A Study on the Impact of Security Analysts' Monitoring and

Marketing Functions on the Market Value of the Firms Included in the

Philippine Composite Index (PHISIX) Covering the Period 1994-1997

Leila Y. Calderon Financial Management Department

De La Salle University-Manila

BACKGROUND

Chung and Jo (1996) found out that analysts following has a significant and positive impact on firm's market value, as proxied by the Tobin's q. The analysts may also influence firm value through its impact on investor's cognizance of securities. Investors become familiar with the securities they trade through the information provided for by analysts. As such, firms with large number of analysts following may also have an expanded breadth of investor cognizance. Also, high quality firms are usually followed by a larger number of analysts because the analysts' brokerages will find it easier to market these firms. Thus, analysts have a stronger incentive to follow stocks of high quality companies, since they are familiar to investors.

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18 PHISIX 1994-1997

The researcher will take off from Chung and Jo's (1996) study using the companies included in the 1996 Philippine Stock Composite Index (PHI SIX). (Appendix 1 ). The main treatise of this paper is to probe on the relationship of analysts' following a firm on the market value of the firm.

To further support this treatise, the following hypotheses will be validated in this study:

1. There is no significant relationship between security analysts' following and market value as proxied by Tobin's q.

2. Security analysts do not have an incentive to follow stocks of high quality firms.

3. There is no significant relationship between analysts' following with firm size, trading volume, variability of stock return and share price.

4. Quarterly earnings announcements of index stocks do not affect stock prices.

DATA COLLECTION

The thirty (30) firms in the 1996 Philippine Stock Exchange (PSE) Composite Index (PHISIX) were used as the sample firms in the study. (Appendix 1 ).

A detailed computation for the market value, tobin's q, gross capital adjusted for inflation, rate of return and firm size is presented in Appendix 2.

All information in computing for Tobin's q were derived from the annual reports of Firm ; in Year t. All annual reports were audited and considered to be accurate. The accounts used for each variable were noted on the company's respective computations for Tobin's q. In some cases, proxy accounts were used. Each firm's Tobin's q is summarized on Table 1.

In order to select stocks to be included in the Reformulated Composite Index, the following criteria was set based on market capitalization, liquidity, representation, maturity, and stock type. (Source: PSE News Release, Nov. 13, 1996)

Closing stock prices and volume of each firm in the sample from January 2, 1994 to December 29, 1997 were obtained from the Philippine Stock Exchange (PSE) research department. Data were the nominal closing stock prices, unadjusted for dividends.

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Leila Calderon 19

Table 1. Summary of Companies Tobin's Q

Company 1994 1995 1996 1997

ABS-CBN 5.3210 3.9581 3.2400 1.6385 AC 4.4204 2.2000 2.5338 1.8411 AEV 2.3149 2.1498 1.3919 0.6745 All 4.7486 4.5046 4.8747 2.5894 BEL 2.1169 1.5876 2.2989 0.8038 BPC 2.4971 1.4806 1.6139 0.7971 CMP 2.8856 2.3380 0.7454 CMT 1.7322 2.4742 1.6223 0.5091 DMC 0.2204 0.2629 0.3080 FDC 0.3901 2.5097 1.6275 0.6675 FLI 3.5883 2.1651 1.5803 0.2815 ICTS 2.2690 1.8145 2.3124 1.1422 ION 0.3204 5.2759 3.3938 2.5325 JFC 3.9868 4.8998 5.7275 3.0677 JGS 1.2795 0.9464 0.8710 0.7583 LND 0.5639 3.7729 2.2431 0.5538 MBTC 1.1228 1.0729 1.2625 0.9463 MEG 3.3694 1.1962 0.8170 0.3560 MER 2.2035 1.5930 1.3425 1.0386 MPC 1.0561 1.0656 1.5542 0.4406 PCIB 0.7807 0.8051 0.8174 0.7995 PCOR 3.2745 3.0383 1.6114 0.9401 PLTL 0.6558 2.0639 1.4518 0.8520 PNB 0.9918 1.0186 1 .0152 0.9455 PX 1.1663 0.9160 0.7353 0.4824 SMC 2.1085 1.4367 1.5386 1.0959 SMPH 2.8429 3.0115 2.3806 1.8957 TEL 1.2356 1.1887 1.1193 1.1754 UBP 1.1186 0.9967 1.0141 0.9319 URC 1.6538 1.4202 1.4518 0.7190

Mean 2.1118 2.1223 1.8681 1.0510

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20 PHISIX 1994-1997

Using each firm's closing prices for each year, the mean value of the daily closing price is computed as:

L Daily Closing Stock Prices Meanval '·' = ---------------------------------------- Eq.l

Number of trading days

To obtain the daily stock returns of each firm,

Today's Closing Price- Yesterday's Closing Price Daily Return. = ----------------------------------------------------------- • l 00 Eq.2

'·' Yesterday's Closing Price

Using the daily stock returns, the mean return (retvar) is computed to obtain the average stock return during Year t.

L Daily Returns Retvar. =

'·' * 100 Eq.3

Number of trading days

The trading volume of Firm , during Year , (Tradvol ,,,) is measured by the mean value of daily peso trading volume during the year.

L Daily Trading Volume Tradvol. =

'·' Eq.4

Number of trading days

Lastly, we obtained the number of stockholders of Firm, (noshares) as given in the annual report during Year,.

Analysts' forecasts for each firm were obtained from the publications made by the research department of various stock brokerages. (Appendix 3 ). However, for confidentiality purposes, the securities firms will be identified as SF#.

For each firm, we obtain a one-year earnings forecast for each year covering the period 1994-1997. Each firm was assumed to be monitored by at least two analysts.

The study is limited to the financial/ security/ research analysts who used fundamentals such as previous earnings report and company information to project future earnings. The study did not include the technical analysts whose main concern is

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Leila Calderon 21

examining the movements and patterns of prices of said index stocks.

The number of analysts' following a firm was measured the number of analyst's following variance (Nafvar) for firm i at year t,

Actual Earnings-Consensus Forecast Nafvar. =

'·' * 100 Eq.5

Consensus Forecast

Where Actual earnings-based on the earnings in the annual report for firm i at year t.

To get the consensus of the forecasts of various analysts from both local and foreign securities firms, the researcher added all forecasts available divided by the number of analysts following the firm

L of number of analysts' forecast following the firm Consensus - ----------------------------------------------------------- Eq.6

Forecast;,, Number of analysts' following the firm

Nafvar 11

proxies the number of analyst following the firm. The higher the Nafvar,,,. then there are few analysts following the firm thus, the higher the variance in earnings forecast. If Nafvar '·' is low, then there are more analysts following the firm, thus the accuracy of earnings forecast is higher.

If the Nafvar,,, is negative, the analysts have been optimistic about the performance of the company and has given a higher than expected earnings for the firm. On the other hand, if Nafvar, , is positive, the analyst has been pessimistic about the performance of the firm and has given some doubts on the firm's capability of achieving its earnings.

