James Myers provided expert research assistance. ... Cochrane, Shapiro, and Tobin (1995) report that total capitalization of the world's publicly traded equity.
Accounting Diversity and International Valuation by
Richard Frankel
*
University of Michigan Business School Ann Arbor, MI 48109-1234 313-763-6039
and
Charles M. C. Lee Johnson Graduate School of Management Cornell University Malott Hall, Ithaca, NY 14850 607-255-6255
August 1996 May 1999
Comments welcomed
Please direct correspondence to Professor Charles M. C. Lee. *
We thank Warren Bailey, Larry Brown, Ilia Dichev, Carol Frost, Trevor Harris, Jim Leisenring, Stephen Penman, Katherine Schipper, David Senteney, Terry Warfield, and participants at the Harvard Financial Decisions and Control workshop, the University of Michigan workshop, the FASB Professional Development Seminar, the NYSE Conference on Recent Developments in International Equity Markets, and the 1996 AAA Annual Meetings for helpful comments. James Myers provided expert research assistance. The international analyst earnings forecast data were provided by I/B/E/S. Financial support from the Q-Group, and the KPMG Peat Marwick Foundation (Lee) are gratefully acknowledged. Much of this study was completed during Lee's stay at the New York Stock Exchange as the 1995-96 Visiting Economist.
Abstract International differences in accounting rules pose a significant challenge to investors interested in making cross-border comparisons of firm value. While current efforts to harmonize international standards are laudable, they are unlikely to completely eliminate cross-border accounting diversity.
In this study, we suggest an alternative, and
complementary, approach for coping with international diversity. Our approach is based on the Discounted Residual Income or the Edwards-Bell-Ohlson (EBO) valuation model. The model is potentially attractive because, it provides a method for translating accounting numbers produced under alternative accounting systems into more comparable measures of firm value. However, the model must overcome a number of potential problems in actual implementation. We discuss the practical problems that must be resolved in international implementations. Specifically, we identify three major areas of potential difficulty: 1) the availability of reliable earnings forecasts, 2) systematic violations of the clean-surplus assumption, and 3) "poor quality" accounting rules that result in delayed recognition of value changes. These difficulties can introduce noise into the estimation process, the extent of which is likely to be country-specific. Finally, we provide preliminary empirical evidence on the efficacy of the model in crossborder valuations and returns predictions. Despite the limitations discussed above, we find that firm value estimates based on the model are highly correlated with cross-border stock prices. Across 20 countries and over 8 years, our value estimate ("V") consistently dominates earnings and book value in explaining variations in stock prices. Most of the improvement arises from the use of forward-looking analyst forecasts of earnings rather than country specific discount rates. Furthermore, we show that V/P-based cross-country hedge strategies produce significant positive returns, suggesting that the model may be useful in global asset allocation decisions.
I. Introduction International accounting diversity is an old problem that has acquired a new sense of urgency. Fueled by privatization in de-centralized economies and the globalization of 1
capital markets, world-wide demand for equity capital is at an all-time high. As investors and corporations venture beyond domestic boundaries, cross-border differences in accounting rules are becoming an increasing source of frustration. These differences exact a cost on both firms seeking to raise capital in multiple jurisdictions, and investors seeking to make global asset allocation decisions.
Currently, the International Accounting Standards Committee (IASC), with the support of the International Organization of Securities Commissions (IOSCO), is establishing a comprehensive core set of international accounting standards. However, legitimate 2
concerns remain about whether international standards can be totally harmonized. A country’s accounting regulations reflect its cultural, economic and political institutions. While legislating more uniform accounting rules may be possible, eradicating economic and cultural differences is much more difficult. Therefore, laudable as they may be, current efforts to harmonize accounting standards are unlikely to completely eliminate cross-border diversity.
In this paper, we suggest a complementary approach for addressing international accounting diversity. Our approach is based on the Discounted Residual Income or the
1
Cochrane, Shapiro, and Tobin (1995) report that total capitalization of the world’s publicly traded equity surged from $10 trillion at the end of 1990 to $17 trillion by 1995. The same paper contains a good discussion of economic reasons for these trends. 2 Ball (1995) and Zarzeski (1996) are two recent studies that examine the desirability and likelihood of international harmonization.
Edwards-Bell-Ohlson (EBO) valuation model. 3 Specifically, we examine the ability of a residual-income valuation model to produce comparable firm value estimates across different international accounting systems. The model is potentially attractive because, in theory, it provides a technique for translating accounting numbers produced under alternative accounting systems into more comparable measures of firm value. However, the model must overcome a number of potential problems in actual implementation.
Our main objective is to explore the practical issues related to the use of the model in an international context. In implementation, the model relies on imperfect empirical proxies and estimation shortcuts necessitated by data constraints. We discuss the likely impact of these problems. Specifically, we identify three practical issues that must be resolved in international implementations: 1) the availability of reliable earnings forecasts, 2) systematic violations of the clean-surplus assumption, and 3) "poor quality" accounting rules that result in delayed recognition of value changes. A cursory review of international accounting rules suggests that these problems may be more severe in codelaw countries (e.g., France, Germany, Japan) than in common-law countries (U.S., Australia, Canada, and the U.K.).
Our second objective is to provide some empirical evidence on how well the model explains stock prices and how well it predicts returns across different accounting regimes. To address these issues, we compiled a database of more than 6,000 firms across 20 countries using I/B/E/S international earnings forecasts and fundamental accounting data from the Global Vantage database. The focus of our empirical work is on evaluating the
3
The term “Edwards-Bell-Ohlson,” or “EBO,” was coined by Bernard (1994).
2
efficacy of the model in cross-border firm valuations, and on comparing the relative attractiveness of aggregate country portfolios.
Our empirical tests are intended to provide a basis for understanding how well the model operates internationally. It is important to understand the exploratory nature of this analysis. We do not look into the details of accounting differences across individual countries. Rather, we seek to provide a general overview of how well the model works across a large number of countries. We also aim to provide some evidence on the relative importance of various components of the model in explaining stock prices and returns.
Two main results emerge from our empirical work. First, we find that an estimate of firm value based on the residual income model (V) is useful in explaining cross-sectional stock prices in all 20 countries. In most countries, our estimate of V accounts for more than 70% of the cross-sectional price variation. In Germany and Japan, whose accounting systems have been much maligned, the ability of V to explain prices is indeed lower. However, even in these countries, V dominates historical book value and earnings in terms of its correlation with current stock prices. Bernard (1994), Frankel and Lee (1998), and Penman and Sougiannis (1998) show that the residual income model is highly correlated with cross-sectional stock prices in the U.S. We show the model works well in explaining stock prices even when accounting numbers derived from different countries.
We find that V has explanatory power for stock prices beyond a linear combination of earnings and book value. Controlling for both earnings and book value, we find V
3
continues to be an important explanatory variable in price regressions in all 20 countries. The superiority of V over other traditional value indicators in price regressions is stable throughout our sample period (1987 to 1994) and across all major countries.
Furthur investigations reveal that much of the predictive power of V derives from its use of analyst forecasts of future earnings. The model's other key parameters, such as country-specific discount rates and the dividend payout ratios, were less important to the success of V. Interpreted in the context of the valuation model, our results suggest that a two-period-ahead analyst consensus forecast of earnings provides a reasonable proxy of a firm's "normalized" earnings, regardless of the accounting system from which it arises.
We also examine the usefulness of the residual income model as a predictor of crosscountry stock returns. Lee, Myers and Swaminathan (1999) show that, when price is a noisy proxy for the true fundamental value of a firm, superior estimates of firm value should result in P/V ratios that have superior predictive power for stock returns. We test the ability of country-level P/V ratios to predict cross-sectional returns across different countries.
As expected, we find that the average book-to-price ratio across individual countries is negatively correlated with their forecasted abnormal ROEs. Countries trading at higher premiums over reported book values tend to have higher forecasted ROEs relative to their costs of capital. Interestingly, we also find that V/P rankings across countries are positively correlated with subsequent 12-month returns. Specifically, we show that a strategy of buying countries with high average V/Ps and shorting countries with low
4
average V/Ps yields consistently positive and statistically significant returns over our sample period. While also positive, returns to similar trading strategies based on E/P or B/P ratios are far less stable. These results suggest that the EBO model is a potentially useful aid in assessing the relative attractiveness of aggregate country portfolios.
