On the Pricing of Mandatory DCF Disclosures: Evidence from Oil and Gas Royalty Trusts*

Panos N. Patatoukas panos@haas.berkeley.edu

Richard G. Sloan

richard_sloan@haas.berkeley.edu

Jenny Zha jenny_zha@haas.berkeley.edu

University of California at Berkeley Haas School of Business

This Version: October 28, 2014

                                                            

* We thank Korcan Ak, Eric Allen, Mary Barth (editor), Asher Curtis, Patricia Dechow, Efthimios Demirakos, Peter Easton, Dimitrios Ghicas, Maria Loumioti, Jody Magliolo (discussant), Sarah McVay, George Patatoukas, Jason Zweig from the Wall Street Journal, anonymous reviewers, and seminar participants at Athens University of Economics and Business, U.C. Berkeley, USC Marshall School of Business, University of Notre Dame, University of Washington, and the 2014 AAA Annual Meeting for helpful discussions. Panos gratefully acknowledges financial support from the Center for Financial Reporting & Management and the Hellman Fellows Fund. We also thank Robert Oberst and Carl Richard from the oil and gas consulting firm Miller and Lents, Ltd for helpful discussions. We appreciate the comments and suggestions of the Evening & Weekend MBA Students at Haas enrolled in Panos’ course on Financial Information Analysis (Fall 2014).

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On the Pricing of Mandatory DCF Disclosures: Evidence from Oil and Gas Royalty Trusts

ABSTRACT

We identify a novel setting in which firms are required to disclose discounted cash flow (DCF) valuations relating to their primary assets. ASC 932 (formerly SFAS No. 69) has mandated DCF valuation disclosures for proved oil and gas reserves since 1982, and these reserves constitute the primary assets of oil and gas royalty trusts. For the universe of royalty trusts, we find that (i) the mandatory DCF disclosures are incrementally value relevant over historical cost accounting variables; (ii) investors misprice royalty trust units because they underweight the disclosed DCF values when forecasting future distributions; and (iii) media articles bringing attention to discrepancies between price and the disclosed DCF values are significant catalysts for stock price correction. Keywords: Royalty Trusts; ASC 932; DCF Disclosures; Media Coverage. Data Availability: Data are publicly available from the sources indicated in the text.

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I. INTRODUCTION

The trend toward the use of fair values in financial statements increasingly requires

managers to forecast future cash flows and derive discounted cash flow (DCF) valuations for

assets and liabilities without readily observable market quotations. Examples include the

valuation of financial securities falling within the “level 3” category under ASC 820, the

application of impairment tests for long-lived assets under ASC 360, and the application of

impairment tests for intangible assets under ASC 350. Despite this trend, prior evidence on

whether DCF disclosures are relevant for stock market valuation is mixed. The most extensive

body of research in this area examines the value relevance of DCF estimates for proved oil and

gas reserves. ASC 932 has mandated oil and gas firms to disclose standardized DCF valuations

for proved reserves since 1982. Yet research in this area has concluded that mandatory DCF

disclosures have, at best, weak explanatory power for stock prices.1

This study provides the first robust evidence of value relevance for mandatory DCF

valuation disclosures by exploiting a novel setting. Specifically, we examine the relevance of

mandatory DCF valuations for a hand-collected sample of oil and gas royalty trusts. Two aspects

of royalty trusts make them ideally suited to the task at hand. First, ASC 932 (formerly SFAS

No. 69) requires the disclosure of standardized DCF estimates for proved oil and gas reserves.

Second, the DCF estimates relate to the primary assets of royalty trusts, which are overriding

royalty interests in oil and gas reserves. These trusts are set up by oil and gas companies seeking

to monetize mature wells while continuing to service them. Royalty trusts have no employees, no

exploration and production activities, and no other significant assets. They are also free of                                                             1 See Boone (2002) for a review of research in oil and gas firms. Research finding weak and inconsistent evidence on the value relevance of ASC 932 disclosures includes Magliolo (1986), Harris and Ohlson (1987), Doran et al. (1988), Alciatore (1993), Shaw and Wier (1993), Spear (1994), Clinch and Magliolo (1992), and Boone (2002).

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significant liabilities and are required to pay out essentially all of their net income as

distributions. These features of royalty trusts allow us to construct a sample where the mandatory

DCF valuations relate directly to the primary assets of the firm.

We find robust evidence that mandatory DCF valuations disclosed by royalty trusts are

value relevant. The DCF disclosures explain 71 percent of the variation in one-year-ahead

distributions and 64 percent of the variation in contemporaneous stock prices. Moreover, DCF

disclosures have incremental explanatory power for future distributions and contemporaneous

stock prices over recognized net income and book value of equity. Additional tests, however,

indicate that stock prices appear to underweight the DCF disclosures, but not the recognized

historical cost variables.

We next investigate why the disclosed DCF valuations do not explain more of the

variation in stock prices. If stock prices are efficient and the DCF disclosures correctly reflect

royalty trust values, then the DCF disclosures should explain 100 percent of the variation in

stock prices. Yet as indicated above, the observed explanatory power of disclosed DCF values

for stock prices is only 64 percent. We examine two non-mutually exclusive explanations for this

phenomenon. The first explanation is that the differences are due to stock market mispricing (the

mispricing hypothesis), while the second explanation is that the DCF disclosures measure royalty

trust values with error (the measurement error hypothesis). We test these explanations by

modelling the determinants of the ratio of stock market value to the disclosed DCF value, which

we refer to as the royalty trust premium.

Consistent with the mispricing hypothesis, we find strong and consistent evidence that

royalty trust premia are negatively related to future stock returns. Our evidence of stock return

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predictability is economically significant and is not explained by risk factors identified in prior

research. Turning to the measurement error hypothesis, we consider several potential sources of

error in the disclosed DCF values, including (i) measurement error due to the use of a uniform 10

percent discount rate mandated by ASC 932, (ii) measurement error due to the use of historical

spot oil and gas prices rather than expected future commodity prices, (iii) estimation error in

proved reserve quantities, and (iv) measurement error due to the omission of unproved reserves.

We find that royalty trust premia are positively related to subsequent revisions in prices and

production costs, which is consistent with measurement error in the disclosed DCF values due to

variation in future oil and gas prices, and positively related to subsequent revisions of quantity

estimates, which is consistent with estimation error in proved reserve quantities. Overall, we find

support for both the mispricing and the measurement error hypotheses. We conclude that

variation in royalty trust premia is attributable to a combination of mispricing relative to the

disclosed DCF values and measurement error in the proved reserves underlying the DCF

disclosures.

Our final set of tests investigates mechanisms leading to the correction of mispricing in

royalty trusts. We examine the role of (i) future distribution realizations and (ii) media articles

identifying deviations between stock prices and the disclosed DCF values as stock price

correction catalysts. Our first set of tests indicates that high royalty trust premia are associated

with subsequent reductions in distributions. Thus, it appears that investors tend to extrapolate

historical distributions and overprice trusts in which the disclosed DCF values indicate declining

distributions. Consistent with this explanation, we find that royalty trust premia negatively

predict returns around subsequent distribution declaration dates. Our second set of tests examine

a sample of articles published by the Wall Street Journal and the popular social media platform

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Seeking Alpha that alert investors to discrepancies between stock prices and the disclosed DCF

values. We find that these media articles serve as stock price correction catalysts by recycling

and disseminating ASC 932 DCF disclosures to a wide audience of retail investors. At the same

time, we do not find evidence that investors respond to the DCF valuations when they are

initially disclosed in the SEC filings. We conclude that investors initially underweight the

disclosed DCF values and that reductions in subsequent distributions and media coverage are

catalysts for subsequent stock price correction.

Our study has significant implications for existing research. Ours is the first study to

report consistent and robust evidence on the incremental value relevance of ASC 932 DCF

valuation disclosures. Our results suggest that the mixed results of prior research are due to low

test power and model misspecification. Prior studies employ samples of firms engaged in oil and

gas exploration and production, for which proved oil and gas reserves comprise only a fraction of

firm value. To the extent that a significant portion of firm value is attributable to unproved

reserves or to assets deployed in exploration and production activities, value relevance tests

suffer an omitted variables problem that reduces test power and can result in misspecified tests.

By focusing on the universe of oil and gas royalty trusts whose primary assets are proved oil and

gas reserves, we mitigate power and model misspecification problems.

Our results speak directly to the value relevance of ASC 932 DCF disclosures for U.S. oil

and gas royalty trusts, which currently have an aggregate market capitalization of over $6 billion.

More generally, our results speak indirectly to the value relevance of mandatory DCF disclosures

for proved reserves in oil and gas firms at large. Since these firms follow the same reporting

rules and use the same valuation consulting firms to produce their ASC 932 disclosures, our

results suggest that their disclosed DCF values should also be value relevant but omitted

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variables confound inferences from prior research. This is an economically significant group of

firms; the market capitalization of oil and gas firms trading on major U.S. stock exchanges

exceeds $1.78 trillion, or almost 10 percent of market capitalization at the aggregate level.

Finally, our results provide general evidence on the usefulness of mandated fair value estimates

in settings where the inputs for forecasting future cash flows are amenable to measurement and

independent verification (e.g., Cotter and Richardson, 2002).

Our findings also contribute to research examining the efficiency with which the market

processes information that is disclosed in the footnotes versus recognized in the financial

statements (e.g., Aboody, 1996; Davis-Friday et al., 1999; Ahmed et al., 2006; Barth et al. 2003).

The royalty trust setting has three characteristics that make it particularly suitable for the

examination of this issue. First, the mandatory DCF disclosures relate directly to the value of the

underlying primary assets of the firm. Second, the DCF values are disclosed in the notes to the

financial statements and can only be obtained through manual inspection of the underlying Form

10-Ks. Third, royalty trusts are dominated by retail investors, who are thought to be relatively

unsophisticated users of corporate financial reports (e.g., Walther, 1997; Balsam et al., 2002; De

Franco et al., 2006; Frazzini and Lamont, 2008). We find robust evidence that investors misprice

royalty trusts because they underweight these inconspicuous disclosures when forecasting future

distributions. Indeed, our analyses of articles published by the Wall Street Journal and Seeking

Alpha provide direct evidence that media coverage has served as a significant stock price

correction catalyst by highlighting significant deviations between stock prices and stale ASC 932

DCF disclosures. At the same time, we do not find evidence that investors under- or over-weight

recognized historical cost variables. These findings indicate that investors can underweight value

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relevant information when it is relegated to footnote disclosures, potentially due to lack of

financial statement user attention and expertise (e.g., Schipper, 2007).

The remainder of our study is organized as follows. Section II reviews prior research on

the relevance of ASC 932 disclosures for the valuation of oil and gas firms. Section III provides

a primer on royalty trusts. Section IV describes our royalty trust universe. Section V examines

the relevance of ASC 932 disclosures for royalty trust valuation, while Section VI investigates

whether stock prices correctly reflect the information in such disclosures. Section VII concludes.

II. PRIOR RESEARCH ON ASC 932 DISCLOSURES

SFAS No. 69, Disclosures about Oil and Gas Producing Activities (effective December

15, 1982), now codified into  Accounting Standards Codification Topic 932, Extractive

Activities–Oil and Gas (ASC 932), requires oil and gas firms to make annual DCF disclosures

about the estimated value of proved reserves based on current oil and gas prices and a uniform

discount rate of 10 percent. Proved reserves are those quantities of oil and gas, which by analysis

of geoscience and engineering data can be estimated with reasonable certainty to be

economically producible from known reservoirs and under existing economic conditions,

operating methods, and government regulations. SFAS No. 69 was originally passed with a four-

to-three margin, with the dissenting FASB members raising concerns that DCF disclosures

would lack reliability (FASB, 1982).

