John S. Jahera,, Jr., is an Associate Professor of Finance at Auburn University. William P. Lloyd is Professor and Head of the Department of Finance at Auburn University. Daniel E. Page is an Associate Professor of Finance at Auburn University

Jahera, John S., Jr.

Lloyd, William P.

Page, Daniel E.

English

Georgia Southern University: Digital Commons@Georgia Southern

Southern Business Review Volume 14 Issue 1 Article 6 April 1988 The Neglected Firm Effect on Stockholder Returns John S. Jahera Jr. Auburn University William P. Lloyd Auburn University Daniel E. Page Auburn University Follow this and additional works at: https://digitalcommons.georgiasouthern.edu/sbr  Part of the Business Commons, and the Education Commons Recommended Citation Jahera, John S. Jr.; Lloyd, William P.; and Page, Daniel E. (1988) "The Neglected Firm Effect on Stockholder Returns," Southern Business Review: Vol. 14: Iss. 1, Article 6. Available at: https://digitalcommons.georgiasouthern.edu/sbr/vol14/iss1/6 This article is brought to you for free and open access by the Journals at Digital Commons@Georgia Southern. It has been accepted for inclusion in Southern Business Review by an authorized administrator of Digital Commons@Georgia Southern. For more information, please contact digitalcommons@georgiasouthern.edu. THE NEGLECTED FIRM EFFECT ON STOCKHOLDER RETURNS John S. Jahera, Jr., William P. Lloyd and Daniel E. Page The relationship between abnormal returns and firm neglect as measured by information availability is a topic of interest to financial economists. A neglected firm is defincJ as one for which there is a lack of information available and / or where the quality of the information i~ poor and difficult to obtain. Research on neglected firms has implied that incomplete information may lead to the oppor-tunity for excess returns. These findings indicate market ineffiencies and suggest a need for further research to either confirm or refute such results. The objective of this research is to test the hypothesis of an inverse relation-ship between excess returns and information availability while controlling for size. The rigorous empirical methodology used is unique to the neglecteJ firm literature. The results of this different approach do not support the existence of a neglected firm effect. This paper b organized al> follows: overview of the research on neglecteJ firms; Jevelopment of the methoJology; discussion of the empirical result~; and. con-clusions anJ implications. Prior Research The efficient market hypothe~is implies that investors. on average. cannot earn abnormal returns . However. such anomalies as the small-firm effect. the day of the week effect, the January effect, and the neglected firm effect are suggestive of market inefficiencies. The neglected firm effect describes the relatton~hip be-tween abnormal returns and the 1nformatton available on the firm . The relatton-~hip between the amount and / or quality of information and excess returns is hypothesized to be inverse. The degree of neglect has been proxied in a variety of ways. including the number of analysts following the stock. the number of financial mst1tuttons holding the stock. the percentage of the firm's outstanding stock held by mMitut10ns. anJ the period of exchange liMing. Table I provides a bnef summary of the relevant literature. As a proxy for infonnatton, Arbel and Strebel [ 19821 used the number of analysts following the stock. Their research implied that firms wtth few analysts have ex-cess return~. In an extension. Strebel and Arbcl [ 19831 explored this relattonship over the decade of the 1970's and examined the results for less than perfectly diversified portfolios. Based on arithmetic averages of annual returns and the Capital A~set Pncing Model. they found that the degree of analyst neglect per-sists in explaining relative performance even when size is held constant. Arbel [ 19851 measured neglect by institutional ownership and by the coefficient of varia-tion of analyst's mean earning~ forecast. He concluded that neglected fi rms suf-fer not only greater infonnation deficiency. but that such deficiency leads to higher returns. Barry and Brown [ 1984 J used the period oflisting. the number of security return observations available, and the divergence of analyst opinion as measures of in-25 -L w Table I Summarie, of "lleglected Firm Studies ---------------i PERIOD OF STlJDY S \\IPLE SIZE :\IEASURE OF EGLECT STUD'\ (YEAR) FINomr.s A rbcl and Strebel Number of Most neglected (1982) 1972-1976 S&P 500 AnalyMs fi rms perfonn b Strebel and Arbel Number of Most neglccttd (1983) 1970-1979 S&P 500 Analy~tl> firms perform b Barr: and Brown Time Period Time of listing (1984) 1931-1980 ~YSE of Lisllng related to small firm effect