In sum, we conclude the residual income model is a useful part of a broader solution to the problem of accounting diversity. The model helps highlight the fact that valuation is a forward-looking exercise that requires forecasts of both future earnings and discount rates. We show that sell-side analyst forecasts are a reasonable first proxy for these forward-looking earnings in international valuations. Specifically, we find that the bias and accuracy of analyst forecasts are no worse in most other countries than they are in the United States. In addition, we provide some evidence that the model operates better in common-law countries than in code-law countries.
We regard these results as an encouraging first step in an on-going effort to help investors make better asset allocation decisions across countries. These results are a first step in that our estimates of cross-country discount rates are crude, and we do not make countryspecific accounting adjustments. Nevertheless, our results are encouraging in that they show even with relatively crude empirical estimates, the model is much better at explaining prices than linear combinations of historical earnings and book value. Our results also suggest it may lead to better cross-country returns predictions.
The remainder of the paper is organized as follows. In the next section, we develop the EBO valuation model and discuss its implications. In Section III, we discuss the
5
minimum conditions for an accounting system to provide consistent results in an EBO valuation. In Section IV, we consider model estimation procedures. In Section V, we discuss sample selection and data issues. Section VI contains the empirical results. Section VII discusses implications for current research and concludes.
II. The EBO Valuation Model The valuation model we use to compute a proxy of Vt* is based on a discounted residual income approach sometimes referred to as the Edwards-Bell-Ohlson (EBO) valuation 4
equation. Independent derivations of this valuation model have surfaced periodically throughout the accounting, finance and economics literature since the 1930’s. Most recently, alternative approaches to empirically implement the model have been discussed extensively in several papers (e.g., Bernard (1994), Abarbanell and Bernard (1995), Penman and Sougiannis (1998), Frankel and Lee (1997), Francis, Olsson, and Oswald (1997), and Dechow, Hutton, and Sloan (1997)). In this section, we present the basic EBO equation and the intuition behind it.
In a series of recent papers, Ohlson [1990, 1991, 1995] demonstrates that, as long as a firm's earnings and book value are forecasted in a manner consistent with “clean surplus” 5
accounting, the present value of future expected dividends can be rewritten as the reported book value, plus an infinite sum of discounted residual income:
4
The term “Edwards-Bell-Ohlson,” or “EBO,” was coined by Bernard (1994). Clean surplus accounting requires that all gains and losses affecting book value are also included in earnings; that is, the change in book value from period to period is equal to earnings minus net dividends (bt = bt-1 + NIt - DIVt). 5
6
∞
Vt
= Bt +
Σ i= 1 ∞
= Bt +
Σ i=1
E t [NIt + i – (re * Bt + i – 1 )] (1 + re) i
Et [(ROEt + i – r e) * Bt + i – 1] (1 + re) i
(1)
where Bt = book value at time t Et[.] = expectation based on information available at time t NIt+i = Net Income for period t+i re = cost of equity capital ROEt+i = the after-tax return on book equity for period t+i
Equation (1) highlights the importance of forward-looking earnings information in equity valuation. Historical book value is an inadequate proxy for intrinsic value because it measures only the invested capital, not the value of future wealth creating activities. Historical earnings is also an inadequate proxy for intrinsic value because it is, at best, a crude proxy for the stream of future earnings. Moreover, the value of the future earnings stream depends critically on the discount rate. In countries where the discount rate is relatively high, the present value of future abnormal earnings will be relatively low. Accounting conservatism aside, forecasted ROEs in competitive equilibrium should 6
equal the cost of equity (forecasted ROE = re).
6
In practice, most firms' accounting systems are conservatively biased, so reported ROEs tend to be above long-run re, with P/B ratios generally above 1.
7
Several recent studies evaluate the ability of this model to explain cross-sectional prices and expected returns. Penman and Sougiannis (1998) implement variations of the model using ex post realizations of earnings to proxy for ex ante expectations. Frankel and Lee (1998) implement the EBO model using I/B/E/S analyst earnings forecasts. They report that the resulting V measure explains close to 70% of cross-sectional prices in the U.S., and that the V/P ratio is a good predictor of cross-sectional returns. Abarbanell and Bernard (1995) use the model to address the question of market myopia with respect to short-term versus long-term earnings expectations. Botosan (1997) uses the model to derive an implicit cost of equity in her analysis of the relation between corporate disclosure and cost of capital. More recently, both Francis, Olsson, and Oswald (1999) and Dechow, Hutton, and Sloan (1998) examine the empirical properties of the model under alternative specifications.
Collectively, these studies show that the residual income model produces intrinsic value estimates that are highly correlated with cross-sectional stock prices in the U.S. Judging from the reported price regression R2s, the ability of the residual income model to explain cross-sectional prices in the U.S. is comparable to the discounted cash flow results reported in Kaplan and Ruback (1995), and much higher than those achievable using earnings, book-value or dividends alone. However, the empirical properties of the model for explaining stock prices and returns across different countries are not known.
In this study, we extend the analysis to international securities. Theory suggests that certain minimal conditions must be met for the model to produce consistent estimates of firm value. Empirically, these conditions are violated to different degrees across
8
alternative accounting systems. Our goal is to examine the extent to which these international accounting differences constrain the ability of the model to explain stock prices and expected returns across countries. In the next section, we discuss the minimum conditions needed for an accounting system to produce consistent value estimates, and the extent to which these conditions might be violated in the international arena.
III. Minimal Conditions for Valuation Ohlson (1995) shows that an accounting system must obey the clean surplus relation (CSR) to produce consistent value estimates. However, the practical implications of the CSR for empirical researchers has not been explored in detail. In this section, we discuss the CSR requirement, with particular emphasis on its implications for the use of accounting numbers from foreign jurisdictions. We also discuss two other necessary conditions for an accounting system to provide reliable input for valuation. These conditions pertain to practical implementation challenges, rather than theoretical merits, of the model.
A. The Clean Surplus Relation The clean surplus relation stipulates that the period-to-period change in the capital base (•Bt) must equal forecasted earnings (NIt), net of investor capital withdrawals or infusions (net dividends, or Divt). Notationally, Bt = Bt-1 + NIt - Divt, where Divt is the net dividends paid in period t (dividends + capital withdrawals - capital infusions) and NIt is the net income for period t. In other words, the CSR requires the balance sheet and
9
income statement to “articulate,” making the bottom-line income statement item (Net Income) equal the change in the book value (net of capital withdrawal or infusions).
Note that the EBO formula does not require firms to have followed clean surplus accounting in the past; rather, it requires them to do so in the future. We can impose this condition by requiring that future Bts increase only by the forecasted NIt and decrease only by the forecasted Divt. However, mechanical imposition of this condition on forecasted book values does not ensure that the model operates properly unless forecasts of future earnings are also consistent with the CSR.
Analyst forecasts of GAAP earnings may violate CSR when the accounting system allows predictable, value-relevant activities to be charged directly to shareholders’ equity, without going through the income statement. These items are sometimes called “dirty surplus adjustments.” For example, under U.S. GAAP, both currency exchange gains/losses on translations of foreign subsidiaries, and unrealized gains/losses on longterm marketable securities are charged directly to shareholders' equity. Similarly, under U.K. GAAP, fixed assets may be reappraised to reflect their market value, with a corresponding adjustment directly to shareholders' equity. When an accounting system contains many dirty surplus adjustments, analyst earnings forecasts may not comply with the CSR.
However, not all future dirty surplus adjustments represent a potential source of valuation bias. CSR violations are problematic only if their present expected value is non-zero. If future CSR violations are mean zero in expectation, analyst forecasts of GAAP earnings
10
will be unbiased with respect to future wealth-creating activities. Therefore, to evaluate the suitability of a national accounting system for use in an EBO valuation framework, we consider two factors: 1) which accounting items systematically violate the CSR; and 2) whether the present expected values of these violations are non-zero.
To illustrate, the Appendix provides an exhaustive list of the items under U.S. GAAP which violate the CSR. On review, these adjustment items all serve to adjust the book value of an asset or a liability to its market value. Once an asset or liability has been marked-to-market, future market value adjustments are, by definition, mean zero in expectation. Because these CSR violations do not affect future projections of earnings, we can compute a consistent measure of V with current earnings forecasts made under U.S. GAAP.7
Handling dirty surplus adjustments under other national accounting systems involves a similar procedure. These items can be analyzed individually as to their likelihood of recurrence. If the present expected value of future dirty surplus adjustments is zero, then we can compute a consistent measure of V using current reported book value and analyst earnings forecasts. However, if these current dirty surplus items represent a foreseeable source of future earnings/losses systematically omitted from income, then either current book value or future earnings forecasts should be adjusted to reflect these items.
