Earnings Surprises and Portfolio Performance: Empirical Evidence from the U.S. Sector Markets

by H. Christine Hsu


peer-reviewed article  H. Christine Hsu Chsu@csuchico.edu is a Professor of Finance, College of Business, California State University, Chico.


Abstract

It is well established in the literature that the portfolios with extreme positive earnings surprises outperformed the portfolios with extreme negative earnings surprises in the U.S. stock market. The purpose of this study is to investigate if the return spreads between the two extreme portfolios indeed exist in the recent U.S. bear market. The main contribution of the study is to provide some of the first empirical evidence on the earnings surprises and portfolio performance over the recent years in the U.S. sector markets. In addition to the sampling period, this study differs from prior studies in two areas: first, an earnings surprise measure other than the popular "standardized unexpected earnings" (SUE) is employed; second, a "sector by sector" analysis is performed in the U.S. stock market. The findings from this study should be of interest to individual investors and institutional investors alike.

 

INTRODUCTION

It is well documented in the literature that security returns are closely associated with earnings surprises, and it is profitable to trade on the basis of the sign and size of the earnings surprises in the U.S. stock market. For example, Latane and Jones (1977) found that the relationship between portfolio returns and earnings surprises was strong, and that the returns of the high earnings surprise portfolios were greater than those of the low earnings surprise portfolios from a study of 975 firms covering 14 quarters from 1971.2 to 1974.3. Rendleman, Jones, and Latane (1982) investigated the firms' reporting earnings one month after the ends of their fiscal years from 1971.3 to 1980.2 and confirmed that the return spread between the high- and low-earnings surprise portfolios was significant. Jones, Rendleman and Latane (1984) reported that the market assimilated only one-half of the quarterly earnings information by the day of the earnings announcement, thus earnings surprises had been reliable in predicting subsequent abnormal returns. Foster, Olsen, and Shevlin (1984) reported that trading on the foreknowledge of earnings surprises was much more profitable than trading on known earnings surprises. After examining New York Stock Exchange and American Stock Exchange firms over the 1974 - 1986 period, Bernard and Thomas (1989) found similar results, especially for small firms. Brown (1997) showed that buying a portfolio of firms expected to have the "best quarterly earnings news" and shorting a portfolio of firms expected to have the "worst quarterly earnings news" were profitable in each of the sample years from 1986 to 1994. Brown and Jeong (1998) showed that this buy/short trading rule was still effective when one waited 31 trading days after earnings announcement to take a position from 1985 to 1994. In a study of the U.S. technology firms over the quarters 1995.1 through 2000.1, Hsu (2002) found that the tech portfolios with extreme positive earnings surprises consistently outperformed the portfolios with extreme negative earnings surprises, and the trading strategy of buying the former and shorting the latter generated a profit equal to the return spread between the two portfolios, transaction costs ignored. It was reported that the buy/short strategy was profitable not only with foreknowledge of earnings surprises, but also with known earnings surprises as well. Hsu (2002) demonstrated that arbitrage profits existed in the U.S. tech sector when the buy/short transactions were made two months after the ending month of the quarter for the first three quarters and/or three months after the ending month of the fourth quarter.

Although the empirical evidence regarding the effectiveness of the buy/short strategy has been overwhelming in the U.S. stock market, it is not yet confirmed whether the strategy is valid in the recent years when most U.S. firms struggled in the bear market over an extended period of time. The trading strategy presented in prior studies should be profitable as long as the return spread between the two portfolios exists. That is, even when the portfolios experience negative returns in a bear market, the buy/sell trading rule should prevail if the returns of the portfolios with extreme earnings surprises exceed those with extreme negative earnings surprises.

The purpose of this study is to investigate if the return spreads indeed exist in the recent bear stock market. The main contribution of the study is to provide some of the first empirical evidence on the earnings surprises and portfolio performance over the recent years in the U.S. sector markets. In addition to the sampling period, this study differs from early studies in two areas: first, an earnings surprise measure other than the popular "standardized unexpected earnings" (SUE) is employed; second, a "sector by sector" analysis is performed in the U.S. stock market. The findings from this study should be of interest to individual investors and institutional investors alike.

