Premiums. New York:

John Wiley & Sons, Inc., 2001.

G. Bibliography

DLOM Job Aid page 83


Howard, Frazier, Barker, Elliot, Inc. (


NERA (National Economic Research Associates) (

Options Education ( )

Partnership Profiles (aka “Partnership Spectrum”) (

Table 1 page 84

Table 1 Analysis of SEC Institutional Investors Restricted Stock Study


REFERENCE - Institutional Investor Study ("SEC Study") data1

Discounts on Purchase Price of Restricted Common Stock

( see note [2] )

================ Range of Discounts by Respective Groupings ================

-15% to 0% discount 0% to 10% discount 10% to 20% discount 20% to 30% discount 30% to 40% discount 40% to 50% discount 50% to 80% discount

Transactions As a Transactions As a Transactions As a Transactions As a Transactions As a Transactions As a Transactions As a

Average Total in this Percent in this Percent in this Percent in this Percent in this Percent in this Percent in this Percent

Discount Transactions Grouping of Total Grouping of Total Grouping of Total Grouping of Total Grouping of Total Grouping of Total Grouping of Total

26% 398 26 6.5% 67 16.8% 78 19.6% 77 19.3% 67 16.8% 35 8.8% 48 12.1%

Weighted-average "Discount"

( see note [3] ) Grouping Respective Grouping Respective Grouping Respective Grouping Respective Grouping Respective Grouping Respective Grouping Respective

Discount Weighting Discount Weighting Discount Weighting Discount Weighting Discount Weighting Discount Weighting Discount Weighting

-7.5% 6.5% 5.0% 16.8% 15.0% 19.6% 25.0% 19.3% 35.0% 16.8% 45.0% 8.8% 65.0% 12.1%

26% Weighted-Average Discount

greatest weighting within these two groupings

( see note [4] )





Source: Quantifying Marketability Discounts, by Z. Christopher Mercer, ASA, CFA, Peabody Publishing, LP , 1997, Exhibit 2-1, page 70.

Data range includes a low of -15% (a negative discount), to a high of 80% discount.

Greatest weighting of transactions occurs within the 15% and 25% implied discount groupings, suggesting a most-common discount of 20%.

Calculated result equals the reported 26% "Average Discount".

Table 2 page 85

Table 2 Analysis of MPI Restricted Stock Study


REFERENCE - Management Planning Study data1

Analysis of Restricted Stock Discounts by Revenue Size


Number of Revenues Average Range of Discounts

Revenues Observations ($ Millions) Discounts Low High

Under $10 Million ( see note [2] ) 14 $6.6 32.9% 2.8% 57.6%

$10 - $30 Million 11 $22.5 30.8% 15.3% 49.8%

$30 - $50 Million 10 $35.5 25.2% 5.2% 46.3%

$50 - $100 Million 8 $63.5 19.4% 11.6% 29.3%

Over $100 Million (Adjusted) * 4 $224.9 14.9% 0.0% 24.1%

Overall Sample Averages $47.5 27.7% 0.0% 57.6%

Totals 47

* Over $100 Million (Actual Calculation) 2 $187.1 25.1% 0.0% 46.5%

Totals 49

Excludes Sudbury Holdings, Inc., whose private placement consisted of 125% of the pre-transaction shares outstanding.

Excludes Starrett Housing Corp., which is one of the five most thinly traded companies in the sample.



Source: Quantifying Marketability Discounts, by Z. Christopher Mercer, ASA, CFA, Peabody Publishing, LP , 1997,

Figure 12-1, page 346.

Discounts for the smallest companies occurred over a range of [2.8% – 57.6%].

Exhibit A page 86

Exhibit A—Review FMV Restricted Stock Model

DATE: February 18, 2009

TO: Mike Gregory, Program Manager, Field Specialists West

Sue Kurzweil, National Business Valuation Issue Coordinator

THRU: Robin Ruegg, Manager, Field Specialists Team 1864

FROM: Tom Kelley, Engineer, Field Specialists Team 1864

SUBJECT: Update: FMV Opinions’ Model and Database

This memorandum is a summary of the results of my two-part assignment 1) To

analyze FMV Opinions’ (FMV) model for determining the discount for lack of

marketability (DLOM) on private equity, and 2) To determine whether it is

possible to use FMV’s 475-transaction database to develop a statistically valid

regression-based model to determine this discount.

It begins with a description and critique of FMV’s model, continues with a

discussion of multiple regression, and concludes with a statement as to whether

multiple regression can be applied to FMV’s database in order to confidently

ascertain the DLOM on private equity.

The bottom line of my inquiry is threefold:

1) FMV Opinions’ model is flawed insofar as explanation of the DLOMs on

the restricted stock transactions in their database;

2) Valuators cannot confidently rely on FMV’s model when determining

DLOMs on restricted stocks, much less on interests in private equity; and

3) Neither FMV’s model nor multivariate regression analysis can be applied

to FMV’s database to confidently determine the DLOM on private equity.

LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 87

Description of FMV Opinions’ Model

My understanding of FMV’s model is based on two articles by Espen Robak,

CFA (Robak): “Marketability discounts: Using four measures of risk and adjusting

for relative liquidity” and “FMV introduces detailed Restricted Stock Study.”53

These are not included, but are available upon request.

Following are four quotes from these two articles that explain FMV’s thinking and

methodology. The first three are from “Marketability discounts: Using four

measures of risk and adjusting for relative liquidity”:

. . . there are inherent and significant differences between the liquidity of

restricted stock and the liquidity of . . . private equity . . .

