THE ACCOUNTING REVIEW
Vol. 79, No. 2
2004
pp. 453–472
Fair Values, Income Measurement,
and Bank Analysts’ Risk and
Valuation Judgments
D. Eric Hirst
The University of Texas at Austin
Patrick E. Hopkins
James M. Wahlen
Indiana University
ABSTRACT: We examine how fair-value-income measurement affects commercial
bank equity analysts’ risk and value judgments. Normatively, holding information and
other underlying economics constant, bank analysts’ risk and valuation assessments
should distinguish between banks with different risks, but should not depend on how
banks measure income. In our experiment, we vary income measurement—full-fairvalue (all fair-value changes recognized in income) versus piecemeal-fair-value (some
fair-value changes recognized in income, others disclosed in the notes). We also vary
interest-rate-risk exposure (exposed versus hedged). We find that bank analysts’ risk
and value judgments distinguish banks’ exposure to interest-rate risk only under fullfair-value-income measurement. Our evidence contributes to research concerned with
financial performance reporting, risk, and fair-value accounting by demonstrating that
differences in income measurement affect fundamental judgments of specialist analysts. Our findings are striking because they: (1) point toward an important role for
measurement and recognition of fair-value gains and losses in income, and (2) suggest
that note disclosure is not a substitute for financial-statement recognition (even for
professional analysts specializing in banks and working in a context that involves assessment of core operations of a bank). These results should be of interest to accounting standard setters as they evaluate whether to require full-fair-value-income
measurement.
We very much appreciate the analysts who generously contributed their time and effort to this study and the helpful
comments of two anonymous reviewers, Denny Beresford, Linda Bamber, Mike Bamber, Leslie Hodder, Vicky
Hoffman, Laureen Maines, Mary Lea McAnally, Molly Mercer, Don Moser, Mark Nelson, Steve Salterio, Rick
Tubbs, the participants at Emory University’s 2001 Behavioral Financial Reporting Conference, the 2001 Big Ten
Research Conference, the 2002 Utah Winter Accounting Conference, the 2002 Accounting, Behavior and Organizations Conference, and workshop participants at the Austin Society of Financial Analysts, the Boston Accounting
Research Colloquium, Emory University, University of Georgia, Michigan State University, University of Minnesota, Northwestern University, University of Pittsburgh, The University of Texas Brownbag Series, Texas A&M
University, and Washington University. We are grateful for the research assistance of D. Craig Nichols and Alex
Yen. Funding for this research came from the Center for Business Measurement and Assurance Services at The
University of Texas at Austin and the Kelley School of Business summer research fund.
Editor’s note: This paper was accepted by Marlys Gascho Lipe, Editor.
Submitted February 2003
Accepted September 2003
453
454
Hirst, Hopkins, and Wahlen
Keywords: banks; fair value; risk; performance reporting; financial analysts; behavioral
finance.
Data Availability: Contact the authors.
I. INTRODUCTION
re the judgments of financial analysts, when working within their area of specialization, affected by methods of income measurement? Specifically, do the risk and
value judgments of equity analysts who specialize in commercial-bank stocks depend on whether banks measure income based on full-fair-value accounting versus the
current piecemeal-fair-value accounting? We address this question by conducting an experiment in which we vary two factors, while holding constant the total amount of available
information and the underlying economics of the situation. First, we vary whether the bank
takes or hedges interest-rate risk. Second, we construct two alternate measures of the bank’s
income: (1) full-fair-value income, recognizing fair-value gains and losses on all financial
assets and liabilities, consistent with a proposed shift to full-fair-value-income measurement; and (2) piecemeal-fair-value income, with fair-value gains and losses on availablefor-sale securities recognized in income, but fair-value gains and losses on all other financial
instruments disclosed in the notes, consistent with SFAS Nos. 107, 115, and 130. Our
primary tests compare bank analysts’ risk and value judgments across the two income
measures for the exposed and hedged banks.1
Our research question and findings are important to accounting-research scholars, bank
managers, and analysts interested in whether piecemeal versus full recognition of fair-value
gains and losses in income affects analysts’ judgments of bank risk and value. Beaver
(1997), Feltham and Ohlson (1999), and others characterize equity value as a function that
increases in expected future profitability and decreases in nondiversifiable risk, all else
equal. Common notions of market efficiency suggest share prices should reflect all publicly
available value-relevant information (including any value-relevant information in fair values
of financial instruments), independent of whether market participants obtain the information
from the financial statements, footnotes, or sources outside of the financial statements. Thus,
firm value should depend on the fundamental information available to forecast profitability,
assess risk, and determine share value, not on how firms measure income.2 Therefore, two
straightforward normative predictions emerge: (1) analysts who specialize in evaluating
banks should assess the exposed bank to have greater risk and lower share value than the
hedged bank, holding profitability and all else equal, and (2) holding constant the total
amount of information and the underlying economics of the bank, these analysts’ risk and
value judgments should depend only on fundamental elements of the bank’s profitability
and risk, not on how the bank measures income.
A
1
2
Banks’ balance sheets are almost wholly comprised of financial instruments. Banks can hedge interest-rate risk
(i.e., unexpected changes in interest rates in the economy) either by matching maturities of fixed-rate financial
assets (e.g., investment securities and loans) with fixed-rate financial liabilities (e.g., deposits), or by matching
repricing dates of variable-rate assets and liabilities. Banks can take interest-rate risk by holding interest-bearing
financial assets and liabilities with differing maturities or repricing dates, triggering gains or losses when interest
rates change. The U.S. thrift crisis, which may have been exacerbated by limited recognition and disclosure of
the effects of interest-rate risk on thrifts’ historical-cost-based financial statements, triggered (in part) the evolution toward more complete fair-value recognition and disclosure. See Ryan (2002) for an excellent text on the
accounting and economics associated with financial institutions and financial instruments.
Differences in how firms measure income can, however, trigger contracting and regulatory consequences, which
can indirectly impact firm value. For purposes of this study, we do not focus on these indirect valuation consequences of income measurement.
The Accounting Review, April 2004
Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
455
Archival research on the value- and risk-relevance of fair values provides only mixed
support for these normative predictions. Capital-markets-based studies provide mixed results
on the association between bank-share prices and fair values of financial instruments (e.g.,
Barth 1994, and many others). Archival studies also provide mixed evidence on whether
the capital markets price as risk the incremental volatility in bank income from changes in
fair values (Barth et al. 1995; Hodder et al. 2003). Of course, archival research cannot test
directly these normative predictions because it cannot vary how banks measure and report
fair-value gains and losses in income.
Prior experimental research on the influence of reporting format on analysts’ judgments
also casts doubt on whether these normative predictions will hold. In particular, prior studies
find that when firms report income more completely and transparently, nonspecialist analysts and nonprofessional investors make judgments that more completely distinguish differences in firm risk and value (e.g., Hirst and Hopkins 1998; Maines and McDaniel 2000).
