Performance of Malaysian IPOs: Underwriters reputation and management earnings forecasts

Pacific-Basin Finance Journal 9 Ž2001. 457–486 www.elsevier.comrlocatereconbase

Performance of Malaysian IPOs: Underwriters reputation and management earnings forecasts Ranko Jelic a,) , Brahim Saadouni b, Richard Briston c a

Department of Accounting and Finance, Birmingham Business School, UniÕersity of Birmingham, Birmingham, B15 2TT, UK b UMIST, Manchester, UK c UniÕersity of Hull, Hull, UK Received 11 September 2000; accepted 15 March 2001

Abstract This paper examines the financial performance of Malaysian initial public offerings ŽIPOs. during the period 1980–1995. The major focus of the study is on the role of management earnings forecasts and underwriters in the valuation of IPOs. The results suggest extremely high and statistically significant initial premiums and positive and statistically significant long-term returns up to 3 years after listing. The findings for long-term returns contradict the consensus of the IPO literature that documents a significant negative long-term performance. Our results indicate a negative association of upward bias in management earnings forecasts with IPOs’ performance during the first 12 months after the IPOs. q 2001 Elsevier Science B.V. All rights reserved. JEL classification: G14; G24; G32 Keywords: Initial public offerings; Financial performance; Underwriters; Management earnings forecasts

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Corresponding author. Tel.: q44-121-414-5990; fax: q44-121-414-6238. E-mail address: [email protected]. ŽR. Jelic..

0927-538Xr01r$ - see front matter q 2001 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 7 - 5 3 8 X Ž 0 1 . 0 0 0 1 3 - 0

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1. Introduction The extensive literature on the short-run performance of new issues reveals short-term excess returns internationally ŽRitter, 1991.. Countries with the lowest underpricing tend to be those in which most of the firms going public are relatively large firms with long operating histories and where the contractual mechanism used has auction-like features ŽLoughran et al., 1994.. The empirical evidence on the long-run performance of IPOs, using data from countries other than South East Asian countries, seems to suggest that positive initial returns are in general followed by underperformance in the long run. It is worth noting that the evidence on South East Asia is not conclusive. Kim et al. Ž1995. find positive long-run returns for Korean IPOs, most of which come from the early weeks. Dawson Ž1987. reports negative long-run performance for IPOs in Hong Kong and Singapore but positive for Malaysia Ž18.2%.. Cai and Wei Ž1997. report a significant aftermarket underperformance of their sample of 180 Japanese IPOs over the period 1971–1992. The worst underperformance was found for IPOs with the highest level of underpricing. Wu Ž1993. examines both short- and long-run performance for 70 Malaysian IPOs in the period between 1974 and 1989. Adjusted buy-and-hold 1-, 2-, and 3-year period returns are positive, but only significant in year 1 at 10% level. Sufar Ž1993. examines the performance of a sample of 43 new issues made over the 1980–1986 period. The results show underpricing on the first day of trading Ž140.5%. and positive after-market performance 12 months following official listing Ž10.9%.. Mohamad et al. Ž1994. examine the initial and the long-term performance of 65 IPOs from the Kuala Lumpur Stock Exchange ŽKLSE. during 1975–1990 ŽKuala Lumpur Stock Exchange, 1996.. Their findings show an initial underpricing of 135% and significant positive cumulative abnormal returns after 2 and 3 years. It is worth noting that in the case of Dawson and Sufar, the KLSE Industrial Indices are used as proxies for market returns. These indices may not adequately reflect total market movements. In addition, the findings of these papers are based on relatively small sample sizes. Holding period returns reported by Wu and Sufar do not measure the total compounded returns from a buy and hold strategy where a stock is purchased at the first closing market price after going public and held until its first, second, and third anniversary. Instead, only capital gains based on the first market price after going public and the market price on the stock’s first, second, and third anniversaries are calculated. This study contributes to the existing literature by providing additional evidence on financial performance of Malaysian IPOs. We have extended both the period and sample size used in previous studies on Malaysia. This is particularly important for the evidence on long-run performance involving firms with overlapping observations so that the number of independent observations is limited ŽIbbotson and Ritter, 1995.. Furthermore, we analyse the role of management earnings forecasts and underwriters in the market valuation of companies seeking

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listing at the KLSE. Our analysis of the role of various players and related institutional arrangements on the primary market may provide some insights to policy makers involved in the current reforms of Malaysian financial markets.1 In a wider context, the justification for this study stems from the fact that there is a paucity of research on the effect of the management earnings forecasts on the returns on IPOs. The mandatory requirement in Malaysia for IPOs to furnish management earnings forecasts in their prospectuses provides a rare test case for an ongoing debate on the usefulness of the forecasts in the market valuation of IPOs. The paper is organised as follows. In the next section we discuss institutional aspects of the Malaysian primary market. The sample selection process, data sources, descriptive statistics, and the methodology used to measure short and long-term financial performance are discussed in Section 3. In Sections 4 and 5, we develop empirical models to investigate the determinants of the short and long-term financial performance of IPOs. The results of the analysis are discussed in Section 6. The final section presents the conclusions and policy implications.