Arbel ( 19851 1971-1982 1.000 Jn<,tJtutJonal Neglected fillll! Ownerl,h1p have higher rtll Barry and Brown fl985) 1931-1980 NYSE Period of liMing, Significant number of l,ecurity relationship return ob,ervations between rneasw a\•ailable. and and excess J'ClW divergence of analyM opinion Peter,on. Peterl>on. and Ang (1986) 1976-1981 571 to 986 Number of analysts M 1xed results Edelman and Baker lns11tut1onal PIE ratio rclate1 (1986) 1980-1985 128 Ownerl,hip neglect Barry and Brown Penod of listmg Confirm ncgled (1986) 1931 -1980 NYSE firm effect Jahera. Lloyd and Number of Does not suppl Page 1978-1981 596-613 Analysts neg. firm cffed 26 formation. For the period 1931 to 1980 they grouped securities by size, number of months since the security was first listed on the NYSE, and beta (calculated using OLS procedures). Portfolio return measures were calculated by equally weighting returns for securities within each size group. Their results showed that the period listing is associated with the small firm anomaly. However. despite this association the results indicate a neglected firm effect over and above the size effect. The neglected firm effect was strongest for the smallest firms. They conclude that further research using other proxies is needed. In subsequent studies. Barry and Brown I I 985 and 1986] confirmed their earlier results. Edelman and Baker [ 1986) used the number of financial institution~ holding the stock as the measure of neglect. They hypothesized that financial institution~ consistently avoid certain companies because of external and self-imposed con-straints. The resulting avoidance creates informational vacuums which in turn produce the neglected firm. Edelman and Baker, using ANOVA for the period of 1980 - 1985. found the existence of the institutionally neglected firm effect to be significant. Peterson. Peterson. and Ang 11986] used the number of analysts submitting forecasts of a company ·s annual earnings per share as the measure of neglect. Regression analysis for the period 1976-1981 implied a neglected firm effect. However. the relationship is not always significant and there are time periods when widely followe<l firms outperform neglected firms. Data and Empirical Methodology The hypothesis to be tested in this research is that an inverse relationship exists between excess returns and informallon as measured by the numb.:r of analysb. The sample was obtained from the Compustat PDE tape for the period 1978 -198 I. Monthly common stock returns were calculated from the PDE tape for the penod I 978-1981. To avoid any potential selection bias. all firms appearing on the tape were mdude<l. If a firm had incomplete data. a search was conducted using the Wall Street Journal Index to ascertain the reason. If a stock was dropped from the tape due to bankruptcy. a - I 00% return was given in the month of bankruptcy. Merged firms remained in the sample after the merger. Firms from the NYSE. AMEX. and OTC were repre~ented in the ~ample. Market values were calculated by multiplying the number of shares outstanding as of December 31. I 977. the beginning of the analysis period. by the market pnce of the stock. The number of shares outstanding wa~ obtained from Standard and Poor's Stock Guide. The initial sample used in the first ~tep of the analysis consisted of 1459. 1494. 1535 and 1572 firms for the pcnod 1978 to 1981. re~pectively . The number of analy~t~ reporting earning forecast~ as compiled in the Standard and Poor's Earnings Forecaster wa~ u~ed as the measure of analysts· attention. Numerous studie~ of neglected firms have indicated that size and risk must be controlled. To control for risk, a procedure using excess returns developed by Rozeff I 1984] i~ utilized. This procedure removes the portion of ex-post returns contributed by the firm·~ beta value. In this manner. beta risk is controlled. The Roze ff procedure begins with the determination of capital market parameters for use in determining the excess returns. First. fifty portfolios are formed by ranking the firms into ten group~ based on size and then further ranking within each of the ten size groups based on beta. (There are five beta groups per size 27 J '11 group.) The beta value for each firm is esumated using data for the prior four ye.a.rs. 1974-1977. An equally weighted index of all firms on the Compustat PDE tape is used in the beta computation. The effect of this procedure is to yield fifty very different portfolios. The monthly return~ for each of the fifty portfolios are then determined for the subsequent twelve month~. This procedure is followed again at the end of 1978, 1979. and 1980. In other words, the estimation period is four years and rolls forward each year. The result of this procedure is