DATA AND METHODOLOGY

The analysts' earnings estimation and stock market data for the firms in US sectors (industry groups) are obtained from the Institutional Brokers Estimate System (I/B/E/S) Database [1] covering the quarters 1999.1 to 2003.3. In accordance with the screening methodology of Hsu (2002), only the firms followed by at least three financial analysts with fiscal year ending in March, June, September, or December are included in the study. In contrast to a "single-sector" analysis in Hsu (2002), however, this study includes all firms meeting the screening criteria from all sectors (except for the miscellaneous sector due to insufficient observations) in the I/B/E/S Database. Moreover, rather than the popular SUE measure [2], the earnings surprise of a firm is calculated as the difference between the actual quarterly earnings per share and the analysts' consensus earnings per share for the quarter divided by the actual earnings. The study employs this simple percentage earnings surprise measure because it is much easier to calculate and there is no need to obtain the standard deviation of the analysts' earnings estimates, which is required in calculating SUE. The analysts' consensus earnings per share used in this study is the analysts' median consensus earnings published in the I/B/E/S Database in the ending month of the quarter. [3] The percentage earnings surprise measure (ES) is computed once a quarter over the study period for each of the firms in the sample. At the ending month of each quarter from 1999.1 to 2003.2, stocks are ranked in terms of their quarterly earnings surprises and the three-month stock returns are computed as the sum of its quarterly dividend yield and capital gains yield.

As the main objective of the study is to investigate if the buy/short strategy works in the recent U.S. sector markets, the focus is on the two extreme portfolios in each of the U.S. sector markets. Panel A (B) of Tables 1 and 2 presents the sample portfolios with earnings surprises greater (less) than or equal to 10 percent (-10 percent) sector by sector. Table 1 summarizes the descriptive statistics of the sample earnings surprises (ES) and the three-month portfolio returns assuming that the investments are made at the ending month of the ES quarter. That is, the investments are made at the end of each quarter on the basis of the foreknowledge of that quarter's earnings surprises. Table 2, on the other hand, shows the summary statistics of the sample earnings surprises and the three-month portfolio returns assuming that the investments are made at the ending month of the quarter following the ES quarter. In other words, the investments are made at the end of each quarter based upon the prior quarter's known earnings surprises. Across all the sectors in the sample, there are 17,858 (16,492) paired quarter-firm observations with extreme earnings surprises in Table 1 (Table 2) for the study. Among all the sectors in the sample, technology (consumer durables) contains the highest (lowest) count of quarter-firm observations; there are 5,157 (474) observations with extreme earnings surprises in the technology (consumer durables) sector in Table 1 and 4,758 (430) observations in Table 2.

EMPIRICAL RESULTS [4]

Table 3 shows that the portfolios with extreme positive earnings surprises persistently outperform those with extreme negative earnings surprises in the three-month holding period immediately following the portfolio formation date. It is evident from Panel C of the Table that the trading strategy of buying the portfolios with extreme positive earnings surprises and selling short those with extreme negative earnings surprises generates significant profits in both the technology and finance sectors quarter after quarter from 1999.2 to 2003.3 (except for 2001.1), i.e., a success rate of 17 out of 18 quarters. Of the 17 quarters, the return spread ranges between a high of 52 percent (with t-statistic of 8.358) in 1999.4 and a low of 10.5 percent (with t-statistic of 3.136) in 2002.1 for the technology sector. Although the return spreads between the two extreme portfolios in the finance sector are not as big as those in the technology sector, they are statistically significant, ranging from a high of 29.2 percent (with t-statistic of 6.363) in 2002.2 to a low of 8.6 percent (with t-statistics of 3.062) in 2003.3.

Table 3 also suggests that the buy/short strategy is effective in the consumer services and health sectors, with the respective success rate of 16 out of 18 and 14 out of 18 quarters, and that the strategy is least effective in the utility sector with a success rate of 7 out of 18 quarters. Nonetheless, this Table shows that the buy/short strategy leads to a handsome 7 percent average quarterly gain (with t-statistic of 2.615) in the utility sector when the strategy is carried out at the ending month of each quarter throughout the entire sample period 1999.1 - 2003.2. In fact, when the strategy is carried out throughout the entire18 quarters in the study period, the analysis of the two extreme portfolios in Table 3 documents significant quarterly return spreads for all the sectors in the sample, ranging from 19.3 percent (with t-statistic of 8.327) in the consumer non-durables sector to 4.7 percent (with t-statistic of 3.39) in the energy sector. Over the entire sample period, the average spread between the two extreme portfolios is statistically significant at .001 level for all sectors except for the utility and the transportation sectors with significance level of  .01 and  .05, respectively.

The results in Table 3 strongly suggest that buying the portfolios with extreme positive earnings surprises and shorting the portfolios with extreme negative earnings surprises is profitable in each of the recent U.S. sector markets. Moreover, Figure 1 and the "all sectors" column in Panel D of Table 3 depict the three-month holding period returns of the two extreme portfolios in all U.S. sectors combined; it is evident that the portfolio with extreme positive earnings surprises outperform those with extreme negative earnings surprises in all quarters examined except for the quarter 2001.1. The findings reported here are broadly consistent with the previous studies in the U.S. market as a whole [e.g., Latane and Jones (1977), Brown (1997), among others] and also with the study in the U.S. technology sector [Hsu (2002)]. It is confirmed in this study that the buy/short trading strategy is very powerful when one has the foreknowledge of earnings surprises even in the recent down markets in the U.S.. The empirical results seem to violate the strong form of efficient market hypothesis, which states that the stock price reflects all publicly and privately available information (e.g., the foreknowledge of earnings surprise). If the market is efficient in strong sense, all information should be reflected in the stock price and it is impossible to beat the market consistently even with the foreknowledge of earnings surprise. While obtaining perfect foreknowledge of the earnings surprise is not possible, the earnings surprise is predictable to a considerable extent [see for example, Brown, Han, Keon and Quinn (1996), among others]. Therefore, with a good earnings surprise predictor model, significant profits can be generated from applying the buy/short trading rule in the recent U.S. sector markets.

