This paper finds that the majority of stock price movements remain unexplained after controlling for both public and private information. This suggests that economists’ inability to explain asset price movements is the result of either noise or naive asset pricing models.asset pricing; news; private information

William O. Brown, Jr.

English

Research Papers in Economics

Inside Information and Public News:
R
2 and Beyond
William O. Brown
*
Claremont McKenna College
Forthcoming Journal Of Applied Economic Letters
ABSTRACT
This paper finds that the majority of stock price movements remain unexplained after
controlling for both public and private information. This suggests that economists’
inability to explain asset price movements is the result of either noise or naive asset pricing
models.
JEL Codes: G12, G14
Key words: Asset Pricing, News, Private Information
* Department of Economics
Claremont McKenna College
Claremont, CA 91711
Phone (909) 607-3664
Fax (909) 621-8249
wbrown@benson.mckenna.edu
       Claremont Colleges
               working papers in economics
Claremont Graduate University • Claremont Institute for Economic 
Policy Studies • Claremont McKenna College • Drucker  Graduate 
School of Management • Harvey Mudd College • Lowe Institute • 
Pitzer College • Pomona College • Scripps College I. Introduction
Traditional economic theory predicts that changes in an asset’s price are caused by
unanticipated events that influence the fundamental value of the underlying asset. If we are
able to identify and control for such events ex-post, then we should be able to accurately
explain past price movements. After the elimination of news days from a sample of
common stocks, Roll (1988) is unable to explain a significant fraction of the remaining
price movements. He argues that the unexplained movements in asset prices are caused
"either by private information or occasional frenzy unrelated to concrete information."
1
The purpose of this paper is to add to the existing literature by controlling for the
influence of private information. The SEC's Official Summary is used to identify days
where corporate insiders complete transactions in a company's common stock. Seyhun
(1986) finds that these transactions are based on private information. The ex-post
identification and elimination of insider trading days, in addition to the public news days,
from the sample will allow us to determine to what extent private information is
responsible for the unexplained component of stock price movements.
II. The Data
The sample consists of the thirty firms comprising the Dow-Jones Industrial
Average from January 1, 1990 to December 31, 1992. The SEC's Official Summary is
used to identify the days where corporate insiders acquire or dispose of shares. The Wall
Street Journal Index is used to identify the news days for each firm. News stories occur
almost daily for these large firms. In order to solve this problem, I identify and include
only those stories that are major news events. The majority of news items include:
announcements of layoffs, corporate mergers or spin-offs, labor problems, the firm2
receiving large contracts, new product introductions, earnings reports, and top
management changes.
2 The main goal is consistency in the treatment of events across
firms.
III.  Tests and Result
The market model was estimated eliminating the news and insider trading days as
well as the four-day window surrounding the event.
3 Table 1 presents the results of
controlling for the news days, the insider trading days, and both the insider trading and
news days simultaneously. The average R
2 for all days is 28.95 percent. The average when
excluding the news days is 32.07 percent. Excluding the private information days actually
leads to a drop in the average R
2 to 28.78 percent and excluding both news days and
private information days leads to an average R
2 of 31.82 percent.
The average R
2 increase of 3.1 percent from the elimination of the news days is not
impressive in an explanatory sense. It is, however, higher than the 1.4 percent average
increase reported for Roll's eighty-nine firms. There are some relatively large increases
among the individual companies. Most notably, the R
2 for Westinghouse increases from
12.3 percent to 24.7 percent from the elimination of news days. Only three of the thirty
R
2s decrease after the elimination of the news days; each of these decreases is smaller than
one percent.
The results provide little support for the notion that private information is the
source of the previously unexplained variation in asset prices. The average R
2 decreases by
0.17 percent and it decreases for fifteen of the thirty firms. The largest increase is only3
4.21 percent while the largest decrease is 5.37 percent. The combined results suggest that
the exclusion of private information days adds little the explanatory power of the model.
The nature of these tests, especially the elimination of observations that have
informational content, may obscure the influence of such information. Mitchell and
Mulherin (1994) provide an alternative approach to finding the relationship between news
and market returns. By regressing the absolute value of the individual firm’s returns on the
absolute value of the CRSP value weighted market return and dummy variables
representing news and insider trading days, I obtain these alternative estimates.