7
A possible exception pertains to predictable reversals related to future sales of assets (or extinguishment of liabilities) with unrealized holding gains or losses already recorded in book value. In non-financial firms, these items should be generally immaterial.
11
B. Reliability and Accuracy of Earnings Forecasts While any accounting system which meets the CSR requirement can provide consistent firm value estimates, not all systems are equally useful. In practice, two additional conditions ensure that we can readily operationalize the model. First, professional analysts must have sufficient information to make reliable earnings forecasts. Second, the country’s accounting system must capture firm value within a few forecasting periods.
The first condition pertains to the availability of value-relevant information to professional analysts whose estimates are central to this valuation model. The theory shows that so long as analysts are faithful to local GAAP in forecasting earnings, it is not necessary for users of these forecasts to make further accounting adjustments for valuation purposes. However, this approach assumes that professional analysts have sufficient information about a company’s accounting policies to make accurate forecasts of future accounting accrual reversals. For example, analysts cannot make reliable forecasts of earnings unless the company’s depreciation policies are transparent.8
Analysts might obtain the necessary information through mandated regulatory filings or voluntary firm disclosures. Some countries, such as the U.S., have extensive regulatory disclosure requirements. Other countries, such as France and Germany, have environments that seem to encourage more voluntary disclosures [Meek and Gray (1989), Frost (1996)]. The quality of the information environment for a given country is difficult
8
It is not possible to avoid this reliance on accounting disclosures by using a discounted cash flow (DCF) model. In fact, DCF models require forecasts of not only depreciation expenses, but also the timing and amount of future capital expenditures.
12
to assess. However, the number of analysts following foreign firms should indicate the availability of forward-looking earnings information. The accuracy and dispersion of analyst forecast errors across countries should shed further light on this issue. Later, we provide some evidence both on the extent of analyst followings and the accuracy of their forecasts for our sample of foreign firms.
C. Capturing value in finite horizon forecasts In theory, any accounting system that satisfies the CSR will eventually capture firm value. However, in practice, a higher quality accounting system will do so more quickly [see Bernard(1995)]. In this sense, an accounting system could be described as higher quality if the resulting V metric converges to firm value with relatively few earnings forecast periods.
For example, the common Japanese practice of reporting on a "parent-only" basis illustrates poor quality accounting. Although some larger Japanese firms now prepare consolidated statements, most firms in Japan continue to use parent-only accounting.
9
Under parent-only accounting, the profit or loss of majority-owned subsidiaries are reflected in the parent's income only to the extent of the dividends paid. Therefore, when we use forecasted Japanese GAAP earnings to value the parent, we are effectively using a dividend discount model (DDM) for that portion of its value pertaining to its majorityowned subsidiaries. Technically, this accounting rule does not violate CSR, because the value created by these subsidiaries will eventually be incorporated in the parent’s income.
9
At the time of writing, 85% of the Japanese EPS forecasts in the I/B/E/S database are on a "parent-only" basis.
13
However, this feature of Japanese GAAP prevents the accounting system from capturing value creation in unconsolidated subsidiaries on a timely basis.
To provide some evidence on the issue, we estimate V using accounting numbers from 20 countries (including separate estimations in Japan for "parent-only" and "consolidated" firms). Specifically, we compare the amount of cross-sectional variation in stock prices explained by V (based on one- and two-year ahead EPS forecasts), relative to historical measures such as book value and earnings. If a country's accounting system does not capture value quickly, V will have little power to explain cross-sectional stock prices beyond historical book and earnings numbers. However, if local analyst earnings expectations are value-relevant, and are impounded in stock prices in a manner consistent with the EBO model, V should explain prices better than either earnings or book value.
IV. Model Estimation Procedures To operationalize equation (4), we need four parameters: the cost of equity capital (re), the current book value (Bt), future earnings forecasts (NIt+i), and future dividends (Divt). In this section, we discuss the specifics of the model estimation procedure, along with assumptions we make about each parameter.
A. Cost of equity capital (re). In theory, re should be firm and time-period specific, reflecting the premium demanded by equity investors to invest in a firm or project of comparable risk at a given point in time. In practice, however, there is little consensus on how this discount rate should be
14
determined. For this study, we derive a country-specific cost of equity based on average local interest rates for each year of our sample. Because earnings forecasts are denominated in nominal local currency, the corresponding discount rate should reflect each country’s inflationary expectations. Allowing the discount rate to vary across countries provides some control over cross-country differences in expected inflation.
To derive a country-specific cost of equity, we add a constant market risk premium to the average annual yield rate on local long-term government bonds (GBYs). During our sample period, the average yield on U.S. government bonds was 7.76 percent. The longterm expect return on U.S. equities is approximately 12 percent (e.g., see Copeland et. al. (1996)). This suggests an equity risk premium of 4.24 percent, which is applied to all countries.10 Specifically, the discount rate for country i in year t (reit) is computed as:
reit = .0424 + GBYit ,
where GBYit is the government bond yield for country i in year t, obtained from the International Financial Statistics Yearbook prepared by the Statistics Department of the International Monetary Fund (IMF). Our choice of the GBY as a benchmark for local interest rates is driven by the availability of this rate across many countries, and the longterm nature of our valuation exercise. 17 of our sample countries had a complete set of annual GBYs over our sample period. Another three countries (Finland, Korea, and
10
Note that our key results are not sensitive to the choice of 4.24 percent as the market risk premium. We obtain similar results using constant risk premiums as low as 0.24 percent and as high as 8.24 percent. While alternatives to a constant market risk premium may be justified, particularly in hyper-inflationary environments, our approach avoids ad hoc adjustments. The use of a constant market risk premium is also
15
Spain) had nearly complete records and we were able to obtain close proxies for their GBYs.11
B. Future Dividends. We estimate future dividends using each firm's current dividend payout ratio. Specifically, we divide dividend to common shareholders by current net income to obtain the current dividend payout ratio (k). If net income is negative, we estimate k by dividing common dividends by 3% of total assets.
12
As discussed later, the payout ratio is
combined with future earnings forecasts and the CSR to derive future book values.
Although firm dividend policy appears to affect firm valuation [violating Miller and Modigliani (M&M, 1961)], in fact, it does not [see Ohlson (1995) and Lee (1996)]. That is, the EBO equation is consistent with M&M’s dividend irrelevance theory; the dividends in the formula simply ensure that predicted book value growth in V is consistent with the capital base anticipated by analysts when predicting future earnings. In effect, we assume that analysts predict this future capital base using earnings forecasts and current dividend payout ratios.
C. Future ROEs
consistent current practice by many international investment firms. 11 Specifically, we constructed annual GBY proxies using three other measures obtained from the IMF Statistical Yearbook: the central bank discount rate (CBD), the money-market rate (MMR), and the average consumer loan rate (CLR). All three measures were available for these three countries over the entire sample period. 12 In our sample, Net Income is, on average, three percent of total assets. Only 1,275 firm-years (8% of our total sample) required this estimation procedure.
16
The most important and difficult task in the EBO valuation exercise is forecasting future ROEs (or, equivalently, future earnings). To forecast future earnings, we use the consensus (mean) one-year-ahead and two-years-ahead EPS predictions from the I/B/E/S International database. We combine these EPS forecasts with the current book value using the CSR to derive future ROEs.
To compute future ROEs, the theory calls for per share book values that "match" the capital base implicit in the analysts EPS forecasts. To obtain these values, we begin with the Global Vantage equity to common shareholders (Item #135 minus Item #119). In most countries, I/B/E/S analysts forecast an EPS number which is close to the comprehensive income number required to satisfy the clean-surplus relation. Or, as in the U. S., income items not included in analyst forecasts are mean zero in expectation. Therefore we do not make any adjustment to the reported book value.
One possible exception to this general rule is Germany. German analysts forecast earnings based on a formula devised by the German Institute of Financial Analysts (DVFA/SG). As part of the DVFA/SG calculation, the amount of the goodwill amortization is added back to reported earnings. This adjustment systematically increases analysts' estimates of future earnings relative to the earnings reported under Germany GAAP. In theory, we should deduct the corresponding asset (i.e., reported goodwill on the balance sheet) from the reported book value for German firms. However, in practice, we find that this adjustment had virtually no effect on our results.13
13
While goodwill is a major component of the DVFA/SG adjustment, not all DVFA/SG adjustments are so readily identified (See Harris, Lang, and Moeller (1994)). To the extent that unidentified systematic
17
D. Forecast horizons and terminal value estimation. Equation (4) expresses firm value in terms of an infinite series, but for practical purposes, an explicit forecast period must be specified. This limitation necessitates a “terminal value” estimate -- that is, an estimate of the value of the firm based on residual income earned after the explicit forecasting period. We estimate the terminal value by first expanding equation (4) to T terms, and then taking the next term in the expansion as a perpetuity. For example, if the explicit forecast period ends after T periods, the “terminal value” is:
(FROE T + 1 – r e) BT (1 + re) T r e
where FROEt = NIt/(Bt-1), and NIt is the forecasted earnings to common shareholders in year t, net of extraordinary items, taxes, and preferred dividends and is obtained from I/B/E/S. Dividing by re implicitly assumes that the firm will earn an abnormal return equal to (FROET+1 - re), in perpetuity, on an asset base of size BT. We assume additional growth will not contribute to wealth creation beyond period T. We base this assumption on the economic intuition that, in a competitive environment, abnormal returns that result from entry barriers eventually erode.