We determine the “restricted stock equivalent” discount, given the financial

characteristics of the company . . . We determine the incremental discount

for the privately held company . . . based on a review of the most illiquid

(i.e., large-block) restricted stock issues.

We must adjust for the fact that private equity is more illiquid than the

typical block of restricted stock in a public company.

In terms of liquidity, large blocks are essentially like private equity.

The last is from “FMV introduces detailed Restricted Stock Study”:

. . . the discounts for restricted stock with longer-than-average holding

periods are particularly applicable to privately held securities. The only

question is “How do we isolate the transactions with longer holding periods

from the rest of the sample? The answer is: “by looking at transactions in

large blocks until 1997.”

Attachment 1 is a 1-page summary of FMV’s two-step methodology as it was

explained in Robak’s article, “FMV introduces detailed Restricted Stock Study.”

With rounding, the 50% DLOM in cell G59 is the same as the final indicated

DLOM in Robak’s article.

In short, FMV’s model is based on the proposition that the DLOM on private

equity is a function of firm characteristics (rows 9-31 in Attachment 1), and the

incremental difference between discounts on the smaller and larger blocks of

restricted stock (rows 36-50). Certain related cells have been identified by

shading to enable the reader to more easily follow the less obvious calculations.

Critique of FMV Opinions’ Model

Here are three major problems with FMV Opinions’ model, and then eight less

consequential questions and comments.

53 The second article appeared in Shannon Pratt’s Business Valuation Update, November 2001, pp. 1-3. I

don’t know

where the first one appeared.

LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 88

Major Problems

1) FMV has not shown that block size is a statistically reliable proxy for

quantifying the supposed difference in liquidity between restricted stocks

and private equity.

2) The first step in FMV’s analysis (rows 9-31 in my Attachment 1) is

intended to account only for the financial risk characteristics of the

subject entity, but it also reflects block size. The second step (rows 36-

50) is intended to segregate and quantify the impact of block size, but it

is also influenced by the same financial risk characteristics in the first

step. While meant to be separate steps, the two are interrelated and,

therefore, corrupted by each other.

3) According to Robak’s article, the first step in FMV’s analysis is to

“determine the ‘restricted stock equivalent’ discount given the financial

characteristics of the company . . .” The tables in Robak’s article – and

on lines 11-14 in my Attachment 1 - show four such firm characteristics.

The discounts in the 475-transaction survey given me are inconsistent

with this purpose because they are a function of both firm characteristics

(such as Z-score54 and Earnings Before Interest, Taxes, Depreciation

and Amortization (EBITDA)), and issue characteristics (such as pershare

offering amount, and block size as a percent of total shares.) They

are the discounts on particular offerings, and not indicators of

marketability or lack thereof.

Other Questions and Comments

4) There is not a statistically significant relationship between discounts to

market value and the four risk characteristics in Robak’s article. I

regressed the discounts in the database against market values, marketto-

book (MTB) ratios, net profit margins, and dividend yields, and found a

0.0238 R-square55, coefficients’ signs contrary to economic theory, and

an F-statistic low enough that the regression equation could not be relied

on even at the 10% level of significance56.

5) Selection of how many and which particular firm characteristics to

include in the model, appears subjective, and has not been explained.

Robak has only noted “we use different indicators in different situations.”

6) FMV has not shown why survey quintiles are the best way – or even a

reliable way – of extrapolating survey results to a subject outside the

54 Developed in 1968 by Edward I. Altman, Ph.D., Z-score is a formula for predicting bankruptcy and a

numerical indicator of a firm’s financial health.

55 R-square, or coefficient of determination, is a measure of the degree of association between the response

variable (the discount) and independent variables, as a whole. By comparison, the most often quoted

minimum acceptable R-square is 0.80.

56 The F-test is a comparison of the F-statistic and critical values of F at various significance levels. In this

case, 1.293 vs 1.972 F-critical at the 10% significance level means one couldn’t even be 90% certain that

the regression equation explains observed discounts.

LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 89

survey. Why weren’t quartiles or deciles or multiple regression used


7) The restricted stock equivalent on line 15 in Attachment 1 is dependent

on whether the analyst chooses to use quintiles or some other measure.

One would get a different result using, say, quartiles or deciles.

8) The example in Robak’s article - and summarized in my Attachment 1 –

did not include the characteristic thought by them57 to be most correlative

with marketability: stock price volatility.

9) FMV Opinions did not explain why they used medians instead of means.

10) FMV Opinions did not explain why they used “additive” and

“multiplicative” calculations to determine the Private Company Increment

in step 2. Why not just one or the other?

11) FMV Opinions didn’t explain how they selected the matching

transactions in rows 17-23. It’s presumed that these were the only

transactions in the same factor quintiles.

The last eight of these factors question FMV’s model. The first three disprove it.

Regression Analysis

Robak refers to regression analysis in his article, “Marketability discounts: Using

four measures of risk and adjusting for relative liquidity”, but he doesn’t explain

why FMV’s model doesn’t use it, or go on to discuss it in either of his articles.

I reviewed FMV’s 475-transaction spreadsheet58 and found two combinations of

firm and issue characteristics that, arguably, do result in regression models that

explain the observed discounts in these transactions. These are in my

Attachments 2 and 3.