These studies argue that more complete and transparent reporting formats increase analysts’
information acquisition and use. Current accounting standards for comprehensive-income
measurement are incomplete for banks insofar as they omit fair-value gains and losses from
changes in market-interest rates on certain financial assets and liabilities (e.g., loans and
deposits) that are central to bank operations. Therefore, users of bank financial statements
must spend additional time and effort to incorporate the effects of unrecognized fair-value
gains and losses in their judgments and decisions (Guay et al. 2002). Professional analysts
have limited time and resources to devote to accounting-data collection and analysis. These
constraints may lead to incomplete acquisition and processing of banks’ unrecognized fairvalue gains and losses (Hirshleifer and Teoh 2002; Hirshleifer et al 2002). If full-fair-value
accounting provides more complete measurement in income of fair-value gains and losses
from banks’ exposure to interest-rate risk, then this information will more likely influence
bank analysts’ judgments about risk and value, consistent with the findings of Hirst and
Hopkins (1998) and Maines and McDaniel (2000).
In contrast, Lipe (1998) and Maines and McDaniel (2000) argue that the judgments of
analysts who specialize in firms for which fair values are central to core operations will
routinely evaluate fair-value information wherever it is disclosed. Thus, consistent with the
normative view, they argue that different measures of income will not affect specialist
analysts’ judgments. Bank analysts should understand that banks face interest-rate risk.
Under full-fair-value accounting, banks would recognize all fair-value gains and losses in
income when interest rates change. However, such a shift in income measurement would
not provide any new information because banks currently report fair values of financial
assets and liabilities in the notes under the requirements of SFAS No. 107. Therefore,
arguments in Lipe (1998) and Maines and McDaniel (2000) imply that full-fair-value accounting will not change bank-specialist analysts’ risk and value judgments; instead, they
should already incorporate full-fair-value information because it relates to banks’ core operations. Our experiment tests whether bank analysts’ risk and value judgments depend on
different fair-value-income measurements, resolving the conflicting views on whether the
findings in Hirst and Hopkins (1998) and Maines and McDaniel (2000) generalize to industry specialists.
Contrary to the normative predictions, we find that bank analysts’ risk and valuation
judgments do depend on how banks measure income, holding constant the available information and underlying economics. In particular, analysts’ risk and value assessments of the
exposed bank depend on how the bank measures income, but analysts’ assessments of
the hedged bank do not. Also, we find that analysts assess statistically significantly higher
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456
Hirst, Hopkins, and Wahlen
risk and lower value judgments for the exposed bank than for the hedged bank only under
full-fair-value-income measurement. Under piecemeal-fair-value-income measurement, analysts assess a slight difference in risk across the exposed and hedged bank, but the difference is only marginally statistically significant. Furthermore, under piecemeal-fair-valueincome measurement, we find that bank analysts’ value judgments do not distinguish
between exposed and hedged banks. Our experiment contributes new evidence to show that
piecemeal- versus full-fair-value-income measures influence fundamental judgments of analysts that specialize in banks, alleviating concerns about whether findings by Hirst and
Hopkins (1998) and Maines and McDaniel (2000) generalize to industry specialists when
evaluating core operations of firms.
In addition to contributing new evidence to the academic research literature, our findings on the effects of fair-value recognition versus disclosure on analysts’ risk and value
judgments are also timely and important for the Financial Accounting Standards Board
(FASB) and the International Accounting Standards Board (IASB). These standard setters
are currently working on proposals to require recognizing all financial assets and liabilities
at fair value on the balance sheet and all fair-value gains and losses in a statement of
financial performance. The Joint Working Group of Standard Setters (JWGSS 2000) supports the FASB’s consideration of full-fair-value recognition of all financial instruments.
The JWGSS (2000, 151) asserts that fair values provide superior information about financial
instruments because they: (1) reflect economic conditions or events in the period in which
they take place, and (2) provide a better basis for analysis and prediction because they
reflect future expectations as of the financial statement date. Although our results cannot
determine whether analysts’ judgments are better per se under full-fair-value-income measurement, our findings suggest that full-fair-value-income measurement enables even professional analysts who specialize in banks to more clearly distinguish fundamental risk and
share value characteristics of banks.
We organize the remainder of the paper as follows. In Section II, we review the current
state of fair-value reporting and the full-fair-value accounting proposals. We also describe
our predictions of how analysts use fair-value data under different income measurement
regimes. We describe our experiment and results in Sections III and IV. We summarize and
conclude in Section V.
II. BACKGROUND AND PREDICTIONS
Current and Proposed Reporting Environment
Accounting standards have increasingly incorporated fair values into financial reports,
but this evolution has resulted in a piecemeal collection of disclosed and recognized fairvalue amounts. For example, SFAS No. 107 (FASB 1991) requires note disclosure—but
does not allow financial statement recognition—of fair values of most financial assets and
liabilities. SFAS No. 115 (FASB 1993) requires balance sheet recognition of fair values of
investment securities classified as trading or available-for-sale. SFAS No. 130 (FASB 1997)
requires firms to report comprehensive income, but SFAS No. 115 requires them to report
fair-value gains and losses on three different categories of investment securities in three
different places (i.e., trading securities in net income; available-for-sale securities in comprehensive income; and held-to-maturity securities in the notes). Finally, regulatory disclosures (e.g., interest-rate gap tables and market-risk disclosures) summarize exposures to
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Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
457
changes in interest rates and other market factors, but do not measure or disclose the impact
of these factors on current performance.3
During the public deliberation of SFAS No. 130, commercial bank representatives repeatedly asserted that piecemeal-fair-value-income measurement would misrepresent banks’
economic risk and performance (Hirst et al. 2002; SFAS No. 115, para. 93). In particular,
these representatives claimed that comprehensive income misrepresents banks’ interest-raterisk management because comprehensive income includes fair-value gains and losses on
available-for-sale securities, but excludes fair-value gains and losses on all other financial
assets (e.g., held-to-maturity securities and loans) and all financial liabilities (e.g., deposits),
thereby causing financial statement users to overestimate risk (particularly for banks that
hedge interest-rate risk).
In response to dissatisfaction with piecemeal recognition of fair values, the FASB and
the IASB are currently considering proposing standards that require full-fair-value accounting for all financial instruments (e.g., FASB 1999, para. 334). Consistent with the recommendation of the JWGSS (2000), the FASB has stated their intention to require full-fairvalue-income measurement, recognizing all fair-value gains and losses in a statement of
performance. The FASB also is reviewing SFAS No. 107 with an eye to providing additional
disaggregation of fair-value changes, as well as a total for the income impact of fair-value
changes (FASB 2002).
Prior Related Archival Research
Existing archival research provides mixed results on the risk- and value-relevance of
reported fair values. These studies find that bank stock prices reflect the levels of some (but
not all) fair values disclosed in the notes to the financial statements under SFAS No. 107,
and find mixed results on whether bank stock returns covary with fair-value gains and
losses (e.g., Barth 1994; Barth et al. 1996; Eccher et al. 1996; Nelson 1996). Carroll et al.