Unfortunately, not all investors have access to a good earnings surprise model. Without a reliable tool to come up with the foreknowledge of earnings surprises, an average investor might want to know: Would the trading strategy be profitable if one waits till the earnings are announced and acts on the known earnings surprises? To answer the question, the study investigates if the return spread between the two extreme portfolios exists when the buy and short decisions are delayed until after the actual earnings are announced and the earnings surprises are known to the public.

Table 4 summarizes the portfolios' three-month holding period returns assuming that the portfolios are traded on the basis of prior quarter's earnings surprises one quarter later. For example, the portfolios are bought/short sold in June 1999 based upon the earnings surprises for the quarter ending in March 1999, the portfolios are bought/short sold in September 1999 based upon the earnings surprises for the quarter ending in June 1999; and so on. In contrast to the findings of Hsu (2002), Panel C of Table 4 suggests that the strategy is not very successful in the recent bear market in U.S. technology sector. It shows that the return spread between the two portfolios with extreme earnings surprises is positive and statistically significant at .05 level only in three quarters (namely, 1999.3, 1999.4 and 2000.2) across the entire study period. It depicts that the strategy generates handsome arbitrage profits (10.8 percent and 15.8 percent) during the last two quarters in 1999 when the market is still moving up. However, as the spread is either insignificant or negative in the rest of the quarters during the sample period, the trading rule fails in the recent bear technology sector. Similar results apply to most other sectors as well.

Table 4 and Figure 2 reveal that there is a general lack of significant spread between the two extreme portfolios in most quarters from 2000.1 to 2003.3. For some quarters, this lack of significant spread stems from the fact that the portfolio with extreme negative earnings surprises outperform the portfolio with extreme positive earnings surprises, thus the negative spread. For others, it results from a wide range of the portfolio's returns, thus the large variance of the returns and the small t-statistic of the return spread. In any case, this lack of significant spread between the two extreme portfolios leads to the failure of the trading strategy and results in considerable losses to the investor adopting the strategy. As a matter of fact, Table 4 shows that the buy/short strategy leads to statistically significant average quarterly losses (ranging from 4.2 percent to 5.7 percent) in the consumer durables, consumer non-durables, and consumer services sectors, and an average quarterly loss of 0.9 percent, albeit not statistically significant, in both the technology and utility sectors over the entire 1999.3 to 2003.3 sample period.

The results appear to support the semi-strong form of efficient market hypothesis, which states that the stock price reflects all published information (such as last quarter's earnings surprise). If the market is efficient in semi-strong sense, one can no longer take advantage of the information since the "surprise" is fully processed by the investors in the market and the stock price has adjusted to the information. Although the data in Table 4 suggests that the strategy is ineffective on quarterly basis in each of the sectors examined, the overall average spread between the two portfolios is positive and statistically significant at .01 (.10) level for the finance (energy) sector over the entire study period. The average quarterly profit from applying the buy/short trading rule at the end of each quarter throughout the entire study period equals 3.4 percent (2.1 percent) in the finance (energy) sector.

IMPLICATIONS AND CONCLUSIONS

Results presented in this study strongly suggest that the buy/short trading strategy based on the foreknowledge of earnings surprises has been profitable in all US sectors for the quarters 1999.2 through 2003.3; it is especially effective in the technology and finance sectors with a success rate of 17 out of 18 quarters. Consistent with prior studies, this study finds that the portfolios with extreme positive earnings surprises persistently outperform those with extreme negative earnings surprises and the return spreads between the two portfolios in each of the sectors in the sample are significant statistically over the quarters examined. The study confirms that it is extremely rewarding to accurately forecast the sign and magnitude of the earnings surprises and formulate the investment strategy accordingly even in the recent bear markets. These findings are against the strong form of efficient market hypothesis. As demonstrated in the study, the market is clearly inefficient in its strong form since there is money to be made from trading based upon the private information of earnings surprises. Nonetheless, the study finds that the buy/short trading rule is ineffective in most of the U.S. sectors when one waits for a quarter and trades on the known earnings surprises in recent down markets. It shows that the buy/short trading strategy resulted in significant quarterly losses in the consumer durables, consumer non-durables, and consumer services sectors for the 1999.3-2003.3 sample period. The results reported here appear to support the semi-strong form of efficient market hypothesis. As one waits for three months to act on the known earnings surprise in this study, one can no longer benefit from the information because the "surprise" is already factored in the stock price. For future research, it would be interesting to investigate whether profits can be generated when one waits for two months (or one month, or even a shorter period of time) and trades on the basis of the known earnings surprises.