Prior research finds weak and inconsistent evidence on the relevance of ASC 932

disclosures for valuation. Harris and Ohlson (1987) find that historical cost accounting measures

of oil and gas assets are more strongly associated with stock prices than mandatory DCF

disclosures, leading them to conclude that managers’ cash flow forecasts suffer from estimation

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error. Magliolo (1986), Doran et al. (1988), Alciatore (1993), and Shaw and Wier (1993) find

little evidence of an association between stock returns and changes in mandatory DCF

disclosures. Spear (1994) uses an event study methodology and concludes that the reserve

quantity disclosures do not provide value-relevant information. Relatedly, Clinch and Magliolo

(1992) argue that the mandatory DCF valuation disclosures are subject to estimation error

because reserve estimates are unreliable. Adams et al. (1994) criticize the valuation model

underlying the ASC 932 disclosures because (i) estimates of future cash flows are based on

current oil and gas prices rather than expected future oil and gas prices and (ii) the required

uniform discount rate of 10 percent is inconsistent with the Statement of Financial Accounting

Concepts No. 7, which advocates time- and firm-specific discount rates. Another criticism of the

valuation model underlying the ASC 932 disclosures has been that it is limited to proved

reserves, omitting probable and possible reserves.

Typically, studies on the value relevance of ASC 932 disclosures employ regressions of

the imputed value of oil and gas assets, which is measured as the total market value of equity

minus the net book value of non-oil-and-gas assets and liabilities. The imputed value of the oil

and gas assets is then regressed on either the historical cost-based measure or the supplementary

DCF measure of oil and gas assets. Given that the book values of non-oil and gas assets and

liabilities typically differ from market values, these regressions suffer from model

misspecification. Boone (2002)—encouraged by positive evidence on the relevance of fair value

estimates in other settings (e.g., Barth, 1994; Barth and Clinch, 1998)—conjectures that model

misspecification rather than measurement error in ASC 932 DCF estimates most likely explains

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the weak evidence for oil and gas firms.2 As explained in the following sections, our focus on

royalty trusts effectively mitigates key shortcomings of prior research and yields robust evidence

supporting the incremental value relevance of mandatory DCF disclosures.

III. A PRIMER ON ROYALTY TRUSTS

A royalty trust is a special type of corporate trust formed solely to receive royalty

interests from certain underlying oil and gas producing properties operated and owned by an oil

and gas company. In a typical transaction, the oil and gas company transfers non-operational

royalty interests in specific oil and gas properties to the trust. Sponsoring oil and gas companies

create royalty trusts to carve out and monetize mature fields where development is largely

completed. Each royalty trust is divided into units (similar to shares of common stock), which

are sold to the public in an initial public offering and are listed on a national stock exchange.

As oil and gas is produced from the properties that are subject to the trust’s royalty

interest, the trust receives royalties which pass through to the unit holders as monthly or

quarterly distributions. In a royalty trust, income is not subject to corporate taxation provided

that (i) at least 90 percent of income is distributed to unit holders and (ii) the trust does not have

significant assets other than the royalty interests conveyed at inception. Due to their high payout

ratios, royalty trusts tend to appeal to retail investors with preferences for high income and are

prominently featured in online lists of high yielding stocks.3 Along with the distributions, the

                                                            2 In order to corroborate the weak results in prior research, we hand-collected a sample of ASC 932 DCF disclosures for oil and gas exploration and production firms (i.e., SIC 1311 firms) as well as integrated petroleum firms (i.e., SIC 2911 firms). Our hand-collected sample includes 1,016 firm-year observations from 1992 to 2012, with a combined market value of $654.4 billion in 2012. Using this updated and expanded sample, we also do not find evidence to support the incremental value relevance of mandatory DCF disclosures (these results are available upon request). 3 For example, at the time of writing, royalty trusts dominate the following lists of high yielding stocks www.dividend.com/dividend-stocks/high-dividend-yield-stocks.php, www.thestreet.com/dividends/leaders/, and  

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trust passes through to unit holders a proportionate interest in any depletion deductions on the

underlying properties. The net effect is that royalty trusts are more tax efficient than standard

fixed income investments, but less tax efficient than most equity investments (see Toolson et al.,

2005).

Royalty trusts hold claims to the future production of mature oil and gas fields. They are

passive vehicles and do not participate in any of the upstream exploration and development or

the downstream refining and distribution activities engaged in by the sponsoring oil and gas

companies. In addition, royalty trusts have no employees and all administrative functions of the

trust are performed by the trustee. The basic function of the trustee is to collect income from the

royalty interest, pay any expenses, charges and obligations of the trust from the trust’s income

and assets, and distribute available cash to unit holders. Because of the passive nature of the

trust’s assets and the restrictions on the power of the trustee to incur obligations, royalty trusts do

not have significant liabilities. The property of the trust consists of the overriding royalty interest

as well as cash and cash equivalents that may be held by the Trustee from time to time.

Pursuant to ASC 932, royalty trusts are required to include in their annual reports

supplementary disclosures regarding the proved reserves attributable to the trust’s royalty

interests. The estimates of proved reserves and the associated cash flow forecasts attributable to

the royalty trust are reviewed, for a fee, by independent oil and gas consulting firms based on

presently known geologic and engineering data. In order to safeguard the objectivity of the

independent consulting firms, the consulting fees are not contingent upon the estimates obtained.

                                                                                                                                                                                                www.nasdaq.com/dividend-stocks/. We note, however, that the high distributions on royalty trusts do not strictly classify as dividends. The reserves underlying the trusts are depleting assets, so the distributions incorporate a return of capital.

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The oil and gas consulting firms are registered with the Texas Board of Professional Engineers

and the engineering staff members are licensed professional engineers, with degrees in petroleum

and chemical engineering.

Under the provisions of ASC 932, the cash flow forecast disclosures ignore probable and

possible reserves that are unproved at the report date. Such unproved reserves are highly

speculative (see, e.g., Howard and Harp, 2009). In addition, our communication with oil and gas

valuation experts at Miller and Lents, Ltd. (one of the independent oil and gas consulting firms

reviewing ASC 932 disclosures) suggests that unproved reserves should have a minor impact on

the valuation of royalty trusts. This is because royalty trusts are typically assigned mature wells

with well-established reserves, therefore reserve movements from unproved into proved reserve

categories are rare.

Our focus on royalty trusts effectively mitigates the key shortcomings of prior research

focusing on oil and gas companies that also engage in upstream exploration and development

activities and downstream refining and distribution activities. Since the mandatory DCF

disclosures relate to the proved oil reserves alone, the value of these upstream and downstream

activities represent significant omitted variables in prior research. Royalty trusts, in contrast,

have no upstream or downstream activities. Moreover, royalty trusts cover mature oil and gas

fields with low uncertainty about reserve quantities, so cash flow forecasts should be accurately

estimable and directly related to the primary assets of the firm.

The accounting principles used to prepare the financial statements of royalty trusts are

based on historical cost accounting. The initial book values of the royalty interests assigned to

the trust are based on their amortized historical costs at the date of transfer from the sponsoring

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oil and gas company. These historical costs are therefore based on the accumulated costs

incurred in discovering and developing the well, less any amortization to date. Following the

creation of the trust, the royalty interest is amortized based on the units-of-production

attributable to the trust relative to the estimated proved reserves attributable to the trust at the

beginning of the fiscal year. Royalty trusts use a modified cash basis of accounting for income

statement purposes, whereby the amortization of the royalty interest is charged directly to the

trust corpus and bypasses the income statement. This modification is designed to produce an

income number that corresponds more closely to the distributions made by the trust and is

therefore considered to be more value relevant (see the SEC Codification of Staff Accounting

Bulletins Topic 12 E). The recognized net income of trusts comprises primarily of the royalty

payments received less the costs of administering the trust.

IV. SAMPLE CONSTRUCTION

Our royalty trust universe

To compile an initial list of royalty trusts, we search the Compustat universe for domestic

publicly traded firms with SIC code 6792 (“Oil Royalty Traders”) and zero employees. We

validate our initial list of royalty trusts with a keyword search on SEC EDGAR for company

names containing any combination of “oil,” “gas,” “royalty,” and “trust”. From this initial list,

we exclude (i) the Marine Petroleum Trust, (ii) the Tidelands Royalty Trust “B”, and (iii) the

North European Oil Royalty Trust because, according to their Form 10-K filing disclosures, the

trustees would have to incur unreasonable efforts and expense in seeking to obtain the

geoscience and engineering data necessary to estimate reserves with reasonable certainty,

therefore they do not disclose ASC 932 DCF estimates.

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For each royalty trust, we download the Form 10-K filings available on SEC EDGAR

and hand collect ASC 932 cash flow forecast disclosures. We also hand collect information on

SEC filing dates and the number of royalty trust units outstanding at fiscal year-end. Next, we

merge our data with information from Compustat relating to book value of equity, distributions,

net income, and stock price per unit. For a small number of royalty trusts with missing data on

Compustat, we hand collect historical cost accounting variables directly from the Form 10-K

filings. Finally, we obtain stock return data (including delisting returns) from CRSP.

For our sample, we require non-missing values for stock price per unit (Pit), book value

of equity per unit (BVit), ASC 932 DCF valuation of proved reserves per unit (DCFit),

distributions per unit (DIit), and net income per unit (NIit). We measure the imputed value of oil

and gas assets per unit (IVit) as stock price per unit minus cash and cash equivalents per unit

(CHEit) plus total liabilities per unit (LTit). Similarly, we measure the historical cost of oil and

gas assets (HOGit) as book value of equity per unit minus cash and cash equivalents per unit plus

total liabilities per unit. We also require non-missing values for year t+1 scaled distribution

changes (ΔDΙit+1) and annual market-adjusted stock returns measured from three months after the

end of year t to three months after the end of year t+1 (RETURNit+1). Appendix 1 provides the

labels and definitions of the key variables used in our study.

Our sample includes 223 observations for 21 royalty trusts from 1992 to 2012. We note

that 1992 is the first year for which we can hand collect ASC 932 cash flow forecast disclosures

from annual filings available on SEC EDGAR. Appendix 3 provides the list of royalty trusts

along with their trustees and independent oil and gas consultants, as well as the distribution of

observations across trusts. All royalty trusts have December fiscal year-ends, so calendar year-

ends coincide with fiscal year-ends. Figure 1 presents the sample distribution over time along

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with the combined market value of royalty trusts. In 2012, the most recent year in our sample,

there are 15 royalty trusts with a combined market value of $6.15 billion.

An illustrative example

Appendix 2 provides an example of ASC 932 disclosures for the BP Prudhoe Bay

Royalty Trust (NYSE:BPT). BPT is the largest royalty trust in terms of market capitalization and

was formed when British Petroleum PLC spun off a portion of its interest in the Prudhoe Bay

field on Alaska’s North Slope. The disclosure is taken from “Note 11” of BPT’s Form 10-K for

the fiscal year ending December 31, 2011. The disclosed DCF valuation of proved reserves as of

the end of 2011 is $1,433,113,000. At that time, there were 21,400,000 units outstanding in the

trust. Thus, the DCF valuation of proved reserves per unit was $66.97. For comparative

purposes, the book value of equity per unit was $0.04. This is because the royalty interest was

fully amortized by the end of 2011, and thus had a zero carrying value. Effectively, the book

value of equity was comprised of a small cash reserve of $0.05 per unit, which was held to

provide liquidity for administrative expenses, minus a small liability balance of $0.01 per unit for

accrued expenses. The recognized net income per unit for 2011 was $9.40, which corresponds

almost exactly to the cash distributions per unit. Note, however, that it is unlikely that net income

and distributions will continue at this level in the future. The properties underlying the royalty

interests are depleting assets with finite lives, so distributions will also cease altogether at some

point in the future. Indeed, as explained in BPT’s Form-10K, the Prudhoe Bay field has been in

production since 1977, development of the field is largely completed, proved reserves are being

depleted, and royalty payments to the trust are projected to cease after 2029. It is interesting to

note that after BPT’s 2011 Form 10-K filing on March 1st 2012, BPT’s stock price was $123.59

per unit, while the disclosed DCF value was only $66.97 per unit. BPT’s price eventually fell

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from around $120 to around $90 during just a few days in August 2012 when articles in the Wall

Street Journal and Seeking Alpha highlighted the discrepancy between stock price and the

disclosed DCF value (Appendix 4 provides links to these articles).

V. ON THE VALUE RELEVANCE OF ASC 932 DISCLOSURES

This section investigates the extent to which ASC 932 disclosures reflect information that

is incrementally useful for the valuation of royalty trusts. We use both future distributions and

contemporaneous stock prices to ascertain value relevance.