(2003) find that fair-value gains and losses explain stock returns for closed-end mutual
funds, which measure financial position and income on a fair-value basis. Archival studies
also report mixed results on the association between fair-value-income volatility and risk.
Barth et al. (1995) find that the market prices do not appear to reflect incremental volatility
in income from fair-value changes in investment securities. In contrast, Hodder et al. (2003)
find that full-fair-value-income volatility correlates positively with market-based measures
of bank interest-rate risk and negatively with bank-share prices, consistent with fair-value
volatility being priced as incremental risk. Competing potential explanations exist for the
mixed results in prior archival studies. Prior empirical tests of banks may not have completely controlled for correlated omitted variables (e.g., fair-value gains and losses omitted
from income), or the market may not completely impound fair values and related risks into
bank-share prices.
Archival research cannot resolve the disputes over the purported problems or benefits
associated with the current piecemeal or potential full-fair-value-income measurement because archival designs cannot vary how banks measure and report income to test whether
(or how) capital-markets participants would use full-fair-value income to assess risk and
share values. Because of these limitations, we conduct an experiment in which we explicitly
vary bank-fair-value-income-measurement methods, to complement prior archival studies
and provide evidence on whether bank analysts’ judgments depend on whether banks measure income based on full-fair-value accounting or piecemeal-fair-value accounting.
3
For a more detailed discussion of regulatory disclosures of fair values and risk measures, see Hodder (2001),
Hodder et al. (2001), and Hodder and McAnally (2001).
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Hirst, Hopkins, and Wahlen
Normative Predictions
A shift to full-fair-value income measurement would change income measurement but
would not provide any new information. Under SFAS No. 107, bank financial statement
footnotes provide sufficient information to compute full-fair-value income. Because of the
importance of financial instruments and interest-rate risk to banks, analysts who specialize
in evaluating banks should use the disclosed information on fair-value gains and losses
(which reflect the outcomes of exposure to interest-rate risk in financial instruments) to
assess profitability, risk, and share value, whether a bank measures income on a full-fairvalue basis or on a piecemeal-fair-value basis with supplemental note disclosure. In addition, because equity valuation models typically increase in profitability and decrease in risk,
analysts should estimate greater risk and lower share value for a bank exposed to changes
in fair values attributable to interest-rate risk, and lower risk and greater share value for a
bank that hedges such risk, holding profitability and all else constant. Thus, our normative
predictions are: (1) holding constant the available information and underlying economics,
the risk and value judgments of bank-specialist analysts will not be affected by incomemeasurement method, and (2) bank-specialist analysts will assess greater risk and lower
share price for an exposed bank than for a hedged bank, holding profitability and all else
constant.
Prior Related Experimental Research
The tension related to these two normative predictions—and thus the primary contribution of this study—emerges from a comparison of these predictions with the results of
prior experimental research related to fair values and comprehensive income. Hirst and
Hopkins (1998) vary comprehensive-income-reporting format and analyze the judgments
of nonspecialist analysts. They find that when firms report more complete and transparent
income measurements, analysts make judgments that more completely distinguish differences in firm risk and value.
In contrast, Lipe (1998), Maines and McDaniel (2000), and others assert that the Hirst
and Hopkins (1998) findings may not generalize to a setting involving specialist analysts
who routinely evaluate firms for which fair values are central to core operations.4 Consistent
with the normative view, their arguments imply that bank analysts will already incorporate
fair-value gains and losses into their assessment of bank risk and share value, regardless of
whether the bank reports piecemeal-fair-value- or full-fair-value-income measures. VeraMuñoz et al. (2001) provide evidence consistent with this position, finding that specialized
experience helps problem solvers gather and use relevant problem-solving information.
Thus, analysts who specialize in banks may be more likely to obtain and use full-fair-valueincome measures to assess banks’ risk and share values.
Why would professional analysts of banks not use fair-value gains and losses information in assessing bank risk and share value? Under what conditions will the normative
predictions not hold? A growing body of evidence in the behavioral finance literature (e.g.,
Barberis and Thaler 2003; Hirshleifer and Teoh 2002; Hirshleifer et al. 2002; Bloomfield
4
Maines and McDaniel (2000) also provide a framework for predicting reporting-format effects for nonprofessional investors and find that nonprofessional investors differentially acquire and weight fair-value gains and
losses, depending on the format of the comprehensive income report. They test the framework in the context of
comprehensive income reporting for an insurer because comprehensive income is related to the insurer’s core
operations. However, they did not test the framework using professional investors who specialize in an industry
for which fair-value gains and losses are important; therefore, Lipe’s concerns about generalizablility also apply
to the Maines and McDaniel’s study.
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Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
459
2002) suggests that analysts face significant constraints on the time and effort they can
devote to accounting-data acquisition and analysis. The typical equity analyst works in a
cognitively demanding environment and must perform a variety of different tasks, including
security analysis, portfolio management, marketing, and other tasks. In addition, buy-side
analysts usually work for funds that own large numbers of companies, requiring analysts
to follow many current and prospective investments.5 Thus, analysts receive a diffuse, steady
flow of potentially relevant information about the economy, industries, and each company
they follow.
Although the current piecemeal-fair-value-income measurement regime provides all of
the data that analysts need to compute full-fair-value income, banks report these data in
different locations in the financial statements and footnotes, increasing the time and effort
to acquire fair-value data. Analysts cannot rely on most commercial electronic databases
to reduce the costs of gathering these data, because many databases do not include fairvalue-footnote data (Sirota Consulting 1998). Buy-side analysts also cannot rely on fairvalue analysis generated by either sell-side analysts6 or the financial press because most
sell-side and press reports use financial data and ratios based on recognized (i.e., piecemealfair-value) accounting numbers, such as book-to-market and price-to-earnings (e.g., Bary
2002). Thus, although fair-value data are relevant elements of banks’ publicly available
financial information, time- and effort-constrained bank analysts must incur incremental
costs to acquire and use these data. Under piecemeal-fair-value-income measurement, even
specialist analysts may not acquire and use fair-value disclosures (Bloomfield 2002;
Hirshleifer and Teoh 2002, Hirshleifer et al 2002; Plumlee 2003).7 Under full-fair-valueincome measurement, where banks measure income with all fair-value gains/losses and
report it in a performance statement, analysts may be more likely to acquire and use riskrelevant and value-relevant fair-value information than under piecemeal-fair-value-income
measurement.
There are, therefore, compelling normative reasons why specialist analysts should acquire and use full-fair-value-income data for banks, consistent with notions of capitalmarket efficiency with respect to value-relevant information and analyst expertise (Lipe
1998). In contrast, compelling practical reasons exist for why specialist analysts may not
acquire and use all of the available fair-value data when they are reported on a piecemeal
basis. Our experiment sheds light on these two possibilities.