1 o test whether or not stock prices change upon the release of the quarterly earnings, the stock prices of each company, seven days before and after the earnings announcement were used. In a previous study, Aguirre and Valdes (1998) used fifteen days before and after the earnings announcement. The result was that there was no difference in stock prices before and after the quarterly earnings release. However, they suggested that a shorter period be used, notably seven days before and after the earnings announcement to determine whether or not there is a difference in stock prices.

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22 PHI SIX 1994-1997

Quarterly earnings announcement dates were proxied by dummy dates. The dummy dates are assumed to be exactly one month after the last day of the preceding quarter. The informational effect of the quarterly earnings was limited to the stock prices on the last seven trading days of the first month of the next quarter and the first seven trading days of the next month of the next quarter.

DATA PRESENTATION AND ANALYSIS

Table 2 presents descriptive statistics of the variables, Tobin's q, Nafvar, Grosscap, Rettocap, Fsize, Meanval, Retvar, Tradvol and Noshares. For each variable, we provide the mean, standard deviation, median, kurtosis and skewness for firm i in year t from 1994-1997.

In 1994, there were six firms [Filinvest Development Corporation (FDC), lonics Circuits (ION), Fii-Estate Land, Inc. (LND), Philippine Commercial and International Bank (PCIB), Pilipino Telephone Company (PL TL) and Philippine National Bank, (PNB)J with Tobin's q less than 1. (Table 1 ). These firms may indicate a deficiency of prospects for the company or alternatively, could be a sign of undervaluation, depending on the particular circumstance. (Farrell, Jr., 1997). All the rest of the firms have Tobin's q greater than 1.

"When the ratio is above 1, then investment is warranted because it would add value to the corporation. Investing would also continue under this circumstance until the q ratio declined to its equilibrium ratio of 1. Also, a q above 1 could be viewed as an indicator of overvaluation, depending on the particular stock." (Farrell, Jr., 1997).

The following firms had Tobin's q less than 1 for most of the years under observation: DMC Holdings, Inc. (DMC) (listed in 1995, Tobin'q less than 1 for 1995-1997), JG Summit (JGS) (1995-1997), PCIB (1994-1997), and Philex Mining (PX) (1995-1997). (Table 1 ).

In 1995, the mean of Tobin's q for all-companies increased slightly. However, the Tobin's q of lonics Circuits (ION) increased to 5.2759 from the previous year's 0.3204. Total assets increased by 272% from P406.6 million in 1994 to P1, 105.9 million in 1995. Improvement in the Tobin's q is attributed to the substantial increase in total assets, stockholder's equity and net income. (lonics Circuits1995 Annual Report).

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TABLE 2. DESCRIPTIVE STATISTICS

YEAR 1994 VARIABLE VAUDN MEAN MIN MAX STDEV Kurt Skew TOBIN'SQ 28 2.1118 0.32041 5.321 1.123 -0.262 0.769 NAFVAR 25 0.7963 -0.5301 14.62 2.943 22.62 4.672 RETIOCAP 28 -0.477 -3.8524 1.636 1.082 3.428 -1.39 GROSCAP 28 2E+08 -3E+09 5E+09 1.5E+09 5.444 1.682 FSIZE 28 3E+09 -7E+06 2E+10 5.2E+09 5.742 2.444 MEANVAL 28 167.32 2.14333 1753 384.569 13.28 3.485 RETVAR 28 0.0016 -0.0034 0.026 0.00658 7.988 2.759 TRADVOL 28 5E+07 1807421 3E+08 6.7E+07 7.114 2.725 NOSHARES 28 1E+09 1366243 6E+09 1 .8E+09 0.934 1.346

1995 VARIABLE VALIDN MEAN MIN MAX STDEV Kurt Skew TOBIN'SQ 30 2.1223 0.22044 5.276 1.309 0.276 0.997 NAFVAR 30 0.0519 -0.4621 0.606 0.249 0.164 0.45 RETIOCAP 30 0.1147 -2.0275 12.35 2.396 25.51 4.845 GROSCAP 30 5E+08 -3E+09 8E+09 2.2E+09 6.082 2.376 FSIZE 30 4E+09 14808 2E+10 6E+09 4.528 2.183 MEANVAL 30 107.57 2.38848 1550 294.407 21.31 4.44 RETVAR 30 -6E-04 -0.007 0.003 0.00188 3.525 -1.23 TRADVOL 30 4E+07 2244492 1E+08 3.2E+07 0.23 1.06 NOS HARES 30 2E+09 2593649 8E+09 2.1E+09 1.882 1.468

1996 VARIABLE VAUDN MEAN MIN MAX STDEV Kurt Skew TOBIN'SQ 30 1.8681 0.26292 5.728 1.122 3.786 1.8 NAFVAR 30 0.2028 -0.3141 1.502 0.437 1.674 1.437 RETIOCAP 30 0.1266 -3.037 11.9 2.373 22.58 4.374 GROSCAP 30 6E+08 -8E+09 9E+09 3E+09 4.123 0.702 FSIZE 30 4E+09 17171 3E+10 7.2E+09 5.465 2.244 MEANVAL 30 116.53 2.2302 1550 304.527 17.89 4.041 RETVAR 30 0.0004 -0.0022 0.003 0.00135 0.232 0.248 TRADVOL 30 4E+07 2718729 1E+08 3.1E+07 -1.061 0.604 NOSHARES 30 2E+09 3265089 1E+10 2.8E+09 0.809 1.304

1997 VARIABLE VAUDN MEAN MIN MAX STDEV Kurt Skew TOBIN'SQ 30 1.051 0.28154 3.068 0.689 1.961 1.559 NAFVAR 30 -0.009 -1.4033 10.48 2.012 27.98 5.2 RETTOCAP 30 0.3244 -3.7592 19.61 3.759 26.11 4.913 GROSCAP 30 -4E+08 -2E+10 1E+10 4.6E+09 7.445 -0.29 FSIZE 30 5E+09 14235 3E+10 2.0375 4.25 2.038 MEANVAL 30 80.576 1.42413 1095 217.06 17.52 4.031 RETVAR 30 -0.004 -0.0102 -4E-05 0.00256 0.058 -0.73 TRADVOL 30 3E+07 1364450 1E+08 3.5E+07 1.207 1.466 NOS HARES 30 3E+09 121.1 1E+10 3.1E+09 0.782 1.28

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24 PHISIX 1994-1997

However, there were decreases in Tobin's q from 1996-1997. For 1996, the mean Tobin's q was 1.8681. Only five firms, namely, DMC, JGS, Megaworld (MEG), PCIB, and PX, had Tobin's q less than 1. (Table 1 ).

The 1997 mean Tobin's q was 1.05 since most companies in the sample had Tobin's q less than 1 for this period. (Table 1 ). It could be possible that the companies' operations have been affected by the Asian financial crisis that transpired in the second half of 1997. Volatile exchange rates, skyrocketing interest rates, the credit crunch, corporate failures, the threat of inflation, weaker demand and slower growth had made the macroeconomic environment chaotic.