Descriptive statistics

Table 1, Panel A, reports the empirical distributions of the key variables. All variables are

scaled by the number of royalty trust units outstanding. On average, the market value of equity

per unit (Pit) is $21.29, which is virtually identical to the imputed value of oil and gas assets

(IVit) of $21.26. This is because royalty trusts are almost free of non-oil-gas assets and liabilities

The book value of equity per unit (BVit) is $3.51, which is close to the historical cost of oil and

gas assets (HOGit) of $3.47. Both observations are consistent with the fact that royalty trusts

have only $0.19 of cash and cash equivalents per unit (CHEit) and $0.16 of total liabilities per

unit (LTit). The ASC 932 discounted (DCFit) and undiscounted (UCFit) cash flow forecasts from

proved reserves per unit are $12.55 and $24.03, respectively. The average distribution per unit

(DIit) is $2.13 and is close to the average reported net income per unit (NIit) of $2.16, consistent

with the fact that royalty trusts are pass-through entities. Indeed, the payout ratio approximates

100 percent for the vast majority of our sample.

Table 1, Panel B, reports pairwise correlations and two-sided p-values. The Pearson

correlation between stock prices and ASC 932 cash flow forecast disclosures is 0.80. In contrast,

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the correlation between stock prices and book value of equity is insignificantly different from

zero. Distributions and recognized net income both have a 0.89 correlation with stock prices and

a 0.99 correlation with each other, prompting us to focus on net income in subsequent tests. The

Pearson correlation between discounted and undiscounted cash flow forecast disclosures is 0.98,

prompting us to focus on DCFit for the value-relevance tests. Although DCFit is virtually

unrelated with BVit, the correlation between DCFit and NIit is 0.75. Thus, while mandatory DCF

disclosures and recognized net income have some overlap, they also contain a significant amount

of different information.

Predictive ability of ASC 932 disclosures for future royalty trust distributions

We first investigate whether the disclosed DCF values have predictive content for future

distributions. Table 2, Panel A, presents results from regressions of one-year-ahead distributions

(DIit+1) on ASC 932 discounted cash flow forecast disclosures (DCFit) and historical cost

variables measured in t:

1 1 12

.K

kit it k it it

k

DI DCF Historical Cost Variable

(1)

Throughout the study, we estimate the models using ordinary least squares regressions.

We conduct statistical inference using (i) White’s (1980) heteroskedasticity-consistent standard

errors with MacKinnon and White’s (1985) finite-sample correction, and (ii) clustered standard

errors. Due to the small number of clusters in our royalty trust universe, clustered standard errors

can be biased. Therefore, we implement Bell and McCaffrey’s (2002) bias-reduced linearization

(BRL) procedure, which adjusts standard errors and effectively reduces few-cluster bias. The

BRL procedure clusters standard errors by firm and does not allow estimation with cluster-

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specific fixed effects (see, e.g., Angrist and Pischke, 2009). Following Angrist and Pischke’s

(2009) view that “an underestimate of precision is less costly than an overestimate,” we base our

statistical inferences on the maximum of the White and BRL standard errors (i.e., the minimum

t-statistics). In additional robustness checks (available upon request), we find that the inferences

are robust based on (i) conventional OLS standard errors, and (ii) p-values from Cameron’s et

al.’s (2008) wild cluster bootstrap-t procedure.

The results in Table 2, Panel A, indicate that mandatory DCF disclosures have significant

predictive ability explaining 71 percent of the variation of one-year-ahead distributions. In

contrast, book value of equity has no predictive ability for one-year-ahead distributions. The

predictive ability of recognized net income is roughly the same as that of mandatory DCF

disclosures explaining 69 percent of the variation in one-year-ahead distributions. Importantly,

the multiple regression results show that the slope coefficient on DCFit remains significantly

positive after controlling for information in recognized net income and book value.

We next investigate the usefulness of ASC 932 disclosures for forecasting distributions

over a longer horizon. Table 2, Panel B, presents results from regressions of realized

distributions cumulated forward over a five-year horizon—a commonly used forecast horizon for

fundamental valuation. When cumulating distributions forward, we only require non-missing

information about one-year-ahead distributions. Again, we find evidence of a significantly

positive intertemporal link between DCFit and forward-cumulated distributions, denoted as

5

1 itDI , that is incremental to the predictive content of recognized net income, while the

book value of equity again has no predictive ability.

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Overall, we find evidence that ASC 932 disclosures contain information that is

incrementally useful for forecasting distributions one- and five-years-ahead. The linear

combination of the mandatory DCF disclosures and historical cost variables explains 82 percent

and 55 percent of the variation in one-year-ahead distributions and forward-cumulated

distributions, respectively. We next investigate whether ASC 932 disclosures are also

incrementally relevant for explaining current royalty trust stock prices.

Explanatory ability of ASC 932 disclosures for current royalty trust stock prices

Table 3, Panel A, presents results from regressions of fiscal year-end stock prices (Pit) on

ASC 932 discounted cash flow forecast disclosures (DCFit) and historical cost variables per

royalty trust unit outstanding in t:

12

.K

kit it k it it

k

P DCF Historical Cost Variable

(2)

On a stand-alone basis, DCFit explains 64 percent of variation in royalty trust stock prices,

book value of equity has limited explanatory power for stock prices, while recognized net

income performs best, explaining 78 percent of variation in stock prices. Consistent with our

evidence that DCFit is incrementally useful for forecasting future distributions, the marginal

effect of DCFit on current royalty trust stock prices remains significantly positive after

controlling for recognized net income. The linear combination of DCFit and historical cost

variables explains 83 percent of the variation in current royalty trust stock prices.

Recall that for our universe of royalty trusts the stock price per unit (Pit) is virtually

identical to the imputed value of oil and gas per unit (IVit), while the book value of equity (BVit)

is virtually identical to the historical cost of oil and gas assets (HOGit). This is because royalty

19

trusts are almost free of non-oil-gas assets and liabilities (see Table 1 for descriptive statistics).

Table 3, Panel B, confirms that our regression results based on equation (2) are virtually

unchanged using (i) IVit in lieu of Pit as well as (ii) HOGit in lieu of BVit. This finding further

reinforces our argument that the royalty trust setting is a powerful experimental setting, which

mitigates model misspecification issues of prior research on the value relevance of ASC 932

disclosures. We also note that our inferences based on equation (2) are not sensitive to measuring

stock prices as of three months after the fiscal year-end.

Focusing on the univariate regressions of stock price or imputed value per unit on DCFit,

i.e., the results in Column 1 of Table 3, Panels A and B, we observe that the intercept is close to

$7 and the estimated slope coefficient is close to 1.14. If DCFit offered an unbiased predictor of

stock price or imputed value per unit, then (i) the intercept should have been equal to zero and

(ii) the slope coefficient should have been equal to one (unbiasedness hypothesis). The F-

statistics from testing the unbiasedness hypothesis, however, are close to 62.5 (Pr > F = 0.0001),

indicating that this hypothesis is rejected at conventional levels. In turn, rejection of the

unbiasedness hypothesis is consistent with two non-mutually exclusive explanations: (i)

investors misprice royalty trusts relative to the disclosed DCF valuations and (ii) the disclosed

DCF valuations measure royalty trust fundamental values with error.

By comparison, the univariate net income regression results in Column 3 of Table 3,

Panels A and B, reveal that in terms of explanatory power a simple valuation model with a zero

intercept and a multiple of approximately 9.4 on recognized net income provides a more accurate

description of current stock prices than the disclosed DCF valuation. Strikingly, the magnitude of

the simple coefficient on recognized net income is close to 10, which is the predicted coefficient

if investors ignored the fact that the properties underlying the royalty interests are depleting

20

assets with finite lives and instead valued royalty trusts as zero-growth perpetuities by simply

capitalizing current net income at a 10 percent discount rate.

Do investors underweight mandatory DCF disclosures?

Although the pricing tests yield evidence that is directionally consistent with the value

relevance of mandatory DCF disclosures, the evidence also points to the possibility that investors

underweight such disclosures from a fundamental valuation perspective. In particular, the

relative weights assigned to DCFit versus NIit for predicting distributions in Table 2 are greater

than those for explaining stock prices in Table 3.4 To test whether investors correctly weight the

mandatory DCF disclosures, we use a two-stage regression approach.

In the first stage, we regress distributions in t+1 (DIit+1) on the mandatory DCF disclosures

(DCFit), recognized net income (NIit), and the book value of equity (BVit). The residual and fitted

values from the first-stage regression measure the unpredictable and predictable portions of one-

year-ahead distributions, denoted 1residualitDI   and 1

fitteditDI , respectively. In the second stage, we

regress market-adjusted stock returns in t+1 (RETURNit+1) on the residual and fitted components

of contemporaneous distributions:

1 1 1 2 1 1.residual fitted

it it it itRETURN DI DI (3)

Column 1 of Table 4 presents the second-stage regression results. The significantly

positive coefficient on 1residualitDI is not surprising: Positive (negative) cash flow news should

translate into higher (lower) stock prices. More relevant to our question is the significantly

                                                            4 For example, the relative magnitude of the coefficients on NIit and DCFit in Column 4 of Table 2, Panel A, is 0.070/0.494=0.14, while the relative magnitude of the coefficients on NIit and DCFit in Column 4 of Table 3, Panel A, is 0.445/6.995=0.06.

21

positive coefficient on 1fitted

itDI , which implies that stock prices also react to the predictable

portion of realized distributions. Column 2 of Table 4 decomposes 1fitted

itDI into the portions of

one-year-ahead distributions predictable, on a stand-alone basis, by the mandatory DCF

disclosures, recognized net income, and the book value of equity, denoted 1DCFititDI , 1

BVititDI , and

1NIititDI , respectively. A comparison of the estimated coefficients reveals that our evidence of

stock market reaction to the predictable portion of royalty trust distributions is primarily

attributable to the portion predicted by DCFit. The coefficient on 1DCFititDI is positive and

statistically significant, indicating that some of the value-relevant information in the mandatory

DCF disclosures is not reflected in stock prices until it is manifested in future distributions. One

key implication is that investors underweight the disclosed DCF values when pricing royalty

trusts. We examine in depth the associated mispricing hypothesis in the next section.

VI. ON THE MISPRICING OF ASC 932 DISCLOSURES

Determinants of royalty trust premia

We further examine the pricing of ASC 932 disclosures by investigating the determinants

of deviations between royalty trust prices and the disclosed DCF values. Table 5, Panel A,

provides descriptive statistics for the ratio of royalty trust price per unit divided by the DCF

value per unit. Royalty trusts tend to trade at a significant premium over the disclosed DCF

values (mean of 2.03), and the magnitude of this premium varies quite considerably (lower

quartile of 1.29 and upper quartile of 2.49). What explains royalty trust premia? We consider two

non-mutually exclusive hypotheses. The first hypothesis is that the premium over the DCF

disclosure is due to stock market mispricing (the mispricing hypothesis). The second hypothesis

22

is that the DCF disclosure measures the underlying value of the royalty trust with error (the

measurement error hypothesis). We consider each hypothesis in turn.

Royalty trust premia: The mispricing hypothesis

Testing the mispricing hypothesis

We first investigate whether evidence of royalty trust premia is due to mispricing. We

start with the mispricing hypothesis because the evidence from the previous section indicates that

investors underweight information in ASC 932 DCF disclosures. Moreover, prior research also

suggests that investors underreact to disclosed items in the notes to the financial statements (e.g.,

Aboody, 1996; Davis-Friday et al., 1999; Hirst et al., 2004; Ahmed, et. al., 2006; Libby et al.,

2006; Schipper, 2007; Muller et al., 2013). In addition, using Form 13F filings (available from

the Thompson Institutional Holdings database), we find that institutional investors hold just 7.5

percent of the royalty trust units outstanding. Therefore, the investor base of royalty trusts is

dominated by retail investors, who are relatively unsophisticated users of corporate financial

reports (e.g., Walther, 1997; Balsam et al., 2002; De Franco et al., 2006; Frazzini and Lamont,

2008).

If royalty trust premia proxy for mispricing, then the testable prediction is that such

premia should have predictive ability for subsequent stock returns: trusts trading at higher premia

should, on average, experience lower future stock returns. Consistent with the mispricing

hypothesis, Table 5, Panel B, reports pairwise correlations providing preliminary evidence of

negative stock return predictability based on royalty trust premia. Next, we search for stock

return predictability using multiple regression analyses.