III. EXPERIMENT
We investigate the effects of fair-value-income measurement on equity analysts’ risk
and share-value judgments with a 2 ⫻ 2 (piecemeal-fair-value versus full-fair-value-income
measurement, and hedged versus exposed interest-rate risk) between-subjects experiment.
5
6
7
For example, the average buy-side analyst in Hirst and Hopkins (1998) spent only 43 percent of his or her time
on security analysis. In addition, the median analyst follows 40–45 companies that are owned by the fund that
employs him / her, and follows an additional 40 companies that are not owned by his / her employer (Hirst and
Hopkins 1998; Hopkins et al. 2000).
We read a variety of sell-side analysts’ bank research reports but found no discussion of fair-value gains / losses
and no valuation models that explicitly used fair-value data.
Assuming that analysts do not fully integrate note-based fair-value information in natural settings is not an
unreasonable assumption. A recent survey of almost 2,000 analysts by the Association for Investment Management and Research indicates that 83 percent wished that stock options were expensed in the statement of
performance and that one-third explicitly ignore stock-option-related expense information in the footnotes (Alpert
2002).
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460
Hirst, Hopkins, and Wahlen
Fifty-six buy-side equity-security analysts and portfolio managers participated in the experiment.8 We recruited all participants individually from the 2000 Association for Investment Management and Research Membership Directory (AIMR 2000) on the basis of their
self-reported industry specialization (banking) and job descriptions. After securing their
agreement to participate, we distributed the materials to the participants and they returned
them via overnight mail.9
The study participants have a median (mean) of 10 (11.8) years of experience as financial analysts (experience ranges from 1 year to 39 years; 77 percent are CFAs). They
spend an average of 50 percent of their time on equity-security analysis and another 30
percent on portfolio management. The average participant performs financial analysis for a
fund that manages $876 million (median $100 million) and invests in 52 companies (median
40). In addition to the companies in their funds’ portfolios, these analysts follow another
88 companies (median 35). On average, their employers have $20 billion (median $4.8
billion) of assets under management.
Procedure
We provided participants with background information about a bank (including an
overview of its interest-rate-risk-management strategy), industry average price-earnings ratios (15x) and ranges (10–20x), a description of the interest-rate environment, summary
historical financial information, and a stylized press release reporting the bank’s annual
earnings. The press release included the current year’s comparative financial statements, a
summary of significant accounting policies, and a summary of significant risks including
relevant footnote and MD&A disclosures regarding liquidity risk, credit risk, interest-rate
risk, and fair values. We asked participants to review these materials and then to estimate
the value of the bank’s common stock. We also asked participants to describe the manner
in which they estimated share value. Following these questions, we asked analysts to assess
various types of risks faced by the bank. Finally, we asked analysts a series of questions
about the financial information in the case, several manipulation checks, and demographic
information. We divided the materials between two packets. We asked for the primary
dependent variables in the first packet, and for the manipulation checks, recall measures,
and demographic questions in the second packet.
Materials and Independent Variables
To create materials representative of a typical commercial bank, we first created a model
of the prototypical bank’s financial statements based on a composite of the financial statements of 11 of the 100 largest U.S. banks as of year-end 1999. We then created a computer
simulation for the prototypical bank’s financial statements over a six-year span, varying a
set of baseline assumptions about asset and liability growth rates, credit losses, dividend
payouts, tax rates, and noninterest income and expense items. We applied these assumptions
equally across all conditions. We presented analysts with the bank’s financial statements
8
9
We received responses from 63 individuals. Because of the criticisms of prior research designs, we decided
(prior to data collection) to only include responses from individuals who actively perform equity-security analysis. Seven individuals indicated that they spent zero percent of their time performing equity-security analysis.
We eliminated them from the sample.
To gain access to significant numbers of experienced and specialized financial analysts, we chose to distribute
the experimental materials by overnight mail, allowing analysts to complete the experiment without our direct
supervision. We recruited the participants individually and they volunteered to participate willingly, so there is
a greater likelihood that they took the task seriously.
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Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
461
for the last three years of the simulation together with summary footnote and MD&A
disclosures as part of the press release described earlier.10
In the early years of the simulation, we assumed that interest rates were steady, varying
only a few basis points up or down each year. This assumption held the effects of interestrate risk constant across the exposed and hedged banks during the first two years included
in the instrument. We introduced a 50-basis-point increase in the Federal Funds target rate
at the end of the final year of the simulation.11
Income Measurement
The first independent variable is income measurement. We vary the income measurement of fair-value gains and losses from interest-rate risk in two ways. In the piecemealfair-value (PFV) condition, we recognize fair-value gains and losses on investment securities in a separate performance statement that follows the income statement, and disclose
fair-value gains and losses on all other financial assets and liabilities in footnotes (consistent
with a recommendation in SFAS No. 130). In the full-fair-value (FFV) condition, we recognize fair values of all financial assets and liabilities on the balance sheet and we recognize
all fair-value gains and losses in a separate performance statement that follows the income
statement (consistent with proposals being developed by the FASB and IASB). In both
income-measurement conditions, we provide equivalent sets of financial information to
analysts. Analysts seeking to adjust reported income to reflect fair-value gains and losses
on any or all interest-rate-sensitive financial assets and liabilities can do so. Figure 1 demonstrates the equivalence of various income measures across conditions.
Interest Rate Risk Exposure
The second independent variable is the relative level of the bank’s interest-rate-risk
exposure.12 We varied the extent to which the bank matched maturities of interest-ratesensitive assets (loans and investment securities) and liabilities (deposits, federal funds,
short-term and long-term liabilities). In both conditions, the banks described their interestrate-risk-management strategy and provided gap tables (i.e., measures of exposure based
on the net differences between interest-rate-sensitive assets and liabilities maturing at different times) consistent with that strategy (see Figure 2). All participants received equivalent
sets of information to determine whether the bank hedges or takes interest-rate risk and to
estimate share value.
In the hedged condition, the bank matched the maturities of interest-rate-sensitive assets
and liabilities, lending and borrowing at fixed rates over five-year maturities. By matching
maturities each year, the hedged bank had relatively small interest-rate-exposure ‘‘gaps.’’
Following an upward movement in rates, the hedged bank experienced fair-value losses on
its fixed-rate assets and roughly equivalent fair-value gains on its fixed-rate liabilities.
In the exposed condition, the bank did not match the maturities of interest-rate-sensitive
assets and liabilities. The exposed bank’s loans and investment securities earned interest
rates fixed over five-year maturities, but it borrowed funds at rates fixed over one-year
10
11
12
We patterned the footnote and MD&A disclosures in the instrument to be similar to the relevant footnote and
MD&A disclosures of these 11 banks in 1999.