fony-eight months of returns for each of the fifty portfolios along with their betas. s Using this data. the portfolio returns are regressed on the respective betas by month to give capital market parameters for each month from 1978 to 1981. These parameters are then used in the determination of the excess returns. The second step in the empirical analysis is the formation of portfolios based on size and neglect as measured by the number of analysts providing an earnings forecast. The portfolio construction procedure is hased on the grouping of firms by ~ize into five groups. Then the ~ame firms are grouped into three groups based on the number of analysts . The size groups and analyst groups are then merged to yield fifteen portfolios. The merge is based on a matching of firms which leads to the elimination of thme firms for which no analyM forecast was made or for which no match is evident. For instance. a firm in portfolio one must have been in both the size group one and the analyst group one. Summary information on these portfolios is presented in Table 2 which gives the number of firms in each portfolio. the average size of the firm~. and the portfolio betas for each of the four years under study. This portfolio procedure reduced the ~ample to 596, 599, 606 and 6 I 3 firms fur the years 1978 to 198 I. respectively. Monthly excess returns for each portfolio are determined for the years 1978 to 1981 using the capital market parameters and betas developed in the first step. Using Rozeffs Model. the excess return for each portfolio is calculated by: Rpt - Xot - X11Bp.t-l where: Rpt = portfolio return in month t. Xot, XI 1 = market parameters in month t. and Bp,t- I = portfolio beta. A two-factor analysis of variance is applied to the excess returns calculated from Rozeff's model. The model i~ given as: rijt = m + ai -bj + (ab>ij + Wt· where rijt = t1h excess return in the ij' cell. m = overall mean exec~~ return. ai = main effect due to size. bj = main effect Jue to neglect, (ab)ij interaction between size and neglect. eijt 1th error term. A priori , firms with the most analyst attention should have the smallest excess return~. Th,~ a~sumes that any neglected firm effect is captured in the proxy used in the ~tudy. 28 Table 2 Descriptive Statistics Number of Analysts By Group Smallest Largest Size I 2 3 1 (Smallest) 1 90 16239 1.12 2 20 21058 1.16 4 9 25879 0.82 1 91 16138 I. 13 2 20 19721 1.16 49 25879 0.79 1 92 15896 I.IS 2 20 19721 1.22 49 25879 0.91 1 95 15817 1.13 2 20 19638 1.16 4 7 23640 0.95 1 92 16023 1.13 2 20 20035 1.18 49 25319 0.87 2 1 67 54528 1.01 2 31 58381 1.14 3 21 54857 1.02 I 68 54235 0.98 2 31 56832 1.14 3 21 54857 0.96 1 69 53282 0.89 2 30 54567 1.07 3 22 55742 1.01 I 68 52291 0.90 2 31 53913 1.00 3 24 53907 1.07 I 68 53584 0.95 2 31 55923 1.09 3 22 54841 1.02 3 I 45 142503 0.88 2 38 148819 0.92 4 37 152610 0.93 I 44 142503 0.84 2 39 147124 0.86 4 37 152610 0.84 I 46 139985 0.89 2 40 14 1449 0.88 4 36 150163 0.88 I 49 135216 0 .87 2 38 136505 0 .87 4 36 150163 0 .92 I 46 140601 0.87 2 39 143474 0.88 4 31 151387 0.89 4 I 44 372035 0.82 2 44 381772 0.85 4 31 385864 0 .84 I 45 369132 0.67 2 44 381772 0.79 4 31 385864 0.79 1 45 362321 0.63 2 -14 373966 0.83 4 32 381327 0.86 I 46 359594 0.64 2 45 363M2 0.83 4 32 381327 0.79 I 45 365771 0 .69 2 44 375288 0.83 4 32 383596 0.82 5 (Largest) I 19 1889703 0 .66 2 29 1224039 0.76 4 71 1900323 0.72 I 19 1889703 0 .58 2 29 1224039 0 .64 4 71 1900323 0.62 I 20 1824054 0 .51 2 30 1202723 0.62 4 71 1900323 0.66 I 20 1824054 0.51 2 31 1182035 0 .60 4 71 1900323 0.66 120 18568790.57 2 30 1208209 0.66 4 71 1900323 0 .67 Note: The first number in each cell represents the average number of analysts. the second number is the number of firms in the portfolio. The third number is the average size in terms of market value (in $000's), and the fourth number is the portfolio beta value. Each portfolio is by year, 1978 • 1981. with the average for each size group. 29 Results Table 3 presents the mean monthly excess returns for each of the portfolios. The results indicate that the firms with the largest group of analysts also have largest excess returns. Casual observation implies that a neglected firm effect does not exist. For example, the mean monthly returns for the smallest size group and the smallest analyst group are smaller than the excess returns of the largest group size and the largest analyst group. This is the opposite of what was expected. Table 3 Excess Returns for Size/Anal)sts Portfolios umber of Anal)sts By Group Smallest Largest Size 1 2 J I (Smallest) -0.009 -0.005 -0.002 2 - 0.009 -0.01 -0.001 3 - 0.012 -0.009 - 0.008 4 - 0.007 - 0.008 -0.008 S (Largest) - 0.009 -0.007 -0.007 The results of the ANO VA are pre!.ented in Table 4. The F-value for the size effect is . 