For an accurate value estimate, T should be set large enough for firms to reach their competitive equilibrium. However, our ability to forecast future ROEs diminishes
adjustments exist, they will introduce noise and reduce the power of our tests.
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quickly over time, and forecasting errors are compounded in longer expansions. Since international I/B/E/S forecasts are typically no longer than two-years ahead, we estimate a form of V which employs only two future earnings forecasts:
Vt = Bt +
(FROE t + 1 – r e) (FROE t + 2 – re) Bt + Bt + 1 (1 + r e) (1 + r e) r e
(6)
Bt is total common shareholders’ equity from the most recently completed fiscal year-end (obtained from Global Vantage) divided by total shares outstanding as of the price date.
14
The forecasted ROE for period t+1 (FROEt+1) is computed by dividing the I/B/E/S consensus forecast for period t+1 (FY1) by the reported book value per share in period t. Bt+1 is derived using the CSR: Bt+1 = Bt + (1 - k) FY1. V. Data and Sample Description Our U.S. sample consists of nonfinancial firms covered by both I/B/E/S and a merged Compustat annual industrial file, including PST, full coverage and research files. Similarly, our foreign firms consist of all companies in the intersection of: (a) the I/B/E/S International database, and (b) the Global Vantage Industrial and Commercial (IC) and the Issues Files. The information in these data sets spans the years 1987 to 1994. For each year, we require I/B/E/S firms to have the actual reported EPS for the most recent fiscal year-end, a one-year ahead EPS forecast (FY1), a two-year ahead
14 We computed V using both I/B/E/S shares outstanding and Global Vantage shares outstanding. In 99.9% of the cases, these two computations were within 5% of each other. We use the I/B/E/S shares outstanding numbers because they are more current, and incorporate any splits or dividends since the fiscal year end.
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forecast (FY2), as well as the stock price and shares outstanding as of the end of September.15
We also require the following fundamental accounting information for the most recent fiscal year (from either Global Vantage or Compustat): total book value to common shareholders, earnings per share, dividend per share, total common shares outstanding, and fiscal year-end date. We limit our analysis to firms with positive stock prices, shares outstanding, book values, sales, and total assets. To ensure firms have economically meaningful stock prices, we examine only firms whose price at the end of September is greater than one U.S. dollar per share.
To match the I/B/E/S forecasts and the fundamental accounting information, we use each firm's SEDOL (or CUSIP) number and fiscal year-end. Specifically, we begin our yearly analyses with I/B/E/S firms from the September statistical period, and match each observation to the Global Vantage (or Compustat) file record that correspond to I/B/E/S fiscal year 0. I/B/E/S firms that specify "parent only" (or "consolidated") accounting are matched with Global Vantage firms with a similar label. We compute per share book values and dividends using the shares outstanding information from I/B/E/S as of the end of each September.
In estimating equation (6), we impose a series of additional filters on the sample firms. The purpose of these filters is to eliminate firms with extreme data values that can have
15 In many countries, regulatory filings are not publicly available until six months after the fiscal yearend. We chose the end of September for our annual analyses to ensure December year-end firms will have ample time to make available their year-end accounting results.
20
an undue influence on the results, or can generate unreasonable input parameters. These filters, and the number of observations eliminated by each, are set out in Panel A of Table 1. The main filters relate to the dividend payout ratio (k), the reasonableness of ROEs and forecasted ROEs, and the requirement that V be positive. A total of 887 non-U.S. observations (6%) were eliminated by these filters. The remaining number of observations by country and year is presented in Panel B of Table 1. A total of 12,883 foreign and 12,026 U.S. firm-years qualified for the final sample. The total number of observations in each foreign country ranges from 33 for South Korea to 4,459 for Japan. Most countries have at least one firm in each of the 8 years covered by our analysis.
VI. Empirical Results Table 2 reports descriptive statistics by country for the total sample. Total market capitalization (in millions of U.S. dollars) and the number of analysts contributing I/B/E/S earnings forecast estimates are presented, as well as the dividend payout ratio, return on equity, and local interest rate (estimated cost of equity). The foreign firms in our sample are somewhat larger in size, having a mean (median) market capitalization of $1.48 billion ($516 million), compared to the mean (median) market capitalization of $1.38 billion ($239 million) for U.S. firms.
Our foreign and U.S. samples are quite comparable in terms of their overall profitability, cost of equity, and analyst coverage. Table 2 shows that the typical foreign firm has a slightly greater analyst following than its U.S. counterpart (8 versus 6), pays out a greater proportion of its earnings in dividends (34.5% versus 9.5%), earns a slightly lower ROE
21
(10.6% versus 11.9%), and faces a slightly lower cost of equity (11.5% versus 12%). Except for the dividend payout ratio, these differences are not statistically significant.
Evidence on the relative accuracy of international forecasts in only emerging [e.g., Capstaff et. al. (1996), Conroy and Harris (1995)]. Figure 1 adds to this evidence by documenting the accuracy of analyst forecasts for the seven major countries in our sample. Panel A reports the mean forecast bias (FER1 and FER2) and Panel B reports the mean absolute forecast error (|FER1| and |FER2|). To construct this graph, we compare the actual reported EPS to the I/B/E/S consensus forecast and scale the result by the absolute value of the actual EPS. For example, the year-one forecast error is computed as: FER1= (Forecastt+1- Actualt+1)/ |Actualt+1|. The countries are presented in ascending order according to their year-one forecast error (or absolute error). Japanese firms reporting under parent-only accounting (JPN(p)) are presented separately from those filing consolidated statements (JPN(c)).
The most salient result from Figure 1 is that earnings forecasts for U.S. firms are not any more accurate than forecasts for foreign firms. Panel A shows that analysts are overly optimistic across all countries: both year-one and year-two forecast errors exhibit a significant positive bias. Among the eight country-groups, the U.S. ranks seventh in terms of the size of its one-year-ahead forecast bias, and fifth in terms of its two-yearahead forecast bias. Panel B shows that, in terms of absolute error, the U.S. ranks last for one-year-ahead forecasts and fourth for two-year-ahead forecasts. A more extensive comparative analysis of international analyst forecast errors is beyond the scope of this
22
paper. However, our findings suggest that foreign earnings forecasts are comparable in terms of accuracy to those available for U.S. firms.16
A. Explaining Cross-Border Stock Prices In this section, we examine the ability of the EBO model to explain the cross-sectional variation in stock prices over different accounting environments. Frankel and Lee (1998) shows that an EBO value measure is able to explain close to 70% of current stock prices in the U.S. (by comparison, reported book values explain only around 35% of the variation in U.S. stock prices). We extend this analysis to the other countries in our sample.
2
Figure 2 shows the rank regression R from three sets of pooled regressions with intercepts constrained to be zero. For each country with at least 600 observations, we separately regress ranked prices (as of September 30th) on the ranks of three accounting variables: 1) book value per share, 2) earnings per share, and 3) the EBO value estimate. The accounting numbers are based on the latest fiscal year-end results available as of September 30th. The EBO value estimate is based on I/B/E/S consensus forecasts from the September statistical period. I/B/E/S disseminates this information on the third Friday of each month, so it is widely available by month end.
Figure 2 shows that in all seven countries, V explains much more cross-sectional price variation than either earnings or book value. In the worst two cases, V explains 48% of
16 Managers in some foreign countries may have greater scope in the accounting rules to "manage" their reported earnings to meet analyst expectations. We thank Jim Leisenring for pointing out this possibility.
23
the cross-sectional stock price variation in Germany, and 50% of the price variation in Japanese firms using parent-only accounting. In the best three cases, V accounts for approximately 70% of the price variation in France, the U.S. and the U.K. Earnings has a higher correlation with stock price than book value, explaining approximately 33% of the price variation, versus 25% for book value. However, neither measure works consistently well across all countries. In Germany, for example, book value accounts for less than 10% of the cross-sectional price variation.