We limit our investigation to the risk associated with an adverse change in interest rates (i.e., resulting in net
financial losses). See Hodder et al. (2001) for a discussion of risk perception and evidence that risk perceptions
may not be symmetric across gains and losses.
Our discussions with finance professionals at financial institutions and our review of bankers’ comment letters
to the FASB in response to the Comprehensive Income exposure draft indicate that banks’ interest-rate-risk
strategies span a wide range between attempts to completely hedge such risk and willingness to take it.
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462
Hirst, Hopkins, and Wahlen
FIGURE 1
Performance Measures Included in Experiment
Panel A: Hedged Conditions (in millions)a
(Regular typeset numbers were explicitly reported in statements of performance in the
experimental materials; bold numbers were calculable from the materials.)
FFV
PFV
Income Measure
20X3
20X2
20X1
20X3
20X2
20X1
Reported Net Income
Reported Comprehensive Income b
20.3
20.2
18.6
18.9
16.7
16.5
20.3
16.7
18.6
18.9
16.7
16.4
Full-fair-value Incomec
20.2
18.9
16.5
20.2
18.9
16.5
Panel B: Exposed Conditions (in millions)a
(Regular typeset numbers were explicitly reported in statements of performance in the
experimental materials; bold numbers were calculable from the materials.)
PFV
FFV
Income Measure
20X3
20X2
20X1
20X3
20X2
20X1
Reported Net Income
Reported Comprehensive Income b
20.3
12.1
18.6
20.1
16.7
15.3
20.3
16.7
18.6
18.9
16.7
16.4
Full-fair-value Incomec
12.1
20.1
15.3
12.1
20.1
15.3
a
In the hedged conditions, the bank matched the maturities of the interest-rate-sensitive assets and liabilities,
lending and borrowing at fixed rates over five-year maturities. In the exposed conditions, the bank’s loans and
investment securities earned fixed rates over five years (exactly equivalent to the hedged conditions), but
borrowed funds at fixed rates with one-year maturities.
b
The financial statements in the FFV conditions explicitly displayed comprehensive income on the same page as
the Income Statement and included changes in the fair values of all financial assets and liabilities in the
calculation of comprehensive income. In conformity with SFAS No. 130, the financial statements in the PFV
condition explicitly displayed comprehensive income on the same page as the Income Statement and, in
conformity with SFAS No. 115, included only changes in the fair values of available-for-sale marketable
securities as a component of comprehensive income.
c
Full-fair-value income equals net income adjusted for changes in fair values of all of the bank’s financial assets
and liabilities. These figures were reported as comprehensive income in the FFV conditions. In the PFV
conditions, FFV income could be derived from the financial statements and the notes thereto.
maturities. By not matching maturities, the exposed bank had relatively large interest-rateexposure ‘‘gaps’’ each year.13 Following an upward movement in rates, the exposed bank
experienced relatively large fair-value losses on its fixed-rate assets, but only modest gains
on its fixed-rate liabilities.
The year-end interest-rate increase triggered fair-value losses of $19.2 million (before
tax) on the interest-rate-sensitive assets for both the exposed and the hedged bank. However,
this interest-rate shock also triggered fair-value gains of $19.0 million (before tax) on
interest-sensitive liabilities for the hedged bank, thereby offsetting almost all of the fairvalue losses. The exposed bank experienced fair-value gains of only $7.1 million, leaving
13
For the exposed bank, we repriced (i.e., applied the currently prevailing interest rates to) roughly 20 percent of
the interest-rate-sensitive assets and 100 percent of the interest-sensitive liabilities each year. By contrast, for
the hedged bank, we repriced 20 percent of both the interest-rate-sensitive assets and liabilities each year.
The Accounting Review, April 2004
463
Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
FIGURE 2
Excerpts from Experimental Materials: Table of Interest-Rate-Repricing Gapa
Panel A: Hedged Conditions
($ in thousands, at amortized cost)
Loans
Investment securities
Deposits
Short-term borrowings
Long-term borrowings
Repricing gap
One Year or Less
One to Five Years
Total
$ 302,516
$ 57,138
$ (217,808)
$ (229,935)
$0
$ 710,066
$ 328,552
$ (871,233)
$0
$ (134,040)
$ 1,012,582
$ 385,690
$ (1,089,041)
$ (229,935)
$ (134,040)
$ (88,089)
$ 33,345
$ (54,744)
One Year or Less
One to Five Years
Total
$ 302,516
$ 57,138
$ (871,233)
$ (229,935)
$0
$ 710,066
$ 328,552
$ (217,808)
$0
$ (134,040)
$ 1,012,582
$ 385,690
$ (1,089,041)
$ (229,935)
$ (134,040)
$ (741,514)
$ 686,770
$ (54,744)
Panel B: Exposed Conditions
($ in thousands, at amortized cost)
Loans
Investment securities
Deposits
Short-term borrowings
Long-term borrowings
Repricing gap
a
In the experimental materials, we provide an interest-rate-repricing-gap table in the descriptive
information that precedes the 20X3 annual earnings release.
a net fair-value loss (before tax) of nearly $12.1 million (roughly 40 percent of net pretax
income).
IV. RESULTS
Manipulation and Other Checks
Bank interest-rate-risk exposure is a critical manipulation in this study. To determine
whether analysts understood the bank’s risk-management strategy, we asked several questions in the post-experiment questionnaire. First, we asked participants to indicate the extent
to which the bank was exposed to interest-rate risk at December 31, 20X3. Using a 15point scale (endpoints labeled 1 ⫽ interest-rate risk is completely hedged and 15 ⫽ interestrate risk is completely exposed), the analysts’ interest-rate-risk assessments for the exposed
bank (11.92) were greater (F ⫽ 36.03, p ⫽ .00) than those for the hedged bank (7.72). To
assess analysts’ expectations for the bank’s interest-rate risk in the future, we also asked
for their expectations of the bank’s exposure over the next two to three years, using an
analogous scale. Participants’ responses regarding expected future interest-rate risk for the
exposed bank (10.48) were greater (F ⫽ 10.65, p ⫽ .00) than for the hedged bank (7.57).
These findings suggest that analysts recognized the difference in interest-rate exposure
across the hedged and exposed bank and did not expect it to change in the near future.
We also asked participants to assess the banks’ market risk, which we defined as the
possibility that changes in future market rates or prices will make positions less valuable,
using a 15-point scale (endpoints labeled 1 ⫽ much lower than the average bank and 15
⫽ much higher than the average bank with a midpoint of 8 ⫽ equal to the average bank).