However, there were firms that had Tobin's q greater than 1 for this year. Those with Tobin's q greater than 1 were ABS­CBN, Ayala Corporation (AC), Ayala Land, Inc. {All), International Container Terminal Services Inc. (ICTSI), lonics Circuits. Inc. (ION), Jollibee Foods Corporation (JFC), Manila Electric Company (Meralco or MER), San Miguel Corporation (SMC), SM Prime Holdings (SMPH), and Philippine Long Distance Company (PLOT or TEL). These companies have prepared themselves well against the economic turmoil that hit the Asian region in the second half of 1997. These firms had streamlined their production costs, increased market coverage, improved services, managed liquidity and debt exposures, thus providing a buffer on the effects of the currency crisis.

The recurring income derived from rents and cinema has provided both the Ayala group of companies and SM Prime Holdings Inc. (SMPH) a stable source of income, thus softening the impact of the economic turmoil.

While other sectors of the economy roiled from the foreign exchange devaluation, ION and TEL, both foreign exchange earner, benefited from the falling peso, thus having income growths.

In 1994, Nafvar, Grosscap, fsize, meanval, retvar, have negative correlations with Tobin's q. All the rest of the variables were positively correlated. However, the correlations whether positive or negative is less than ±0.60 which means that taken individually, these variables do not affect much Tobin's q. The marked correlation of all these variables are also not significant since p>.0500. (see Table 3)

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~ "' c:

"' Table 3 • s- Correlations 1994 ~ Roo Variable TQ NAF RETC GROS FSIZE MEAN RETV TRAD NOSH ~ Q iQ 1.0000 -0.2241 0.0284 -0.2242 -0.1635 -0.3025 -0.2616 -0.0748 0.2545 • ~ p=- p=.281 p=.893 p=.239 p=.435 p=.142 p=.207 p=.722 p=.220 ~- NAF -0.2241 1.0000 0.1935 0.3733 0.0527 -0.0616 .9783. -0.1784 0.0878

"' p=.281 p=- p=.354 p=.066 p=.802 p=.77 p=.ooo· p=.394 p=.676 • "· RETC 0.0284 0.1935 1.0000 0.1896 0.2486 0.0809 0.1571 .5033. -0.2432 • • ~

p=.893 p=.354 p=- p=.364 p=.231 p=.701 p=.453 p=.010* p=.477 .. GROS -0.2242 0.3733 0.1896 1.0000 0.2072 -0.0531 0.3186 0.2570 0.1491 ~ p=.239 p=.066 p=.364 p=- p=.320 p=.801 p=.121 p=.215 p=.477 • ~ FSIZE 0.1635 0.0527 0.2486 0.2072 1.0000 -0.2187 0.0150 -0.0508 .5216. ~

1f p=.435 p=.802 p=.231 p=.320 p=- p=.294 p=.943 p=.810 p=.007' ~ MEAN -0.3025 -0.0616 0.0809 -0.0531 -0.2187 1.0000 -0.0356 0.0170 -0.3094

p=.142 p=.770 p=.701 p=.801 p=.294 p=- p=.866 p=.933 p=.132 RETV -0.2616 .9783* 0.1571 0.3186 0.0150 -0.0356 1.0000 0.1400 0.0234

p=.207 p=.ooo• p=.453 p=.121 p=.493 p=.866 p=-- p=.505 p=.912 r TRAD 0.0748 -0.1784 -0.5033. 0.2570 -0.0508 0.0178 -0.1400 1.0000 .4540. !!!.

p=.722 p=.394 p=.o1o• p=.215 p=.810 p=.933 p=.505 p=.023· .,

p=- &' NOSH 0.2545 0.0878 -0.2432 0.1491 . 5216* -0.3094 0.0234 .4540 • 1.0000 c:

p=.220 p=.676 p=.242 p=.477 p=.007• p=.132 p=.912 p=.023• " ~ p=- a "' Results generated by Statist lea. Marked correlations are significant at p<=.0500

:>

"' "' .:., "' "' "' "' ...

"' N

'"' "' "' c::

"' Table4 ~ Correlations 1995 ., •• :I: • " (jj " Ro Variable TQ NAF RETC GROS FSIZE MEAN RETV TRAD NOSH x -~ 10 1.0000 -0.1448 -0.1629 0.0602 -0.0541 -0.2202 0.1618 0.2152 0.2116 "' "' Q ... ,

p=- p=.445 p=.390 p=.752 p=.776 p=.242 p=.393 p=.253 p=.262 . Q -~ "' NAF -0.1448 1.0000 -0.0280 .3626* 0.0812 0.0790 -0.0283 0.0035 0.1939 "' a· ...,

"' p=.445 p=-- p=.883 p=.049* p=.670 p=.678 p=.882 p=.985 p=.305 • "- RETC -0.1629 -0.0280 1.0000 -0.0466 -0.0659 0.3091 0.0645 -0.0808 -0.2523 • " p=.390 p=.883 p=- p=.807 p=.729 p=.096 p=.735 p=.671 p=.179

~ GROS 0.0602 .3626* -0.0466 1.0000 0.2476 -0.0704 0.2636 0.2946 -0.0139 r p=.752 p=.049* p=.807 p=- p=.187 p=.712 p=.159 p=.114 p=.942 ~ • FSIZE -0.0541 0.0812 -0.0659 0.2476 1.0000 -0.1820 0.1865 -0.0954 .4362* ~ ~

p=.776 p=.670 p=.729 p=.187 p=.336 p=.324 p=.616 p=.016* ~

p=-MEAN -0.2202 0.0790 0.3091 -0.0704 -0.1820 1.0000 0.0725 0.3241 -0.2667

p=.242 p=.670 p=.096 p=.712 p=.336 p=- p=.704 p=.081 p=.154 RETV 0.1618 -0.0283 0.0645 0.2636 0.1865 0.0725 1.0000 0.2974 -0.1842

p=.393 p=.882 p=.735 p=.159 p=.324 p=.704 p=- p=.110 p=.330 TRAD 0.2152 0.0035 -0.0808 0.2946 -0.0954 0.3241 0.2974 1.0000 -0.0063

p=.253 p=.985 p=.671 p=.114 p=.616 p=.081 p=.110 p=- p=.974 NOSH 0.2116 0.1939 -0.2523 -0.0139 .4362* -0.2667 -0.1842 -0.0063 1.0000

~

p=.262 p=.305 p=.179 p=.942 p=.016* p=.154 p=.330 p=.974 p=-'0 Results generated by Statistica. Marked correlations are significant at p<=.0500 '0

'i' "' "' "' "'

1Z "' c:: "' ~ Table 5 ;;·

Correlations 1996 ~

~ Ro g> Variable TQ NAF RETC GROS FSIZE MEAN RETV TRAD NOSH ~ TQ 1.0000 -0.3525 -0.0801 -0.0882 -0.0948 -0.1987 -0.0284 -0.0554 0.1929 0

p=.056 p=.643 ~ p=- p=.674 p=.618 p=.292 p=.882 p=.771 p=.307 ;;· ~ NAF -0.3525 1.0000 -0.0712 0.0107 0.1199 0.0032 0.0628 0.0252 0.0798