76, 3 .22 for the number of analysts. and .63 for the rntt:raction term. These results imply that size is not ~ignificant in explaining exce~!. returns . The number of analysts following the firm is ~ignificant, but the excess returns appear to be positively related to the level of information. This is opposite of the a priori expectations. Table 4 A OVA F-Statistic Size Analysts Interaction Full Model 0.76 3.22* 0.63 Small Size Omitted 0.24 1.85 0 .72 Small Size and Least Analysts Ommed 0.33 2.ss• 1.20 *Denote~ significance at the .OS level of significance. Given the preponderance of evidence supporting a small firm effect. the ANO VA was applied to the data after the deletion of the smallest size portfolios in Table 3. This was done to avoid any domination by the smallest firms. The rc~ults of this, as shown in Table 4, imply no significance to either the size or the number of analysts in explaining excess returns. While o ne would expe~t a ~ignificant size effect, the lack of such significance may be explained by the fact that those firms for which no fo recast is available are not included in the final 30 --sample. T hose firms are likely to be the smaller firms in the sample and thei r elimination will mute any small firm effect. Table 4 also presents the results or the ANOV A when both the smallest size group and the least number or analysts group (column I and row I of Table 3) are omitted. Again. ;ize i, not significant in explaining excess return. However. the number or analysts is ,ignificant, but with a positive relationship rather than negative. In order to test the robustness of the model, portfolios that had no analysts sub-mitting a forecast are created. This increases the sample size to an average of 1200 firms. The purpose of including thb group of portfolio, is to determine 1f there i; ,ignificant differences between zero analysts and one analysts versu~ portfolios that have one analysb and more than one analysts. The results of in-cluding thb new group of portfolio, is the same as the original model. Conclusions The purpo,e of this paper was to examine the neglected firm effect when the number of analysts following the stock was used as a proxy for the degree of neglect. U,ing a similar measure of neglect. Arhel and Strebel [1983] found a ,1gnificant inverse relationship between the degree of neglect and the finn ·s return. Thi, paper. using a different methodology than previous studies. does not sup-port the hypothesi, of a neglected firm effect. The results. taken in the context of other research in the area. indicate the need for additional research to clarify the i,,ue. The con0ieting re,ults lead one to believe that either there is no effect. the effect is un,tablc over time (as ,ugge,ied by Peterson. Peterson. and Ang ( 19861). or that the measurement of the effect in the research to date has suffered from ,ome degree of mea~urement e rror or that the effect empirical methodologies arc flawed. Hopefully. further research will lead to a definitive answer. References Arbel. A ... Generic Sto1:k\: An Old Produi.:t ma New Package." Journal of Portfolio Management. 11 (Summer 1985). 4-13. Arbel A. and P. Strebel .. The Neglected and Small Firm Effet·ts." The Finan-cial Review. 17 (November 1982). 201-218. Arbel. A. and P. Strebel. ··Pay Attention to Neglected Firm~." Journal of Port folio Management, 9 (Winter 1983). 37-42. Barry, C.B. and S.J. Brown ... Differential Information and the Small Firm Effect." Journa l of Fina ncia l Economics, 13 (June 1984 ). 283-294. Barry, C.B. and S.J. Brown. "Limited Information As A Soun:c of Risk." Journal of Portfolio Management , 12 (Winter 1986), 65-72. Barry, C.B. and S.J. Brown, "Differential Information and Security Market Equilibrium." Journal of Financial and Quantitative Analysis, 20 (December 1985), 407-422. 31 Edelman. R.B. and H.K. Baker. "The Relationship Between Neglected Finn Returns and Institutional Ownership." Presented at the 1986 FMA Meetings, New York City, New York, (1986), 19 pages. Peterson, D.R .. Peterson, P .P. and J .S. Ang. "The Neglected Stock Anomaly: Further Evidence." Review of Business and Economic Research, (Fall 1986), 44-52. Rozeff, M. "Coskewness and Dividend Yield." Journal of Financial Research, Vll (Fall 1984), 231-241. John S. Jahera,, Jr., is an Associate Professor of Finance at Auburn University. William P. Lloyd is Professor and Head of the Department of Finance at Auburn University. Daniel E. Page is an Associate Professor of Finance at Auburn University. 32 ... 

The Neglected Firm Effect on Stockholder Returns

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The Neglected Firm Effect on Stockholder Returns

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