Analysts considered the exposed bank (11.14) to be more risky than the hedged bank (8.25)
The Accounting Review, April 2004
464
Hirst, Hopkins, and Wahlen
(F ⫽ 28.68, p ⫽ .00). This held true in each of the income measurement conditions (both
p’s ⬍ .03).14
We also asked participants to recall the amount of the change in the Federal Funds
Target Rate included in our materials. Ninety-four percent of the analysts correctly indicated
that the rate increased by 50 basis points, suggesting that analysts understood the level of
increase in interest rates across all conditions.15 Finally, an important correlated omitted
factor in fair-value research is the potential for different levels of fair-value reliability
between financial statement recognition and disclosure in the notes. Analysts’ responses to
a question about the reliability of fair-value information revealed no differences in perceived
reliability across conditions (all p’s ⬎ .46). Taken together, these data suggest that analysts
understood the critical manipulation in the study and that we controlled for perceived
reliability, an important factor.
Tests of Predictions
We test bank analysts’ judgments using two different dependent measures: investment
risk and share value. Our two normative predictions are that differences in income measurement (PFV versus FFV) will not influence bank analysts’ judgments of risk and share
value for a given bank, and that bank analysts will assess greater risk and lower share value
for the exposed bank compared to the hedged bank. Therefore, if the normative view is
descriptive, we should find a main effect for differences in interest-rate-risk exposure across
banks and no main effect for differences in income measurement for a given bank. However,
when considering the institutional environment faced by buy-side bank analysts, we believe
that analysts must expend additional time and effort to acquire fair-value data under the
PFV condition relative to the FFV condition. If bank analysts are more likely to acquire
and evaluate fair-value gain and loss data when banks measure and report FFV income,
then they will be more likely to distinguish risk and value between hedged and exposed
banks that measure and report FFV income, and less likely to distinguish between hedged
and exposed banks that measure and report PFV income.
Investment Risk Judgments
To examine investment risk judgments, we asked two investment-risk-related questions.
The first question asked analysts to assess the investment risk of the bank relative to that
of an average bank of equivalent size. Analysts provided their relative-risk assessments on
a 15-point scale (endpoints labeled 1 ⫽ much lower than the average bank and 15 ⫽ much
higher than the average bank). The second question asked them to assess the investment
risk of the bank in the context of a diversified portfolio. Analysts provided their risk assessments on a 15-point scale (endpoints labeled 1 ⫽ very low and 15 ⫽ very high). The
responses to these questions were positively correlated (.37, p ⫽ .00), so we analyze the
average of the two.16 Table 1 reports descriptive statistics and tests of analysts’ assessments
of the bank’s risk as an investment.
We begin by establishing whether income measurement (PFV or FFV) affects analysts’
judgments of the risk of investing in a bank with hedged or exposed interest-rate risk.
Results in Table 1 reveal that there is a significant interaction between risk exposure and
income measurement (F ⫽ 4.16, p ⫽ .05). Tests of mean differences indicate that, for the
14
15
16
In addition, participants judged the liquidity and credit risk of the banks. Neither was significantly different
across risk levels (both p’s ⬎ 0.25).
Two analysts indicated that interest rates decreased by 50 basis points and one indicated that rates increased by
100 basis points. Three analysts did not answer this manipulation-check question.
Analyzing each one separately gives qualitatively similar results.
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Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
465
TABLE 1
Analysis of Investment-Risk Judgments by Interest-Rate-Risk
Exposure and Income-Measurement Conditions
Panel A: Investment-Risk Judgments: Mean [Median] (Standard Deviation)a
Interest-Rate-Risk
Exposureb
Exposed
Hedged
Column data
Income Measurementb
PFV
FFV
10.10
[10.50]
(2.42)
n ⫽ 13
6.68
[6.00]
(1.95)
n ⫽ 13
8.39
[8.25]
(2.77)
n ⫽ 26
8.11
[7.50]
(2.45)
n ⫽ 15
6.94
[7.00]
(1.21)
n ⫽ 15
7.52
[7.25]
(1.99)
n ⫽ 30
Row data
9.03
[9.25]
(2.60)
n ⫽ 28
6.82
[6.75]
(1.57)
n ⫽ 28
Panel B: Analysis of Variance
Factor
d.f.
F-value
p-value
Income Measurement
Risk Exposure
Income Measurement * Risk Exposure
Residual
1
1
1
52
2.46
17.31
4.16
.12
.00
.05
Panel C: Tests of Means
Comparison
d.f.
PFV versus FFV (Exposed)
PFV versus FFV (Hedged)
Exposed versus Hedged (PFV)
Exposed versus Hedged (FFV)
52
52
52
52
t-Statistic
2.55
⫺0.33
1.56
4.23
Probability
.01
.74
.06c
.00c
a
Immediately after providing their share-value judgments, analysts assessed the risk of an investment in the
bank’s common stock relative to that of an average bank of equivalent size (15-point scale with endpoints
labeled 1 ⫽ much lower than the average bank and 15 ⫽ much higher than the average bank) and the risk of
investing in the bank’s common stock in the context of a diversified portfolio (15-point scale with endpoints
labeled 1 ⫽ very low and 15 ⫽ very high). The two responses were significantly correlated (.37, p ⫽ .00).
Consequently, we report analyses of the average of the two risk judgments.
b
We manipulated income measurement by varying whether the bank reported fair-value gains and losses on a
full-fair-value (FFV) or a piecemeal-fair-value (PFV) basis. We manipulated risk exposure by varying whether
the bank hedged or was exposed to interest-rate risk.
c
One-tailed.
hedged bank, analysts’ judgments reflect no differences in investment risk across incomemeasurement conditions (t ⫽ ⫺0.33, p ⫽ .74). However, for the exposed bank, analysts
judge the investment risk higher under FFV than PFV income-measurement conditions
(10.10 versus 8.11, t ⫽ 2.55, p ⫽ .01). Furthermore, analysts are better able to discern a
difference in investment risk for the exposed bank versus the hedged bank under the FFVreporting regime than under the PFV regime. Analysts in the FFV conditions assess greater
The Accounting Review, April 2004
466
Hirst, Hopkins, and Wahlen
investment risk for the exposed bank than the hedged bank (10.10 versus 6.68; t ⫽ 4.23,
p ⫽ .00, one-tailed). In contrast, analysts in the PFV conditions also judge the investment
risk to be higher for the exposed bank (8.11) than the hedged bank (6.94), but the difference
is only marginally significant (t ⫽ 1.56, p ⫽ .06, one-tailed).
These results indicate that, contrary to the normative predictions, professional bank
analysts’ investment-risk judgments depend on how banks measure fair-value income. For
the hedged bank, investment-risk judgments do not differ across income measures, consistent with the analysts not being misled by the incomplete income recognition of fair-value
gains and losses under PFV measurement. However, for the exposed bank, the analysts’
investment-risk judgments differ across FFV and PFV income measures.
