外文翻譯---會(huì)計(jì)收益數(shù)據(jù)的實(shí)證評(píng)價(jià)

1、<p>　　附錄2：外文文獻(xiàn)譯文</p><p>　　會(huì)計(jì)收益數(shù)據(jù)的實(shí)證評(píng)價(jià)</p><p><b>　　摘 要：</b></p><p>　　我們假定，在確定能獲取到某特定上市公司有用信息的某一時(shí)期內(nèi)，它的回報(bào)率會(huì)反映只適用于涉及到所有企業(yè)的市場(chǎng)信息。對(duì)市場(chǎng)效應(yīng)[方程(3)]提取分析，我們認(rèn)為這是由個(gè)別企業(yè)的有關(guān)信息所致。然后，我們

2、對(duì)收入變化的可預(yù)期因素和不可預(yù)測(cè)因素分開(kāi)進(jìn)行分析，來(lái)確定其中部分的影響是否與該企業(yè)的會(huì)計(jì)收益信息相關(guān)。</p><p>　　表 1 根據(jù)相關(guān)系數(shù)平方分布的十分位數(shù)，</p><p>　　預(yù)測(cè)企業(yè)收益與市場(chǎng)收益的不同*</p><p>　　*估計(jì)過(guò)去21年（1946-1966）。</p><p>　　如果盈余的預(yù)測(cè)誤差是負(fù)數(shù)（即，如果實(shí)際收益

3、的變化比條件期望收益少），則我們定義其為壞消息，并假設(shè)會(huì)計(jì)收益數(shù)據(jù)和股票價(jià)格相關(guān)聯(lián)，則發(fā)行的收益數(shù)將導(dǎo)致公司證券的報(bào)酬率低于本來(lái)所預(yù)期的。這個(gè)結(jié)果證明公司年度報(bào)告公布期間股票收益殘差也是負(fù)數(shù)的。反之，則盈余的預(yù)測(cè)誤差為正數(shù)。</p><p>　　定義兩個(gè)基本的收益期望模型，回歸模型和簡(jiǎn)單模型。我們將詳細(xì)報(bào)告兩個(gè)關(guān)于收益的方案：回歸模型的[凈資產(chǎn)和每股收益，變量(1)和變量(2)]，以及簡(jiǎn)單模型的[每股收益，變量(

4、3)]。</p><p><b>　　數(shù) 據(jù)：</b></p><p>　　三個(gè)關(guān)于利益的數(shù)據(jù)類(lèi)是：收益報(bào)告的內(nèi)容，報(bào)告公布的日期，以及公布期間股票價(jià)格的變動(dòng)。</p><p><b>　　數(shù)據(jù)來(lái)源：</b></p><p>　　從1946年到1966年的收益數(shù)據(jù)均來(lái)源于標(biāo)準(zhǔn)和普爾公司會(huì)計(jì)資料庫(kù)。個(gè)

5、別企業(yè)的收益變化和市場(chǎng)收益指數(shù)變化的相關(guān)系數(shù)平方分布如表1所示。根據(jù)目前樣本的觀測(cè)，在企業(yè)中位數(shù)的收益變化中約有1/4的差異性與市場(chǎng)指數(shù)變化有關(guān)。</p><p>　　表 2 收益回歸殘差法中關(guān)于一階自相關(guān)系數(shù)分布的十分位數(shù)*</p><p>　　*估計(jì)過(guò)去21年（1946-1966）。</p><p>　　我們已經(jīng)在先前的文章[Ball和Brown (1967)

6、]中對(duì)企業(yè)盈利水平之間的相關(guān)性進(jìn)行了研究。在那時(shí)，對(duì)凈資產(chǎn)和每股收益水平的相關(guān)指標(biāo)進(jìn)行回歸時(shí)，我們提到了自相關(guān)作用的干擾。由于一階差分水平的關(guān)系，在本文中會(huì)有所不同，因?yàn)槲覀冄芯抗墒袑?duì)收益數(shù)的反應(yīng)，并推測(cè)在信息公布前至少12個(gè)月內(nèi)盈余的預(yù)測(cè)誤差是不可預(yù)知的。如果這個(gè)誤差具有自相關(guān)性，則這個(gè)假設(shè)不成立。 </p><p>　　如表2所示：當(dāng)變量變成一階差分后，我們根據(jù)收益回歸模型分析殘差的自相關(guān)程度。結(jié)果表明，這個(gè)