TABLES AND FIGURES 

Table 1. Summary Statistics of the Sample Earnings Surprises and Returns by Sector, Foreknowledge of Earnings Surprises at the Time of the Investments

Panel A. The Sample with Extreme Positive Earnings Surprises 
Sector Observation  Mean Median SD Minimum Maximum Count %
Basic ES Qa 0.562 0.235 1.334 0.100 17.000 558 5.6%
Return Qb 0.074 0.055 0.244 -0.870 1.282 558 5.6%
Capital Goods ES Q 0.345 0.208 0.461 0.100 6.000 431 4.3%
Return Q 0.096 0.078 0.324 -0.670 2.022 431 4.3%
Consumer Durables ES Q 0.319 0.195 0.474 0.100 5.000 277 2.8%
Return Q 0.098 0.036 0.316 -0.705 1.320 277 2.8%
Consumer Non-Durables ES Q 0.384 0.209 0.702 0.100 8.000 380 3.8%
Return Q 0.116 0.071 0.311 -0.569 2.513 380 3.8%
Consumer Services ES Q 0.513 0.224 1.139 0.100 26.000 1724 17.3%
Return Q 0.064 0.023 0.464 -1.000 2.857 1724 17.3%
Energy ES Q 0.507 0.245 1.149 0.100 17.000 782 7.9%
Return Q 0.079 0.059 0.264 -0.685 1.526 782 7.9%
Finance ES Q 0.283 0.176 0.573 0.100 11.500 698 7.0%
Return Q 0.112 0.088 0.243 -0.674 1.385 698 7.0%
Health ES Q 0.562 0.231 1.619 0.100 26.000 1275 12.8%
Return Q 0.130 0.068 0.491 -0.842 5.617 1275 12.8%
Technology ES Q 0.582 0.273 1.114 0.100 26.000 3130 31.5%
Return Q 0.120 0.040 0.551 -0.942 5.395 3130 31.5%
Transportation ES Q 0.528 0.207 1.583 0.100 17.667 231 2.3%
Return Q 0.061 0.046 0.275 -0.793 0.993 231 2.3%
Utility ES Q 0.456 0.211 1.135 0.100 15.000 462 4.6%
Return Q 0.054 0.042 0.426 -0.904 5.962 462 4.6%
ALL ES Q 0.507 0.231 1.157 0.100 26.000 9948 100.0%
Return Q 0.099 0.052 0.445 -1.000 5.962 9948 100.0%

 

Panel B. The Sample with Extreme Negative Earnings Surprises 
Sector Observation Mean Median SD Minimum Maximum Count %
Basic ES Q -1.139 -0.484 2.592 -37.000 -0.100 768 9.7%
Return Q -0.018 -0.018 0.268 -0.870 2.333 768 9.7%
Capital Goods ES Q -1.206 -0.435 3.081 -43.000 -0.100 490 6.2%
Return Q -0.027 -0.033 0.282 -0.794 1.313 490 6.2%
Consumer Durables ES Q -1.581 -0.500 4.542 -56.000 -0.100 197 2.5%
Return Q -0.017 -0.063 0.357 -0.843 1.821 197 2.5%
Consumer Non-Durables ES Q -1.087 -0.435 2.493 -33.000 -0.100 299 3.8%
Return Q -0.078 -0.072 0.292 -0.776 1.913 299 3.8%
Consumer Services ES Q -1.023 -0.429 2.140 -27.000 -0.100 1170 14.8%
Return Q -0.083 -0.087 0.384 -0.981 3.980 1170 14.8%
Energy ES Q -1.289 -0.500 3.011 -36.000 -0.100 617 7.8%
Return Q 0.032 0.018 0.251 -0.783 1.086 617 7.8%
Finance ES Q -1.398 -0.374 3.601 -41.000 -0.100 756 9.6%
Return Q -0.036 -0.040 0.375 -0.934 7.792 756 9.6%
Health ES Q -0.883 -0.333 2.304 -46.000 -0.100 792 10.0%
Return Q -0.024 -0.085 0.462 -0.874 4.053 792 10.0%
Technology ES Q -1.131 -0.519 2.119 -30.000 -0.100 2027 25.6%
Return Q -0.072 -0.134 0.522 -0.941 9.332 2027 25.6%
Transportation ES Q -1.224 -0.541 3.160 -49.000 -0.100 310 3.9%
Return Q 0.006 -0.032 0.419 -0.944 4.136 310 3.9%
Utility ES Q -1.017 -0.293 3.219 -47.000 -0.100 484 6.1%
Return Q -0.016 -0.014 0.396 -0.985 4.514 484 6.1%
ALL ES Q -1.140 -0.444 2.708 -56.000 -0.100 7910 100.0%
Return Q -0.042 -0.057 0.409 -0.985 9.332 7910 100.0%

a ES Q: Earnings surprise for quarter Q

b Return Q: 3-month holding period return for investment made at the ending month of quarter Q