"' p=.056 p=.709 p=.955 p=.528 p=.987 p=.741 p=.895 p=.675 ~ p=-~· ~ RETC -0.0801 -0.0712 1.0000 -0.0523 -0.0842 0.3544 0.2251 0.2519 -0.3399

~ p=.674 p=.709 p=- p=.894 p=.736 p=.055 p=.232 p=.179 p=.066

GROS -0.0882 0.0107 -0.0253 1.0000 0.2212 -0.0596 -0.1464 -0.0219 -0.1059 ~

p=.643 p=.955 p=.894 p=.240 p=.754 p=.440 p=.909 p=.578 ~ p=-~

FSIZE -0.0948 0.1199 -0.0842 0.2212 1.0000 -0.1966 -0.0913 -0.2207 0.2988 ~

~ p=.618 p=.528 p=.736 p=.240 p=- p=.298 p=.631 p=.241 p=.109 MEAN -0.1987 0.0032 0.3544 -0.0596 -0.1966 1.0000 0.0481 .4341* -0.2834

p=.292 p=.987 p=.055 p=.754 p=.298 p=- p=.801 p=.017* p=.129 RETV -0.0284 0.0628 0.2251 -0.1484 -0.0913 0.0481 1.0000 .3685* -0.2596

p=.882 p=.741 p=.232 p=.440 p=.631 p=.801 p=- p=.045* p=.166 r-"' TRAD -0.0554 0.0252 0.2519 -0.0219 -0.2207 .4341* 0.3685 1.0000 -0.1282 iir

p=.771 p=.895 p=.179 p=.909 p=.241 p=.017* p=.045* p=- p=.500 0 ., NOSH 0.1929 0.0798 -0.3399 -0.1059 0.2988 -0.2834 -0.2596 -0.1282 1.0000 c: ..

~ p=.307 p=.675 p=.066 p=.578 p=.109 p=.129 p=.166 p=.500 p=- a "' " "' Results generated by Statistica. Marked correlations are significant at p<=.0500 "' .. "' "' .. "' ...

28 PHISIX 1994-1997

In 1995, nafvar, rettocap, fsize, and meanval have negative correlations with Tobin's q. Similarly, for 1994 results, all the correlations are below ±0.60, thus leaving them with little effect on Tobin's q. We can observed that the marked correlation of all these variables are also not significant since p>.0500. (Table 4)

In 1996, all variable except noshares have negative correlations with Tobin's q. Again, the correlations are less than ±0.60. Like the previous years, the marked correlation of all these variables are also not significant since p>.0500. (Table 5)

In 1997, all variables except nos hare, mean val and retvar have negative correlations with Tobin's q. One variable, retvar has exceeded the benchmark of ±0.60 at .6250. It can be said that this variable influence the Tobin's q by 62%. Like the previous years, the marked correlation of all these variables, except retvar are also not significant since p> .0500. Retvar's marked correlation is significant since p=O.OOO which is below the benchmark p< 0.0500. (Table 6)

Tobin's q and Fsize are negatively correlated in all periods studied and is less than 0.10 in all cases. This means that fsize have very little effect in Tobin's q.

Also, tobin's q and Nafvar are negatively correlated in all periods studied and is less than -0.60 in all cases. Since the correlations are less than -0.60, analysts' following the firm as represented by Nafvar does not have a strong relationship with the market value of the firm as proxied by Tobin's q. Thus, our findings show that there is no significant relationship between security analysts' following and Tobin's q.

One reason why analysts may not affect the market value of stocksis because majority of the securities firms included in the study are foreign-owned. These foreign securities firms have their own fund managers who have already made studies on these index stocks. The forecasts made by analysts based here in the Philippines confirm or give additional information to what these foreign fund managers already know. These locally based analysts provide a more in-depth probe on the index stocks' future earnings.

Chung and Jo (1996) used research, development ratio and advertising ratio to determine the quality of firm. However, because of lack of pertinent data for all the sample companies, these ratios were not used, thus no statistical tool was employed. These companies are assumed of high quality firms in their respective industries since these index stocks have satisfied the

DLSU Business & Economics Review Volume II No. J I 999-2000

~ 13 "' Table 6 • " ;· Correlations 1997 ~ " R-

!;' Variable TQ NAF RETC GROS FSIZE MEAN RETV TRAD NOSH c lQ 1.0000 -0.1223 -0.0050 -0.0872 -0.0495 0.0227 .6250* -0.0018 0.1762 • c

p=.520 p=.979 p=.647 p=.795 p=.905 p=.ooo· p=.993 p=.352 3 p=-n· NAF -0.1223 1.0000 0.0067 -0.0520 -0.0104 -0.0054 -0.0851 -0.1371 -0.0239

"' p=.520 p=.972 p=.785 p=.957 p=.977 p=.655 p=.470 p=.900 • p=-•• • RETC -0.0050 0.0067 1.0000 -0.0016 -0.0727 .3936* -0.0577 .4612* -0.2785 ~

<;' p=.979 p=.972 p=- p=.993 p=.703 p=.031* p=.762 p=.010* p=.136 .. GROS -0.0872 -0.0520 -0.0016 1.0000 -0.2207 0.0285 -0.0606 -0.0273 -0.2113 3 p=.647 p=.785 p=.993 p=-- p=.241 p=.881 p=.750 p=.886 p=.262 • - FSIZE -0.0495 -0.0104 -0.0727 -0.2207 1.0000 -0.2033 0.0243 -02117 0.2269 -"' p=.795 p=.957 p=.703 p=.241 p=- p=.281 p=.899 p=.261 p=.224 c

MEAN 0.0227 -0.0054 .3936* 0.0285 -0.2033 1.0000 0.2500 .6065* -0.2865 p=.905 p=.977 p=.031* p=.881 p=.281 p=- p=.183 p=.ooo· p=.125

RETV 0.625* -0.0851 0.0577 -0.0606 0.0243 0.2500 1.0000 0.0139 0.1829 p=.OOO* p=.655 p=.762 p=.750 p=.899 p=.183 p=- p=.942 p=.333 r

TRAD -0.0018 -0.1371 .4612* -0.0273 -0.2117 .6065* 0.0139 1.0000 -0.0688 !!!. iii

p=.993 p=.470 p=.010* p=.886 p=.261 p=.ooo· p=.942 p=-- p=.718 &' NOSH 0.1762 -0.0239 -0.2785 -0.2113 0.2289 -0.2865 0.1829 -0.0688 1.0000 c:

"' - p=.352 p=.900 p=.136 p=.262 p=.224 p=.125 p=.333 p=.718 p=- a "' " "' Results generaled by Statistica. Marked correlations are signif1cant at p<=.0500 "' .. "' "' .. "' .,

3G PHISIX 1994-1997

criteria to be included in PHIS IX. As such, investors are interested in the future earnings of these firms and monitor their stock price behavior. To help investors in their stock picks, they may rely on the recommendations made by analysts on these issues. Analysts usually monitor the companies in the PHISIX since investors are more familiar with these index stocks. Analysts would have an easier time helping their brokerages in soliciting orders since the investors recognize the stocks. "Assuming that investors trade only those securities that they know about, Merton ( 1987) shows that a firm's market value is positively associated with the fraction of all investors who know about the firm (i.e. the breadth of investor cognizance). To the extent that investors acquire their knowledge through the information provided by financial analysts, the breadth of investor cognizance is likely to be greater for those stocks followed by a larger number of analysts. "(Chung and Jo, 1996)

Through the dissemination and publication of additional information, investors have more basis on what to do with a particular stock, therefore, security analysts have an incentive to follow stocks of high quality.