2. Institutional aspects of the Malaysian market for IPOs The IPOs market in Malaysia differs from other markets in many different ways. One of its most important features is that it represents an instrument of the New Economic Policy that was introduced by the Malaysian government in 1970.2 The primary objective then was to increase Malays ŽBumiputera. participation and ownership in the corporate sector from 4% in 1970 to 30% by the end of 1990. To achieve this objective, as of 1976 it was mandatory requirement for any company seeking listing on the KLSE to allocate 30% of the total issued shares to Malays,3 either direct or via Bumiputera institutions Žinstitutions catering for Malays only. such as unit trusts launched by the National Equity Corporation ŽPermodan Nasional Berhard.. An analysis of the allocation of shares shows that a higher proportion of shares on offer Žan average of 70%. are usually allocated to small investors, while investors applying for 11,000 shares or more are often allocated no more than 5% of the total issued shares. 1

The Malaysian Government responded to the financial crisis in the region by launching the National Economic Recovery Plan ŽNERP. in 1998. Two of the main components of the programme are restructuring in banking sector and changes in the primary market. For more on NERP, see The 1999 Guide to Malaysia, Euromoney, September 1999. 2 The policy was introduced following the race riots in 1969 and was intended to reduce inter-ethnic tensions and create conditions for National Unity. 3 The rule was changed in 1998: ‘Kuala Lumpur Removes Race-Based Equity Quotas’ ŽFinancial Times, 1998..

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Due to the sensitivity of the question of an equitable redistribution of the national wealth in a multi-ethnic country such as Malaysia, it is not surprising that IPOs are strictly regulated and monitored by the government. The approval process is lengthy, and can last up to a year. New public issues, offers for sale and a combination of the two are three recognised methods for IPOs in Malaysia. An application is submitted for approval to the Ministry of International Trade and Industry ŽMITI. and the Foreign Investment Committee ŽFIC. only after a firm and its underwriter have agreed on the price of the issue. Once MITI and FIC have approved the application, the application is submitted for examination and approval to the Securities Commission ŽSC.. The SC then evaluates the company, and particularly examines forecast profits and dividends. Furthermore, the prospective PrE ratio agreed between the firm and its underwriter must fall within a certain boundary set out by the SC.4 This limits the market’s role in the determination of the subscription price, and emphasises the role of accounting values in initial pricing. Subsequent to the approval of the SC and before the conclusion of the underwriting agreement and the announcement of the offer price, the board of directors and its lead underwriter are required to submit to the Main Board and the SC a detailed prospectus. The requirements for the prospectuses are numerous and are in a number of ways different from those in other markets. For example, the prospectuses must include details of the last 5 years’ profit performance, financial position and liquidity, the forecast of next year’s gross earnings per share and gross dividends per share excluding any extraordinary items and the key assumptions on the basis of which the forecast is derived. The profit forecasts are not only mandatory but must also be verified by both the reporting accountants and the advisers.5 The SC recommends that future profits should reflect an increasing trend. Although the earnings forecasts are made for the current financial year, where the end of the financial year is within 3 months from the date of

4 Malaysia, Korea, and Japan are rare countries with binding governmental constraints on the choice of the offer price. Korea and Japan, more recently, relaxed regulation and allowed investors to be more involved in the setting of the offer price. Malaysia moved in a similar direction only in 1995 with effect from January 1996. 5 The term ‘ verify’ in the Malaysian context is related to a proforma balance sheet and profit and loss account of the company after completion of the proposal, and the correctness andror truthfulness of the assumptions, calculations and accounting policies adopted by management in the preparation of their forecasts. The accountantsrauditors also need to confirm that the forecasts and projections have been presented on a basis consistent with the accounting policies normally adopted by the company. The meaning of the terms ‘certified’ ŽUK, Australia., ‘audited’ ŽCanada. and ‘audit-level assurance’ ŽUS. corresponds to the term ‘ verified’ used by Malaysian authorities with regard to management earnings forecasts. For more on the nature of accountants’ involvement in disclosed management forecasts in various countries see McConomy Ž1998..

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submission, the forecasts must be made for the current and the next immediate financial year.6 While an application is being processed the firm must not release any documentation to potential investors. The only method of underwriting in Malaysia is the Firm Commitment. Book building is not allowed and there are no pre-market surveys by which the underwriter can test the market or fine-tune the offer price. The offer price and the number of shares to be issued must be clearly stated in the prospectus and they cannot be changed during the issue process. Since the time between the submission of the prospectus and the issue can be a couple of months, the risk of mispricing the new issue is thus considerable.