7、推測(cè)不是沒(méi)有根據(jù)的。</p><p><b>　　年度報(bào)告公布日期：</b></p><p>　　華爾街日?qǐng)?bào)出版的三種年度報(bào)告：預(yù)測(cè)年收入，例如，公司經(jīng)理在年底前盡快地預(yù)測(cè)今年的收入；一份簡(jiǎn)要的報(bào)告；以及一份完整的年度報(bào)告。雖然有些預(yù)測(cè)往往是不準(zhǔn)確的，不過(guò)簡(jiǎn)要報(bào)告是一份典型的對(duì)年度報(bào)告的概要預(yù)覽。通常，簡(jiǎn)要報(bào)告中所包含的凈資產(chǎn)和每股收益的數(shù)據(jù)與之后完整報(bào)告中所示的相同

8、，假設(shè)公布的日期（或年收入普遍存在的有效日期）就是簡(jiǎn)要報(bào)告刊登在華爾街日?qǐng)?bào)上的日期。如表3所示，在整個(gè)樣本期內(nèi)，從會(huì)計(jì)年度年末到年度報(bào)告公布期間的時(shí)間滯后性正在逐步的下降。</p><p>　　表 3 報(bào)告公布日期的時(shí)間分布表*</p><p>　　a：指截至?xí)?jì)年度年末1957年12月31日，25%的收入報(bào)告是在1958年2月7日宣布的。</p><p><

9、;b>　　股票價(jià)格：</b></p><p>　　股票價(jià)格的相關(guān)數(shù)據(jù)均來(lái)源于美國(guó)芝加哥大學(xué)構(gòu)造的證券價(jià)格研究中心(CRSP)。所采用的數(shù)據(jù)是從1946年1月到1966年6月在紐約證券交易所上市企業(yè)每月的收盤(pán)價(jià)，調(diào)整股息和資本變化。如表4所示，它列出了股票收益回歸系數(shù)平方分布的十分位數(shù) [方程(3)]，以及股票殘差系數(shù)的一階自相關(guān)分布的十分位數(shù)。</p><p>　　表 4

10、 股票收益回歸系數(shù)平方分布的十分位數(shù)，</p><p>　　以及股票殘差系數(shù)的一階自相關(guān)分布的十分位數(shù)*</p><p>　　.* 估計(jì)過(guò)去246個(gè)月，（1946年1月—1966年6月）</p><p><b>　　選擇標(biāo)準(zhǔn)：</b></p><p>　　所研究的企業(yè)應(yīng)符合下列條件：</p><p&

11、gt;　　1、從1946年至1966年，每年的收益數(shù)據(jù)均可在會(huì)計(jì)資料庫(kù)中查得；</p><p>　　2、會(huì)計(jì)年度統(tǒng)一截至12月31日；</p><p>　　3、在CRSP資料庫(kù)中的股票價(jià)格數(shù)據(jù)至少有100個(gè)月；</p><p>　　4、華爾街日?qǐng)?bào)公布的日期真實(shí)有效。</p><p>　　我們的分析僅限于1957年至1965年這9個(gè)會(huì)計(jì)年度。從

12、1957年開(kāi)始進(jìn)行分析，當(dāng)估計(jì)收益的回歸方程時(shí)，我們保證至少有10個(gè)的觀測(cè)值。時(shí)間的上限為（1965年的會(huì)計(jì)年度，其結(jié)果公布于1966年），因?yàn)镃RSP資料庫(kù)在1966年6月終止。</p><p>　　我們的選擇標(biāo)準(zhǔn)可能會(huì)降低結(jié)果的普遍性。該樣本不包括一些小公司，比如：那些沒(méi)上市的，那些會(huì)計(jì)年度報(bào)告不在12月31日，還有一些在會(huì)計(jì)資料庫(kù)、CRSP資料庫(kù)或在華爾街日?qǐng)?bào)上查找不到數(shù)據(jù)的。因此，它不可能代表所有的企業(yè)。

13、但是，請(qǐng)注意：（1）余下的有261家公司符合條件，（2）而且我們對(duì)樣本進(jìn)行了抽樣調(diào)查，結(jié)果與我們的研究結(jié)果密切符合，研究結(jié)果報(bào)告如下。</p><p><b>　　結(jié) 果：</b></p><p>　　定義：以0月作為公布年度報(bào)告的起始月，APIM作為在第M月的異?？?jī)效指標(biāo)，</p><p>　　然后，API指表示在第-12月月末（即，年度報(bào)告