Figure 3 shows that the superiority of V in explaining cross-sectional prices is stable over time. In several countries, the correlation between historical accounting numbers and stock prices has increased over time. For example, in Australia, France, and the U.K., earnings explains a much greater proportion of the price variation in recent years (1993 and 1994) than it did in years (1987 and 1988). However, the most salient result is the consistency of V . In all seven countries, across divergent accounting systems and economic conditions, V has a much higher correlation with stock prices than either earnings or book value.
Table 3 examines the incremental ability of V to explain current stock prices after controlling for earnings and book value. To construct this table, we regress end-ofSeptember stock prices on three variables: book value per share, earnings per share, and V . Our model specification also includes annual indicator variables. A separate regression is run for each country. In addition, we pool all foreign firms in a single
However, this possibility does not reduce the usefulness of foreign earnings forecasts for our purposes.
24
regression reported as "All Foreign." For this regression, we standardize all variables to a mean of zero and standard deviation of 1 by country and year. This standardization prevents cross-country differences in the magnitude of per share variables from influencing the results.
Table 3 demonstrates the incremental value-relevance of V . Controlling for earnings and book value. V is overwhelmingly significant in all 20 countries. The coefficient estimates for V are relatively stable, ranging from 0.67 in Norway to 2.56 in Italy, suggesting a consistent relation between price and V in different accounting regimes. The results for book value and earnings are much less stable. Conditional on V , the coefficient estimates for earnings are consistently negative, and the coefficient estimates on book value are insignificant in 12 out of 20 countries. Clearly, V reflects the market's valuation process in most countries better than a simple linear combination of current earnings and book value.
B. Country Aggregates and Global Asset Allocation Decisions Thus far, our evidence shows the EBO model generates a better measure of firm value than even a linear combination of earnings and book value. However, a better valuation model does not necessarily result in better returns predictions. While regulators are interested in the value-relevance of numbers produced by different accounting systems, global investors are primarily interested in predicting returns. In this section, we investigate the usefulness of the EBO model in global asset allocation decisions -- that
25
is, decisions involving the relative attractiveness of country baskets. Specifically, we examine the ability of aggregate V /P ratios to predict country-level returns.
Due to differences in accounting conventions, tax regimes, and financing environments, making cross-country value comparisons using accounting-based benchmarks (i.e., priceto-earnings ratios, price-to-book ratios, and dividend yields) is notoriously difficult. Firms from countries such as Japan, Germany, France, Denmark and Finland rely primarily on large financial institutions and “insiders” for their financing. These countries typically have financial reporting systems which are closely linked to their taxation systems. As a result, firms’ reported earnings often reflect tax considerations. Other countries, such as the U.S., U.K., Australia, Singapore, and Hong Kong, have legal systems based on common law and financial accounting systems that are largely separate from their taxation system.
17
These environmental differences complicate the
interpretation of country-aggregate accounting numbers.
Table 4 illustrates this point. In this table, we rank 21 country portfolios (including two Japanese entries) by three value indicators, using the most recent stock prices and accounting data available on September 30, 1994. Panel A orders these countries by their average book-to-market ratio (B/P). Panel B orders these countries by their average E/P ratio, where E is the most recent reported earnings. Panel C orders these countries by their V /P ratio, where V is the EBO value measure.
17 See Nobes (1994, 1995) for a discussion of accounting differences across these countries.
26
While these rankings are clearly correlated, Table 4 shows that they can also differ substantially. For example, South Africa and Thailand have the lowest average B/P ratios, but are ranked 7th and 10th respectively by average E/P. Similarly, Belgium is ranked 5th by its average B/P ratio, but is last (21st) by the E/P ranking. The U.S. is ranked below the middle of the pack by either B/P or E/P (14th by B/P and 12th by E/P), yet is the 5th most attractive alternative according to the V /P ranking.
The EBO model can offer important insights on these seemingly conflicting results. According to the model, high P/B (low B/P) countries should be associated with high expected abnormal ROEs. Indeed, it would be inappropriate to compare B/P ratios across countries without considering the earning potential of each country as measured by its forecasted ROEs, relative to its cost-of-equity. To examine this relation, Figure 4 plots the average B/P ratio for each country against the ratio of its forecasted ROEs to its discount rates (FROE/r) using data from September 30, 1994.
As expected, Figure 4 shows that low B/P countries tend to have higher ROEs. Fitting a linear regression line for these observations results in a statistically significant negative slope coefficient of -0.260. However, the EBO model suggests that the relation is nonlinear. Specifically, the model implies the relation between FROE/r and B/P should approximate an inverse function.
18
This is illustrated in the graph by a curved line.
Countries along the same curve have approximately the same V /P. Countries far above the curve (such as Norway and the Netherlands) have higher V /P values and are
18 To see this, note that FROE/r based on two-year-ahead earnings forecast is highly correlated with the terminal value in equation (6). Accordingly, FROE/r should be a linear with respect to P/B, and should
27
potentially more attractive investments. Countries substantially below the curve (for example, Japan) have lower V /Ps and are less attractive from a value-to-price perspective.
Table 5 presents evidence on the efficacy of the V /P ratio in predicting cross-country returns. To construct this table, we rank 16 country portfolios each year on the basis of their average V /P ratios.
19
Each ratio is computed using publicly available information
as of September 30th. We evaluate seven difference hedge strategies. In the "Hedge 1" strategy, we buy the top V/P country and sell an equal amount of the bottom V /P country. In the "Hedge 2" strategy, we buy the top two V /P countries and sell the bottom two V /P countries. The remaining strategies follow this pattern. In each case, we hold the hedge position for 12 months and rebalance next September 30th. Table 5 reports the individual countries in the long and short portfolios each year, as well as annual returns to each strategy.
Table 5 shows several interesting results. First, the V /P strategy yields consistently positive returns over the eight holding periods (1987 to 1994). This strategy is successful in global down markets (1987, 1989 and 1991) as well as up markets (1988, 1990, 1992, and 1993). Second, the strategy is not dependent on the same countries every year. Some countries, such as Switzerland (Japan) had consistently high (low) V/P rankings. However, other countries' relative ranking displayed substantial year-to-year variation.
approximate an inverse function with respect to B/P. 19 Austria, Finland, South Korea, and Thailand are excluded because they do not have representation in each of the 8 sample years. The U.S. was excluded in 1994 because the 1995 returns were not available to
28
For example, Spain had the lowest V/P ranking for 1987-1989, but moved to one of the highest V/P rankings in 1990. Similarly, Germany was a buy in the first two years and migrated to the sell portfolio for the last six years.
Table 6 reports the mean annual return for three sets of hedge strategies, based on V /P, B/P and E/P, as well as t-statistics based on variations in their annual returns over time. Panel A of this table shows that all three trading strategies have some ability to predict aggregate country-level returns. The V /P-based strategy is particularly impressive. Buying the top V /P country and shorting the bottom V /P country results in an average annual return of 20.9 percent (t=3.15) with 8 out of 8 years of positive returns. All 7 V /P-based hedges result in significant positive returns, and most of these strategies yield positive returns in 7 out of 8 years. The E/P and B/P based strategies also result in positive returns, but neither performs as consistently as the V /P strategy.
Panel B of Table 6 reports returns for each strategy based on U.S. dollars. To construct this panel, we use the exchange rate in effect at the end of September in year t to establish the initial position and the exchange rate at the end of September in year t+1 to unwind the position. Dividends received are converted at the exchange rate in effect in the month of receipt. Panel B shows that returns in U.S. dollars are much more volatile than returns in foreign currencies. The mean annual return for the V /P strategy is higher than in Panel A. However, the year-to-year performance is less consistent, resulting in lower tstatistics. Interestingly, neither the B/P nor the E/P strategy yields statistically significant
us at the time of writing.
29
returns once exchange rates are taking into account. However, the V /P strategy continues to yield significant positive returns.
VII. Summary In this paper, we examined the efficacy of the residual income model in explaining crossborder stock prices and in evaluating country portfolios. We find that an empirical estimate of firm value based on this model is much more highly correlated with international stock prices than traditional accounting numbers such as book value and earnings. Indeed, we find an EBO value metric has substantial explanatory power for cross-sectional prices, even after controlling for both earnings and book value. This result is robust over time and across a variety of accounting systems.