Attachment 2 shows that, collectively, stock price volatility, per-share offering

price, offering as a fraction of total shares outstanding, and offering dollar

amount, could be used to make predictions of discounts for restricted stock

transactions outside the database. The 22.20 F-statistic, significant even at the

1% level (22.20>3.36), indicates that one could be 99% confident that this

combination is related to the discount in a restricted stock transaction.

In regard to interests in private equity – which is more often the subject of IRS

valuations - this model is lacking because -

1) It could not be used to determine lack-of-marketability discounts on

interests in private companies; and

57 BVR April 2006 Telephone Conference: “Discounts for Lack of Marketability”, Page 2.

58 Of the 563 trillion combinations of firm and issue characteristics in the 53-column, 49-

“driver”spreadsheet, I tested approximately thirty of the most promising combinations of characteristics.

LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 90

2) According to a number of authors (most of whom have Ph.D.’s in

economics)59, it does not control for (isolate and quantify) the nonmarketabilty

determinants of observed discounts. Unlike the traditional

Restricted Stock Approach, these two studies suggested that only a

portion of the overall discount represents a lack-of-marketability.

With the second limitation of Attachment 2 in mind, I tested other combinations of

characteristics to see if there might be a combination which does control for nonmarketability

factors. Of the combinations of characteristics I looked at60, the

model in Attachment 3 comes closest to allowing for determination of the DLOM

on interests in private equity.

This model is adequate in that -

The F test indicates that, collectively, this combination of characteristics is

adequate for prediction of the DLOM on restricted stock.;

All four coefficients are consistent with economic theory; and

By differentiating between stocks with registration rights and stocks without

registration rights, the “Registered vs Restricted” term61 serves the

purpose of quantifying the impact of marketability.

Unfortunately, this model, too, is lacking. While it could have been argued that

the DLOM on restricted stock is 2.42%62 were it not for the registration indicator’s

statistically unacceptable 0.188 P-value, the registration indicator’s high P-value

(greater then 0.1) invalidates use of this model for determining DLOMs.

Summary – Attachments 2 and 3

While there are at least two combinations of firm and issue characteristics in

FMV’s database that adequately explain the discounts in it, neither can be used

to predict the lack-of-marketability discount on an interest in a private company.

The regression models in Attachments 2 and 3 both fail because of the difference

between private equity and the restricted stocks in FMV’s database. The model

in Attachment 2 also fails because it does not include “registration indicator”,

arguably the only variable that measures marketability. The model in Attachment

3 also fails because the P-value of the “registration indicator” renders this model

less than a reliable predictor.

59 Bajaj, et al “Firm Value and Marketability Discounts”, 27 J. Corp. L. 89, 98 (2001) and Hertzel and

Smith’s “Market Discounts and Share holder Gains for Placing Equity Privately”, 48 J. Fin. 459 (1993).

60 This included holding period, offering price, block size, stock price volatility, z-score, retained earnings,

market value, revenues, and whether or not registered.

61 Also called the “registration indicator.”

62 The coefficient of “r.”

LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 91


FMV Opinions’ 2-part model is based on the proposition that the DLOM on

private equity is the sum of –

The relationship between the financial risk characteristics of, and the

discounts on restricted stocks; and

The difference between the discounts on smaller and larger blocks of


Three of the more important problems with FMV Opinions’ model are:

1) FMV has not shown that block size is a statistically reliable proxy for the

supposed difference in liquidity between restricted stocks and private


2) The two steps in FMV Opinions’ model are interrelated and, therefore,

corrupted in that they are both influenced by firm characteristics and by

block size; and

3) The discounts in FMV’s database are the discounts on particular offerings,

comprised of marketability and non-marketability factors, and not

necessarily indicators of marketability or the lack thereof.

Applying multivariate regression analysis to FMV’s database, I found two

combinations of four firm and issue characteristics which could be used, with

some degree of statistical certainty, to explain the discounts in FMV’s study.63

The difference between them is that the model in Attachment 3 includes

“registration indicator”, the variable certain authors64 believe is the only one

measuring marketability.

Whether looking at the model in my Attachment 2 or the model in my Attachment

3, or whether one agrees with the proposition that the registration indicator,

alone, measures marketability, the fact is:

1) FMV Opinions’ model cannot be used to reliably predict lack-ofmarketability

discounts on restricted stock transactions, much less interests

in private equity; and

2) No one – FMV using their methodology, or someone using regression

analysis – could use FMV’s database to confidently predict lack-ofmarketability

discounts on either restricted stock transactions or interests in

private equity.

If you have any questions, please contact me at 651-726-1512

Tom Kelley

63 The 0.17 R-square notwithstanding. It is less than problematic because of the large number of data


64 Bajaj et al and Hertzel and Smith.

LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 92




Step 1 - Restricted Stock Equivalent Basis

9 Dimension Variable Subject Company Median Discount -

10 Value Quintile Subject Company's Quintile

11 Size Market Value $15,000,000 5 37.3%

12 Risk Market-to-Book Ratio 8.5X 2 29.5%

13 Profitability Net Profit Margin 9% 1 15.5%

14 Distributions Dividend Yield 5% 1 13.1%

15 Average = Indicated Restricted Stock Equivalent, Part A 24%


17 Matching Quintiles Private

18 Companies Market Market-to-Book Net Profit Dividend Placement

19 Value Ratio Margin Yield DLOM

20 Company A 5 = 5th quintile 2 = 2nd quintile 1= 1st quintile 1= 1st quintile 29.3%

21 Company B 5 2 1 1 42.6%

22 Company C 5 2 1 1 18.9%

23 etc. 5 2 1 1

24 Reconciled/Indicated Restricted Stock Equivalent - Part B 32%



27 Restricted Stock Equivalent Discount Indicated by Quintile Medians, Part A 24%

28 Restricted Stock Equivalent Discount Indicated by Matching Companies, Part B 32%

29 Restricted Stock Equivalent Discount, Average of Parts A and B

30 (The discount at which the company would issue restricted stock, if it were a public company 28%