 

Table 2. Summary Statistics of the Sample Earnings Surprises and Returns by Sector, Earnings Surprises Known at the Time of the Investments

Panel A. The Sample with Extreme Positive Earnings Surprises 
Sector Observation Mean Median SD Minimum Maximum Count %
Basic ES Qa 0.573 0.235 1.371 0.100 17.000 526 5.7%
Return Q+1b 0.013 0.003 0.362 -0.816 6.314 526 5.7%
Capital Goods ES Q 0.337 0.208 0.458 0.100 6.000 394 4.3%
Return Q+1 0.036 0.028 0.289 -0.738 1.380 394 4.3%
Consumer Durables ES Q 0.302 0.194 0.455 0.100 5.000 248 2.7%
Return Q+1 0.024 -0.034 0.318 -0.668 1.821 248 2.7%
Consumer Non-Durables ES Q 0.368 0.211 0.603 0.100 6.000 347 3.8%
Return Q+1 -0.001 -0.019 0.242 -0.701 0.841 347 3.8%
Consumer Services ES Q 0.509 0.222 1.154 0.100 26.000 1595 17.4%
Return Q+1 -0.023 -0.043 0.425 -0.945 2.857 1595 17.4%
Energy ES Q 0.527 0.250 1.187 0.100 17.000 734 8.0%
Return Q+1 0.058 0.046 0.240 -0.702 1.666 734 8.0%
Finance ES Q 0.289 0.175 0.605 0.100 11.500 622 6.8%
Return Q+1 0.050 0.031 0.245 -0.934 1.225 622 6.8%
Health ES Q 0.549 0.231 1.544 0.100 26.000 1177 12.9%
Return Q+1 0.055 -0.005 0.439 -0.886 5.441 1177 12.9%
Technology ES Q 0.581 0.270 1.126 0.100 26.000 2882 31.5%
Return Q+1 0.013 -0.059 0.510 -0.952 4.960 2882 31.5%
Transportation ES Q 0.422 0.203 1.112 0.100 14.000 212 2.3%
Return Q+1 0.048 0.008 0.458 -0.944 4.136 212 2.3%
Utility ES Q 0.447 0.211 1.105 0.100 15.000 417 4.6%
Return Q+1 -0.008 -0.002 0.411 -0.917 4.514 417 4.6%
ALL ES Q 0.504 0.231 1.142 0.100 26.000 9154 100.0%
Return Q+1 0.019 -0.010 0.420 -0.952 6.314 9154 100.0%
Panel B. The Sample with Extreme Negative Earnings Surprises 
Sector Observation Mean Median SD Minimum Maximum Count %
Basic ES Q -1.127 -0.493 2.556 -37.000 -0.100 712 9.7%
Return Q+1 0.007 0.002 0.288 -0.870 2.142 712 9.7%
Capital Goods ES Q -1.145 -0.437 2.494 -25.000 -0.100 459 6.3%
Return Q+1 0.029 0.028 0.297 -0.813 1.716 459 6.3%
Consumer Durables ES Q -1.592 -0.500 4.695 -56.000 -0.100 182 2.5%
Return Q+1 0.081 0.015 0.424 -0.840 1.885 182 2.5%
Consumer Non-Durables ES Q -0.988 -0.432 1.704 -14.333 -0.100 282 3.8%
Return Q+1 0.041 0.003 0.397 -0.780 2.513 282 3.8%
Consumer Services ES Q -1.016 -0.429 2.165 -27.000 -0.100 1082 14.7%
Return Q+1 0.020 -0.007 0.469 -0.988 5.333 1082 14.7%
Energy ES Q -1.213 -0.500 2.636 -36.000 -0.100 564 7.7%
Return Q+1 0.037 0.031 0.254 -0.952 1.206 564 7.7%
Finance ES Q -1.407 -0.364 3.670 -41.000 -0.100 707 9.6%
Return Q+1 0.016 0.018 0.263 -0.936 1.762 707 9.6%
Health ES Q -0.887 -0.333 2.373 -46.000 -0.100 726 9.9%
Return Q+1 0.038 -0.007 0.439 -0.926 2.934 726 9.9%
Technology ES Q -1.152 -0.525 2.184 -30.000 -0.100 1876 25.6%
Return Q+1 0.021 -0.041 0.536 -0.973 5.529 1876 25.6%
Transportation ES Q -1.184 -0.535 3.150 -49.000 -0.100 302 4.1%
Return Q+1 0.021 0.011 0.302 -0.930 1.174 302 4.1%
Utility ES Q -0.991 -0.286 3.231 -47.000 -0.100 446 6.1%
Return Q+1 0.001 -0.012 0.496 -0.833 5.962 446 6.1%
ALL ES Q -1.128 -0.444 2.652 -56.000 -0.100 7338 100.0%
Return Q+1 0.024 -0.001 0.423 -0.988 5.962 7338 100.0%