The main lesson we take from this analysis is that accounting numbers produced under any system must be understood in context. Reported earnings, book values, and other numbers are not designed to communicate a firm’s fundamental value, and should not be used naively as surrogates for firm value. Except under strong assumptions, none of these measures, taken alone, captures the concept of intrinsic firm value. However, when combined with forecasted earnings in a theoretically consistent framework, accounting numbers produced under a variety of systems all can be highly value-relevant.
We also discuss the minimal conditions necessary for successful implementation of this valuation model. Specifically, the model requires that: 1) future “dirty surplus” adjustments in the accounting system have zero expected value, 2) sufficient information is available for professional analysts to make reliable earnings forecasts under local 30
GAAP, and 3) the local accounting system is capable of capturing firm value “quickly,” using only a few earnings forecast periods. We note that these conditions are imperfectly satisfied in our sample countries, particularly in Japan and Germany. The relatively poor correlation between price and value for German and Japanese firm (particularly Japanese firms on parent-only accounting) suggest these accounting problems add noise to the value estimation process.
These results have implications for the establishment of international accounting standards. Specifically, our findings imply that regulatory efforts to harmonize international standards need not focus on achieving “superficially comparable” earnings and book values, or standardizing specific rules such as the amortization of goodwill. 20 Rather, greater emphasis might be more profitably placed on finding low-cost solutions to three implementation problems cited above. For example, the clean-surplus accounting requirement has direct implications for the reporting of the components of comprehensive income, a current agenda item for the Financial Accounting Standards Board. Greater consistency in the reporting of these items will enhance users' ability to monitor a firm's adherence to clean surplus accounting, and to assess the likelihood of reoccurrence of "dirty surplus" items. In the same spirit, more stringent requirements to report on a consolidated basis will mitigate the "slow value convergence" problem confronting many Japan firms using parent-only accounting. More transparent and
20 Several recent studies address the information content of Form 20-F U.S. GAAP reconciliation items (for example, see Amir, Harris, and Venuti (1993), Bandyopadhyay et. al. (1994), Barth and Clinch (1996), Chan and Seow (1995), McQueen (1993)). Our work does not relate directly to this literature. However, our results suggest that earnings forecasts based on local GAAP may represent an omitted variable in the valuation equations used in some of these studies. To the extent that 20-F reconciliation items are already incorporated in analyst earnings forecasts (a possibility implied by Amir, Harris and Venuti (1993)), some of these prior studies might ascribe more value relevance to the Form 20-F items than is warranted.
31
consistent accounting rules in these two areas can have a direct impact on the usefulness of accounting information in international valuation applications.
Our analysis also highlight several important limitations of the EBO model. First, our estimation procedure is hampered by the relative scarcity of long-term analyst earnings forecasts for international firms. Second, the cost-of-capital estimate used in our tests is a coarse approximation. We allow this rate estimate to vary by country and time-period, and our results are insensitive to relatively large perturbations in the market risk premium (+/- 4 percent). Nevertheless, we do not adjust for industry risk factors, nor do we allow the risk premium component of the discount rate to vary across countries. Accordingly, our estimate of V is best regarded as a first approximation of the present value of future dividends. We expect empirical results in both valuation and returns prediction to improve as longer-term earnings forecasts and better measures of country-specific risk become available.
Despite these limitations, our empirical results are encouraging. We find that our relatively simple estimate of V has more power to explain cross-border firm values than a linear combination of earnings and book value. Moreover, we show that a trading strategy based on country-level V /P ratios yields consistently positive returns between 1987 and 1994. This result may be due to risk differences across countries and is not necessarily evidence of global market inefficiencies. Nevertheless, whether these return differentials are due to market mispricings or country-specific risk premiums, the empirical fact that V /P predicts subsequent country-level returns is, we believe, an important contribution. 32
This study suggests several interesting venues for future research. First, our analysis brings into sharp focus the important role of analyst forecasts of earnings in firm valuation. A key question is whether these forecasts fully incorporate currently available information. Frankel and Lee (1998) examine the predictability of analyst forecast errors in the U.S., and conclude that a portion of this error is predictable using ex ante firm characteristics. Similarly, Brown et. al. (1995) develop a model for predicting one-quarter ahead earning surprises, and report success in a short-term trading strategy. The extent to which such results hold in foreign markets will provide additional insights on both the reliability of analyst forecasts for foreign firms, and the relative efficiency of foreign capital markets.
Second, surprisingly little work has been done on the predictability of cross-sectional returns in foreign equity markets. Brouwer, van der Put, and Veld (1996) and Haugen and Baker (1996) evaluate value-based investment strategies in an international context. These studies demonstrate that accounting-based ratios such as B/P, CF/P and E/P have predictive power for cross-sectional returns in several major countries. Frankel and Lee (1998) show that V /P ratios predict returns in the U.S. Questions remain, however, as to whether returns to such value-based strategies are due to risk differences or market inefficiencies. International evidence on the ability of the EBO model to predict crosssectional stock prices should help shed additional light on this subject.
In sum, we believe that the EBO model is a promising tool for international investment and global asset allocation decisions. It is conceptually superior to other accounting33
based valuation metrics for this purpose. Empirically, our results demonstrate that this model also exhibits surprisingly high resilience to cross-border accounting differences. We regard these findings as a promising first step towards a unified valuation model which will better accommodate the accounting numbers produced by the myriad of accounting systems world-wide.
34
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McQueen, P. D. “The Information Content of Foreign and U.S. GAAP Earnings in S.E.C. Form 20-F.” Working paper, New York University, (January 1993): Meek, G. K., and S. J. Gray. “Globalization of Stock Markets and Foreign Listing Requirements: Voluntary Disclosures By Continental European Companies Listed on the London Stock Exchange.” Journal of International Business Studies, (Summer 1989): 315-336. Nobes, C. International Guide to Interpreting Company Accounts: A Financial Times Management Reportt. Financial Times: London, 1994. . German Accounting Explained. Financial Times Insurance and Professional Publishing: London, 1995. Ohlson, J. A. “A Synthesis of Security Valuation Theory and the Role of Dividends, Cash Flows, and Earnings.” Contemporary Accounting Research 6 (1990): 648-676. . "The Theory of Value and Earnings, and an Introduction to the BallBrown analysis." Contemporary Accounting Research 7 (Fall 1991): 1-19. . “Earnings, Book Values, and Dividends in Security Valuation.” Contemporary Accounting Research (Spring 1995): 661-687. Peasnell, K. “Some Formal Connections Between Economic Values and Yields and Accounting number.” Journal of Business Finance and Accounting (October 1982): 361-381 Penman, S. H. "Return to Fundamentals." Journal of Accounting, Auditing, and Finance, 7 (1992): 465-483. Penman, Stephen H., and Theodore Sougiannis. "A comparison of dividend, cash flow, and earnings approaches to equity valuation," Contemporary Accounting Research 15 (1998), forthcoming.
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Pope, F. P., and W. P. Rees. “International Differences in GAAP and the Pricing of Earnings,” Journal of International Financial Management and Accounting, 4 (1992) 190-219. Preinreich, G “Annual Survey of Economic Theory: The Theory of Depreciation.” Econometrica 6 (1938): 219-241. Rappaport, A. Creating Shareholder Value: The New Standard for Business Performance. New York: The Free Press, 1986. Stewart, G. B. The Quest for Value. New York: Harper-Collins, 1991. Tully, S. “The Real Key to Creating Wealth” Fortune 20 (September 1993): 38-50. Zarzeski, M. T. “Spontaneous Harmonization Effects of Culture and Market Forces on Accounting Disclosure Practices.” Accounting Horizons 10 (March 1996): 18-37.
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Appendix Summary of Dirty Surplus Adjustments under U.S. GAAP In U.S. GAAP, the following items are currently required to be reported directly in equity instead of in net income. [source: Johnson, Reither, and Swieringa (1995)]
Item Description
Foreign currency translation adjustments
U.S. GAAP Reference
FASB Statement 52, paragraph 13
Probable Effect on EBO Valuation
Marks a firm’s net investment in foreign subs at year-end to U.S. dollars at current exchange rates; zero expected value; unlikely to affect earnings forecasts.
Gains and losses on foreign currency FASB translations that are designated as, Statement 52, and are effective as, economic paragraph 20b hedges of a net investment in a foreign entity
Mark-to-market accounting for economic hedges of the above item; zero expected value; unlikely to affect earnings forecasts.
A change in the market value of a futures contract that qualifies as a hedge of an asset reported at fair value
FASB Statement 80, paragraph 5
Mark-to-market accounting for economic hedges in general; zero expected value; unlikely to affect earnings forecasts.