23

Table 6, Panel A, presents results from the multiple regression of one-year-ahead market-

adjusted stock returns (RETURNit+1) on the premium over the disclosed DCF value

(PREMDCFit) and a vector of control variables:

1 1 12

.K

kit it k it it

k

RETURN PREMDCF Control Variable

(4)

The vector of control variables in equation (4) includes the premium over the book value

of equity (PREMBVit), the earnings yield (YIELDit), which is virtually identical to the distribution

yield (because payout ratios approximate 100 percent), as well as the 10-year Treasury-bond

yield (RFt), which proxies for variation in nominal interest rates, the spread of Moody’s

investment grade (Baa) corporate bond yield over the 10-year Treasury-bond yield (SPREADt),

which proxies for variation in the unobservable equity risk premium, and an index of future oil

and gas prices (FTRt), which proxies for variation in future commodity prices. Together, RFt and

SPREADt proxy for temporal variation in aggregate discount rates.5 We obtain Treasury and

corporate bond yield data from the Board of Governors of the Federal Reserve System (Release

H.15: Selected Interest Rates). We obtain future prices from the U.S. Energy Information

Administration for two widely used benchmarks for oil and gas pricing traded on the New York

Mercantile Exchange: (i) the West Texas Intermediate crude oil prices (in dollars per barrel) and

(ii) the Henry Hub natural gas prices (in dollars per million BTU). To capture common variation

in future oil and gas prices, we construct a standardized index computed as the first principal

component of the two series, denoted FTRt.

                                                            5 Dating back to Chan et al. (1985), Chen et al. (1986), Ferson and Harvey (1991), Jagannathan and Wang (1996), and several other studies, it is widely accepted that the spread of investment grade corporate bond yields over 10-year Treasury bond yields tracks countercyclical variation in the unobservable equity risk premium.

24

Consistent with the pairwise correlations and the simple regression results reported in

Column 1, the multiple regression results reported in Column 2 provide evidence of stock return

predictability based on royalty trust premia. The slope coefficient on PREMDCFit is significantly

negative. In contrast, we do not find evidence of stock return predictability based on other

valuation ratios. Moreover, evidence of stock return predictability based on royalty trust premia

is not sensitive to controlling for temporal variation in aggregate discount rates as well as in

future oil and gas prices.6

We note that evidence of stock return predictability based on royalty trust premia is not

only statistically significant but also economically important. To calibrate the magnitude of the

effect, we measure one-year-ahead stock returns across tercile portfolios based on PREMDCFit.

Consistent with the regression results, Figure 2, Panel A, shows that average one-year-ahead

market-adjusted stock returns are negative (positive) for the top (bottom) tercile portfolios. The

top (bottom) portfolio underperforms (outperforms) the stock market by -6.4 percent (+14.4

percent). The annual spread in the stock return performance of the top portfolio over the bottom

portfolio is -20.8 percent, which is significantly negative at the 1 percent level.

To further investigate the sensitivity of the results to the use of the uniform 10 percent

discount rate mandated by ASC 932, Columns 3 and 4 present simple and multiple regression

results after replacing PREMDCFit in the right-hand-side of equation (4) with the ratio of stock

price per unit divided by the undiscounted cash flow forecasts per unit, denoted PREMUCFit.

                                                            6 As an additional robustness check, we construct an index of spot oil and gas prices (SPOTt). Consistent with prior research (e.g., Schwartz, 1997), we find that spot oil and gas prices are highly correlated with future oil and gas prices: the correlation between SPOTt and FTRt is 99 percent. Not surprisingly, our evidence of stock return predictability remains robust after including SPOTt as a regressor. We do not include FTRt and SPOTt together as regressors due to the high correlation between the two series.

25

Our key finding here is that evidence of stock return predictability based on royalty trust premia

is not sensitive to whether we use the discounted or undiscounted ASC 932 cash flow forecast

disclosures: the slope coefficient on PREMUCFit remains significantly negative and

economically important. Figure 2, Panel B, also reports average one-year-ahead market-adjusted

stock returns across tercile portfolios based on PREMUCFit. The top (bottom) portfolio

underperforms (outperforms) the stock market by -7.8 percent (+12.1 percent). Again, the annual

spread in the stock return performance of the top portfolio over the bottom portfolio is roughly

equal to -20 percent, which is significantly negative at the 1 percent level.

As a final robustness check, Table 6, Panel B, repeats the analyses using one-year-ahead

factor-adjusted stock returns, in lieu of market-adjusted returns, as the dependent variable in

equation (4). We measure factor-adjusted stock returns (RESRETURNit+1) as the residual stock

returns after subtracting the returns to the Fama and French (1993) size and book-to-market

factors and the Carhart (1997) momentum factor. We obtain factor returns from Professor

Kenneth French’s website. Our inferences regarding stock return predictability based on royalty

trust premia remain unchanged when using factor-adjusted stock returns, therefore our results are

not explained by risk factors identified in prior research.

Mispricing versus arbitrage opportunity

We hasten to add that a trading strategy based on royalty trust premia is likely to face

significant barriers and costs to implementation, so it seems unlikely to offer an obvious

arbitrage opportunity. First, due to the small number of observations, both the long and short

portfolios would be thinly populated, exposing arbitrageurs to idiosyncratic risk. Second, our

analysis of Form 13F filings shows that institutional investors hold just 7.5 percent of the units

outstanding. In turn, low institutional ownership among royalty trusts implies that it would be

26

costly or even impossible to arbitrage mispricing by taking short positions. This is because

institutional investors provide the bulk of stock loan supply in the equity lending market

therefore short selling is constrained when retail ownership is high (e.g., Nagel, 2005). Indeed,

our analysis of equity lending data from Data Explorers reveals that by 2012 all royalty trusts are

classified as hard-to-borrow or “special” stocks (i.e., stocks with high lending fees, negative

rebate rates, and/or zero active supply in the equity lending market).

We note that the combination of an unsophisticated investor base with binding short-

selling constraints (i.e., short sales are either very expensive or impossible) implies that the

royalty trust universe is especially susceptible to overpricing (e.g., Miller 1977; Stambaugh et al.,

2012). We also note that our evidence of mispricing in the royalty trust universe is related to

research on the mispricing of equity carve outs and spin offs as well as the role of limits to

arbitrage in correcting mispricing (e.g., Shleifer and Vishny, 1997; Lamont and Thaler, 2003). 

Royalty trust premia: The measurement error hypothesis

The second non-mutually exclusive hypothesis for explaining variation in royalty trust

premia is that the disclosed ASC 932 DCF estimate measures the underlying value of the royalty

interests with error, and that investors identify and adjust for these errors when pricing royalty

trusts. There are several potential sources of measurement error. First, the uniform 10 percent

discount rate mandated by ASC 932 could differ from the actual discount rate used by investors

when valuing royalty trusts. Second, the ASC 932 DCF estimate employs historical spot oil and

gas prices that may not reflect expected future oil and gas prices. Third, the ASC 932 estimates

of proved reserves could contain estimation error that is anticipated by investors. Finally,

unproved reserves are ignored under ASC 932, while investors could adjust for expected future

27

reserve movements from unproved into proved reserve categories. Next, we consider each of

these potential sources of measurement error in turn.

Potential sources of measurement error

Measurement error in ASC 932 disclosures due to variation in discount rates

One potential source of measurement error in the disclosed DCF values is that the

underlying valuation model is based on a uniform 10 percent discount rate, ignoring cross-

sectional and temporal variation in discount rates. Note that since royalty trusts engage in very

similar activities, have very similar macroeconomic exposures, and have effectively zero

financial leverage, it seems unlikely that there is much cross-sectional variation in discount rates.

Discount rates, however, are expected to vary over time due to temporal variation in nominal

interest rates and the equity risk premium. We employ the 10-year Treasury-bond yield (RFt),

and the spread of Moody’s investment grade (Baa) corporate bond yield over the 10-year

Treasury-bond yield (SPREADt) to proxy for temporal variation in the nominal interest rate and

the equity risk premium.

Measurement error in ASC 932 disclosures due to historical spot oil and gas prices

A second potential source of measurement error in ASC 932 disclosures is that the cash

flow forecasts are based on historical spot oil and gas prices rather than expected future oil and

gas prices.7 If investors’ expectations about future oil and gas prices differ from historical spot

prices, then stock market valuations can differ from the disclosed DCF values. To examine the

impact of stale oil and gas prices, we hand-collect information from the notes to the financial

                                                            7 The SEC Final Rule on the modernization of oil and gas reporting, issued on December 31, 2008, requires for the pricing of proved oil and gas reserves the use of twelve-month historical average spot prices, calculated as the arithmetic average of the first-day-of-the month price. Prior to the Final Rule, firms were required to price proved oil and gas reserves based on fiscal year-end spot prices.

28

statements about the DCF estimate change in the subsequent year that is attributable to revisions

in prices and production costs, denoted CHPRCt+1.

Measurement error in ASC 932 disclosures due to estimation error in proved reserves

A third potential source of measurement error in ASC 932 disclosures is estimation error

in proved reserve quantity estimates. Prior studies of oil and gas companies conclude that

disclosed reserve quantities are noisy due to estimation error or purposeful manipulation (e.g.,

Clinch and Magliolo 1992; Hall and Stammerjohan, 1997). For our universe of royalty trusts,

however, we expect that reserve quantities are more accurately estimable because royalty trusts

cover mature oil and gas fields with low uncertainty about reserve quantities. We examine the

accuracy of proved reserve quantities using hand-collected information about the DCF estimate

change in the subsequent year that is attributable to revisions in proved reserve quantity

estimates, denoted CHESTt+1.

Measurement error in ASC 932 disclosures due to the omission of unproved reserves

A fourth potential source of measurement error in the disclosed DCF values is that no

weight is given to unproved (probable and possible) reserves. In general, however, such reserves

are highly speculative (e.g., Howard and Harp, 2009). In addition, as explained in Section III,

royalty trusts cover mature oil and gas fields where development is largely complete, so probable

and possible reserves are not expected to be a significant source of value for royalty trusts. We

corroborate this expectation with valuation experts at Miller and Lents, Ltd. (one of the

independent oil and gas consulting firms reviewing the ASC 932 disclosures), who explained to

us that probable and possible reserves should have a minor impact on the valuation of royalty

trusts. Nevertheless, we explicitly examine the importance of unproved reserves using hand-

collected information about the DCF estimate change in the subsequent year that is attributable

29

to additions to proved reserves resulting from extensions, discoveries, and additions, denoted

CHEXTt+1.8

Testing the measurement error hypothesis

We begin our discussion of the empirical results by examining the principal sources of

change in the ASC 932 DCF valuations. Pursuant ASC 932, oil and gas firms are required to

present the principal sources of change in the DCF disclosure, including (i) sales and transfers of

oil and gas produced net of production costs, which corresponds to royalty income received for

our universe of trusts, (ii) accretion of discount, (iii) net change in prices and production costs,

(iv) net change in income taxes, (v) development costs incurred during the period, which are zero

for royalty trusts, as well as (vi) the revision of previous proved reserve quantity estimates, and

(vii) additions to proved reserves resulting from extensions, discoveries, and improved recovery,

net of related costs. We hand-collect these amounts from the Form-10-K filings.

Figure 3 presents the means (shaded bars), medians (◊), and interquartile ranges (×) for

each of the sources of change based on our hand-collected information from the notes to the

financial statements. To facilitate comparisons, we express these values on a per unit outstanding

basis. The average year-over-year change in the mandatory DCF disclosure is -$0.22 per unit and

is consistent with the fact that the oil and gas fields underlying the royalty interests are depleting

assets with finite lives. The primary sources of the DCF change is royalty income (-$2.24 per

unit) and the accretion of discount (+$1.25 per unit). The only other significant contributors to

DCF change are the change in prices and production costs (+$0.46 per unit) and the revisions of

quantity estimates (+$0.22), while extensions, discoveries and additions contribute very little                                                             8 Reserve movements from unproved into proved reserve categories should flow through “extensions, discoveries, and additions”.

30

(+$0.12). Thus, it appears unlikely that estimation error attributable to unproved reserves

explains much of the variation in royalty trust premia.