14、公布前第12個(gè)月的月份）投資1美元有價(jià)證券n（n = 1, 2,…, N），并持有它到任意一個(gè)持有期結(jié)束，經(jīng)過(guò)市場(chǎng)的影響提取，估計(jì)它的價(jià)值（在同等金額的情況下）。等價(jià)解釋?zhuān)杭僭O(shè)有兩個(gè)人A和B都要進(jìn)行投資。B建立了一個(gè)投資組合，要把1美元等額投資到有價(jià)證券N上。在第-12月月末購(gòu)買(mǎi)這個(gè)有價(jià)證券，并可以一直持有它直到第T月月末。由于一些利益關(guān)系，B與A制定了合約，約定在第M月月末以一定價(jià)格轉(zhuǎn)讓給A，則在第T月月末，只有正常的收益（或損失）返

15、還給A，即1美元加上或減去任何不正常的收益或虧損。則APIM是第M月月底在相互組合投資下A的權(quán)益價(jià)值。</p><p>　　數(shù)值結(jié)果已經(jīng)列于兩個(gè)表格中。圖1繪制的異?？?jī)效指標(biāo)：</p><p>　　第1條線(xiàn)，從企業(yè)當(dāng)年的盈余預(yù)測(cè)誤差中構(gòu)建三個(gè)投資組合，根據(jù)這3個(gè)變量，API是正數(shù)（上半部分）；</p><p>　　第2條線(xiàn)，從企業(yè)當(dāng)年的盈余預(yù)測(cè)誤差中構(gòu)建的三個(gè)投資組

16、合，其API是負(fù)數(shù)（下半部分）；</p><p>　　第3條，在當(dāng)年所有企業(yè)組成的樣本下一個(gè)單一的投資組合（該線(xiàn)在兩部分分界線(xiàn)的下方）。表5中包含了圖1的基本數(shù)據(jù)。</p><p>　　對(duì)應(yīng)于年報(bào)公布日期的月份</p><p>　　圖1 各種投資組合下的異常績(jī)效指標(biāo)</p><p>　　由于第一組結(jié)果的股票收益分布可能存在一定的敏感性，干擾

17、了第二組所示的結(jié)果。在表5中每個(gè)標(biāo)題變量下的第三列根據(jù)該月盈余預(yù)測(cè)誤差和股票的剩余報(bào)酬給出了二對(duì)二企業(yè)分類(lèi)的卡方統(tǒng)計(jì)量。</p><p><b>　　概 述：</b></p><p>　　正如我們?cè)诖髽颖鞠滤A(yù)期的，兩組的結(jié)果基本上都反映了同樣的情況。它們表明，在實(shí)際收益與預(yù)期收益不同的情況下，包含有年收益數(shù)的信息是非常有用的，且市場(chǎng)通常會(huì)作出相同的反應(yīng)。支持這一論點(diǎn)

18、的除了圖1所揭示的盈余預(yù)測(cè)誤差和異?？?jī)效指標(biāo)相互之間的正相關(guān)，還有卡方統(tǒng)計(jì)量（如表5所示）。后者證實(shí)了在年度報(bào)告公布的大多數(shù)月份中盈余預(yù)測(cè)誤差和剩余報(bào)酬率之間肯定存在著相關(guān)性。</p><p>　　表 5 按月總結(jié)統(tǒng)計(jì)相對(duì)的年報(bào)公布日期</p><p><b>　　a 列標(biāo)題：</b></p><p>　?。?）異?？?jī)效指標(biāo)——企業(yè)當(dāng)年盈余的

19、預(yù)測(cè)誤差為正數(shù)。</p><p>　?。?）異?？?jī)效指標(biāo)——企業(yè)當(dāng)年盈余的預(yù)測(cè)誤差為負(fù)數(shù)。</p><p>　　（3）二對(duì)二企業(yè)分類(lèi)的卡方統(tǒng)計(jì)量——通過(guò)盈余預(yù)測(cè)誤差（會(huì)計(jì)年度）和股票的剩余報(bào)酬（指定月份）獲取。</p><p>　　注：概率 (卡方 ≥ 3.84 | χ2= 0 ) = 0.05，自由度為1。 概率 (卡方 ≥ 6.64 | χ2= 0 )

20、= 0.01，自由度為1。</p><p>　　然而，在市場(chǎng)的機(jī)制下，很多信息顯示在年報(bào)公布之前收益數(shù)已經(jīng)被提前預(yù)知了。事實(shí)上，如此準(zhǔn)確的預(yù)測(cè)，導(dǎo)致實(shí)際的收益數(shù)并沒(méi)用在報(bào)告公布的月份引起異差績(jī)效指標(biāo)的異常波動(dòng)。為了解釋這種現(xiàn)象，在宣布前至少12個(gè)月內(nèi)（當(dāng)構(gòu)建了第一個(gè)投資組合時(shí)），股市就開(kāi)始上下波動(dòng)了，并持續(xù)將近1個(gè)月。這個(gè)波動(dòng)的持續(xù)性，由指標(biāo)不斷的更新顯示，以及它們幾乎呈絕對(duì)增長(zhǎng)的趨勢(shì)(如圖1所示)所表明。建議市