The results provided in Table 2 indicate that the news dummy is positive, as
expected, for all but one of the firms. The coefficient is significant at the one- percent level
for twenty firms, and at the five- percent level for three firms. The dummy variable for the
insider trading days is positive as expected for eighteen of the thirty firms. The coefficient
is positive and significant at the five- percent level for one firm but also negative and
significant for one firm. The results indicate a stronger effect for both public and private
information. However, the overall link is still weak.
IV. Conclusions
The results are similar to those of Roll (1986, 1988), Cornell (1990), and Mulherin
and Mitchell (1995) in that I find the majority of asset price movements are unexplained
after controlling for proxies of information flow. The most important result is that private
information, as measured by the presence of legal insider trading, is not responsible for
these movements. While corporate insiders earn significant abnormal returns (Seyhun
(1986)), the information contained in these transactions is not responsible for unexplained4
stock price movements. This leaves alternative sources of private information, noise, and
the need for more complex models of asset price movements (e.g. Romer (1993),
Grossman (1995)) as possible explanations for Roll’s findings.
References
Cornell, B., 1990, Volume and R
2: A First Look, The Journal of Financial Research 13, 
1-6.
Grossman, S., 1995, Dynamic Asset Allocation and the Informational Efficiency of 
Markets, The Journal of Finance 50, 773-788.
Mitchell, M. and H. Mulherin, 1994, The Impact of Public Information on the Stock 
Market, The Journal of Finance 49, 923-950.
Roll, R., 1986, Orange Juice and Weather, American Economic Review 741, 861-880.
Roll, R., 1988, R
2, The Journal of Finance 43, 541-566.
Romer, D., 1993, Rational Asset-Price Movements without News, American Economic 
Review 83, 1112-30.
Seyhun, N., 1986, Insiders' Profits, Costs of Trading and Market Efficiency," Journal of 
Financial Economics 16, 189-212.Table 1
R
2s from Estimating the Market Model for All Days,
Non-Insider Trading Days, and non-News Days
All Excluding Private Info/ Excluding Public Info/ Excluding Public and
Days Insider Trading Days News Days Private Info Days
R
2 R
2 Change R
2 Change R
2 Change
Alcoa 0.2357 0.2482 0.0125 0.2644 0.0287 0.2819 0.0462
Allied Signal 0.1715 0.1722 0.0007 0.2124 0.0409 0.2241 0.0526
Amer Express 0.3095 0.3067 -0.0028 0.3495 0.0400 0.3548 0.0453
ATT 0.3464 0.3576 0.0112 0.3781 0.0317 0.3850 0.0386
Boeing 0.3124 0.3149 0.0025 0.3348 0.0224 0.3502 0.0378
Bethlehem Steel 0.1461 0.1336 -0.0125 0.1495 0.0034 0.1384 -0.0077
Caterpillar 0.1698 0.1815 0.0117 0.1779 0.0081 0.1779 0.0081
Chevron 0.2267 0.2321 0.0054 0.2456 0.0189 0.2577 0.0310
Coca-Cola 0.5015 0.4921 -0.0094 0.5428 0.0413 0.5437 0.0422
Disney 0.3500 0.3420 -0.0080 0.3703 0.0203 0.3583 0.0083
Du Pont 0.3869 0.4086 0.0217 0.4188 0.0319 0.4252 0.0383
Exxon 0.2106 0.2140 0.0034 0.2048 -0.0058 0.2106 0.0000
General Electric 0.5399 0.5248 -0.0151 0.5379 -0.0020 0.5225 -0.0174