The firms included in the study are also considered as large firms in their respective industries. "Firm size has often been used as a proxy for the amount of information that is publicly available about a firm. Relative to smaller firms, larger firms are typically more closely watched by the investment community and there is a greater amount of public information available. This implies that market participants can better assess the future performance of larger firms and that there would be smaller bias for larger firms." (Das, Levine, and Sivaramakrishnan, 1998)

For Nafvar, for 1994, four companies (AC, JGS, PL TL, SMC) have variances greater than 1. Particularly for PL TL with 1462%, wherein the consensus forecast was only P26.2 billion as compared to the year's actual earnings of P415.39 billion. Increase in revenues for the year came from interconnecting toll and local services, circuit and trunk rental. (Table 7 shows the summary of Nafvar for each firm for the period 1994-1997)

The mean Nafvar for the year was at 80%, which means analysts have been pessimistic about the performance of the firms and has given some doubts on the firms' capability of achieving its earnings.

In 1995, the highest Nafvar was posted by AC at 60%. However, the mean Nafvar for the period is at 5% which means that the

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Leila Calderon 31

Table 7 Summary of Companies Number of Analysts

Following Variance (NAFVAR) 1994 1995 1996 1997

ABS-CBN 2.29% -4.96% -5.95% -5.90%

AC 201.89% 60.61% 21.52% -12.31%

AEV 13.02% -5.73% -19.03% -50.32%

All 15.26% 14.71% 13.65% ..0.41%

BEL 66.13% -20.72% 45.06% -31.36%

BPC -9.69% -4.57% -8.63% -9.09%.

CMP 9.37% 3.92% -87.54%

CMT -33.78% 38.58% 13.06% -77.22%

DMC -20.64% 11.98% -40.79%

FDC 8.05% 71.02% -50.25%

FLI 3.84% 18.26% 31.37% -34.65%

ICTSI -53.01% -22.55% 2.49% -53.58%

ION -46.21% -27.30% -36.83%

JFC -1.25% -0.12% -15.49% -47.79%

JGS 176.09% 13.36% 98.63% -73.75%

L.ND 0.06% 16.43% -7.21%

MBTC -2.77% 6.38% 10.48% -13.80%

MEG 41.39% 51.22% 108.01% -12.39%

MER 1.78% -13.14% -10.98% -13.90%

MPC 16.80% 37.64% 59.77% -19.40%

PCIB 0.84% 23.88% 1.75% -6.54%

PCOR -4.65% -11.81% -15.68% -115.16%

PLTL 1461.62% 51.35% -31.41% -140.33%

PNB -2.16% -5.18% 85.55% -58.01%

PX -19.08% -31.43% 150.22% 1047.89%

SMC 133.41% -6.02% -10.45% -57.28%

SMPH -0.23% 6.94% 2.08% -9.80%

TEL -1.63% 17.89% 19.29% 19.12%

UBP -12.23% 1.11% 3.34% -9.65%

URC -3.09% -10.47% -16.25% -19.32%

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32 PHISIX 1994-1997

consensus forecast is very close to the actual earnings. It could be interpreted as analysts may have enough information about Firm i to help them predict more accurately the earnings of the firms.

In 1996, Nafvarwas greater than 1 for MEG (1.08) and PX (1.50). The rest of the sample firms had less than 1 for Nafvar. Overall mean NAFVAR for 1996 is 20%, higher than the previous year.

Actual net income for Megaworld (MEG) in 1996 amounted to P2,687.21 billion for a growth rate of 181% from the previous year's net income of P957.6 million. The 1996 consensus accounted only to P1 ,291.86 billion. Net income after tax rose to P2,687.21 billion in 1996 from the previous year's P958 million due to the sale of a portion of its stake in its housing subsidiary, Empire East Land Holdings, Inc. to realize a gain of P697 million. (Megaworld Properties and Holdings, Inc. 1996 Annual Report)

Actual net income for PX in 1995 amounted to P336.04 million, for a growth of 62% from the 19941evel of P207 .37 million. The 1996 consensus forecast amounted to P550.256 billion, which is a 64% growth from the 1995 actual net income. We could assume that analysts followed the trend from the previous net income. However, actual net income for 1996 amounted to P1.38 billion. The increase in income was due to non-recurring gains from the sale of City Trust holdings amounting to P1.35 billion and income from the initial public offering of Philex Gold Inc. (PGI) shares of a total of P900 million. To take advantage of the high extraordinary gains, a provision for write-downs of assets and accrual of expenses amounting to P996.5 million was booked. (Philex Mining 1996 Annual Report)

In 1997, because of the economic slump, all companies have had negative NAFVAR except PX and TEL. It can be noted also that PCOR and PL TL had more than -1 for nafvar (PCOR at-1.1516 and PL TL at -1.4033). Overall, the mean NAFVAR is -0. 92%. Although, the analysts were optimistic with the firms' earnings, the mean prediction error was very low.

Petron Corporation (PCOR) ended 1997 with a net loss of P631 million. This resulted from the company's inability to pass on to the pump price the higher cost of crude and product imports due to the peso depreciation. However, volume-wise, Petron's performance continued to be healthy. It sold 61.4 million barrels of refined products during the year, 5% higher than the 1996 level of 58.7 million. Growth was posted in most product lines, including premium gasoline, diesel, and jet fuel. This boosted the

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Leila Calderon 33

company's market share from 41.4% in 1996 to 42.7 in 1997. (Petron Corporation 1997 Annual Report)

Piltel also suffered a net loss of P621 million at the end of 1997, a reversal from the 1996 net income of P71 0 million. Piltel continued to be haunted by the previous years' subscriber fraud that affected the company's performance. To have a clean slate in operations, operating income stood at a loss of P795 million as one-time charges against revenues were made to cover for doubtful accounts and inventory losses. Due to the cloning problems, the company's subscriber based dwindled from 330,000 in end-1996 to 200,000 in end-97. (All Asia Securities Corporation, July-Dec 1998)

In 1994, Nafvar and retvar have a positive correlation of 0.9783 which is the highest among the variables. (Table 3) This means that changes in stock prices can affect returns. Changes in stock prices may attract more analysts to follow the firm. Hillmer and Yu (1979) suggest that the market react to infonmation in different ways. An information release could change asset returns but leave volatility unchanged, or it could leave mean returns intact yet alter return volatility ( Chen, Lin, Sauer, 1997). The retvar is also significant since p< 0.0500 at p=O.OOO. (Table 3)

Also, for 1994, grosscap, rettocap, fsize, and noshares have positive correlations with Nafvar. This means that increases in any of these variables would lead to an increase in analyst following for firm i. Increases in the variables, grosscap, rettocap, noshares will also result to a larger firm size. And as was discussed earlier, larger firms are followed by more analysts.