a ES Q: Earnings surprise for quarter Q

b Return Q+1: 3-month holding period return for investment made at the ending month of quarter Q+1

Table 3. 1999.2 - 2003.3 Returns of Portfolios with Extreme Earnings Surprises by Sector, Foreknowledge of Earnings Surprises at the Time of Investment

Panel A. Basic, Capital Goods and Consumer Durables Sectors

Basic Capital Goods Consumer Durables
Quarter ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD 
1999.2 0.224 0.167 0.056* 0.229 0.034 0.195*** 0.154 -0.095 0.249****
    (1.293)     (2.760)     (4.184)
1999.3 0.047 -0.046 0.093** 0.038 -0.054 0.092* -0.014 -0.185 0.171***
    (2.047)     (1.319)     (2.856)
1999.4 0.043 -0.109 0.151*** 0.031 -0.181 0.212*** -0.026 -0.077 0.051
    (2.717)     (3.043)     (0.260)
2000.1 -0.035 -0.139 0.104** 0.180 -0.016 0.196** 0.153 -0.069 0.222**
    (1.720)     (1.886)     (1.862)
2000.2 0.192 -0.095 0.287**** 0.119 0.030 0.090 0.138 -0.153 0.291***
    (5.502)     (1.006)     (2.833)
2000.3 0.124 -0.071 0.195*** 0.078 -0.063 0.141* 0.315 0.106 0.209
    (2.976)     (1.670)     (0.936)
2000.4 0.019 -0.149 0.168** -0.085 -0.167 0.082 0.115 -0.268 0.383**
    (2.279)     (0.602)     (2.477)
2001.1 0.143 0.119 0.024 0.093 0.070 0.022 0.165 0.089 0.076
    (0.302)     (0.301)     (0.416)
2001.2 0.198 0.064 0.133*** 0.116 0.098 0.018 0.236 -0.012 0.248**
    (2.481)     (0.310)     (2.321)
2001.3 -0.161 -0.192 0.031 -0.182 -0.259 0.077 -0.227 -0.304 0.076
    (0.811)     (1.049)     (1.020)
2001.4 0.174 0.074 0.100** 0.528 0.093 0.435**** 0.501 0.106 0.396***
    (1.907)     (4.553)     (3.224)
2002.1 0.155 0.060 0.095** 0.085 0.073 0.012 0.309 0.118 0.190**
    (2.102)     (0.190)     (1.744)
2002.2 0.014 -0.027 0.041 -0.054 -0.153 0.099* 0.018 -0.182 0.200**
    (1.139)     (1.574)     (1.970)
2002.3 -0.157 -0.268 0.111** -0.224 -0.302 0.079* -0.163 -0.292 0.129
    (1.937)     (1.355)     (1.307)
2002.4 0.067 -0.041 0.108** 0.172 -0.025 0.198*** 0.020 -0.083 0.103
    (2.220)     (2.620)     (0.961)
2003.1 0.024 -0.041 0.066 0.007 -0.076 0.084** 0.009 -0.117 0.126
    1.190     (1.748)     (0.786)
2003.2 0.197 0.118 0.079* 0.332 0.226 0.106* 0.446 0.343 0.103
    (1.578)     (1.305)     (1.073)
2003.3 0.117 0.083 0.033 0.185 0.090 0.095 0.146 0.147 -0.002
    (0.714)     (1.169)     (-0.022)
ALL 0.074 -0.018 0.093**** 0.096 -0.027 0.124**** 0.098 -0.017 0.115****
    (6.546)     (6.131)     (3.622)