We examine the extent to which the mispricing hypothesis and the measurement error

hypothesis can explain observed royalty premia in Table 7. This table presents results from

regressions of royalty trust premia measured in t on one-year-ahead market adjusted stock return

(RETURNit+1), which captures the reversal of prior stock market pricing errors, along with RFt

and SPREADt, which proxy for temporal variation in aggregate discount rates, CHPRCit+1, which

captures revisions in prices and production costs, CHESTit+1, which proxies for the reversal of

prior estimation errors in proved reserves, and CHEXTit+1, which proxies for extensions,

discoveries, and additions:

1 1 2 3

4 1 5 1 6 1 .it it t t

it it it it

PREMDCF RETURN RF SPREAD

CHPRC CHEST CHEXT

(5)

The multiple regression results in Column 3 of Table 7 show that royalty trust premia are

(i) negatively related to subsequent stock returns, which is consistent with the mispricing

hypothesis and the stock return predictability results in Table 6, (ii) positively related to

subsequent revisions in prices and production costs, which is consistent with measurement error

in the disclosed DCF values due to variation in future oil and gas prices, and (iii) positively

related to subsequent revisions of quantity estimates, which is consistent with estimation error in

proved reserve quantities. Overall, we find support for both the mispricing and the measurement

error hypotheses. We conclude that variation in royalty trust premia is attributable to a

combination of mispricing relative to the disclosed DCF values and measurement error in the

proved reserves underlying the DCF disclosures.

31

Stock price correction catalysts

The analysis so far presents evidence of stock return predictability based on royalty trust

premia, which is consistent with investors mispricing royalty trusts relative to the disclosed DCF

values. To gain insights into mechanisms facilitating the correction of the pricing errors, we

examine the role of (i) future distribution realizations and (ii) media articles highlighting

deviations of stock prices from the disclosed DCF values, as stock price correction catalysts.

Future distribution realizations as stock price correction catalysts

The evidence presented in Section V indicates that investors underweight information in

ASC 932 DCF valuation disclosures and stock prices do not fully reflect this information until it

impacts future distributions. To further investigate the role of future distributions as a stock price

correction catalyst, we estimate regressions of subsequent distribution changes realized in t+1

scaled by beginning of period stock price per unit (ΔDIit+1) on royalty trust premia measured in t:

1 1.it it itDI PREMDCF (6)

Table 8, Panel A, presents results based on equation (6) and shows that royalty trust

premia negatively predict subsequent distribution changes. This evidence suggests that investors

underweight information in the disclosed DCF values about reductions in future distributions. If

this is indeed the case, the prediction that follows is that royalty trust premia should negatively

predict stock returns around subsequent distribution declaration dates.9 To test this prediction, we

estimate the following regression of stock returns measured around distribution declarations in

t+1 (DISTRETURNit+1) on royalty trust premia in t:

                                                            9 This prediction is similar in spirit to the mispricing tests proposed by Bernard et al. (1997).

32

1 1.it it itDISTRETURN PREMDCF (7)

We collect information about royalty trust distribution declaration dates from the daily

CRSP file and measure DISTRETURNit+1 as the sum of three-day, cumulative market-adjusted

stock returns centered on declaration dates in t+1. Consistent with investors failing to anticipate

the predictable distribution reductions, Table 8, Panel B, reports evidence of a significantly

negative intertemporal link between distribution declaration stock returns in t+1 and royalty trust

premia in t. Taken together, the evidence in Table 8, Panels A and B, suggests that royalty trust

premia capture pricing errors associated with predictable reductions in future distributions that

are subsequently corrected as the future distributions are realized.

Media articles as stock price correction catalysts

Next, we examine the role of media coverage as a catalyst for stock price correction. We

search for media articles on royalty trusts published by the Wall Street Journal and the

investment research website Seeking Alpha, which recycle information from ASC 932

disclosures. Seeking Alpha is a popular social media platform focusing on personal investment

and covering stocks with high retail investor interest (e.g., Chen et al., 2014). The first Seeking

Alpha article recycling ASC 932 disclosures was published on 1/21/2011. We identify 22 such

media articles including a total of 26 royalty trust mentions post-2011. Appendix 4 provides our

list of media articles. With the exception of one article published on 8/24/2012 by Jason Zweig,

the personal finance columnist for the Wall Street Journal, all other articles were published by

Seeking Alpha. We note that none of the publication dates coincides with any type of SEC filing

by the covered royalty trusts.

33

Our review of the media articles indicates there is no new information revealed to

investors and that the authors merely recycle ASC 932 disclosures. The authors consistently

point out that the retail investors dominating royalty trusts often appear to ignore the ASC 932

disclosures because they do not review carefully, if at all, the Form 10-Ks. The media articles on

our list all make claims of overpricing and include “sell” recommendations based on the

argument that large premia over the mandatory DCF disclosures are not sustainable. To

illustrate, in his Intelligent Investor column published by the Wall Street Journal on 8/24/2012,

Jason Zweig points out the following:

“…In their latest annual reports, for example, BP Prudhoe Bay Royalty Trust and Whiting USA Trust I calculated that the current value of their future cash available for distributions was $1.4 billion and $109 million, respectively. Yet this week the total market value of BP Prudhoe stood at $2.3 billion; Whiting USA I, at $123 million. That means investors remain willing to pay 61% more for a stake in the BP trust than all its future cash flows are likely to be worth, and they are shelling out 13% more for Whiting than Whiting itself says they will probably earn from it—before tax…Do investors understand that they are often overpaying? “In some cases, they probably don’t,” says an official at Bank of New York Mellon, which acts as trustee for several of these vehicles, including the BP Prudhoe Bay Royalty Trust. “I wouldn’t argue with that. That’s why it’s so important for investors to review the financial filings.”

To test the role of media coverage as a catalyst for stock price correction, we search for

an association between daily stock returns and media article releases using the following

regression model:

,id id idRETURN MEDIA (8)

where RETURNid is the market-adjusted stock return for royalty trust i on trading day d and

MEDIAid is an indicator variable that is set to one if the trust has media coverage recycling ASC

932 DCF disclosures.

34

We estimate equation (8) using daily trading data for a total of 56,108 trading days,

which corresponds to roughly 252 trading days for each of the 223 royalty trust firm-years in our

sample. Out of the 56,108 trading days in our sample, we identify 26 trading days with media

coverage.  Note that since our first media coverage event is in 2011, we also replicated this

analysis using only daily observations post-2011. Not surprisingly, the results are almost

identical to those reported for the full sample. In equation (8), the intercept measures the average

stock return for trading days without media coverage and the slope measures the average stock

return spread between trading days with and without media coverage. If the “sell”

recommendations of the media articles in our sample have served as stock price correction

catalysts, then the slope coefficient in equation (8) should be significantly negative.

Column 1 of Table 9, Panel A, presents results based on equation (8). The intercept

implies that the average market-adjusted stock return on trading days without media coverage is

0.02 percent, which is close to zero. The slope coefficient implies that the average stock return

spread between trading days with and without media coverage is -5.85 percent, which is

significantly different from zero. In combination, the intercept and slope coefficient imply that

the average market-adjusted stock return on days with media coverage is -5.83 percent. Column

1 of Table 9, Panel B, presents results based on equation (8) after replacing the raw values of

RETURNid with its absolute values. In essence, |RETURNid| offers an “unsigned” measure of

market reaction. Again, we find consistent evidence that stock prices have reacted significantly

on days with media coverage. As a sensitivity check, we extend the market reaction window to

include days +/-1 relative to the media coverage day (day 0) and find consistent evidence.

35

To gain further insights into the impact of media coverage on investors’ trading behavior,

we test for an association between daily trading volume turnover and media article releases using

the following regression model:

,id id idVOLUME MEDIA (9)

where VOLUMEid is the daily dollar trading volume for royalty trust i on trading day d scaled by

the number of units outstanding.

Column 1 of Table 9, Panel C, presents results based on equation (9). The intercept

implies that the average trading volume on trading days without media coverage is 0.37 percent,

which corresponds to an annualized turnover rate of roughly 93 percent. The slope coefficient

implies that the average trading volume spread between trading days with and without media

coverage is 2.87 percent, which is significantly different from zero. In combination, the intercept

and slope coefficient imply that the average trading volume on days with media coverage is 3.24

percent and corresponds to an annualized unit turnover rate of 817 percent.

To gain further insights, we report results after replacing the indicator variable MEDIAid

in equations (8) and (9) with (i) an indicator variable that is set to one if royalty trust i filed its

annual or quarterly report on trading day d (FILINGid), and (ii) an indicator variable that is set to

one if royalty trust i declared a distribution on trading day d (DECLARid). Across specifications,

the slope coefficients on FILINGid are close to zero, which implies that trading days with SEC

filings are no different from all other trading days in terms of both stock price movements and

trading volume activity. This finding is consistent with the view that investors misprice royalty

trusts because they do not review carefully, if at all, their SEC filings. In contrast, the slope

coefficients on DECLARid are significantly positive, which implies that investors are responsive

36

to distribution declarations and that royalty trust stock prices on average rise around distribution

declaration dates.10

An illustrative example

Overall, we find evidence suggesting that media articles have served as stock price

correction catalysts in the post-2011 period by recycling and disseminating ASC 932 disclosures

to a wide audience of retail investors. To illustrate, the most significant stock price correction in

response to a media article was recorded for the Hugoton Royalty Trust (NYSE:HGT) on

5/22/2012 in response to a Seeking Alpha article entitled “Hugoton Royalty Trust: How to buy 60

cents for a dollar.” This article included a sell recommendation based on the argument that the

large premium of HGT’s market value over the mandatory DCF disclosure is not sustainable.

Although the article merely recycled ASC 932 disclosures available to the public since HGT’s

Form 10-K filing on 2/29/2012, it attracted the attention of several Seeking Alpha readers—as

indicated by the numerous comments posted in response to this article—and caused HGT’s stock

price to crash on high trading volume. On this trading day HGT underperformed the market by -

34.12 percent, experiencing the most negative daily stock return in its trading history.

Post-media-coverage drift 

A related question that emerges is whether media coverage leads to a complete and

timely correction in royalty trust stock prices. To address this question, we extend the stock

market reaction window beyond day zero (i.e., beyond the publication date of media articles) and

cumulate stock returns forward. Figure 4 confirms that the average day zero market-adjusted

stock return of around -6 percent, but also shows that negative returns continue, amounting to -                                                            10 Our finding of positive distribution declaration returns parallels prior evidence of positive earnings announcement returns (e.g., Ball and Kothari, 1991).

37

13 percent and -15 percent cumulated over the subsequent two and four trading weeks,

respectively. Stated otherwise, while royalty trusts tend to experience significantly negative

market-adjusted stock returns on day zero, stock prices continue to drift downward, and the drift

persists for at least four trading weeks. This finding implies that investors underreact to “second

hand” information in media articles recycling ASC 932 DCF disclosures.

Figure 4 also provides evidence that the “sell recommendations” included in our list of

media articles have a negative spillover effect to royalty trusts with no media coverage. The

negative spillover effect amounts to -4 percent and -8 percent average market-adjusted returns

cumulated over the subsequent two and four trading weeks, respectively, and is significantly

different from zero. For comparison purposes, Figure 4 also reports the average returns for 100

“placebo” events. The placebo events correspond to 100 days with no media coverage randomly

selected from the trading history of royalty trusts. Not surprisingly, the cumulated market-

adjusted returns for the placebo events are close to zero. This finding provides additional

evidence that trading days with media coverage differ from other trading days.

Summary of media coverage analysis and relation to prior research

Overall, we find direct evidence that media coverage has served as a significant stock

price correction catalyst in recent years. Our evidence indicates that media coverage can alert

investors to value relevant supplementary disclosures and thus facilitate more efficient pricing.

Our findings are related to prior evidence that stock prices react to news that is already public

information, even when the “new-news” content of media coverage is nil (e.g., Huberman and

Regev, 2001). Our findings also complement recent evidence on the role of the business press in

the pricing of accounting information (e.g., Drake et al., 2014).

38

VII. CONCLUSION

We find that ASC 932 DCF disclosures are incrementally useful for forecasting

distributions and for explaining royalty trust stock prices. Our novel setting mitigates power and

model misspecification problems of prior studies and provides robust evidence on the

incremental relevance of ASC 932 DCF disclosures for valuation. We also find evidence that

investors underweight information in the DCF disclosures when forecasting distributions,

resulting in the mispricing of royalty trusts. Consistent with this explanation, we find that high

royalty trust premia are associated with subsequent reductions in distributions. We also find that

media articles have served as stock price correction catalysts by recycling and disseminating

ASC 932 DCF disclosures to a wide audience of retail investors. Overall, our evidence indicates

that ASC 932 DCF disclosures contain information that is incrementally relevant for valuation,

but that relegating this information to footnote disclosures may limit the extent to which it is

correctly processed and priced by unsophisticated users of corporate financial reports.