In 1995, Nafvar is positively correlated with Groscap, fsize, meanval, tradvol, and noshares. The rest of the variables were negatively correlated. (Table 4)

In 1996, Nafvar is positively correlated to Groscap, fsize, meanval, retvar, tradvol and nosh ares. (Table 5)

In 1997, Nafvar is positively correlated with rettocap. However, the correlation at 0.0067 is very low, thus maybe considered insignificant. Although, all the rest of the variables have had negative correlation, they are still very low and maybe considered insignificant. (Table 6)

In most cases, Nafvar was positively correlated with groscap, fsize, and noshares. However, the correlation was very low, thus maybe considered not significant. Therefore, based on our results: There is no significant relationship between analyst following (Nafvar) with firm size (fsize), trading volume (tradvol),

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34 PHISIX 1994-1997

variability of stock return (retvar) and mean value of share prices (meanval) and number of shares outstanding (noshares).

Table 8 shows the effect of earning announcements on the stock prices using the t-test. There were only eight (8) companies,

Table 8 Summary of Companies Accepting/Rejecting Ho 4

January-March 1994 January-March 1995 ACCEPT HO REJECT HO ACCEPT HO REJECT HO ICTSI ABS-CBN PCI ABS-CBN WCR All MER AC PNB AC MBTC AEV MBTC All PX BEL MPC BPC FU BEL SMC CMT PX JGS

BPC TEL FLI SMC PCI JFC UBP ICTSI SMPH PNB JGS URC JFC UBP TEL MPC MEG URC

April-June 1994 April-June 1995 ACCEPT HO REJECT HO ACCEPT HO REJECT HO WCR ABS-CBN JGS AC PX ABS-CBN JFC MBTC AC MPC ICTSI SMPH ALl MEG PCI All PNB JGS TEL AEV MBTC SMC BEL PX MER UBP BEL MPC

BPC TEL PNB URC BPC PCI FLI UBP GMT SMC ICTSI URC FLI JFC

July-September 1994 July-September 1995 ACCEPT HO REJECT HO ACCEPT HO REJECT HO AC ABS-CBN PCI ABS-CBN MER AEV MBTC ICTSI All PNB AC MPC BEL PLTL JFC BEL PX All PCI BPC SMC JGS BPC SMC FLI PCOR CMP SMPH MEG FLI TEL ICTSI PNB GMT TEL MPC MER UBP JFC PX ION URC SMPH MBTC MEG UBP JGS URC

October-December 1994 October-December 1995 ACCEPT HO REJECT HO ACCEPT HO REJECT HO AC ABS-CBN MBTC AC JGS ABS-CBN MBTC All BEL PNB All MEG AEV MPC AEV BPC PX BEL MER BPC PCI GMT FLI SMPH CMT PLTL DMC PCOR ICTSI JFC TEL CMP PNB LND PX MPC JGS UBP FDC SMC JFC UBP PCI MEG URC FLI SMPH SMC WCR ION TEL

ICTSI URC

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January-March 1996 January-March 1997

ACCEPT HO REJECT HO ACCEPT HO REJECT HO ABS-CBN MPC AEV BPC MBTC ABS-CBN AC PCI BPC CMP r.I'C AC All PCOR CMP CMT PX All BEL PLTL CMT DMC SMPH AEV DMC PNB FDC LND URC BEL FLI PX ICTSI FDC LND SMPH FLI ION TEL ION JFC UBP ICTSI

JFC

April-June 1996 April-June 1997

ACCEPT HO REJECT HO ACCEPT HO REJECT HO AEV MER ABS-CBN ABS-CBN LND ALl ION BPC MBTC AC AC MEG BEL ICTSI FDC PLTL All AEV r.I'C CWP JFC FLI SMPH BEL BPC PLTL FDC JGS ION U8P CMP CMT PX JFC URC CMT DMC SMC

DMC FLI TEL LND ICTSI

July-September 1997

July-September 1996 ACCEPT HO REJECT HO ABS-CBN ICTSI CMP

ACCEPT HO REJECT HO AC JFC ION AC JFC ABS-CBN ALl MER JGS AEV MEG All AEV MBTC MEG BEL PCI 8PC BEL MPC PLTL CMT PLTL CMP BPC PCI PNB DMC PNB FDC CMT PCOR SMC FLI SMC LND DMC PX UBP ION SMPH ICTSI FDC SMPH

UBP FLI TEL LND URC

OctoberpDecember 1996 October·December 1997

ACCEPT HO REJECT HO ABS-CBN JFC AC ACCEPT HO REJECT HO BEL MEG All JFC ABS-CBN FLI 8PC MER AEV DMC PCI CMP MER AC LND FDC PCOR CMT All ION FLI SMPH ION AEV ICTSI LND TEL ICTSI BEL JGS

UBC 8PC MEG DMC

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36 PHISIX 1994-1997

namely: AC, CMT, DMC,FLI, LND, MER, PCIB, and SMPH that accepted the null hypothesis for most of the quarters. The rest rejected the null hypothesis. However, we observed that on a per quarter basis, companies may either reject or accept the null hypothesis. A company may accept or reject the null hypothesis depending on the economic situation for the quarter.

It can be noted that the quarter of July-September 1997 brought many companies' earnings down due to the economic plague in the Asian region. As such, investors have already discounted the possibility of lower than anticipated earnings, thus hardly affecting the stock prices when earnings were released for the quarter. Since majority of the index stocks were affected by the Asian economic crisis, the release of the fourth quarter earnings had telling signs on the index stock prices. Thus, the Phisix experienced several lows as compared with the previous year's because investors may have taken the wait and see attitude or have become more cautious. Based on the findings, we can conclude that earnings announcements of index stocks do affect stock prices.

CONCLUSIONS Based on the correlation test conducted, we found out that

there is no significant relationship between security analysts' following and market value (as proxied by Tobin's q). Also, we found out that there is no significant relationship between analyst following (Nafvar) with firm size (fsize), trading volume (tradvol), variability of stock return (retvar) and mean value of share prices (meanval) and number of shares outstanding (noshares).

Since, there was no test conducted to validate the quality of firms, we assumed that they are quality firms after satisfying the criteria set by PSE to be included in the PHISIX. We conclude that if more analysts follow a particular stock, the breadth of investor cognizance expands making it easier for the brokerage to market such stock.

We conclude that earnings announcements do affect stock prices. However, we observed that there were quarters when the null hypothesis was accepted, that is earnings announcement do not affect stock prices. For the quarter October-December 1997, only two (2) companies, JFC and MER accepted the null hypothesis.

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Leila Calderon 37

RECOMMENDATIONS The researcher recommend that further investigation could

be done on the same topic but concentrating on particular industries. Using industries as sample would determine whether or not the same conclusions would be arrived at. Also, longer time period and additional variables are suggested to have better results in the correlation.

A survey could also be conducted on analysts on why they follow or concentrate on other stocks, aside from the index stocks. They can also be asked on their perceptions or characteristics of a high quality firm.