31 with the same financial risk characteristics



34 Step 2 - Private Company Increment


36 Percent of Shares Placed Median Additive Multiplicative Indicated

37 Discount DLOM

38 Small Block Sample 27.2% NA NA NA

39 More than 25% 35.3% 8.1% 1.3 35%

40 More than 30% 47.7% 20.5% 1.8 49%

41 More than 35% 59.0% 31.8% 2.2 60%


43 Additional Private Company Adjustment

44 Percent of Shares Placed ( Adjustment for the fact that private equity is more illiquid than the

45 typical block of restricted stock in a public company. Based on

46 presumption that large blocks are essentially like private equity.)

47 Small Block Sample NA

48 More than 25% 8%

49 More than 30% 22%

50 More than 35% 33%



53 Reconciliation - Selected Discount for Lack of Marketability - Private Equity


55 Private Company Increment

56 Step 1 Restricted Stock Median Discount, Step 2 Indicated

57 Equivalent Discount Small Block Indicated Step 2 Difference DLOM

58 Sample DLOM (Step1 + Step 2)

59 28% 27.2% 49% 22% 49% - 27.2% 50% = 28% +


LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 93


Following are the regression equation and a tabular presentation of model

validity statistics regarding a regression-based model that, arguably, explains the

discounts in FMV’s 475-transaction database.

The relatively low R-square term notwithstanding, this model is arguably

adequate because -

Compared to the 22.2 F-statistic, the critical values of F indicate that,

collectively, these four variables explain the observed discounts;

All of the coefficients have signs that are consistent with economic theory;


The P-values are such that there is a 95% probability that there is a strong

relationship with the discount for three of them, and a 90% probability that

there is a strong relationship for the fourth.

d = 0.1505 + 0.0490v – 0.0016s + 0.3948p – 0.000000000636a

where d = discount

v = stock price volatility

s = offering price per share

p = offering as a % of pre-offering shares outstanding

a = offering amount

R- Square Term * 0.1612

F- Statistic 22.20

10% 1.96

F-critical @ ___ 5% 2.39

Significance Level 2.5% 2.21

1% 3.36

Volatility 8.81E-11

P-Values Offering $/Share 0.0357

Block Size - % of Total Outstanding 0.0001

Offering Amount 0.0601

* Note: While 80% is the most widely quoted minimum R-square, the 16% Rsquare

in this case is less important than the F-test and the P-values.

LMSB:FS:ENG:Team 1864;TPK February 2009

Exhibit A page 94


A Regression-based Model That 1) Controls for the Non-marketability

Components in Discounts to Market Price in Restricted Stock

Transactions, and 2) Isolates the Lack-of-Marketability Component

Regression Equation

d = 0.1143 + 0.0878v – 0.0020s + 0.4186p – 0.0242r

where d = discount

v = stock price volatility

s = offering price per share

p = offering as a % of pre-offering shares outstanding

r = registration indicator (1 if the stock was issued with

registration rights, and 0 if the stock was NOT

issued with registration rights)

Model Validity Statistics

R- square Term 0.1703

F- Statistic 16.98

10% 1.96

F-critical @ ___ 5% 2.40

Significance Level 2.5% 2.82

1% 3.38

Registered vs Restricted 1.88E-01

P-Values Offering $/Share 3.45E-04

Block Size - % of Total Outstanding 7.50E-05

Volatility 4.38E-07


These four variables explain 17% of the variation in the discounts in this

sample. While 80% is the most widely quoted minimum, the 17% R-square

in this case is less important than the F-test and the P-values.

The 16.98 F-statistic, significant even at the 1% level (16.98>>3.38),

indicates that collectively, one can be 99% confident that these four

characteristics influence discounts.

The P-values of three of these are far less than 1%.

The reason why this model is arguably better than the model in Attachment

2, but still inadequate for determining the DLOM on interests in private

equity, is discussed on Page 5.

Exhibit B page 95

Exhibit B—Pre-IPO Studies

Willamette Management Associates65 (WMA) Original: A series of

studies on the prices of private stock transactions relative to those of

public offerings of stock of the same companies. The studies covered the

years 1975 through 1997.

(*) Excludes the highest and lowest deciles of indicated discount

Willamette Management Associates (WMA) Subsequent: Over the last

several years, Willamette Management Associates conducted 12 studies

on the prices of private stock transactions relative to those of subsequent

offerings of stock of the same companies. The 12 studies covered the

years 1975 through 1992. Each private transaction was compared with the

subsequent public offering price. In one of the studies, Willamette checked

trading prices six months after the initial public offering to see whether the

IPO prices were upwardly or downwardly biased compared to a more

seasoned market price. While after six months some prices increased and

some decreased, the average change from the IPO price was


65 Willamette’s studies are unpublished. However, the summary tables are presented in Business Valuation

Discounts and Premiums, Chapter 5, by Shannon Pratt (New York: John Wiley & Sons, Inc., p. 85).