General Motors 0.2913 0.2877 -0.0036 0.3548 0.0635 0.3991 0.1078
Goodyear 0.1091 0.1050 -0.0041 0.1365 0.0274 0.1386 0.0295
IBM 0.2509 0.1972 -0.0537 0.3294 0.0785 0.2714 0.0205
Intl Paper 0.3032 0.3031 -0.0001 0.2996 -0.0036 0.2967 -0.0065
Kodak 0.2588 0.2675 0.0087 0.3263 0.0675 0.3292 0.0704
McDonalds 0.3101 0.2737 -0.0364 0.3171 0.0070 0.2905 -0.0196
Merck 0.4431 0.4605 0.0174 0.4666 0.0235 0.4751 0.0320
MMM 0.4160 0.4050 -0.0110 0.4510 0.0350 0.4414 0.0254
Morgan (J. P.) 0.3182 0.3500 0.0318 0.3222 0.0040 0.3569 0.0387
Procter&Gamble 0.4419 0.4840 0.0421 0.4843 0.0424 0.3989 -0.0430
Philip Morris 0.4376 0.4102 -0.0274 0.4567 0.0191 0.4354 -0.0022
Sears 0.2416 0.2437 0.0021 0.2915 0.0499 0.3079 0.0663
Texaco 0.1450 0.1271 -0.0179 0.1461 0.0011 0.1281 -0.0169
Union Carbide 0.1928 0.1962 0.0034 0.2325 0.0397 0.2335 0.0407
United Tech 0.2357 0.2362 0.0005 0.2797 0.0440 0.2842 0.0485
Westinghouse 0.1230 0.1055 -0.0175 0.2447 0.1217 0.2324 0.1094
Woolworth 0.2595 0.2517 -0.0078 0.2962 0.0367 0.2977 0.0382
Average 0.2895 0.2878 -0.0017 0.3207 0.0312 0.3182 0.0288
Median 0.2754 0.2706 0.0002 0.3197 0.0302 0.3028 0.0349
Maximum 0.5399 0.5248 0.0421 0.5428 0.1217 0.5437 0.1094
Minimum 0.1091 0.1050 -0.0537 0.1365 -0.0058 0.1281 -0.0430Table 2
The Cross Sectional Influence of
Public News and Private News on Security Returns
The results are from estimating the following model:
rit = ait + bit VWRETD g1itNEWS + g2itINSIDER TRADING + eit
where VWRETD is the CRSP value weighted return, NEWS is a dummy variable that is
equal to one if there is a major public news story about firm i on that day, and INSIDER
TRADING is a dummy variable that is equal to one if there if insider trading is reported to
have occurred for firm i on that day. Significance at the 1 percent and 5 percent levels are
noted by the superscripts a and b.
Firm Intercept VWRETD News Insider R
2 ADJ R
2
Alcoa 0.009130 0.513961 0.004880 -0.001035 0.0852 0.0816
15.350
a 7.029
a 3.687
a -1.851
Allied Signal 0.009011 0.615604 0.006437 -0.001032 0.0918 0.0882
12.814
a 7.331
a 4.442
a -1.305
Amer Express 0.009293 1.141189 0.005551 0.001719 0.1720 0.1687
11.899
a 11.936
a 3.963
a 1.272
ATT 0.006546 0.720851 0.002163 -0.001467 0.1817 0.1785
13.660
a 12.199
a 3.088
a -1.585
Boeing 0.006898 1.005033 0.002167 0.000139 0.1887 0.1855
11.181
a 13.079
a 2.075
b 0.131
Beth. Steel 0.016626 0.505771 0.003761 -0.001885 0.0267 0.0228
16.984
a 4.185
a 1.832 -0.953
Caterpillar 0.009257 0.585342 0.004809 0.002512 0.0837 0.0801
14.041
a 6.975
a 4.081
a 1.427
Chevron 0.007178 0.342091 0.001161 -0.000147 0.0556 0.0518
17.202
a 6.517
a 1.341 -0.130
Coca-Cola 0.005042 1.098789 0.005399 -0.000447 0.3177 0.3150
10.184
a 17.853
a 5.246
a -0.501
Disney 0.007474 0.854601 0.001211 0.000209 0.1749 0.1716
13.645
a 12.637
a 1.056 0.225
Du Pont 0.005995 0.918709 0.003986 0.001067 0.2264 0.2234
11.277
a 14.601
a 3.851
a 1.847
Exxon 0.006613 0.437061 0.000358 0.000190 0.0864 0.0828
15.505
a 8.439
a 0.581 0.309
General Electric 0.004237 1.018890 0.002165 0.000611 0.3445 0.3419
10.457
a 19.611
a 2.455