39

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42

APPENDIX 1 Labels and definitions of key variables

Label Definition

BVit Book value of equity divided by units outstanding as of end of year t.

CHEit Cash and cash equivalents per unit outstanding as of end of year t.

CHEXTit+1 Extensions, discoveries, and improved recovery, less related costs, disclosed in t+1 per unit outstanding.

CHPRCit+1 Net changes in prices and production costs disclosed in t+1 per unit outstanding.

CHESTit+1 Revisions of previous quantity estimates disclosed in t+1 per unit outstanding.

DCFit Discounted cash flow forecasts of proved reserves divided by units outstanding as of end of year t.

DECLARid Indicator variable =1 if royalty trust i declared a distribution on trading day d.

DIit Distributions divided by units outstanding as of end of year t.

DISTRETURNit+1

The sum of three-day, cumulative market-adjusted stock returns centered on each distribution declaration date in year t+1. We collect information about royalty trust distribution declaration dates from the daily CRSP file.

ΔDIit+1 Change in distributions from year t to year t+1 divided by stock price per unit in t.

FILINGid Indicator variable =1 if royalty trust i filed its annual or quarterly report with the SEC on trading day d.

FTRt The first principal component of the West Texas Intermediate future prices and the Henry Hub natural gas future prices, available from the U.S. Energy Information Administration.

HOGit Historical cost of oil and gas assets divided by units outstanding measured as: BVit – CHEit + LTit.

IVit Imputed value of oil and gas assets per unit outstanding measured as: Pit – CHEit + LTit .

LTit Total liabilities per unit outstanding as of end of year t.

MEDIAid Indicator variable =1 if royalty trust i has media coverage recycling ASC 932 cash flow forecast disclosures on trading day d.

NIit Net income divided by units outstanding as of end of year t.

Pit Stock price per unit outstanding as of the end of year t.

PREMBVit Stock price per unit divided by book value of equity per unit.

43

PREMDCFit Stock price per unit divided by discounted cash flow forecasts per unit.

PREMUCFit Stock price per unit divided by undiscounted cash flow forecasts per unit.

RESRETURNit+1 The residual portion of RETURNit+1 that is not explained by the Fama and French (1993) factors as well as Carhart’s (1997) momentum factor. All factors are available from Professor Kenneth French’s website.

RETURNid Market-adjusted stock return for royalty trust i on trading day d.

RETURNit+1

Buy-and-hold stock return earned from holding a royalty trust unit from three months after the end of fiscal year t to three months after the end of fiscal year t+1 minus the buy-and-hold return earned from holding the CRSP value-weighted index (including distributions) over the same period.

RFt The 10-year Treasury-bond yield as of the end of year t.

SPREADt The spread of the 10-year Treasury-bond yield over Moody’s investment-grade (BAA) corporate bond yield as of the end of year t.

UCFit Undiscounted cash flow forecasts of proved reserves divided by units outstanding as of end of year t.

VOLUMEid Dollar trading volume for royalty trust i on trading day d scaled by the number of units outstanding.

YIELDit The ratio of net income per unit divided by stock price per unit.

44

APPENDIX 2 Mandatory DCF disclosures: An example

The following is an illustrative example of ASC 932 disclosures from the Form 10-K of BP Prudhoe Bay Royalty Trust (NYSE:BPT) for the fiscal year ending December 31, 2011. Note 11: Supplemental Reserve Information and Standardized Measure of Discounted Future Net Cash Flow Relating to Proved Reserves (Unaudited) The standardized measure of discounted future net cash flow relating to proved reserves disclosure required by FASB ASC 932 assigns monetary amounts to proved reserves based on current prices. This discounted future net cash flow should not be construed as the current market value of the Royalty Interest. A market valuation determination would include, among other things, anticipated price changes and the value of additional reserves not considered proved at the present time or reserves that may be produced after the currently anticipated end of field life. At December 31, 2011, 2010 and 2009, the standardized measure of discounted future net cash flow relating to proved reserves attributable to the Trust (estimated in accordance with the provisions of FASB ASC 932), based on the 12-month average WTI Prices for 2011, 2010 and 2009 of $96.19, $79.43 and $61.18 per barrel, respectively, scheduled chargeable costs in future years and production taxes were as follows (in thousands): December 31, 2011 2010 2009 Future cash inflows $ 2,460,471 $ 1,992,585 $ 1,331,319 10% annual discount for estimated timing of cash flows (1,027,358) (806,097) (494,758) Standardized measure of discounted future net cash flow $ 1,433,113 $ 1,186,488 $ 836,561

Key metrics from BPT’s financial statements for the fiscal year ending December 31, 2011 Cash and cash equivalents = $1,018,000 Total liabilities = $128,000 Book value of equity = $890,000 Net income = $201,109,000 Distributions = $201,092,000 Units outstanding = 21,400,000 Cash and cash equivalents per unit (CHEit) = $0.05 Total liabilities per unit (LTit) = $0.01 Book value of equity per unit (BVit) = $0.04 Net income per unit (NIit) = $9.40 Distributions per unit (DIit) = $9.40 Discounted future net cash flows per unit (DCFit) = $66.97 Unit price (Pit), NYSE Closing Trade on March 1st, 2012 (day after Form 10-K filing) = $123.59

45

APPENDIX 3 List of royalty trusts

Royalty trust name Trustee name Oil & gas consulting firm Sample distribution (percent)

BP Prudhoe Bay Royalty Trust Bank of New York Mellon Trust Company Miller and Lents, Ltd. 9.0

Burlington Resources Coal Seam Gas Royalty Trust NationsBank Trust Division Netherland, Sewell & Associates, Inc. 2.2

Cross Timbers Royalty Trust U.S. Trust, Bank of America Private Wealth Management Miller and Lents, Ltd. 8.1

Dominion Resources Black Warrior Trust U.S. Trust, Bank of America Private Wealth Management Ralph E. Davis Associates, Inc. 7.6

ECA Marcellus Trust I Bank of New York Mellon Trust Company Ryder Scott Company, L.P. 0.9

Enduro Royalty Trust Bank of New York Mellon Trust Company Cawley, Gillespie & Associates, Inc. 0.4

Freeport McMoran Oil & Gas Royalty Trust JPMorgan Chase Bank Ryder Scott Company, L.P. 2.2

Hugoton Royalty Trust U.S. Trust, Bank of America Private Wealth Management Miller and Lents, Ltd. 5.8

LL&E Royalty Trust Bank of New York Mellon Trust Company Miller and Lents, Ltd. 7.2

Mesa Royalty Trust Bank of New York Mellon Trust Company DeGolyer and MacNaughton 8.1

MV Oil Trust Bank of New York Mellon Trust Company Cawley, Gillespie & Associates, Inc. 2.2

Permian Basin Royalty Trust U.S. Trust, Bank of America Private Wealth Management Cawley, Gillespie & Associates, Inc. 8.5

Sabine Royalty Trust U.S. Trust, Bank of America Private Wealth Management DeGolyer and MacNaughton 8.5

San Juan Basin Royalty Trust Compass Bank Cawley, Gillespie & Associates, Inc. 8.5

Sandridge Mississippian Trust I Bank of New York Mellon Trust Company Netherland, Sewell & Associates, Inc. 0.4

Sandridge Permian Trust Bank of New York Mellon Trust Company Netherland, Sewell & Associates, Inc. 0.4

TEL Offshore Trust Bank of New York Mellon Trust Company DeGolyer and MacNaughton 3.1

Torch Energy Royalty Trust Wilmington Trust Company T.J. Smith & Company, Inc./ Netherland, Sewell & Associates, Inc.

7.2

VOC Energy Trust Bank of New York Mellon Trust Company Cawley, Gillespie & Associates, Inc. 0.4

Whiting USA Trust I Bank of New York Mellon Trust Company Cawley, Gillespie & Associates, Inc. 1.8

Williams Coal Seam Royalty Trust U.S. Trust, Bank of America Private Wealth Management Miller and Lents, Ltd. 7.2

Notes: The sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

46

APPENDIX 4 List of media articles recycling mandatory DCF disclosures

Publication Date Royalty Trust Name Source Link

1/21/2011 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/article/247756

2/6/2011 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/symbol/bpt/instablogs

2/10/2011 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/article/251928

6/3/2011 Whiting USA Trust Seeking Alpha seekingalpha.com/symbol/whx/instablogs

8/11/2011 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/article/286706

5/22/2012 Hugoton Royalty Trust Seeking Alpha seekingalpha.com/article/608191

5/23/2012 Hugoton Royalty Trust Seeking Alpha seekingalpha.com/symbol/hgt/instablogs

5/23/2012 San Juan Royalty Trust Seeking Alpha seekingalpha.com/symbol/sjt/instablogs

7/12/2012 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/article/717481

7/17/2012 Whiting USA Trust Seeking Alpha seekingalpha.com/article/725671

7/17/2012 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/article/725671

8/7/2012 San Juan Royalty Trust Seeking Alpha seekingalpha.com/article/787351

8/10/2012 Hugoton Royalty Trust Seeking Alpha seekingalpha.com/article/618821

8/10/2012 San Juan Royalty Trust Seeking Alpha seekingalpha.com/article/618821

8/14/2012 Whiting USA Trust Seeking Alpha seekingalpha.com/article/804861

8/24/2012 BP Prudhoe Bay Royalty Trust Wall Street Journal online.wsj.com/news/articles/

8/24/2012 Whiting USA Trust Wall Street Journal online.wsj.com/news/articles/

8/29/2012 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/symbol/bpt/currents

8/29/2012 Dominion Black Warrior Trust Seeking Alpha seekingalpha.com/symbol/dom/currents/on-the-move

8/29/2012 Hugoton Royalty Trust Seeking Alpha seekingalpha.com/symbol/hgt/currents/on-the-move

8/29/2012 San Juan Royalty Trust Seeking Alpha seekingalpha.com/symbol/sjt/currents/on-the-move

10/15/2012 SandRidge Mississippian Trust I Seeking Alpha seekingalpha.com/article/923441

1/23/2013 BP Prudhoe Bay Royalty Trust Seeking Alpha seekingalpha.com/article/1128591

2/27/2013 ECA Marcellus Trust I Seeking Alpha seekingalpha.com/article/1228231

3/19/2013 SandRidge Mississippian Trust I Seeking Alpha seekingalpha.com/article/1285851

3/19/2013 ECA Marcellus Trust I Seeking Alpha seekingalpha.com/article/1285931

Notes: The list includes 22 media articles recycling ASC 932 DCF disclosures for a total of 26 royalty trust mentions.