Number of


Number of


Standard Mean









1975-78 17 31 34.0 43.3 52.5 58.6

1979 9 17 55.6 56.8 62.7 30.2

1980-82 58 113 48.0 51.9 56.5 29.8

1983 85 214 50.1 55.2 60.7 34.7

1984 20 33 43.2 52.9 73.1 63.9

1985 18 25 41.3 47.3 42.6 43.5

1986 47 74 38.5 44.7 47.4 44.2

1987 25 40 36.9 44.9 43.8 49.9

1988 13 19 41.5 42.5 51.8 29.5

1989 9 19 47.3 46.9 50.3 18.6

1990 17 23 30.5 33.0 48.5 42.7

1991 27 34 24.2 28.9 31.8 37.7

1992 36 75 41.9 47.0 51.7 42.6

1993 51 110 46.9 49.9 53.3 33.9

1994 31 48 31.9 38.4 43.0 49.6

1995 42 66 32.2 47.4 58.7 76.4

1996 17 22 31.5 34.5 44.3 45.4

1997 34 44 28.4 30.5 35.2 46.7

Exhibit B page 96

The findings of the Willamette studies are summarized in the following














1991-1993 443 54 45% 44%

1990-1992 266 35 42% 40%

1989-1990 157 23 45% 40%

1987-1989 98 27 45% 45%

1985-1986 130 21 43% 45%

1980-1981 97 13 60% 55%

All Studies 1,191 173 N/A N/A

Of the twelve (12) studies conducted by Willamette, each compared pre-

IPO transactions to the IPO price in estimating the marketability discount.

One study went one-step further by observing price changes in the

publicly-traded stocks six-months subsequent to the IPO. Although this

one study found that after six months the change in the subject stock

prices from the IPO prices were insignificant; a six month time period

allows for market and company specific conditions to change. It should be

noted that no conclusions regarding marketability discounts were based

on the post-IPO pricing.

Robert W. Baird & Company Studies (Emory) Original: John D. Emory

of Robert W. Baird & Company conducted pre-IPO studies. The studies

covered various time periods from 1981 through 1997. The basic

methodologies for the eight studies were identical. The population of

companies in each study consisted of initial public offerings during the

respective period in which Baird & Company either participated or

received prospectuses. The prospectuses of these over 2,200 offerings

were analyzed to determine the relationship between (1) the price at which

the stock was initially offered to the public and (2) the price at which the

latest private transaction occurred up to five months prior to the IPO.

In 2002, John Emory updated his studies in an article titled, "Discounts for

Lack of Marketability, Emory Pre-IPO Discount Studies 1980-2000 as

Adjusted October 10, 2002.”66 This source also has “expanded” and “Dot-

Com” data for 1997-2000.

66 Business Valuation Review, Vol. 21 No. 4 (December, 2002).

Exhibit B page 97

A summary of Emory’s Pre-IPO studies is shown below:













1997-2000 1847 36 48 44

1995 - 1997 732 91 43 42

1994 - 1995 318 46 45 45

1991- 1993 443 54 45 44

1990 - 1992 266 35 42 40

1989 - 1990 157 23 45 40

1987 - 1989 98 27 45 45

1985 - 1986 130 21 43 43

1980 - 1981 97 13 60 66

All 9 studies 4,088 346 46 % 45 %

Exhibit C page 98

Exhibit C–Analytical Approach Revisited

Other Reviewed Studies

An introduction to the analytical approach to estimating the discount for lack of

marketability was provided in the main body of this job aid. This Exhibit provides

summaries of six additional studies that utilize an analytical approach. These

summaries are included herein for the interested reader who may want a further

background in this growing area of analysis into understanding the mechanics of

corporate capital formation.

The authors and dates of the included studies are:

John D. Finnerty – 2003

Michael J. Barclay, Clifford G. Holderness and Dennis P. Sheehan – 2007

Phyllis Keys and Norris Larrymore – 2004

Armando Gomes and Gordon Phillips – 2005

Stanley Jay Feldman – Undated

Espen Robak – 2007

The study summaries are followed by a commentary on the strength and

weaknesses of these types of studies. However, these studies are basically

academic in nature and are not traditionally used by the valuation community to

set discount numbers. Nor have they been vetted in any meaningful way by the


John D. Finnerty, 2003, The Impact of Transfer Restrictions on Stock

Prices, Fordham University, Presentation at the Meeting of the

American Finance Association

Finnerty was interested in the impact of transfer restrictions on stock prices and

set about to investigate the factors responsible for the discount when

unregistered shares of common stock are privately placed. He analyzed a

sample of 101 private placements of transfer-restricted stock all of which involved

unregistered shares. Finnerty postulated that the following factors influenced the

size of required placement discounts:

-Volatility of the publicly traded stock of the entity

-Length of the restriction period

-Risk-free interest rate

-Dividend yield

-Information requirements

-Ownership concentration effects

Exhibit C page 99

His premise was that, beyond marketability concerns, a discount compensates

an investor for the due diligence and monitoring costs required by the

investment, the effects due to ownership structure change and the implied

certification effect of having a private investor choose the firm for investment.

Finnerty asked the question that, if the proper discount is as large as is implied

by the so-called benchmark studies, why don’t arbitrageurs enter the market, use

hedging opportunities and capture a guaranteed profit? He believed that the

existence of the equity derivative markets has acted to significantly reduce the

discounts that might have existed in earlier years.