b 0.413General Motors 0.009918 0.924875 0.003403 -0.001179 0.1471 0.1437
13.288
a 10.774
a 4.033
a -2.013
b
Goodyear 0.012069 0.710767 0.003541 -0.000594 0.0700 0.0663
14.738
a 7.106
a 2.361
b -0.437
IBM 0.007438 0.491296 0.004064 -0.000526 0.0937 0.0901
13.132
a 7.051
a 5.358
a -0.810
Intl Paper 0.007434 0.715692 0.001125 0.000299 0.1523 0.1490
15.106
a 11.598
a 0.968 0.337
Kodak 0.006962 0.778289 0.006571 0.000535 0.1514 0.1481
11.556
a 10.497
a 4.711
a 0.519
McDonalds 0.008113 0.728243 0.005499 0.000963 0.1554 0.1521
14.749
a 10.680
a 4.306
a 1.967
b
Merck 0.006199 0.870567 0.001206 -0.000198 0.2292 0.2261
12.729
a 14.894
a 1.244 -0.291
MMM 0.004231 0.700663 0.005157 0.000650 0.2564 0.2534
11.584
a 15.100
a 4.800
a 0.698
Morgan (J. P.) 0.007744 0.822524 0.006419 -0.000187 0.1627 0.1594
12.910
a 11.233
a 4.669
a -0.283
Proc. & Gamb. 0.004749 0.890451 0.004464 0.000155 0.2827 0.2799
10.341
a 16.533
a 5.054
a 0.392
Philip Morris 0.005897 0.876664 -0.00034 0.000386 0.2402 0.2371
12.522
a 15.395
a -0.38 0.467
Sears 0.008092 0.821898 0.003442 0.000758 0.1346 0.1311
12.662
a 10.372
a 3.410
a 0.460
Texaco 0.007213 0.349116 0.003258 0.001059 0.0618 0.0580
16.334
a 6.495
a 2.872
a 1.609
United Carbide 0.010328 0.610044 0.008872 0.002666 0.0938 0.0902
14.353
a 6.693
a 5.633
a 0.935
United Tech. 0.007508 0.617514 0.005356 0.000427 0.1098 0.1063
13.006
a 8.611
a 4.563
a 0.438
Westinghouse 0.012017 0.485997 0.007465 -0.000934 0.0459 0.0422
12.408
a 4.020
a 4.373
a -0.556
Woolworth 0.007997 0.788746 0.007116 0.000913 0.1296 0.1262
12.387
a 10.000
a 4.192
a 0.938ENDNOTES
1 Cornell (1990) uses abnormal trading volume as a proxy for both public and private information flows.
He finds that the elimination of high volume days from his sample allows for a larger increase in
explanatory power than Roll's approach but still leaves the majority of the movements unexplained. This
approach does not allow him to distinguish between public and private information.
2 The number of public news days and insider trading days for each of the thirty companies is as follows:
Alcoa (23, 82), Allied Signal (26, 70), ATT (50, 33), American Express (35, 34), Boeing (39, 25),
Bethlehem Steel (26, 21), Caterpillar (31, 15), Chevron (25,16), Coca-Cola (27,32), Disney (28,31), Du
Pont (27,75), Exxon (41, 47), General Electric (24, 10), General Motors (66,141), Goodyear  (31, 29),
IBM (55, 57), International Paper (21, 31), Kodak (22, 39), McDonalds (21, 97), Merck (27, 54),
Minnesota Mining and Manufacturing (14, 18), Morgan (J.P.) (21, 75), Procter & Gamble (28, 127),
Philip Morris (32, 39), Sears (44,17), Texaco (17, 43), United Carbide (25, 8), United Technology (28,
36), Westinghouse (32, 35), Woolworth (16, 42).
3 Event windows of various lengths were tried; they all produced similar results  I eliminate days
following the event to make sure that any feedback effects where market participants react to other market
participants’ reaction to the news are fully captured (Grossman (1995)) .

Inside Information and Public News: R-Squared and Beyond

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