The excess of the additional pension liability over unrecognized prior service cost (that is, net loss not yet recognized as net periodic pension cost)
FASB Statement 87, paragraph 37
Future adjustments to this item reflect unforeseeable changes in pension liability; unlikely to affect earnings forecasts.
Unrealized holding gains and losses on available-for-sale securities
FASB Statement 115, paragraph 13
Mark-to-market accounting for marketable securities; zero expected value; unlikely to affect earnings forecasts.
Unrealized holding gains and losses that result from a debt security being transferred into the available-for-sale category from the held-to-maturity category Subsequent increases (decreases) in the fair value of available-for-sale securities, (if not an other-thantemporary impairment), previously written down as impaired
FASB Statement 115, paragraph 15c
Mark-to-market accounting for transfers to the available-for-sale category. If analysts already have information on the market value of these assets, these transfers should not affect earnings forecasts
FASB Statement 115, paragraph 16
Market-to-market accounting for previously impaired marketable securities; unlikely to affect earnings forecasts.
40
Table 1 Sample Selection Panel A. Sample Selection and Number of Observations Removed by Each Filter This panel reports the sequential filters applied to obtain the final sample of observations. All firms must be in the I/B/E/S database. In addition, U.S. firms must be in the Computstat database and foreign firms must be in the Global Vantage database. Foreign U.S. Number of Firm-years meeting the initial data requirements for both I/B/E/S and Global Vantage (or Compustat): Eliminate: 1) Firms with extreme current or forecasted ROEs: (|ROEt| or |FROEt+2| >2.0) 2) Firms with extreme dividend payout ratios (k > 2 or K < 0) 3) Firms with extreme B/P and V/P ratios (B/P > 10 or V/P > 10) 4) Firms with negative EBO values ( Vt > 0.0) 5) Firms with significant differences in shares outstanding between fiscal year-end and September 30 Total Remaining Observations
13,770
13,389
(265)
(316)
(317)
(322)
(45)
(227)
(256)
(481)
(4)
(17)
12,883
12,026
Table 1 Sample Selection (continued) Panel B. Observations by Year and Country This panel presents the number of observations in our sample by year and country. Years Country 1987 1988 1989 1990 1991 1992 1993 1994 Country Total U.S. 1,320 1,368 1,420 1,398 1,429 1,491 1,685 1,915 12,026 All Foreign 810 1,333 1,611 1,700 1,848 1,866 1,785 1,930 12,883 Australia 68 67 82 71 71 77 83 94 613 Austria 0 0 8 12 21 15 17 26 99 Belgium 10 13 14 13 15 14 14 21 114 Canada 164 196 206 190 178 192 194 206 1,526 Denmark 8 8 8 11 16 16 14 28 109 Finland 0 5 7 11 6 8 12 22 71 France 50 65 76 96 98 119 95 121 720 Germany 52 55 68 70 87 90 94 135 651 Italy 6 7 14 16 33 42 28 29 175 Japan 102 494 584 669 699 675 632 604 4,459 Netherlands 17 21 25 58 61 69 57 61 369 Norway 2 1 2 11 12 9 13 19 69 So. Africa 8 16 22 15 19 23 23 25 151 So. Korea 0 0 4 3 5 6 7 8 33 Spain 7 6 15 23 32 50 32 40 205 Sweden 7 9 11 11 10 11 11 20 90 Switzerland 6 8 8 9 9 12 10 21 83 Thailand 0 1 8 19 40 40 26 28 162 U.K. 303 361 449 392 436 398 423 422 3,184 Year Total 2,130 2,701 3,031 3,098 3,277 3,357 3,470 3,845 24,909
Table 2 Descriptive Statistics by Country
Country
U.S. All Foreign Australia Austria Belgium Canada Denmark Finland France Germany Italy Japan Netherlands Norway South Africa South Korea Spain Sweden Switzerland Thailand U.K.
No. of Obs
12,026 12,883 613 99 114 1,526 109 71 720 651 175 4,459 369 69 151 33 205 90 83 162 3,184
Market Cap. ($U.S. million) Mean 1,379 1,482 1,380 604 1,836 762 1,155 436 3,040 1,974 2,325 1,778 1,886 624 1,070 1,568 1,463 1,375 6,102 368 1,405
Median 239 516 516 259 940 235 329 187 3,040 667 474 609 344 201 589 1,278 635 591 1,017 117 289
Number of Analyst Following Mean 9 9 10 7 8 9 10 7 12 15 12 7 17 9 3 6 15 9 16 5 9
Median 6 8 10 6 8 8 9 5 10 13 11 6 16 8 3 5 15 9 15 4 8
Dividend Payout
Mean 0.233 0.360 0.540 0.529 0.453 0.296 0.261 0.363 0.316 0.499 0.322 0.377 0.364 0.335 0.453 0.486 0.355 0.398 0.331 0.440 0.441
Median 0.095 0.345 0.550 0.471 0.386 0.238 0.196 0.246 0.278 0.494 0.306 0.319 0.368 0.316 0.410 0.493 0.315 0.345 0.303 0.418 0.401
Return on Equity
Mean 0.102 0.096 0.120 0.068 0.111 0.074 0.123 0.066 0.111 0.074 0.095 0.062 0.141 0.075 0.195 0.054 0.087 0.146 0.086 0.171 0.167
Median 0.119 0.106 0.110 0.061 0.121 0.091 0.118 0.069 0.124 0.078 0.091 0.058 0.133 0.106 0.186 0.045 0.082 0.145 0.086 0.165 0.159
Local Interest Rate Mean 0.120 0.115 0.154 0.111 0.124 0.135 0.136 0.127 0.128 0.106 0.153 0.081 0.110 0.144 0.193 0.120 0.164 0.146 0.085 0.136 0.132
Table 3 Regression of Stock Price on Accounting Variables
coeff. t-stat coeff t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat coeff. t-stat
Country
BPS
EPS
Value
U.S
0.07 9.16 0.11 17.23 0.10 1.58 0.50 3.59 0.74 4.94 0.13 7.53 0.26 3.50 0.02 1.03 -0.08 -1.24 -0.02 -0.37 0.03 0.25 0.34 5.35 0.68 17.48 0.06 1.40 0.08 1.19 -0.01 -0.06 0.18 1.38 0.21 2.24 0.02 0.46 0.00 -0.05 0.46 1.41 0.07 4.59
-0.10 -2.05 -0.09 -13.3 -0.02 -0.04 -0.51 -0.38 -1.87 -1.77 -0.20 -2.24 -1.62 -3.12 -0.61 -3.33 -1.41 -3.50 -1.14 -2.84 -5.07 -6.54 -6.91 -5.62 -4.08 -7.95 -1.21 -3.25 0.65 2.62 4.94 6.07 -1.74 -1.00 -2.13 -2.75 -0.50 -1.63 0.71 1.22 -2.17 -1.37 -0.40 -5.98
1.23 156.8 0.83 132.1 1.63 31.9 1.55 16.7 1.31 6.2 0.84 42.7 1.53 21.1 1.32 26.5 1.73 38.6 1.61 23.8 2.56 29.2 2.33 24.8 2.30 47.5 1.18 33.5 0.67 5.21 1.33 10.8 1.83 16.7 1.72 13.4 1.32 7.87 1.05 27.9 1.66 13.7 1.77 122.2
All Foreign Australia Austria Belgium Canada Denmark Finland France Germany Italy Japan (C) Japan (P) Netherlands Norway South Africa South Korea Spain Sweden Switzerland Thailand U.K.
R2 0.88
F-statistic
Obs.
8073.9
12026
0.72
3015.7
11881
0.94
804.2
613
0.93
137.9
99
0.82
49.0
114
0.87
929.2
1526
0.94
166.5
109
0.96
174.1
71
0.88
474.6
720
0.85
341.7
651
0.91
158.7
175
0.92
623.7
585
0.85
2072.1
3874
0.92
413.5
369
0.89
53.0
69
0.91
138.5
151
0.98
217.2
33
0.74
55.0
205
0.87
55.8
90
0.97
261.8
83
0.80
65.1
162
0.91
3013.3
3184
Table 4 Country Rankings by Various Accounting-based Value Metrics (B/P, E/P, and Vt /P) Panel A Ranking by Average B/P (book value) Rank
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Country
Obs.
Switzerland 21 Sweden 20 Finland 22 Norway 19 Belgium 21 Netherlands 61 Italy 29 Denmark 28 Spain 40 South Korea 8 Canada 206 Austria 26 France 121 U.S. 1915 Germany 135 U.K. 422 Japan (c) 86 Japan (p) 518 Australia 94 South Africa 25 Thailand 28
Panel B Ranking by Average E/P (earnings)
Avg B/P
Rank
Country
Obs.