Finnerty’s analysis covered private placements during the period January 1, 1991

through February 3, 1997 and involved 101 placements of which 77 were either

traded on NASDAQ or over-the-counter. His measurement dates were 10 trading

days prior to the announcement date and the day prior. The average discounts

calculated were 20.13% for the day prior measurement and 18.41% for the 10

day prior measurement. The respective median discounts were 15.50% and


A regression analysis was performed which indicated that the most significant

variables influencing total discounts are the volatility of the stock and the length

of the restriction period. Finnerty concludes based on this analysis that a range of

discounts from 25% to 35% is proper for moderate volatility stocks (30% to

120%) but that this range is too high for low volatility stocks (<30%). For low

volatility stocks (20% to 30%), he found the following ranges to apply:

-Dividend paying: 11.5% to 16.0%

-Non-Dividend paying: 15.8% to 20.1%

These ranges apply assuming a 2 year holding period; if a 1 year holding period

is assumed the discounts are reduced by about 50%.

Finnerty found no significant relationship between the discount amount and the

regression variable representing ownership concentration. This is consistent with

the findings of Hertzel & Smith but contrary to the findings of Wruck.

Michael J. Barclay, Clifford G. Holderness and Dennis P. Sheehan,

2007, Private Placements and Managerial Entrenchment, Journal of

Corporate Finance 13, 461-484,

These researchers studied the question of private placements and managerial

entrenchment. Their premise was that many private placements are made to

facilitate management entrenchments rather than for benefiting the firm from

monitoring and certification services provided by the involved investors. The

thesis of using private placements at discounts to entice investment by allies to

management was earlier advanced by Dann & DeAngelo and by Wruck.

Exhibit C page 100

Whereas the monitoring and certification effects hypotheses are favorable to

existing shareholders, the management entrenchment hypothesis is not.

Barclay et al believe that although private placements result in short-term positive

effects on firm value, the long-term effect is negative and leads to firm value

declines. Most private placement investors are seen as passive with only about

12% estimated to be active participants in firm governance and management

persuasion efforts.

These researchers analyzed data from the years 1979 through 1997 and

considered only those placements involving more than 5% of outstanding

common stock. Some 594 placements were identified with the investors

classified as 12% active, 5% managerial and 83% passive. The average discount

found was 18.7% from traded value with a median discount of 17.4%. The

various kinds of investors had discount ranges as follows:

-Active: 1.8% average and 7.5% median

-Managerial: 24.2% average and 18.2% median

-Passive: 20.8% average and 19.5% median

Barclay et al found that registration status is not a substantial factor in the

discount amounts.

Private placements reduce the chances of a downstream acquisition or merger

by about 50%. There is no distinction in this statistic based on the kinds of

investors involved.

Trades of significant sized blocks of stock in the public market were also studied

with 204 data points considered. Investors acquiring interests in such trades

were more likely to take an active role in the firm and these investments were

more likely to lead to a downstream acquisition. These types of trades were also

more likely to be opposed by management since it has no control over who the

buyers might be.

Per Barclay et al, the cost of private placements is about two times the cost of a

seasoned (non-IPO) equity offering when discounts and out-of-pocket costs are

considered. This is not the most cost effective way to raise capital and gives

support to the thesis that management is proceeding in this way for its own

protection and betterment. Passive investors are considered the norm for private

placements per Barclay since such represent over 80% of the investors in the

transactions study. Thus, they believe that the discounts required by passive

investors are most representative of reality.

Exhibit C                                                                            page 100

Phyllis Keys and Norris Larrymore, 2004, Integration of Private and

Public Offerings, Presentation at the Conference of the Eastern

Finance Association

Keys and Larrymore studied the question of integrating public and private share

offerings to receive the best overall effect with regard to the raising of capital.

They note that private placements relate to a less restrictive offering process but

also involve asymmetry of information between investors and management.

Public offerings require more complete information to be available to investors

but also require more disclosure and a less flexible issuing procedure. SEC Rule

155 instituted in March 2001 grants issuers more flexibility to offer securities

privately following a public offering and vice versa. In general, the market

responds positively to private offerings and negatively to seasoned public


Keys and Larrymore studies a total of about 1,020 equity offerings for 2000 and

2002 (before Rule 155 and after Rule155). Some 710 of these were public

offerings and about 310 were private offerings. They found that there is a

significant difference in the two day market reaction to private as compared to

public offerings both before and after Rule 155. There is, however, no significant

long-term (120 day) difference.

This conclusion relates to the work of Wruck, Hertzel & Smith and Bajaj et al as

these researchers made their measurements very close to the announcement

date and did not include a longer-term perspective. Analyzing the Keys result

would indicate that much of the discount found for private offerings may be due

to a short term bounce effect that gradually disappears.

Armando Gomes and Gordon Phillips, 2005, Why Do Public Firms

Issue Private and Public Equity, Convertibles and Debt? Presentation

at the Research Seminar in Law, Economics and Organization

Gomes and Phillips (G & P) were interested in the question of why public firms

issue various kinds of equity, convertibles and debt using both public and private

issuance modes. They believe that asymmetric information effects and moral

hazard problems play a large role in the public versus private market choice and

the security type choice. In the private market, they find that firms with high

measures of asymmetric information are more likely to issue equity where the

public market would prefer debt. Firms with high risk, low profitability and good

investment opportunities for acquired capital are more likely to issue equity

and/or convertibles publicly than to do so privately. Private securities give

investors more incentives to produce information and also to monitor the firm.