47

TABLE 1 Descriptive statistics for value-relevance tests

Panel A: Empirical distributions. Mean Std. Dev. Q1 Median Q3 Pit 21.29 19.93 7.00 15.45 28.50 CHEit 0.19 0.33 0.01 0.05 0.22 LTit 0.16 0.31 0.01 0.03 0.15 IVit 21.26 19.89 7.02 15.45 28.51 DCFit 12.55 14.05 4.32 7.62 16.11 UCFit 24.03 30.18 6.74 14.06 29.65 BVit 3.51 4.47 0.32 1.91 5.07 HOGit 3.47 4.49 0.13 1.87 5.07 DIit 2.13 1.90 0.77 1.69 2.86 NIit 2.16 1.88 0.81 1.72 2.91 Panel B: Pairwise correlations. Variable (1) (2) (3) (4) (5) (6) (7) (8) (1) Pit 1.00 0.80 0.75 0.01 -0.00 0.89 0.89 <0.001 <0.001 <0.001 0.908 0.990 <0.001 <0.001

(2) IVit 1.00 0.80 0.75 0.01 0.00 0.89 0.89 <0.001 <0.001 <0.001 0.896 0.995 <0.001 <0.001

(3) DCFit 0.86 0.86 0.98 0.08 0.08 0.75 0.75 <0.001 <0.001 <0.001 0.235 0.257 <0.001 <0.001

(4) UCFit 0.86 0.86 0.99 0.08 0.08 0.68 0.68 <0.001 <0.001 <0.001 0.213 0.227 <0.001 <0.001

(5) BVit 0.29 0.29 0.38 0.36 1.00 0.08 0.11 <0.001 <0.001 <0.001 <0.001 <0.001 0.217 0.115

(6) HOGit 0.22 0.22 0.32 0.30 0.99 0.08 0.10 0.001 0.001 <0.001 <0.001 <0.001 0.255 0.144

(7) DIit 0.88 0.88 0.82 0.80 0.38 0.31 0.99 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001

(8) NIit 0.89 0.89 0.83 0.80 0.41 0.33 0.99 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001

This table reports descriptive statistics for the following variables: stock price per unit (Pit), cash and cash equivalents per unit (CHEit), total liabilities per unit (LTit), imputed value of oil and gas assets per unit (IVit), ASC 932 discounted cash flow forecasts per unit (DCFit), ASC 932 undiscounted cash flow forecasts per unit (UCFit), book value of equity per unit (BVit), historical cost of oil and gas assets per unit (HOGit), distributions per unit (DIit), and net income per unit (NIit). Panel A reports the empirical distributions. Panel B reports Pearson (Spearman) pairwise correlations above (below) the main diagonal and two-sided p-values. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

48

TABLE 2 Predictive ability of mandatory DCF disclosures for future distributions

Panel A: Predictive content for one-year-ahead distributions. Dependent variable = DIit+1 (1) (2) (3) (4) Intercept 0.641 2.033 0.269 0.220 t-statistic (White) 4.21*** 11.39*** 1.73* 2.69*** t-statistic (BRL) 2.22** 3.68*** 2.24** 1.58 DCFit 0.117 0.070 t-statistic (White) 7.99*** 4.82*** t-statistic (BRL) 3.92*** 3.41*** BVit 0.025 -0.010 t-statistic (White) 1.31 -1.06 t-statistic (BRL) 0.43 -0.60 NIit 0.872 0.494 t-statistic (White) 9.72*** 5.50*** t-statistic (BRL) 13.10*** 13.44*** Adj. R2 0.707 0.000 0.691 0.815 Panel B: Predictive content for forward-cumulated distributions.

Dependent variable = 5

1 itDI

(1) (2) (3) (4) Intercept 3.854 9.252 2.272 2.382 t-statistic (White) 5.52*** 11.64*** 3.16*** 3.64*** t-statistic (BRL) 3.81*** 3.63*** 2.96*** 2.49** DCFit 0.428 0.240 t-statistic (White) 6.64*** 4.23*** t-statistic (BRL) 6.12*** 11.70*** BVit 0.017 -0.115 t-statistic (White) 0.19 -1.74* t-statistic (BRL) 0.06 -1.16 NIit 3.296 2.028 t-statistic (White) 8.09*** 5.21*** t-statistic (BRL) 20.32*** 12.17*** Adj. R2 0.462 -0.004 0.482 0.552 This table reports results from regressions of future distributions per unit on ASC 932 discounted cash flow forecasts per unit (DCFit), book value of equity per unit (BVit), and net income per unit (NIit). Panel A presents results for one-year-ahead distributions per unit (DIit+1). Panel B presents results for distributions per unit cumulated forward over a five-year horizon. The t-statistics are based on White’s (1980) heteroskedasticity-consistent standard errors or Bell and McCaffrey’s (2002) bias reduced linearization (BRL) standard errors. ***, **, and * indicate statistical significance at 1, 5, and 10 percent levels, respectively, using two-tailed tests. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

49

TABLE 3 Explanatory ability of mandatory DCF disclosures for current stock prices

Panel A: Regressions of stock price per unit.

Dependent variable = Pit (1) (2) (3) (4) Intercept 7.031 21.169 1.041 1.990 t-statistic (White) 4.25*** 11.42*** 0.83 2.38* t-statistic (BRL) 2.49** 3.96*** 1.09 2.20** DCFit 1.137 0.445 t-statistic (White) 6.97*** 3.24** t-statistic (BRL) 4.92*** 4.72*** BVit 0.035 -0.388 t-statistic (White) 0.16 -3.12** t-statistic (BRL) 0.06 -1.82* NIit 9.392 6.995 t-statistic (White) 12.82*** 7.43*** t-statistic (BRL) 50.43*** 11.32*** Adj. R2 0.640 -0.004 0.783 0.832 Panel B: Regressions of imputed value per unit.

Dependent variable = IVit (1) (2) (3) (4) Intercept 7.007 21.249 1.043 1.998 t-statistic (White) 4.24*** 11.45*** 0.83 2.38** t-statistic (BRL) 2.50** 3.97*** 1.09 2.23** DCFit 1.136 0.447 t-statistic (White) 6.98*** 3.26*** t-statistic (BRL) 4.94*** 4.79*** HOGit 0.002 -0.391 t-statistic (White) 0.01 -3.16*** t-statistic (BRL) 0.00 -1.87* NIit 9.375 6.958 t-statistic (White) 12.83*** 7.45*** t-statistic (BRL) 50.53*** 11.40*** Adj. R2 0.642 -0.005 0.783 0.833 Panels A and B of this table reports results from regressions of stock price per unit (Pit) and imputed value of oil and gas assets per unit (IVit) on ASC 932 discounted cash flow forecasts per unit (DCFit), book value of equity (BVit), historical cost of oil and gas assets per unit (HOGit), and net income per unit (NIit). The t-statistics are based on White’s (1980) heteroskedasticity-consistent standard errors or Bell and McCaffrey’s (2002) bias reduced linearization (BRL) standard errors. ***, **, and * indicate statistical significance at 1, 5, and 10 percent levels, respectively, using two-tailed tests. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

50

TABLE 4 Stock market reaction to predictable distributions

Dependent variable = RETURNit+1 (1) (2)

Intercept -0.181 -0.163 t-statistic (White) -2.34** -0.84 t-statistic (BRL) -2.31** -1.20

1residualitDI 4.338 4.338

t-statistic (White) 5.81*** 5.59*** t-statistic (BRL) 5.17*** 5.07***

1fitted

itDI 2.017 t-statistic (White) 2.75*** t-statistic (BRL) 2.97***

1DCFititDI 2.284

t-statistic (White) 3.52*** t-statistic (BRL) 3.62***

1BVititDI -2.128

t-statistic (White) -1.49 t-statistic (BRL) -2.15**

1NIititDI 1.695

t-statistic (White) 1.52 t-statistic (BRL) 1.65 Adj. R2 0.266 0.274 This table presents results from regressions of market-adjusted stock returns in t+1 (RETURNit+1) on the residual and fitted portions of distributions in t+1 (DIit+1). In Column 1, the residual and fitted portions of DIit+1 are based on a first-stage regression of DIit+1 on (i) the ASC 932 discounted cash flow forecasts in t (DCFit), (ii) the book value of equity in t (BVit), and (iii) net income in t (NIit). In Column 2, we decompose the fitted portion of DIit+1 into the portions predictable on a stand-alone basis by DCFit, BVit, and NIit. To allow comparisons with returns, distributions and distribution components in t+1 are scaled by stock price per unit in t. The t-statistics are based on White’s (1980) heteroskedasticity-consistent standard errors or Bell and McCaffrey’s (2002) bias reduced linearization (BRL) standard errors. ***, **, and * indicate statistical significance at 1, 5, and 10 percent levels, respectively, using two-tailed tests. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

51

TABLE 5 Descriptive statistics for royalty trust premia tests

Panel A: Empirical distributions.

Mean Std. Dev. Q1 Median Q3 PREMDCFit 2.03 1.15 1.29 1.88 2.49 I(PREMDCFit) 0.87 0.34 1.00 1.00 1.00 PREMUCFit 1.19 0.83 0.71 1.04 1.42 I(PREMUCFit) 0.53 0.50 0.00 1.00 1.00 PREMBVit 87.00 312.21 2.68 10.47 46.26 I(PREMBVit) 0.95 0.23 1.00 1.00 1.00 YIELDit 0.12 0.07 0.08 0.10 0.13 ΔDIit+1 0.00 0.08 -0.03 0.00 0.03 RETURNit+1 0.05 0.49 -0.29 -0.04 0.26  

Panel B: Pairwise correlations. Variable (1) (2) (3) (4) (5) (6) (1) PREMDCFit 0.96 0.10 -0.19 -0.26 -0.17 <0.001 0.121 0.004 <0.001 0.009

(2) PREMUCFit 0.95 0.09 -0.09 -0.25 -0.17 <0.001 0.161 0.179 <0.001 0.013

(3) PREMBVit 0.33 0.28 -0.11 -0.03 -0.03 <0.001 <0.001 0.099 0.707 0.631

(4) YIELDit -0.23 -0.11 -0.32 -0.42 0.12 <0.001 0.093 <0.001 <0.001 0.067

(5) ΔDIit+1 -0.31 -0.32 0.01 -0.44 0.38

<0.001 <0.001 0.853 <0.001 <0.001

(6) RETURNit+1 -0.11 -0.13 0.12 0.09 0.30 0.090 0.062 0.069 0.200 <0.001

This table reports descriptive statistics for the following variables: premium of market value over the ASC 932 discounted cash flow forecasts (PREMDCFit), premium of market value over the ASC 932 undiscounted cash flow forecasts (PREMUCFit), premium of market value over the book value of equity (PREMBVit), along with indicator variables I(Variable) =1 if Variable>1 and =0 otherwise, as well as the net income yield (YIELDit), one-year-ahead distribution changes (ΔDIit+1), and one-year-ahead market-adjusted stock returns (RETURNit+1). Panel A reports the empirical distributions. Panel B reports Pearson (Spearman) pairwise correlations above (below) the main diagonal and two-sided p-values. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

52

TABLE 6 Predictive ability of royalty trust premia for future stock returns

Panel A: Regressions of one-year-ahead market-adjusted stock returns.

Dependent variable = RETURNit+1 (1) (2) (3) (4)

Intercept 0.197 -0.265 0.163 -0.335 t-statistic (White) 2.72*** -0.90 2.71*** -1.18 t-statistic (BRL) 5.18*** -1.16 4.74*** -1.55 PREMDCFit -0.074 -0.078 t-statistic (White) -2.80*** -2.88*** t-statistic (BRL) -4.24*** -4.49*** PREMUCFit -0.098 -0.107 t-statistic (White) -2.72*** -2.92*** t-statistic (BRL) -3.63*** -4.07*** PREMBVit 0.000 0.000 t-statistic (White) 0.35 0.40 t-statistic (BRL) 0.23 0.25 YIELDit 0.032 0.180 t-statistic (White) 0.04 0.24 t-statistic (BRL) 0.08 0.46 RFt 4.889 5.371 t-statistic (White) 1.19 1.31 t-statistic (BRL) 1.62 1.83* SPREADt 9.512 9.453 t-statistic (White) 1.81* 1.80* t-statistic (BRL) 2.21** 2.20** FTRt -0.043 -0.040 t-statistic (White) -1.31 -1.25 t-statistic (BRL) -1.46 -1.42 Adj. R2 0.026 0.039 0.023 0.040

53

Panel B: Regressions of one-year-ahead factor-adjusted stock returns. Dependent variable = RESRETURNit+1 (1) (2) (3) (4)