Also, investors maybe surveyed on how they view analysts' recommendations. It would be worthwhile to find out how many of these investors followed analyst's recommendations and what was the investors' rate of return on this investment decision.

BIBLIOGRAPHY

Books: Emory, William and Cooper, Donald. Business Research

Methods. Richard D. Irwin, Inc. Philippine Copyright 1993. Farrell, James, Jr. Portfolio Management: Theory and Application.

Second Edition. McGraw-Hill Book Co-Singapore, 1997. Grinold, Richard and Kahn, Ronald. Active Portfolio Management.

Irwin Professional Publishing. 1995. Lofthouse, Stephen. Equity Investment Management. John Wiley

& Sons, 1994. Mason, Robert, Lind, Douglas, and Marchal, William. Statistics:

An Introduction. Harcounrt Brace Jovanovich, Inc. 1988. Schwert G. William and Smith, Clifford, Jr. Empirical Research

in Capital Markets. Mc-Graw Hill International Editions. 1992.

Journal Articles: Chen, Carl, Lin, James Wuh, and Sauer, David. "Earnings

Announcements, Quality and Quantity of Information, and Stock Price Changes." The Journal of Financial Research. Vol. XX, No.4. Pages 483-502, Winter 1997.

Chung, Kee and Jo, Hoje. "The Impact of Security Analysts' Monitoring and Marketing Functions on the Market Value of Firms." Journal of Financial and Quantitative Analysis. Vol. 31, No.4 December 1996, pp. 493-511.

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38 PHISIX 1994-1997

Das, Somnath, Levine Carolyn, and Sivaramakrishnan, K. "Earnings Predictability and Analysts' Earnings Forecasts." The Accounting Review. Vol. 71, No.2 April 1998. pp. 277-294.

Hall, Brownwyn. "The Stock Market's Valuation of R&D Investment During the 1.980s." AEA Papers and Proceedings. May 1993, Vol. 83, No. 2 pp 259-264.

Lo, May and Elgers, Pieter. "Alternative Adjustments to Analysts' Earnings Forecasts: Relative and Complementary Performance." The Financial Review. 33 (1998) pp. 99-114.

Morek, Randall, Shleifer, Andrei and Vishny, W. "Management Ownership and Market Valuation." Journal of Financial Economics. 20 (1988) pp. 293-315.

Servaes, Henri. "Tobin's Q and The Gains from Takeovers." The Journal of Finance. Vol. LXVI No. 1, March 1991, pp. 409-419

Thesis: Aguirre, Joseph Jasper & Valdes, Dennis. "A Study on the

Informational Effect of the Earnings Announcement to Stock Prices of the Selected Real Estate Sector Firms for the Period Covering the 1 ''quarter of 1996 to the 2nd Quarter of 1998." November 1998.

Audited Annual Reports ABS-CBN Broadcasting Corporation Aboitiz Equity Ventures Ayala Corporation Ayala Land Inc. Belle Corporation Ben pres Holding Corporation C & P Homes DMCI Holdings, Inc. Filinvest Development Corporation Filinvest Land Inc. Fit-Estate Land, Inc. tonics Circuits, Inc. International Container Terminal Services, Inc. JG Summit Jollibee Food Corporation Manila Electric Company

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Leila Calderon 39

Megaworld Properties & Holdings, Inc. Metropolitan Bank and Trust Corporation Metro Pacific Corporation Petron Corporation Philippine Commercial and International Bank Philippine National Bank Philippine Long Distance Telephone Company Philex Mining Corporation Pilipino Telephone Company San Miguel Corporation SM Prime Holdings, Inc. South East Asian Cement Corporation Union Bank of the Philippines Universal Robina Corporation

Investment Strategies Reports: All-Asia Securities Corporation Asia Equities Phils. Asian Capital Equities BPI Securities BZW Research HGAsia lNG Barings Kerry Securities Orion Squire Capital, Inc. SBC Warburg Sun Hung Kai Securities Vickers Ballas

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40 PHISIX 1994-1997

APPENDIX1

1996 PHILIPPINE COMPOSITE STOCK INDEX

1. ABS-CBN Broadcasting Corporation 2. Aboitiz Equity Ventures 3. Ayala Corporation 4. Ayala Land Inc. 5. Belle Corporation 6. Benpres Holding Corporation 7. C & P Homes 8. DMCI Holdings, Inc. 9. Filinvest Development Corporation

10. Filinvest Land Inc. 11. Fii-Estate Land, Inc. 12. lonics Circuits, Inc. 13. International Container Terminal Services, Inc. 14. JG Summit 15. Jollibee Food Corporation 16. Manila Electric Company 17. Megaworld Properties & Holdings, Inc. 18. Metropolitan Bank and Trust Corporation 19. Metro Pacific Corporation 20. Petron Corporation 21. Philippine Commercial and International Bank 22. Philippine National Bank 23. Philippine Long Distance Telephone Company 24. Philex Mining Corporation 25. Pilipino Telephone Company 26. San Miguel Corporation 27. SM Prime Holdings, Inc. 28. South East Asian Cement Corporation 29. Union Bank of the Philippines 30. Universal Robina Corporation

Source: Philippine Stock Exchange

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leila Calderon 41

APPENDIX2 MASTER WORKSHEET FOR COMPUTING TOBIN'S Q

Name of Company Stock Symbol Years Covered

Year (Consolidated) 94 ( 1) PREFST (based on balance sheet figures) (2) VCOMS•(price of common stock 'no. of shares 0

outstanding at the close of the year} (3) LT Debt•(based on balance sheet figures) ( 4) ST Debt= current liabilities (5) ADJ= book value of net short-term assets=

proxy cash and cash equivalents or marketable securities, if available (marketable equity securities)

(6) Market Value = [(1)+(2)+(3)+(4)]-(5) (7) Total Assets•balance sheet figure (8) Capital stock (9) Capital paid in excess of par value (1 0) Cumulative translation adjustment (11) Retained earnings appropriated

(reported as Retained Earnings) (12) Treasury Stock (13) BKCAP=book-value of net capital stock=

(8)+(9)+( 1 0)-( 11 )-( 12) (14) Netcap • (13) • (1+inflation rate for the year) (15) Replacement Costs • (7)-(13)+(14) (16) Tobin's Q = (6~ (15) (17) Sales ( 1 8) Research and Development (19) Advertising Expense or selling and promotions (20) R&D Ratio= (18~ (17) (21) Adv Exp. = (19~ (17) (22} Net income before extraordinary items (23) Depreciation (24) lnteresllncome (25) Inventory valuation adjustment=

based on balance sheet figures (26) Cash and cash equivalents

(or marketable securities if available} (27) Gross cash flow =[(22)+(23)+(24)]-[(25)+(26)] (28) Gross capital adjusted for inflation =

(8)+(9)+(10)-(12) • inflation rate for the year (29) Rate of return to capital of firrn=(27Y(28) (30) Firm Size = book value of total assets

(Total Assets-(Total Liabilities+ Preferred Stocks) Variance of returns

(31) Mean Value of daily closing price for the year (32} Average Variance of returns for the year (33) Trading volume=mean value of daily peso

volume for the year (34) No. of shares outstanding for year ended (35) Inflation rate• 9% (36) Closing prices

*Source: Bangko Sentral ng Pilipinas

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95 96 97

0 0 0

8.10% 8.40% 5.10%

1999-2000

Appendix 3 Consensus of Analysts' Forecasts and Actual Results with Variance

1994C 1994A Variance 1995C 1995A Variance 1996C 1996A Variance 1997C 1997A Variance ~ ...