Avg E/P
Rank
1.74 1.22 1.09 0.97 0.91 0.91 0.89 0.85 0.78 0.69 0.66 0.65 0.64 0.59 0.57 0.52 0.52 0.51 0.50 0.48 0.38
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Sweden Finland Switzerland Denmark Norway Netherlands South Africa U.K. Australia Thailand Italy U.S. Austria Canada Spain France South Korea Japan (p) Germany Japan (c) Belgium
20 22 21 28 19 61 25 422 94 28 29 1915 26 206 40 121 8 518 135 86 21
0.123 0.094 0.082 0.071 0.065 0.052 0.049 0.048 0.045 0.043 0.042 0.038 0.030 0.029 0.027 0.025 0.020 0.013 0.013 0.011 -0.006
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Panel C Ranking by Average (EBO value) Country Obs.
Norway Netherlands Switzerland Finland U.S. Sweden U.K. Denmark Canada France Belgium Austria Australia Spain Germany Thailand Italy South Africa South Korea Japan (c) Japan (p)
19 61 21 22 1915 20 422 28 206 121 21 26 94 40 135 28 29 25 8 86 518
Vt /P Avg
Vt /P
1.232 0.808 0.765 0.750 0.736 0.676 0.640 0.606 0.597 0.577 0.573 0.564 0.527 0.527 0.468 0.466 0.440 0.332 0.314 0.292 0.275
Table 5 Returns to V/P rankings at the Country Level
CTRY SPN SAF JAP AUS SWE ITA NOR FRA DEN U.K. CAN U.S. GER BEL SWI NET
V/P 0.055 0.249 0.256 0.343 0.375 0.461 0.477 0.510 0.511 0.517 0.539 0.614 0.631 0.633 0.682 0.950
1987 RET1 -0.068 -0.378 0.019 -0.218 -0.041 -0.121 -0.683 -0.033 0.212 -0.148 -0.113 -0.049 -0.062 0.011 -0.183 -0.045
CTRY SPN JAP SAF DEN ITA GER CAN FRA AUS SWE NOR BEL U.S. U.K. NET SWI
V/P 0.067 0.195 0.426 0.452 0.467 0.560 0.574 0.586 0.596 0.598 0.606 0.621 0.714 0.757 0.889 0.914
1989 RET1 -0.444 -0.344 0.033 -0.077 -0.254 -0.086 -0.170 -0.272 -0.127 -0.199 0.140 -0.208 0.099 -0.239 -0.123 -0.219
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.022 0.109 0.070 0.092 0.072 0.061 0.129
CTRY SPN JAP DEN SAF SWE ITA AUS FRA CAN GER BEL U.S. U.K. SWI NET NOR
V/P 0.083 0.266 0.515 0.529 0.546 0.582 0.599 0.651 0.674 0.676 0.711 0.715 0.759 0.987 1.070 1.324
1988 RET1 0.110 0.503 0.381 0.629 0.318 0.211 0.211 0.515 0.208 0.504 0.406 0.148 0.170 0.251 0.345 0.659
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.225 0.223 0.058 0.088 0.079 0.104 0.085
CTRY JAP SAF GER DEN CAN ITA NOR AUS U.S. SWE FRA BEL U.K. SPN NET SWI
V/P 0.251 0.498 0.535 0.542 0.584 0.629 0.663 0.690 0.705 0.767 0.819 0.859 0.885 0.889 0.940 1.193
1990 RET1 0.130 0.253 0.178 0.216 0.122 0.044 0.071 0.125 0.062 0.321 0.222 0.142 0.395 0.350 0.145 0.140
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.549 0.195 0.087 -0.049 -0.073 -0.029 0.017
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.010 -0.049 0.025 0.063 0.054 0.075 0.100
Table 5 (continued) Returns and V/P rankings at Country Level
CTRY JAP SAF GER ITA DEN AUS CAN SPN SWE U.K. BEL NOR FRA U.S. NET SWI
V/P 0.248 0.413 0.456 0.460 0.461 0.510 0.511 0.546 0.552 0.598 0.613 0.628 0.632 0.701 0.846 0.874
1991 RET1 -0.295 -0.130 -0.186 -0.374 -0.245 0.107 0.093 -0.303 -0.212 -0.099 0.027 -0.395 -0.030 0.115 -0.003 -0.107
CTRY JAP SWE SPN ITA GER DEN SAF CAN FRA AUS U.K. BEL U.S. NET SWI NOR
V/P 0.276 0.447 0.460 0.482 0.485 0.487 0.495 0.502 0.531 0.574 0.579 0.626 0.763 0.799 0.816 0.872
1993 RET1 -0.035 0.102 0.269 0.272 0.140 0.096 0.818 0.050 0.103 0.124 0.063 0.160 0.033 0.242 0.168 0.193
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.188 0.157 0.205 0.240 0.162 0.122 0.077
CTRY JAP SAF CAN AUS GER DEN BEL U.K. SPN U.S. FRA ITA NOR SWE NET SWI
V/P 0.355 0.362 0.518 0.621 0.631 0.645 0.663 0.698 0.715 0.743 0.758 0.762 0.785 0.876 0.982 1.238
1992 RET1 0.267 0.487 0.448 0.437 0.251 0.265 0.133 0.482 0.437 0.241 0.285 0.659 0.751 0.930 0.132 0.326
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.227 0.147 0.089 0.007 0.010 0.002 -0.097
CTRY JAP SAF ITA GER SPN AUS BEL FRA CAN DEN U.K. SWE SWI NET NOR
V/P 0.278 0.332 0.440 0.468 0.527 0.527 0.573 0.577 0.597 0.606 0.640 0.676 0.765 0.808 1.232
1994 RET1 -0.126 0.008 -0.099 -0.019 0.018 0.041 -0.025 -0.064 0.084 0.029 0.122 0.200 -0.011 0.111 0.261
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.059 -0.147 0.062 0.126 0.182 0.155 0.148
Strategy Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
HRET1 0.387 0.245 0.193 0.199 0.180 0.148 0.143
Table 6 Hedge Returns for B/P, E/P, and V/P Strategies Panel A: Returns in Foreign Country Currencies Strategy
Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
V/P Portfolios Mean T-stat Annual Return 0.209 3.152*** 0.110 2.254** 0.099 4.282*** 0.096 2.861** 0.083 2.624** 0.080 3.401*** 0.075 2.607**
Years Positive
Strategy
8 of 8 6 of 8 8 of 8 7 of 8 7 of 8 7 of 8 7 of 8
Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
Years Positive
Strategy
6 of 8 6 of 8 6 of 8 5 of 8 5 of 8 7 of 8 7 of 8
Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
B/P Portfolios Mean T-stat Annual Return 0.092 1.374 0.108 1.403 0.099 2.597** 0.063 1.906** 0.042 1.496* 0.046 1.943** 0.052 3.051***
Years Positive
Strategy
6 of 8 6 of 8 7 of 8 6 of 8 6 of 8 7 of 8 7 of 8
Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
Years Positive
Strategy
6 of 8 5 of 8 5 of 8 5 of 8 3 of 8 2 of 8 4 of 8
Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
E/P Portfolios Mean T-stat Annual Return 0.246 1.905** 0.143 2.593** 0.095 2.183** 0.100 2.350** 0.078 1.905** 0.076 2.337** 0.080 2.566**
Years Positive 6 of 8 7 of 8 6 of 8 6 of 8 5 of 8 6 of 8 7 of 8
Panel B: Returns in U. S. Dollars Strategy
Hedge 1 Hedge 2 Hedge 3 Hedge 4 Hedge 5 Hedge 6 Hedge 7
V/P Portfolios Mean T-stat Annual Return 0.236 1.599* 0.324 1.273 0.340 1.488* 0.372 1.652* 0.316 1.396 0.472 2.161** 0.570 3.468***
B/P Portfolios Mean T-stat Annual Return 0.012 0.154 0.131 1.086 0.099 0.719 -0.088 -0.406 -0.155 -0.598 -0.152 -0.675 -0.110 -0.441
E/P Portfolios Mean T-stat Annual Return 0.108 0.833 0.058 0.418 0.169 1.071 0.136 0.563 0.222 0.798 0.194 0.633 0.199 0.589
Years Positive 5 of 8 5 of 8 5 of 8 5 of 8 4 of 8 4 of 8 4 of 8