Panel B. Consumer Non-Durables, Consumer Services and Energy Sectors

Consumer Non-Durables Consumer Services Energy
Quarter ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD 
1999.2 0.154 -0.081 0.235*** 0.128 -0.044 0.172**** 0.346 0.268 0.079
    (2.983)     (3.600)     (1.089)
1999.3 0.001 -0.215 0.216**** 0.100 -0.104 0.204**** 0.192 0.092 0.100***
    (3.830)     (4.516)     (2.655)
1999.4 -0.002 -0.182 0.180** 0.313 0.012 0.301**** -0.150 -0.203 0.053
    (2.312)     (3.669)     (1.262)
2000.1 -0.041 -0.073 0.032 0.125 -0.124 0.249**** 0.312 0.118 0.194****
    (0.516)     (5.016)     (3.501)
2000.2 0.279 -0.202 0.480**** -0.133 -0.288 0.155*** 0.353 0.260 0.094*
    (5.318)     (2.730)     (1.512)
2000.3 0.293 -0.102 0.395*** -0.022 -0.111 0.088** 0.129 0.053 0.077**
    (3.349)     (1.959)     (2.117)
2000.4 0.157 -0.244 0.401*** -0.421 -0.361 -0.060 -0.020 -0.093 0.073
    (2.520)     (-0.992)     (1.061)
2001.1 0.152 0.113 0.039 -0.071 -0.189 0.118** 0.201 0.119 0.082
    (0.312)     (2.040)     (1.290)
2001.2 0.342 -0.004 0.346**** 0.423 -0.047 0.471**** 0.100 0.042 0.058
    (4.485)     (5.494)     (1.186)
2001.3 0.007 -0.231 0.238*** -0.309 -0.335 0.026 -0.244 -0.287 0.042
    (2.610)     (0.699)     (0.953)
2001.4 0.184 0.139 0.044 0.669 0.236 0.432**** 0.113 0.077 0.036
    (0.507)     (3.970)     (0.805)
2002.1 0.157 0.145 0.011 0.096 -0.040 0.137**** 0.158 0.103 0.055
    (0.085)     (3.204)     (1.087)
2002.2 0.110 -0.105 0.215** -0.036 -0.322 0.286**** -0.006 -0.060 0.054*
    (2.215)     (4.657)     (1.660)
2002.3 -0.117 -0.222 0.105** -0.140 -0.350 0.210**** -0.145 -0.263 0.118***
    (1.689)     (5.136)     (3.007)
2002.4 0.004 -0.069 0.073 0.114 0.000 0.114** 0.133 0.013 0.120***
    (1.165)     (2.087)     (2.879)
2003.1 0.055 -0.128 0.183** 0.035 -0.231 0.266**** -0.004 -0.071 0.067**
    (1.778)     (5.792)     (1.859)
2003.2 0.395 0.155 0.240** 0.448 0.262 0.186**** 0.170 0.195 -0.025
    (1.880)     (3.293)     (-0.571)
2003.3 0.150 -0.024 0.175*** 0.246 0.020 0.227**** -0.022 -0.045 0.024
    (2.794)     (5.732)     (0.921)
ALL 0.116 -0.078 0.193**** 0.064 -0.083 0.147**** 0.079 0.032 0.047****
    (8.327)     (9.282)     (3.390)

Panel C. Finance, Health and Technology Sectors

Finance Health Technology
Quarter ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD 
1999.2 0.144 0.052 0.092** 0.070 0.023 0.047 0.250 0.000 0.250****
    (1.684)     (0.693)     (4.984)
1999.3 -0.076 -0.187 0.110*** 0.275 -0.076 0.352**** 0.304 0.002 0.302****
    (2.945)     (3.886)     (6.434)
1999.4 0.082 -0.160 0.242**** 0.082 -0.131 0.213**** 0.589 0.070 0.520****
    (4.372)     (3.316)     (8.358)
2000.1 0.025 -0.148 0.173**** 0.817 0.450 0.366** 0.621 0.371 0.249***
    (3.252)     (1.857)     (2.970)
2000.2 0.209 0.001 0.209*** 0.053 -0.217 0.270**** -0.210 -0.441 0.231****
    (2.648)     (3.658)     (7.125)
2000.3 0.156 -0.003 0.159*** 0.314 0.163 0.150** 0.116 -0.190 0.306****
    (2.696)     (1.791)     (6.021)
2000.4 -0.043 -0.164 0.120* -0.045 -0.111 0.066 -0.270 -0.456 0.186****
    (1.442)     (0.808)     (4.626)
2001.1 0.101 0.224 -0.123 -0.207 -0.247 0.040 -0.295 -0.213 -0.082
    (-0.546)     (0.729)     (-0.895)
2001.2 0.272 0.057 0.214**** 0.339 0.134 0.205** 0.233 0.001 0.232****
    (3.895)     (2.083)     (4.468)
2001.3 0.003 -0.180 0.183**** -0.233 -0.325 0.092* -0.305 -0.446 0.141****
    (4.494)     (1.651)     (4.580)
2001.4 0.217 0.080 0.137** 0.282 0.216 0.066 0.723 0.418 0.306****
    (2.126)     (1.048)     (4.088)
2002.1 0.115 0.003 0.112*** 0.002 -0.156 0.158*** -0.040 -0.145 0.105****
    (2.584)     (2.611)     (3.136)
2002.2 0.183 -0.109 0.292**** -0.057 -0.304 0.247**** -0.261 -0.424 0.163****
    (6.363)     (3.541)     (5.747)
2002.3 -0.011 -0.186 0.175**** -0.135 -0.228 0.093** -0.218 -0.403 0.185****
    (5.903)     (1.769)     (6.080)
2002.4 0.067 -0.077 0.144**** 0.090 -0.087 0.177*** 0.238 0.049 0.189****
    (4.230)     (3.097)     (4.323)
2003.1 0.045 -0.070 0.115**** 0.061 -0.149 0.209**** 0.029 -0.105 0.134****
    (4.153)     (3.594)     (4.176)
2003.2 0.318 0.177 0.141**** 0.541 0.363 0.178** 0.506 0.280 0.226****
    (3.179)     (2.031)     (4.827)
2003.3 0.125 0.038 0.086*** 0.229 0.137 0.092** 0.329 0.172 0.157****
    (3.062)     (1.949)     (3.378)
ALL 0.112 -0.036 0.148**** 0.130 -0.024 0.154**** 0.120 -0.072 0.192****
    (8.992)     (7.183)     (12.632)