Intercept 0.153 -0.243 0.120 -0.297 t-statistic (White) 2.71*** -0.97 2.45** -1.20 t-statistic (BRL) 3.31*** -1.08 2.88*** -1.39 PREMDCFit -0.075 -0.065 t-statistic (White) -3.22*** -2.69*** t-statistic (BRL) -3.65*** -3.65*** PREMUCFit -0.101 -0.092 t-statistic (White) -3.02*** -2.78*** t-statistic (BRL) -3.22*** -3.35*** PREMBVit -0.000 -0.000 t-statistic (White) -0.56 -0.50 t-statistic (BRL) -0.29 -0.25 YIELDit 0.478 0.595 t-statistic (White) 0.82 1.03 t-statistic (BRL) 1.54 1.79* RFt 4.596 4.983 t-statistic (White) 1.47 1.59 t-statistic (BRL) 1.66* 1.82* SPREADt 4.222 4.189 t-statistic (White) 0.89 0.88 t-statistic (BRL) 1.01 1.00 FTRt 0.029 0.032 t-statistic (White) 1.00 1.11 t-statistic (BRL) 1.30 1.43 Adj. R2 0.042 0.039 0.039 0.041 This table reports results from regressions of one-year-ahead stock returns on the premium of market value over the ASC 932 discounted cash flow forecasts (PREMDCFit) or the premium of market value over the undiscounted cash flow forecasts (PREMUCFit), the premium of market value over the book value of equity (PREMBVit), the net income yield (YIELDit), the 10-year Treasury-bond yield (RFt), the spread of the 10-year Treasury-bond yield over Moody’s investment grade corporate bond yield (SPREADt), and our index of future oil and gas spot prices (FTRt). Panel A reports results from regressions of one-year-ahead market-adjusted stock returns (RETURNit+1). Panel B reports results from regressions of one-year-ahead factor-adjusted stock returns (RESRETURNit+1). Factor-adjusted stock returns are measured based on the residual portion of RETURNit+1 that is not explained by the Fama and French (1993) factors as well as Carhart’s (1997) momentum factor. All factors are available from Professor Kenneth French’s website. The t-statistics are based on White’s (1980) heteroskedasticity-consistent standard errors or Bell and McCaffrey’s (2002) bias reduced linearization (BRL) standard errors. ***, **, and * indicate statistical significance at 1, 5, and 10 percent levels, respectively, using two-tailed tests. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

54

TABLE 7 Sources of variation in royalty trust premia:

Tests evaluating mispricing and measurement error explanations

Dependent variable = PREMDCFit (1) (2) (3) Intercept 2.045 2.303 1.845 t-statistic (White) 26.11*** 4.15*** 3.29*** t-statistic (BRL) 18.87*** 3.43*** 2.56** RETURNit+1 -0.410 -0.723 t-statistic (White) -3.34*** -5.00*** t-statistic (BRL) -4.05*** -3.85*** RFt -7.960 -2.049 t-statistic (White) -0.92 -0.23 t-statistic (BRL) -0.69 -0.17 SPREADt 3.310 11.671 t-statistic (White) 0.36 1.42 t-statistic (BRL) 0.37 1.26 CHPRCit+1 0.015 0.025 t-statistic (White) 2.19** 3.18*** t-statistic (BRL) 2.16** 1.99** CHESTit+1 0.074 0.092 t-statistic (White) 3.22*** 3.60*** t-statistic (BRL) 1.91* 1.67* CHEXTit+1 0.028 0.013 t-statistic (White) 0.21 0.11 t-statistic (BRL) 0.16 0.07 Adj. R2 0.026 0.056 0.131 This table reports results from regressions of the premium of market value over the ASC 932 discounted cash flow forecasts (PREMDCFit) on the following variables: one-year-ahead market-adjusted stock returns (RETURNit+1), the 10-year Treasury-bond yield (RFt), the spread of the 10-year Treasury-bond yield over Moody’s investment grade corporate bond yield (SPREADt), the one-year-ahead net changes in prices and production costs (CHPRCit+1), the one-year-ahead revisions of previous quantity estimates (CHESTit+1), as well as the one-year-ahead extensions, discoveries, and additions, less related costs (CHEXTit+1). The t-statistics are based on White’s (1980) heteroskedasticity-consistent standard errors or Bell and McCaffrey’s (2002) bias reduced linearization (BRL) standard errors. ***, **, and * indicate statistical significance at 1, 5, and 10 percent levels, respectively, using two-tailed tests. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

55

TABLE 8 Future distribution changes as stock price correction catalysts

Panel A: Regressions of one-year-ahead distribution changes. Dependent variable = ΔDIit+1 (1) (2) Intercept 0.035 0.027 t-statistic (White) 2.32** 2.01** t-statistic (BRL) 2.53** 2.17** PREMDCFit -0.017 t-statistic (White) -2.62*** t-statistic (BRL) -2.70*** PREMUCFit -0.023 t-statistic (White) -2.16** t-statistic (BRL) -2.27** Adj. R2 0.062 0.057 Panel B: Regressions of one-year-ahead distribution declaration returns. Dependent variable = DISTRETURNit+1 (1) (2) Intercept 0.092 0.081 t-statistic (White) 3.54*** 3.83*** t-statistic (BRL) 5.08*** 4.46*** PREMDCFit -0.022 t-statistic (White) -2.19** t-statistic (BRL) -2.73*** PREMUCFit -0.028 t-statistic (White) -2.11** t-statistic (BRL) -2.07** Adj. R2 0.021 0.018 Panel A of this table reports results from regressions of the one-year-ahead change in distributions scaled by the beginning of year stock price per unit (ΔDIit+1) on the premium of market value over the ASC 932 discounted cash flow forecasts (PREMDCFit) and the premium of market value over the ASC 932 undiscounted cash flow forecasts (PREMUCFit). Panel B of this table reports results from regressions of distribution declaration returns in t+1 (DISTRETURNit+1) on royalty trust premia in t. We collect information about royalty trust distribution declaration dates from the daily CRSP file and measure DISTRETURNit+1 as the sum of three-day, cumulative market-adjusted stock returns centered on declaration dates in t+1. The t-statistics are based on White’s (1980) heteroskedasticity-consistent standard errors or Bell and McCaffrey’s (2002) bias reduced linearization (BRL) standard errors. ***, **, and * indicate statistical significance at 1, 5, and 10 percent levels, respectively, using two-tailed tests. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

56

TABLE 9 Media articles recycling mandatory DCF disclosures as stock price correction catalysts

Panel A: Daily market-adjusted stock returns. Dependent variable = RETURNid

1

1

d

iddRETURN

(1) (2) (3) (4) (5) (6) Intercept 0.0002 0.0002 0.0002 0.0007 0.0006 0.0005 t-statistic (White) 2.01** 1.66* 1.30 3.52*** 3.09*** 2.36** t-statistic (BRL) 2.45** 1.98** 1.53 2.33** 2.06** 1.60 MEDIAid -0.0585 -0.1120 t-statistic (White) -3.67*** -3.81*** t-statistic (BRL) -3.68*** -2.67*** FILINGid 0.0010 0.0019 t-statistic (White) 1.01 1.24 t-statistic (BRL) 0.98 0.91 DECLARid 0.0018 0.0055 t-statistic (White) 2.47** 4.01*** t-statistic (BRL) 2.70*** 4.00*** Adj. R2 0.002 -0.000 0.000 0.003 0.000 0.000 Panel B: Absolute daily market-adjusted returns. Dependent variable = |RETURNid|

1

1

d

iddRETURN

(1) (2) (3) (4) (5) (6) Intercept 0.0175 0.0175 0.0174 0.0299 0.0299 0.0298 t-statistic (White) 185.31*** 183.39*** 181.37*** 199.90*** 197.72*** 197.21*** t-statistic (BRL) 14.28*** 14.28*** 14.35*** 16.15*** 16.22*** 16.29*** MEDIAid 0.0409 0.0868 t-statistic (White) 2.57** 3.03*** t-statistic (BRL) 2.60*** 2.15** FILINGid 0.0001 -0.0013 t-statistic (White) 0.11 -1.10 t-statistic (BRL) 0.11 -0.74 DECLARid 0.0026 0.0041 t-statistic (White) 4.68*** 3.78*** t-statistic (BRL) 1.77* 2.19** Adj. R2 0.002 -0.000 0.000 0.003 -0.000 0.000

57

Panel C: Daily trading volume turnover. Dependent variable = VOLUMEid

1

1

d

iddVOLUME

(1) (2) (3) (4) (5) (6) Intercept 0.0037 0.0038 0.0037 0.0112 0.0113 0.0112 t-statistic (White) 160.67*** 157.33*** 155.30*** 187.30*** 183.74*** 181.56*** t-statistic (BRL) 9.21*** 9.13*** 9.12*** 9.21*** 9.13*** 9.15*** MEDIAid 0.0287 0.0780 t-statistic (White) 3.72*** 4.16*** t-statistic (BRL) 3.86*** 3.73*** FILINGid -0.0003 -0.0006 t-statistic (White) -1.81* -1.19 t-statistic (BRL) -1.14 -0.74 DECLARid 0.0003 0.0007 t-statistic (White) 2.54** 2.02** t-statistic (BRL) 1.07 1.05 Adj. R2 0.012 0.000 0.000 0.014 0.000 0.000 This table report results from regressions of various measures of market reaction on (i) an indicator variable =1 if royalty trust i has media coverage recycling ASC 932 DCF disclosures published by either the Wall Street Journal or the social media platform Seeking Alpha on trading day d (MEDIAid), (ii) an indicator variable =1 if royalty trust i filed its annual or quarterly report with the SEC on trading day d (FILINGid), and (iii) an indicator variable =1 if royalty trust i declared a distribution on trading day d (DECLARid). Panel A measures the daily market-adjusted stock returns (RETURNid), Panel B measures the absolute value of daily market-adjusted return (|RETURNid|), and Panel C measures the daily trading volume turnover (VOLUMEid). The t-statistics are based on White’s (1980) heteroskedasticity-consistent standard errors or Bell and McCaffrey’s (2002) bias reduced linearization (BRL) standard errors. ***, **, and * indicate statistical significance at 1, 5, and 10 percent levels, respectively, using two-tailed tests. Our sample includes 56,108 trading days for 21 royalty trusts with fiscal years ending from 1992 to 2012.

58

FIGURE 1 Time series of combined market value for royalty trust universe

Using t This figure presents the distribution of observations over time along with the combined market value of royalty trusts. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

0

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Total m

arket value ($ Billion)

Num

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lty tr

usts

N of Royalty Trusts Total Market Value

59

FIGURE 2 Predictive ability of royalty trust premia for future stock returns:

Portfolio analysis

Panel A: Portfolios based on premium over ASC 932 discounted cash flows forecasts.

Panel B: Portfolios based on premium over ASC 932 undiscounted cash flows forecasts.

Panels A and B of this figure present average one-year-ahead market-adjusted stock returns across tercile portfolios (low, medium, and high) formed based on the premium of market value over ASC 932 discounted and undiscounted cash flow forecasts, respectively. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

14.4%

6.0%

-6.4%

-20.8%-25%

-20%

-15%

-10%

-5%

0%

5%

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Low Medium High High-Low

Ave

rage

one

-yea

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ead

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12.1%9.6%

-7.8%

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Low Medium High High-Low

Ave

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60

FIGURE 3 Principal sources of change in mandatory DCF disclosures

This figure presents bar charts with the average values for the principal sources of change in the mandatory DCF disclosures scaled by the number of units outstanding, using hand-collected information from the notes to the financial statements pursuant FASB ASC 932. The principal sources of changes presented are (i) royalty income, (ii) other revisions, (iii) changes in income taxes, (iv) development costs incurred during the period, (v) extensions, discoveries, and additions, less related costs, (vi) revisions of previous quantity estimates, (vii) net changes in prices and production costs, and (viii) accretion of discount. We note that the average change in the mandatory DCF disclosures per unit is equal to the sum of the average values of all principal sources of change (i)-(viii). The hollow diamonds correspond to the median values and the stars correspond to the inter-quartile range. Our sample includes 223 observations for 21 royalty trusts with fiscal years ending from 1992 to 2012.

-$2.24

-$0.03

$0.00 $0.00 $0.12 $0.22$0.46

$1.25

-$0.22

Royaltyincome

Otherrevisions

Change inincome taxes

Developmentcosts

Extensions,discoveries &

additions

Revisions ofquantityestimates

Change inprices andproduction

costs

Accretion ofdiscount

Change inDCF

61

FIGURE 4 Media articles recycling mandatory DCF disclosures as stock price correction catalysts:

Event-time analysis

This figure presents average market-adjusted stock returns for our sample of media articles published by either the Wall Street Journal or the social media website Seeking Alpha recycling ASC 932 DCF disclosures. The media articles are published on trading day zero and daily market-adjusted stock returns are cumulated forward starting from the beginning of day zero. The figure also presents the average market-adjusted stock returns for royalty trusts without media coverage cumulated forward over the same measurement window as well as the average returns for 100 “placebo” events. The placebo events correspond to 100 days with no media coverage randomly selected from the trading history of royalty trusts. Appendix 4 provides our list of media articles.

-0.16

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0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Cum

ulat

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tock

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urns

Trading day relative to media coverage date

with Media Coverage w/o Media Coverage Placebo