21、場(chǎng)不僅要在報(bào)告公布的12個(gè)月前就開(kāi)始預(yù)測(cè)盈余的預(yù)測(cè)誤差，還要繼續(xù)加強(qiáng)和完善全年的監(jiān)管制度。</p><p>　　附錄3：外文文獻(xiàn)原文</p><p>　　An Empirical Evaluation of Accounting Income Numbers</p><p>　　此文選自 Journal of Accounting research , Volume

22、 6 , Issue 2 (Autumn 1968). 159-178</p><p>　　作者：Ray Ball and Philp Brown</p><p><b>　　SUMMARY</b></p><p>　　We assume that in the unlikely absence of useful information ab

23、out a particular firm over a period, its rate of return over that period would reflect only the presence of market-wide information which pertains to all firms . By abstracting from market effects [equation (3)] we ident

24、ify the effect of information pertaining to individual firms . Then, to determine if part of this effect can be associated with information contained in the firm's accounting income number, we segregate the expected

25、a</p><p><b>　　TABLE 1</b></p><p>　　Deciles of the Distributions of Squared Coefficients of Correlation, </p><p>　　Changes in Firm and Market Income*</p><p>

26、　　* Estimated over the 21 years, 1946-1966 .</p><p>　　If the income forecast error is negative ( that is, if the actual change in income is less than its conditional expectation ), we define it as bad news a

27、nd predict that if there is some association between accounting income numbers and stock prices, then release of the income number would result in the return on that firm's securities being less than would otherwise

28、have been expected. Such a result would be evidenced by negative behavior in the stock return residuals around the annual report </p><p>　　Two basic income expectations models have been defined, a regressi

29、on model and a naive model. We report in detail on two measures of income [ net income and EPS, variables (1) and (2) ] for the regression model, and one measure [ EPS, variable (3) ] for the naive model.</p><

30、p><b>　　Data</b></p><p>　　Three classes of data are of interest: the contents of income reports; the dates of the report announcements ; and the movements of security prices around the announce

31、ment dates .</p><p>　　INCOME NUMBERS</p><p>　　Income numbers for 1946 through 1966 were obtained from Standard and Poor's Compustat tapes. The distributions of the squared coefficients of c

32、orrelation between the changes in the incomes of the individual firms and the changes in the market's income index are summarized in Table 1. For the present sample, about one-fourth of the variability in the changes

33、 in the median firm's income can be associated with changes in the market index.</p><p><b>　　TABLE 2</b></p><p>　　Deciles of the Distributions of the Coefficients of First-Order

34、Autocorrelation in the Income Regression Residuals*</p><p>　　* Estimated over the 21 years, 1946-1966.</p><p>　　The association between the levels of the earnings of firms was examined in the fo

35、rerunner article [Ball and Brown (1967)]. At that time, we referred to the existence of autocorrelation in the disturbances when the levels of net income and EPS were regressed on the appropriate indexes. In this paper,

36、the specification has been changed from levels to first differences because our method of analyzing the stock market's reaction to income numbers presupposes the income forecast errors to be unpredi</p><p&

37、gt;　　We tested the extent of autocorrelation in the residuals from the income regression model after the variables had been changed from levels to first differences. The results are presented in Table 2. They indicate th

38、at the supposition is not now unwarranted.</p><p>　　ANNUAL REPORT ANNOUNCEMENT DATES</p><p>　　The Wall Street Journal publishes three kinds of annual report announcements: forecasts of the ye

39、ar's income, as made, for example, by corporation executives shortly after the year end; preliminary reports; and the complete annual report. While forecasts are often imprecise, the preliminary report is typically a

40、 condensed preview of the annual report. Because the preliminary report usually contains the same numbers for net income and EPS as are given later with the final report, the announcement</p><p><b>　　T

41、ABLE 3</b></p><p>　　Time Distribution of Announcement Dates</p><p>　　a Indicates that 25 per cent of the income reports for the fiscal year ended 12/31/1957 had been announced by 2/07/195

42、8. </p><p>　　STOCK PRICES</p><p>　　Stock price relatives were obtained from the tapes constructed by the Center for Research in Security Prices (CRSP) at the University of Chicago. The data use

43、d are monthly closing prices on the New York Stock Exchange, adjusted for dividends and capital changes, for the period January, 1946 through June, 1966. Table 4 presents the deciles of the distributions of the squared c