N

"' ABS-CBN 914.15 935.11 2.29% 1,315.76 1,250.53 -4.96% 1,626.85 1,530.11 ·5.95% 1,853.36 1,743.93 ·5.90% <::

"' AC 1,720.86 5,195.18 201.89% 3,413.90 5,483.05 60.61% 5,125.71 6,229.00 21.52% 7,284.60 6,388.00 -12.31% • AEV 430.90 487.00 13.02% 1,142.51 1,077.00 -5.73% 1,340.04 1,085.00 -19.03% 1,543.82 767.00 -50.32% - ..., •• • All 1,877.17 2,163.65 15.26% 2,709.44 3,108.11 14.71% 3,528.59 4,010.40 13.65% 4,223.00 4,205.86 -0.41% :I: ~ BEL 318.10 528.47 66.13% 750.59 595.06 -20.72% 755.07 1,095.30 45.06% 1,760.38 1,208.32 -31.36% iii Ro BPC 1,294.43 1,169.00 -9.69% 1,693.44 1,616.00 -4.57% 2,206.44 2,015.98 -8.63% 2,529.86 2,300.00 -9.09% x

~

1:' CMP 1,838.73 2,010.94 9.37% 2,599.29 2,701.25 3.92% 3,503.77 436.48 -87.54% "' "' • CMT 118.90 78.73 -33.78% 254.73 353.00 38.58% 900.28 1,017.90 13.06% 336.30 -77.22% ! , 1,476.05 • 3 DMC 494.00 392.05 ·20.64% 937.66 1,050.00 11.98% 1,187.30 703.05 -40.79% "' fi' "' FDC 479.67 841.30 909.00 8.05% 2,358.52 4,033.42 71.02% 5,061.40 2,518.16 -50.25% .... "' FLI 597.62 620.58 3.84% 854.03 1,010.00 18.26% 1,539.43 2,022.27 31.37% 2,300.00 1,502.95 -34.65% ~ ICTS 404.00 189.85 -53.01% 414.46 321.00 -22.55% 463.44 475.00 2.49% 638.57 296.43 -53.58% ;;;· • ION 108.50 528.00 284.00 -46.21% 537.93 391.10 -27.30% 832.67 526.00 -36.83%

~ JFC 408.90 403.81 -1.25% 537.64 537.00 -0.12% 712.33 602.00 -15.49% 846.06 441.76 -47.79% .. JGS 2,173.44 6,000.75 176.09% 2,543.32 2,883.00 13.36% 3,198.54 6,353.17 98.63% 3,702.50 971.77 -73.75%

3 LND 54.00 783.50 784.00 0.06% 1,557.20 1,813.10 16.43% 2,244.54 2,082.71 -7.21% • MBTC 2,592.85 2,521.14 ·2.77% 3,291.66 3,501.65 6.38% 4,528.36 5,002.74 10.48% 6,D91.16 5,250.70 -13.80% ~ ~ MEG 294.15 415.90 41.39% 633.24 957.56 51.22% 1,291.86 2,687.21 108.01% 2,140.94 1,875.73 -12.39% ~ MER 3,558.88 3,622.40 1.78% 5,078.39 4,411.00 -13.14% 5,687.96 5,063.65 -10.98% 6,695.48 5,765.10 -13.90% ~ MPC 197.70 230.92 16.80% 372.94 513.33 37.64% 528.19 843.86 59.77% 884.17 712.84 -19.40%

PCIB 1,546.00 1,559.00 0.84% 2,078.67 2,575.00 23.88% 2,943.62 2,995.00 1.75% 3,882.86 3,629.00 ·6.54% PCOR 3,918.90 3,736.65 -4.65% 4,558.58 4,020.00 -11.81% 5,025.81 4,238.00 -15.68% 4,162.59 (631.00) -115.16% PLTL 26.60 415.39 1461.62% 543.16 822.08 51.35% 1,035.18 710.00 -31.41% 1,539.54 (620.83) -140.33% PNB 2,027.90 1,984.07 ·2.16% 2,195.46 2,081.78 -5.18% 2,518.76 4,673.65 85.55% 2,716.58 1,140.80 -58.01% PX 256.28 207.37 ·19.08% 490.04 336.04 -31.43% 550.26 1,376.83 150.22% 574.86 6,598.73 1047.89% SMC 5,081.48 11,860.80 133.41% 6,208.56 5,835.00 -6.02% 6,799.43 6,089.00 -10.45% 6,916.33 2,955.00 -57.28% SMPH 1,016.50 1,014.12 -0.23% 1,411.70 1,509.65 6.94% 1,874.65 1,913.58 2.08% 2,508.07 2,262.24 ·9.80% TEL 4,921.47 4,841.30 ·1.63% 4,878.30 5,751.10 17.89% 5,398.91 6,440.40 19.29% 6,421.30 7,649.10 19.12%

~ UBP 672.45 590.21 -12.23% 720.61 728.58 1.11% 930.93 982.05 3.34% 1,328.31 1,200.11 -9.65% "' "' URC 1,187.95 1,151.21 -3.09% 1,383.61 1,238.75 -10.47% 1,535.98 1,286.32 -16.25% 1,614.30 1,302.46 -19.32% "' ' "' "' Legend: C- consensus "' "' A- actual

V- variance

Leila Calderon 43

APPENDIX4 ACTUAL ANNUAL NET INCOME {PMN)

ACTUAL NET INCOME {Pmn)

1994 1995 1996 1997 ABS-CBN 935 1251 1530 1744 AC 5195 5483 6229 6388 AEV 487 1077 1085 767 ALl 2164 3108 4010 4206 BEL 528 595 1095 1208 BPC 1169 1616 2016 2300 CMP 2011 2618 2301 CMT 79 353 1018 DMC 392 1050 703 •1995-10mos. operations FDC 480 909 4033 2518 FLI 621 1010 2022 1503 ICTS 190 321 475 296 ION 109 264 391 526 JFC 404 537 602 442 JGS 6001 2883 6353 972 LND 54 784 1813 2083 MBTC 2521 3502 5003 5251 MEG 416 958 2687 1876 MER 3622 4411 5064 5765 MPC 231 513 844 713 PCIB 1559 2575 2995 3629 PCOR 3737 4020 4238 -631 PLTL 415 822 710 PNB 1984 2082 4674 1141 PX 207 336 1377 6599 SMC 11861 5835 6089 2955 SMPH 1014 1510 1914 2262 1994-11 mos operations

TEL 4841 5751 6440 7649 UBP 590 729 962 1200 URC 1151 1239 1286 1302

Source: Annual Reports of each company

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