Exhibit C page 102

Gomes and Phillips studied 13,000+ security issuances with more than half in the

private market where public companies were the issuers. They used the

accuracy of analyst earnings predictions and the dispersion of analyst errors as a

proxy for asymmetric information effects for private equity and convertibles and

for public debt. They hypothesized that public debt and all kinds of private

offerings serve a “disciplining” function for management due to increased


Per Gomes and Phillips, the level of abnormal returns (returns above average)

should be positively correlated with the degree of information asymmetry for

private offerings; the more information sensitive the security’s value, the stronger

the correlation should be. As risk rises in a firm’s operations it will tend to move

from public debt to private debt and from private debt to convertibles to raise

capital. Private equity is issued when risk levels rise to the point where it is the

last alternative. Agency problems between management and shareholders

increase the need for the use of debt or private equity placements to prevent

management distortions and abuses.

The G & P database consisted of 13,282 issuances during the period January

1995 through December 2003 and involved 4,137 different firms. No secondary

offerings or short-term offerings were included. It was determined that the market

reacts most favorably to private equity issuances and least favorably to public

equity issuances. Once again, this finding indicates that the discount found with

regard to private placements as opposed to public traded prices may result from

a short-term bounce effect that then disappears with time. Marketability may not

be a significant concern in the overall picture.

Stanley Jay Feldman, Revisiting the Liquidity Discount Controversy:

Establishing a Plausible Range, Bentley College and Axiom

Valuation Solutions

Feldman focused his attention on the liquidity discount controversy and worked

to establish a plausible range for such discounts. He found the following in


-Minority privately held C Corp shares have a liquidity discount in the area

of 14%

-Minority S Corp shares are less liquid than C Corp shares

-Control shares of a C Corp have discounts in the area of 20%

-Discounts >30% for any share blocks are not supported by research

Feldman believes that liquidity may be as important as risk in determining stock

returns. Investors demand discounts for lack of liquidity as compensation for their

higher costs of trading. Liquidity can be measured by the increase in share price

if an OTC firm gets listed on the New York Stock Exchange (NYSE) but such a

Exhibit C page 103

rise in stock price can also be due to other factors such as information signaling

(the willingness to disclose) and certification by seasoned investor buy-ins.

Feldman examines abnormal returns to control for the effects of overall market

movements. He reviews the data from a 1966-1970 study by Sanger and

McConnell on movements from OTC trading to the NYSE since in this timeframe

the NASDAQ did not yet exist. In this study an implied liquidity discount of 20%

was found based on an overall set of cumulative abnormal returns of 25.68%. Of

these abnormal returns analysis indicates that about 14% are due to lack of

liquidity and about 11% are due to information signaling. The liquidity effect is

estimated based on a 1982-1989 study by Edelman and Baker on stocks moving

from the NASDAQ to the NYSE.

The 14% level of abnormal returns converts to a straight liquidity discount of

about 12%. This is seen as being a floor for liquidity discount since there are

shares that need to be analyzed that are not traded on any exchange. For these

shares, Feldman believes that a 3% additional abnormal return amount is

appropriate implying an added discount of 2.5% and resulting in an overall

liquidity discount of 14.5% for these kinds of shares.

Feldman notes that this is close to the discount derived by H & S for lack of

marketability (13.5%) but is much lower than the discounts implied by the pre-

IPO and Restricted Stock Studies of >35%. He believes that there are a myriad

of problems with these latter studies that make them very unreliable including

high ranges among results and wide coefficients of dispersion that make the use

of measures of central tendencies (averages and medians) generally


Feldman cites a study by Koeplin et al that estimates marketability discounts for

control interests in the range of 18% to 30% with a reasonable estimate of the

average at 20%. He believes that an additional increment of <5% should be

added on for S Corp shares. Finally, he concludes that for pure liquidity

estimation purposes, control blocks are less liquid than minority blocks with the

difference being about 5.5% (20% for control versus 14.5% for minority).

However, he admits that minority blocks might give rise to higher overall

discounts due to the effects of information signaling and certification.

Espen Robak, 2007, Discounts for Illiquid Shares and Warrants: The

LiquiStat Database of Transactions on the Restricted Securities

Trading Network, Pluris Valuation Advisors White Paper, January


Robak postulates that it is not possible to precisely sort out the effect of illiquidity

from all of the factors contributing to total discounts in private placement

transactions, be they of registered shares or unregistered shares. Instead, he

analyzes a specially constructed database referred to as LiquiStat which

incorporates data on investor to investor trades of restricted securities rather than

Exhibit C page 104

trades involving the issuer as the seller. By using investor to investor trades he

believes that he has eliminated the effects of information asymmetry, of firm

financial condition and of assessment and monitoring costs since both buyer and

seller should be on equal ground as far as knowledge of the firm and its financial

conditions are concerned. He argues that this is the pricing concept that should

be involved in fair market value where both buyer and seller are hypothetical

persons and are considered to be equally knowledgeable of the conditions

surrounding the trade transaction.

The LiquiStat database was compiled from April 2005 to December 2006 and

contains information on 61 investor to investor trades. All investors are

independent with no firm affiliates represented in any of the trades. Analysis of

the data provides the following results with regard to discounts for the traded

shares as compared to the present public market price of those shares.

Average Discount 32.8%

1st Quartile Discount 19.1%

Median Discount 34.6%

3rd Quartile Discount 44.0%

The average fraction traded in the population was 0.47%, the average stock

volatility was 89% and the average remaining restriction period was 138 days.

