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Fair values, income measurement, and bank analysts' risk and valuation judgments.

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-fair-value (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 full-fair-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.

Keywords: banks; fair value; risk; performance reporting; financial analysts; behavioral finance.

Data Availability: Contact the authors.

I. INTRODUCTION

Are 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 available for-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, of 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.

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 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-value-income 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 fair-value 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 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-rate-risk 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-fair-value-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.

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-fair-value basis of 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 income-measurement 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. Vera-Munoz 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-value-income 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 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 fair-value-footnote data (Sirota Consulting 1998). Buy-side analysts also cannot rely on fair-value analysis generated by either sell-side analysts (6) or the financial press because most sell-side and press reports use financial data and ratios based on recognized (i.e., piecemeal-fair-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-value-income 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 risk-relevant 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 capital-market 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 x 2 (piecemeal-fair-value versus full-fair-value-income measurement, and hedged versus exposed interest-rate risk) between-subjects experiment. 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 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 interest-rate 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 piecemeal-fair-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-rate-sensitive assets (loans and investment securities) and liabilities (deposits, federal funds, short-term and long-term liabilities). In both conditions, the banks described their interest-rate-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 maturities. By not matching maturities, the exposed bank had relatively large interest-rate-exposure "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 fair-value losses. The exposed bank experienced fair-value gains of only $7.1 million, leaving a net fair-value loss (before tax) of nearly $12.1 million (roughly 40 percent of net pre-tax 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 15-point 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) (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 hedged bank, analysts' judgments reflect no differences in investment risk across income-measurement 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 FFV-reporting regime than under the PFV regime. Analysts in the FFV conditions assess greater 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 ate 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 industry-specialist 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 fair-value-data acquisition, and the effects of fair-value-data acquisition on analysts' risk and value judgments.

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.

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) of 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 FFV-hedged 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 ([chi square] = 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 ([chi square] = 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) Similarly, we do not believe that larger differences in risk assessments and value judgments across income-measurement 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.

(19) 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.

(20) 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. 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 ([chi square] = 6.62, p = .01). For the available-for-sale security recall data, there was no relation between recall and number of firms followed ([chi square] = .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-fair-value) 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 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 banking-analyst 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.
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      Income Measurement (b)
Exposure (b)           FFV      PFV     Row data

Exposed               10.10     8.11      9.03
                     [10.50]   [7.50]    [9.25]
                      (2.42)   (2.45)    (2.60)
                      n = 13   n = 15     n = 28

Hedged                 6.68     6.94      6.82
                      [6.00]   [7.00]    [6.75]
                      (1.95)   (1.21)    (1.57)
                      n = 13   n = 15    n = 28

Column data            8.39     7.52
                      [8.25]   [7.25]
                      (2.77)   (1.99)
                      n = 26   n = 30

Panel B: Analysis of Variance

Factor                 d.f.   F-value   p-value

Income Measurement       1      2.46      .12
Risk Exposure            1     17.31      .00
Income Measurement *     1      4.16      .05
  Risk Exposure
Residual                52

Panel C: Tests of Means

Comparison                    d.f.   t-Statistic   Probability

PFV versus FFV (Exposed)       52       2.55          .01
PFV versus FFV (Hedged)        52      -0.33          .74
Exposed versus Hedged (PFV)    52       1.56          .06 (c)
Exposed versus Hedged (FFV)    52       4.23          .00 (c)

(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.

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      Income Measurement (b)
Exposure (b)           FFV       PFV     Row data

Exposed               11.26     13.06      12.22
                     [11.75]   [12.38]    [12.18]
                      (1.98)    (2.10)     (2.20)
                     n = 13    n = 15     n = 28
Hedged                14.10     13.92      14.00
                     [14.00]   [14.00]    [14.00]
                      (2.44)    (2.07)     (2.20)
                     n = 13    n = 15      n = 28
Column data           12.68     13.49
                     [12.75]   [12.9]
                      (2.62)    (2.09)
                     n = 26    n = 30

Panel B: Analysis of Variance

Factor                               d.f.   F-value   p-value

Income Measurement                     1      1.99     .16
Risk Exposure                          1     10.33     .00
Income Measurement * Risk Exposure     1      2.97     .05 (c)
Residual                              52

Panel C: Tests of Means

Comparison                    d.f.   t-Statistic   Probability

PFV versus FFV (Exposed)       52       -2.21        .03
PFV versus FFV (Hedged)        52         .22        .83
Exposed versus Hedged (PFV)    52       -1.09        .14 (c)
Exposed versus Hedged (FFV)    52       -3.37        .00 (c)

(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.

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      20.3   18.6   16.7   20.3   18.6   16.7
Reported Comprehensive   20.2   18.9   16.5   16.7   18.9   16.4
  Income (b)
Full-fair-value          20.2   18.9   16.5   20.2   18.9   16.5
  Income (c)

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.)

                                FFV                  PFV

Income Measure           20X3   20X2   20X1   20X3   20X2   20X1

Reported Net Income      20.3   18.6   16.7   20.3   18.6   16.7
Reported Comprehensive   12.1   20.1   15.3   16.7   18.9   16.4
  Income (b)
Full-fair-value          12.1   20.1   15.3   12.1   20.1   15.3
  Income (c)

(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.

FIGURE 2
Excerpts from Experimental Materials: Table of Interest-Rate-Repricing
Gap (a)

Panel A: Hedged Conditions

($ in thousands,           One Year   One to Five           Total
at amortized cost)          or Less         Years

Loans                     $ 302,516     $ 710,066     $ 1,012,582
Investment securities      $ 57,138     $ 328,552       $ 385,690
Deposits                $ (217,808)   $ (871,233)   $ (1,089,041)
Short-term borrowings   $ (229,935)           $ 0     $ (229,935)
Long-term borrowings            $ 0   $ (134,040)     $ (134,040)

Repricing gap            $ (88,089)      $ 33,345      $ (54,744)

Panel B: Exposed Conditions

($ in thousands,           One Year   One to Five           Total
at amortized cost)          or Less         Years

Loans                     $ 302,516     $ 710,066     $ 1,012,582
Investment securities      $ 57,138     $ 328,552       $ 385,690
Deposits                $ (871,233)   $ (217,808)   $ (1,089,041)
Short-term borrowings   $ (229,935)           $ 0     $ (229,935)
Long-term borrowings            $ 0   $ (134,040)     $ (134,040)

Repricing gap           $ (741,514)     $ 686,770      $ (54,744)

(a) In the experimental materials, we provide an
interest-rate-repricing-gap table in the descriptive information that
precedes the 20X3 annual earnings release.


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.

(1) 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.

(2) 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.

(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).

(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.

(5) 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).

(6) 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.

(7) 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).

(8) 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.

(9) 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.

(10) 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.

(11) 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.

(12) 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 bedge such risk and willingness to take it.

(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.

(14) In addition, participants judged the liquidity and credit risk of the banks. Neither was significantly different across risk levels (both p's > 0.25).

(15) 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.

(16) Analyzing each one separately gives qualitatively similar results.

(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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D. Eric Hirst

The University of Texas at Austin

Patrick E. Hopkins

James M. Wahlen

Indiana University

Submitted February 2003

Accepted September 2003
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