Share Value Judgments
Normatively, bank analysts should assign a higher share value to the bank with lower
risk, holding all else equal. For a given bank, analysts’ share-value judgments should not
be influenced by how income is measured (FFV versus PFV). Table 2 provides descriptive
and inferential statistics for the analysts’ share-value judgments. Consistent with the pattern
of judgments of investment risk, we find that there is a significant interaction between risk
exposure and income measurement (F ⫽ 2.97, p ⫽ .05). Tests of mean differences indicate
that, for the hedged bank, analysts’ judgments reflect no difference in share value across
income-measurement conditions (t ⫽ .22, p ⫽ .83). However, for the exposed bank, analysts’ share-value estimates are lower under FFV than PFV income-measurement conditions
($11.26 versus $13.06, t ⫽ ⫺2.21, p ⫽ .03). Furthermore, analysts’ share-value estimates
are more reflective of interest-rate-risk exposure under the FFV-reporting regime than under
the PFV regime. Analysts in the FFV conditions assessed lower share values for the exposed
bank than the hedged bank ($11.26 versus $14.10, t ⫽ ⫺3.37, p ⫽ .00, one-tailed). However, under the PFV regime, share-value estimates are not different across the hedged versus
the exposed bank (t ⫽ ⫺1.09, p ⫽ .14, one-tailed).17
Discussion and Further Evidence
Our results show that analysts’ judgments about investment risk and share value consistently distinguish between the exposed and hedged bank only under the FFV condition,
where income includes full recognition of fair-value gains and losses in a performance
statement. In contrast to the normative predictions and the concerns of Lipe (1998), Maines
and McDaniel (2000), and others, we find that FFV-income measurement aids industryspecialist analysts in distinguishing fundamental characteristics of risk and value across
hedged and exposed banks. This suggests the FFV-income measurement helps analysts
reduce the cognitive costs of acquiring fair-value data, linking these data to performance
and risk, and impounding these effects into valuation judgments. In this section, we discuss
several limitations of our analyses, and present supplemental data on analysts’ recall of
fair-value data (to infer acquisition of these data), the effects of work environment on fairvalue-data acquisition, and the effects of fair-value-data acquisition on analysts’ risk and
value judgments.
17
We also asked analysts to estimate the bank’s PE ratio based on trailing net income, which is constant across
conditions (see Figure 1). We instructed analysts that ‘‘even if you did not use an earnings-multiple-based
approach to arrive at your stock-price estimate, please provide a PE ratio that you believe is appropriate for
estimating the value of [the bank’s] common stock.’’ The results (not tabulated) indicate that, consistent with
the investment-risk and share-value judgments, there is a statistically significant interaction between risk exposure
and income measurement. Results of detailed tests of the PE judgments are similar to the results from the tests
of share-value judgments.
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Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
467
TABLE 2
Analysis of Share-Value Judgments by Interest-Rate-Risk
Exposure and Income-Measurement Conditions
Panel A: Share-Value Judgments: Mean [Median] (Standard Deviation)a
Interest-Rate-Risk
Exposureb
Exposed
Hedged
Column data
Income Measurementb
PFV
FFV
11.26
[11.75]
(1.98)
n ⫽ 13
14.10
[14.00]
(2.44)
n ⫽ 13
12.68
[12.75]
(2.62)
n ⫽ 26
13.06
[12.38]
(2.10)
n ⫽ 15
13.92
[14.00]
(2.07)
n ⫽ 15
13.49
[12.94]
(2.09)
n ⫽ 30
Row data
12.22
[12.18]
(2.20)
n ⫽ 28
14.00
[14.00]
(2.20)
n ⫽ 28
Panel B: Analysis of Variance
Factor
d.f.
F-value
p-value
Income Measurement
Risk Exposure
Income Measurement * Risk Exposure
Residual
1
1
1
52
1.99
10.33
2.97
.16
.00
.05c
Panel C: Tests of Means
Comparison
d.f.
t-Statistic
Probability
PFV versus FFV (Exposed)
PFV versus FFV (Hedged)
Exposed versus Hedged (PFV)
Exposed versus Hedged (FFV)
52
52
52
52
⫺2.21
.03
.83
.14c
.00c
.22
⫺1.09
⫺3.37
a
Analysts estimated the value of a share of the bank’s common stock immediately after receiving information
about the bank. All participants received background information that included a description of the bank’s
liquidity, credit, and market risks (including an interest-rate gap analysis) and an earnings-announcement press
release that included an income statement, balance sheet, statement of changes in equity, and a summary of
significant accounting policies (including SFAS No. 107 and SFAS No. 115 data).
b
Refer to Table 1 for a description of the independent variables.
c
One-tailed.
Our experimental design is limited insofar as it does not include a universally accepted
‘‘correct’’ set of responses, so we cannot unconditionally claim that FFV reporting leads to
‘‘better’’ judgments. We find it striking, however, that bank specialists assess greater risk
and lower share value to the exposed bank than the hedged bank only under FFV-income
measurement. Under PFV-income measurement, banks analysts do not assess consistently
significant differences in risk or share value across banks with fundamentally different levels
of risk.
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468
Hirst, Hopkins, and Wahlen
Our results cannot be attributed to several specific forms of fixation, or lack of effort,
on the part of the analysts. For example, if analysts simply fixated on reported comprehensive income, we would have found significant value-judgment differences across PFV and
FFV conditions for the hedged bank—we did not. If analysts simply focused on net income
(which was the same across conditions) or did not attend to the task, we would have found
no differences across conditions. Again, the pattern of results rules this out.18
Supplemental data on analysts’ recall provide evidence of the cognitive effects of FFV
versus PFV income measurement. We included two questions in the post-experiment questionnaire (in packet 2) to measure whether analysts acquired fair-value gain and loss data.
Specifically, we asked each participant to recall the location that the bank reported unrealized gains and losses on (1) available-for-sale investment securities and (2) deposits and
borrowings.19 We asked for recall data on these two sets of unrealized gains and losses
because their locations varied across the different income-measurement conditions. For the
available-for-sale securities, the bank reported unrealized gains and losses in a performance
statement in all four experimental conditions, whereas the bank reported unrealized gains
and losses on deposits and borrowings in a performance statement only in the two FFV
conditions.
The recall questions gave participants four choices: ‘‘net income,’’ ‘‘comprehensive
income but not net income’’ (the correct choice for deposits and borrowings in the FFVhedged and FFV-exposed conditions), ‘‘not net income or comprehensive income but rather
in the notes to the financial statements’’ (the correct choice for deposits and borrowings in
the PFV-hedged and PFV-exposed conditions), and ‘‘can’t recall.’’ For the available-for-sale
securities the overall correct recall rate was 73 percent. There were no differences across
cells (␹2 ⫽ 2.65, p ⫽ .45). For deposits and borrowings, the overall correct recall rate was
52 percent. A Chi-square test revealed differences across the cells (␹2 ⫽ 8.76, p ⫽ .03). In
the FFV-Exposed cell, the correct recall rate was 85 percent. In the remainder of the cells,
correct recall rates were 53 percent for PFV-Hedged, 40 percent for PFV-Exposed, and 31
percent for FFV-Hedged. This suggests analysts were more likely to attend to fair-value
gain and loss data on deposits and borrowings when they were relevant (i.e., the exposed
bank) and the cognitive costs were low (i.e., FFV-income measurement).20
As we noted previously, constraints on time and effort may limit the extent to which
analysts acquire and evaluate all fair-value data. Analysts who follow relatively few firms
have the opportunity to engage in more extensive fundamental analyses, thereby increasing
the likelihood that they evaluate fair-value information as part of their routine valuation
activities. Analysts who routinely search for and analyze fair-value gain and loss data will
18
19
20
Similarly, we do not believe that larger differences in risk assessments and value judgments across incomemeasurement conditions for the exposed bank reflect analysts’ overreactions to FFV data. Recall that analysts
judged the reliability of the FV data to be the same across conditions. We also asked participants about the
relevance of the fair-value data for AFS securities, loans, and deposits, and found no differences across conditions
(not tabulated). Given no difference in perceived reliability or relevance across income-measurement conditions,
and the expertise of participants chosen for this study, we believe it is unlikely that overreaction explains our
findings.