44、oefficient of correlation for the stock return regression [equation (3)], and of the coefficient of first-order autocorrel</p><p><b>　　TABLE 4</b></p><p>　　Deciles of the Distributio

45、ns of the Squared Coefficient of Correlation for the Stock Return Regression, and of the Coefficient of First-Order Autocorrelation in the Stock Return Residuals</p><p>　　.* Estimated over the 246 months, Ja

46、nuary, 1946 through June, 1966.</p><p>　　INCLUSION CRITERIA</p><p>　　Firms included in the study met the following criteria:</p><p>　　1. earnings data available on the Compustat ta

47、pes for each of the years 1946-1966;</p><p>　　2. fiscal year ending December 31;</p><p>　　3. price data available on the CRSP tapes for at least 100 months; and</p><p>　　4. Wall Str

48、eet Journal announcement dates available. </p><p>　　Our analysis was limited to the nine fiscal years 1957-1965. By beginning the analysis with 1957, we were assured of at least 10 observations when estimati

49、ng the income regression equations. The upper limit (the fiscal year 1965, the results of which are announced in 1966) is imposed because the CRSP file terminated in June, 1966.</p><p>　　Our selection criter

50、ia may reduce the generality of the results. The subpopulation does not include young firms, those which have failed, those which do not report on December 31, and those which are not represented on Compustat, the CRSP t

51、apes, and the Wall Street Journal. As a result, it may not be representative of all firms. However, note that (1) the 261 remaining firms are significant in their own right, and (2) a replication of our study on a differ

52、ent sample produced results which confor</p><p><b>　　Results</b></p><p>　　Define month 0 as the month of the annual report announcement, and API M , the Abnormal Performance Index at

53、 month M , as: </p><p>　　Then API traces out the value of one dollar invested (in equal amounts) in all securities n (n = 1, 2,…, N) at the end of month -12 (that is, 12 months prior to the month of the annu

54、al report) and held to the end of some arbitrary holding period (M = -11, -10,…,T) after abstracting from market affects. An equivalent interpretation is as follows. Suppose two individuals A and B agree on the following

55、 proposition. B is to construct a portfolio consisting of one dollar invested in equal amounts in </p><p>　　Numerical results are presented in two forms. Figure 1 plots APIM first for three portfolios constr

56、ucted from all firms and years in which the income forecast errors, according to each of the three variables, were positive (the top half); second, for three portfolios of firms and years in which the income forecast err

57、ors were negative (the bottom half); and third, for a single portfolio consisting of all firms and years in the sample (the line which wanders just below the line dividing the two h</p><p>　　Fig. 1 Abnormal

58、Performance Indexes for Various Portfolios</p><p>　　Since the first set of results may be sensitive to the distributions of the stock return disturbances, a second set of results is presented. The third colu

59、mn under each variable heading in Table 5 gives the chi-square statistic for a two-by-two classification of firms by the sign of the income forecast error, and the sign of the stock return residual for that month.</p&

60、gt;<p><b>　　OVERVIEW</b></p><p>　　As one would expect from a large sample, both sets of results convey essentially the same picture. They demonstrate that the information contained in the

61、annual income number is useful in that if actual </p><p>　　income differs from expected income, the market typically has reacted in the same direction. This contention is supported both by Figure 1 which rev

62、eals a marked, positive association between the sign of the error in forecasting income and the Abnormal Performance Index, and by the chi-square statistic (Table 5). The latter shows it is most unlikely that there is no

63、 relationship between the sign of the income forecast error and the sign of the rate of return residual in most of the months up to </p><p><b>　　TABLE 5</b></p><p>　　Summary Statisti

64、cs by Month Relative to Annual Report Announcement Date</p><p>　　a Column headings :</p><p>　　(1) Abnormal Performance Index—firms and years in which the income forecast error was positive.<

65、/p><p>　　(2) Abnormal Performance Index—firms and years in which the income forecast error was negative.</p><p>　　(3) Chi-square statistic for two-by-two classification by sign of income forecast e

66、rror (for the fiscal year) and sign of stock return residual (for the indicated month).</p><p>　　Note: Probability (chi-square ≥ 3.84 | χ2 = 0) = .05 , for 1 degree of freedom.</p><p>　　Probabil

67、ity (chi-square ≥ 6.64 | χ2 = 0) = .01 , for 1 degree of freedom.</p><p>　　However, most of the information contained in reported income is anticipated by the market before the annual report is released. In

68、fact, anticipation is so accurate that the actual income number does not appear to cause any unusual jumps in the Abnormal Performance Index in the announcement month.To illustrate, the drifts upward and downward begin a