Panel D. Transportation, Utility and All Sectors

Transportation Utility All Sectors
Quarter ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD  ES 10% ES 10% SPREAD 
1999.2 0.091 -0.158 0.249*** 0.254 0.102 0.152 0.193 0.052 0.141****
    (3.033)     (1.249)     (6.568)
1999.3 -0.028 -0.095 0.067 0.087 -0.007 0.094* 0.152 -0.051 0.203****
    (0.813)     (1.401)     (9.945)
1999.4 0.029 -0.149 0.178** 0.102 -0.040 0.141** 0.259 -0.080 0.338****
    (1.890)     (1.764)     (11.894)
2000.1 0.008 -0.172 0.180*** 0.173 0.062 0.111* 0.329 0.075 0.254****
    (2.701)     (1.385)     (7.340)
2000.2 0.072 -0.023 0.096 0.027 -0.046 0.073 -0.028 -0.187 0.159****
    (1.139)     (0.811)     (6.795)
2000.3 0.072 -0.100 0.172* 0.173 0.140 0.033 0.118 -0.040 0.158****
    (1.648)     (0.247)     (6.283)
2000.4 0.204 -0.042 0.246*** -0.170 -0.160 -0.010 -0.197 -0.251 0.055**
    (2.844)     (-0.087)     (2.284)
2001.1 0.083 -0.015 0.098 -0.054 -0.129 0.075 -0.100 -0.063 -0.036
    (1.213)     (1.220)     (-1.025)
2001.2 0.226 0.081 0.146** 0.091 -0.002 0.093 0.262 0.023 0.239****
    (2.106)     (1.291)     (9.304)
2001.3 -0.112 -0.315 0.203*** -0.190 -0.180 -0.010 -0.233 -0.326 0.093****
    (2.497)     (-0.138)     (5.693)
2001.4 0.253 0.284 -0.031 0.261 0.036 0.225 0.465 0.221 0.244****
    (-0.530)     (0.709)     (6.939)
2002.1 0.158 0.120 0.038 -0.142 -0.002 -0.139 0.047 -0.016 0.062****
    (0.749)     (-1.457)     (3.586)
2002.2 -0.006 -0.060 0.054* -0.223 -0.215 -0.007 -0.083 -0.255 0.173****
    (1.660)     (-0.071)     (8.949)
2002.3 -0.161 -0.395 0.233** -0.037 -0.315 0.278**** -0.154 -0.315 0.161****
    (2.191)     (3.472)     (10.296)
2002.4 0.060 0.098 -0.038 0.160 -0.119 0.279**** 0.138 -0.015 0.153****
    (-0.371)     (3.554)     (7.872)
2003.1 -0.098 -0.133 0.036 0.009 -0.064 0.073** 0.028 -0.117 0.145****
    (0.382)     (1.915)     (9.264)
2003.2 0.272 0.626 -0.355 0.244 0.818 -0.574 0.411 0.286 0.125****
    (-1.504)     (-1.572)     (4.419)
2003.3 0.369 0.055 0.314*** 0.080 -0.014 0.094** 0.218 0.067 0.151****
    (3.503)     (1.951)     (8.679)
ALL 0.061 0.006 0.055** 0.054 -0.016 0.070*** 0.099 -0.042 0.141****
    (1.836)     (2.615)     (21.947)

* Significant at .10 level

** Significant at .05 level

*** Significant at .01 level

**** Significant at .001 level

 

Table 4. 1999.3 - 2003.3 Returns of Portfolios with Extreme Earnings Surprises by Sector, Earnings Surprises Known at the Time of Investments

Panel A. Basic, Capital Goods and Consumer Durables Sectors

Basic Capital Goods