We designed these questions to determine whether analysts collected data on fair-value gains / losses on financial
liabilities that at least partially hedge positions in financial assets. We explicitly asked analysts to answer these
questions without referring to the financial statement data (in packet 1). Data on analysts’ recall of these items
enable us to infer the analysts’ implicit strategies for information search and use.
Note that the analysts in the FFV-Hedged condition experienced the lowest correct recall rates, inconsistent with
the notion that all fair-value gain and loss data are always more salient under FFV-income measurement than
PFV-income measurement. In addition, although analysts distinguished the hedged versus exposed banks,
interest-rate risk alone does not determine recall rates.
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Fair Values, Income Measurement, and Bank Analysts’ Risk and Valuation Judgments
469
also be more likely to impound such information in their valuation-related judgments
(Hunton and McEwen 1997).
To investigate whether analysts’ work environment affects the likelihood of utilizing
more-complete directed search, we divided analysts into two groups based on a proxy for
the cognitive requirements of their individual work environments: analysts who routinely
follow greater than, versus fewer than or equal to, the sample median number of companies
(40). A Chi-square test reveals that analysts following fewer firms are more likely to correctly recall the financial statement location of the deposit and borrowing information than
analysts following more firms (␹2 ⫽ 6.62, p ⫽ .01). For the available-for-sale security recall
data, there was no relation between recall and number of firms followed (␹2 ⫽ .29,
p ⫽ .59).
To test whether the acquisition of these fair-value data influenced the share-value judgments, we reran the ANOVAs, splitting the data on the basis of correct response to the
deposit-and-borrowings recall question. These analyses should be interpreted with caution
as the cell sizes are small and unbalanced. Nonetheless, they provide insight into the findings of the complete dataset. We expect that analysts who acquire fair-value data will
evaluate it similarly, regardless of its location. Therefore, based on this split of the data,
the normative predictions suggest that we should find only a main effect for risk exposure,
with no main effect for income measurement and no interaction between income measurement and risk exposure.
When we isolate the share value judgments of the analysts who correctly recalled the
location of the deposits and borrowings data, an ANOVA indicates that risk exposure is the
only significant variable (F ⫽ 8.83, p ⫽ .01). These analysts provided a statistically higher
stock price for the hedged bank ($14.38) than the exposed bank ($11.54). In contrast, when
we included in the ANOVA only the analysts that did not correctly recall the deposits and
borrowing data, we obtained no significant effects (all p’s ⬎ .29).
Together with the main findings on risk and valuation judgments, these supplemental
data suggest that bank income measurement (full versus piecemeal fair-value gains and
losses in income) influences the likelihood that bank-specialist analysts acquire and use the
fair-value information. In turn, this affects the likelihood that they distinguish between
banks’ interest-rate-risk strategies and price those differences.
V. CONCLUSIONS
We examine whether differences in fair-value-income measurement systematically affect bank-industry-specialist analysts’ fundamental judgments of risk and value. In our
experiment, we vary the bank’s income measurement (piecemeal-fair-value versus full-fairvalue) and the level of its interest-rate risk (exposed versus hedged). We frame our analyses
around two normative predictions: (1) bank-specialist analysts will assess greater risk and
lower share price for an exposed bank than for a hedged bank, holding all else equal, and
(2) holding constant the available information and underlying economics, risk and value
judgments of bank-specialist analysts will not be affected by income-measurement method.
In contrast, we propose that full-fair-value income measurement may reduce the time and
effort needed to acquire fair-value gain and loss data, thereby increasing the likelihood
analysts will use fair-value gains and losses to assess risk and value.
Contrary to the normative view, we find that income measurement methods do influence
bank-specialist analysts’ risk and share-value judgments. In particular, for the bank exposed
to interest-rate risk, analysts’ risk assessments are higher and value estimates are lower
under FFV income measurement than under PFV income measurement. For the hedged
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470
Hirst, Hopkins, and Wahlen
bank, income measurement does not affect analysts’ risk or valuation judgments. We find
that bank analysts’ investment-risk judgments distinguish between exposed and hedged
banks to a greater degree under FFV income measurement than under PFV income measurement. Furthermore, different valuation judgments across the exposed and hedged banks
emerge only under FFV income measurement. Supplemental analyses reveal that differential
acquisition of fair-value information is associated with analysts’ success in distinguishing
between banks with different levels of risk.
This study contributes to research related to fair-value-income measurement, performance reporting, and risk. With respect to the literature on income measurement, we address
limitations in the inferences that can be drawn from Hirst and Hopkins (1998). In particular,
Lipe (1998), Maines and McDaniel (2000), and others expressed concern that Hirst and
Hopkins’ (1998) financial statement presentation effects would not exist among specialist
analysts evaluating core earnings of the firm. Our interest-rate-risk context and bankinganalyst participants directly address this concern. We find that differences in income measurement influence bank-specialist analysts’ judgments. This finding is important because
it suggests that recognition versus disclosure of fair-value gains and losses influences even
specialist analysts evaluating core elements of bank risk and performance, and supports the
findings of prior research on presentation effects. These issues are at the heart of financial
reporting where researchers, preparers, and standard setters debate the fundamental question
of how to measure and report performance. Our supplemental analyses point to the possibility that more careful attention to the attributes of security analysts’ work environment
will help researchers to better understand analysts’ judgments and decisions.
Our evidence on the effects of income recognition versus disclosure of fair-value gains
and losses is also informative for standard setters as they consider new accounting standards
and evaluate existing rules. Although our data do not allow us to comment directly on
issues of security pricing in capital markets, they do allow us to comment on how financial
statement users gather and process value-relevant data—a topic of central interest to standard setters and a factor that, in natural settings, has the potential to affect security pricing
and wealth distribution. Our findings suggest that more complete measurement of fair-value
gains and losses in income can aid even industry-specialist analysts as they assess risk and
link those assessments to valuation judgments.
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