Robak notes that these results are higher than those found by Hertzel & Smith,

Bajaj et al and Finnerty and hypothesizes that this is because the shares studied

were more volatile and had longer required holding periods than is often the case

for restricted stock private placements where registration is often a condition of

the placement. Per the LiquiStat data, there is a clear and increasing relationship

between the discount and the remaining required holding period, although the

increase tends to flatten out over time. For a 25 day holding period the discount

range is 16% to 24% while for a one year holding period the discount range is

30% to 57%.

Based on his data, instead of supporting the premise that others have advanced

that private placement discounts are too high to represent the effects of illiquidity

alone, Robak suggests that they instead may be too low. Having eliminated the

other causes of discounting through the construction of his database, he feels

that the statistics derived should represent a measure of the illiquidity discount in


Exhibit C page 105

General Strengths and Weakness of Exhibit C Studies

One of the strengths that is attributable to the analytical approach to DLOM and

DLOL is that the studies underlying the approach were not made for tax

purposes or by practitioners in the generally recognized tax valuation community.

They were instead primarily academic exercises aimed at better understanding

operating company capitalization choices and effects. Thus, there was generally

no attempt made to either support or criticize the traditional benchmark study

approach or to promote a new approach that could be marketed for application in

tax service engagements.

A second strength is the attempt to pursue the question in an analytical manner

and to parse the discounts found into contributing components. Although overall

discounts were found and summary statistics identified, the researchers were

more interested in the causes of the discounts than in the pure size of the

discounts. Various theses were advanced as to why discounts exist with DLOL

and DLOM only being one set of contributing factors. Also mentioned were

assessment costs, monitoring costs, management entrenchment motives,

investor expectations and certification compensation. The attempt to break out

actual discount portions for these components was not necessarily successful

but the conclusion that all of a given measured discount may not measure simply

the lack of marketability is important.

Another potential strength is that the several researchers took several different

approaches to sample selection and measurement such that the effects of these

parts of the discount estimation process can be considered as part of the overall

discount evaluation process. A valuator can make his or her own determination

based on the facts and circumstances under study as to how data selection

should be handled and how discount measurement can best be made.

The studies all suffer from the same kinds of weaknesses that make the actual

numerical results achieved difficult to rely upon. These weaknesses result from

problems in sample selection, problems in sample point classification, problems

in discount measurement point selection, problems in variable selection,

problems in variable estimation and the use of certain proxy variables with a

binary quantification attribute. The various models also result in less than

impressive data fits as measured by such things as R2. In many cases the

number of available data points is small and large time frames are required to

yield an adequate number of data points for analysis. Many of the studies do not

consider factors that would seem from a common sense point of view to have

significant impact on discounts such as required holding periods and the volatility

of the stock as publicly traded. Finally, although the fact that the studies were not

made for tax purposes was cited as a possible strength, it is also a potential

weakness in that it is dangerous to apply the results of a study made for one

purpose to entirely different purposes.

Exhibit D page 106

Exhibit D—DLOM Files on Shared Folder

(as of September 25, 2009)

Folder Subfolder Filename DLOM

Job Aid




Restricted Stock


FMV Opinions 2001 study.pdf D.1.a

FMV Opinions-Hall & Polacek 1994articles.rtf





Management Planning Inc.TIF


SEC Investor Study (1).pdf

Silber Impact on Liquidity.pdf

Standard Research Consultants.TIF


Pre-IPO Studies Philip Saunders Associates D.1.b

EmoryPreIPODiscount.pdf D.1.b

Cost of Flotation ritter cost of going public modified version.pdf D.1.d

Ritter cost of going public original.pdf D.1.d

N/A Robak-LiquidityFramework-BVUOct2004.pdf

(Restricted Stock Equivalent Analysis)




LEAPS BVWire #76-3 Seaman comments LEAPS



BVWire #76-4 LEAPS-Fuhrman responds to






N/A chaffee dlom article.pdf D.2.c

N/A Longstaff-How Much Can Marketability Affect

Security Values.pdf




N/A Abbott-BVUpdate-




N/A Abbott-




Bajaj Bajaj Denis Ferris Sarin.pdf D.3.c

Subfolder: Response to Bajaj

(Contains 4 articles)


Exhibit D page 107


Folder Subfolder Filename DLOM

Job Aid


N/A Hertzel & Smith.doc D.3.b

N/A Wruck Article.pdf D.3.a

Other Analytical


Subfolder: Liquistat

(Contains 1 article)

Exhibit C



Koeplin-Sarin-Shapiro article-Prvt Co Disct.pdf



Public and Private Placements(Keys).pdf

Public v. Private Issuances(Gomes).pdf




NERA NERA Tabak’s working paper.pdf D.4.c

NICE 1 of 4 NICE.pdf

2 of 4 NICE.pdf

3 of 4 NICE.pdf

4 of 4 NICE.pdf


NICE_Frazier_2008ASA-AICPA_presentation.pdf D.4.b

Other DLOM


N/A CurrentStateofMarketabilityDiscounts.pdf n/a

Hall-NewTacticstoProveDLOM-Value Examiner Jan-






reilly rotkowski DLOM update on current studies.pdf n/a

Rotkowski Current Contrversies Regarding DLOM.pdf n/a



Contains 15 files n/a

Files provided

at 09-18-08


Summit in

San Diego

Numerous files of seminar presentations n/a


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