3. Data and methodology 3.1. Data The sample comprises 182 IPOs on the KLSE Main Board over the period January 1980 to December 1995. The sample represents the whole population of IPOs in the KLSE Main Board during the same period of time.7 None of the IPOs or the matching firms was de-listed due to bankruptcy or take-over during this period. The sample is extracted from the databases of the KLSE, the Arab–Malaysian Securities Research department, and Investors Digest. Data for the proportion of shares sold and retained, total assets, underwriters, profit forecasts, the offer price, the closing date, number of purposes mentioned, age of companies, and gross proceeds were collected from the prospectuses. The demand multiples were taken from Malaysian Industrial Development Finance Consultancy and Corporate Services press releases, and the New Straits Times and Star newspapers. Data for share pricesrreturns, KLSE Composite Index, actual profits for the financial year-end following official listing, market values, net and total assets, and industry classification were extracted from PACAP database, and various issues of the KLSE Annual Companies Handbook.8 Descriptive statistics for the main variables are reported in Table 1. The gross proceeds raised by the sample varied substantially. The highest amount is raised by the privatisation of Telecom Malaysia ŽRM 3185 million. while the lowest amount is raised by the Malaysian Corporation ŽRM 2 million.. The sector with the highest average proceeds is industrial and production and the one with the lowest is construction. The biggest company measured by market values is Tenaga 6 From January 1996 the minimum forecast horizon is 6 months; Malaysian Security Commission, 1995. 7 The total number of listings during the period is extracted from the KLSE Annual Companies Handbook, 1996, vol. 21, book 3, p. 598. 8 Data for pricesrreturns for 1996 and 1997 are from the Datastream.

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Table 1 Descriptive statistics for Malaysian IPOs, 1980–1995 Total assets represent end of listing year total assets in million Malaysian Ringits ŽRM. and US$ Žin parentheses.; Market value is the end of listing year market capitalisation in million RM and US$ Žin parentheses.; Gross proceeds is proceeds raised by the issue in million RM and US$ Žin brackets.; Conversion at December 1990 exchange rate, 1 US$s 2.6983 RM; Number of purposes mentioned in IPO prospectuses; Age is length of operating history Žyears.; Retained ownership is the percentage of new shares retained by owners; Market performance is the percentage change in the KLSE index during the 3 months prior to listing; Time to listing is number of days from the date on prospectus to the listing date; Excess demand multiple is measured by times over-subscription; Forecast error ŽFE s wŽActual ProfityForecast Profit.r
Total assets Market value Number of purposes Age Retained ownership Gross proceeds Market performance Time to listing Forecast error Demand multiple

Mean

Median

Std. dev.

Min

Max

N

721.55 Ž267.41. 692.74 Ž256.73. 3.19 19.57 75.10 94.00 Ž34.84. 2.00 32 24.38 27.67

163.20 Ž60.48. 183.53 Ž68.02. 3.00 16.00 77.00 26.00 Ž9.64. 2.00 30 1.61 21.59

1829.81 Ž678.13. 2706.39 Ž1003.00. 0.77 15.24 12.69 336.00 Ž124.73. 13.00 9 324.78 25.75

12.22 Ž4.53. 5.15 Ž1.91. 1.00 3.00 1.00 2.00 Ž0.74. y46.00 10 y136.17 0.34

14,855.10 1Ž5505.36. 29,850.00 Ž11062.52. 6.00 84.00 98.52 3185.00 Ž1180.37. 51.00 79 4110.53 146.2

182 182 172 182 182 182 182 182 162 150

Nasional, a company responsible for generation, transmission and distribution of electricity. On average, the sample companies gave three different purposes for going public. The maximum and the minimum number of purposes are six and one, respectively. The need to finance new projects and expansion are the most commonly stated motives Ž56% of the companies.. In 54% of the cases in which the reasons are given, the IPO is presented as an attempt to enable the public to participate in the equity of the company. Incentives to employees are mentioned in 48% of the cases.9 The average IPO in the sample is oversubscribed by 27.65 times, with a standard deviation of 25.75. The maximum over-subscription is 146.2, and the minimum is 0.34. The average proportion of shares retained by management for

9 New projects and expansions are the most commonly mentioned reasons in other countries Žsee Pagano et al., 1996.. Other motives mentioned by Malaysian companies are: change in ownership Ž18%., listing a subsidiary Ž12%., greater bargaining power with the banks Ž9%., and the need to change from family business to a larger company Ž7%.. The less frequently mentioned reasons are: mergers and take-overs Žtwo cases., improvement in corporate image Žone case., increase in the liquidity of the stock Žsix cases., and compliance with the government’s policy on corporatisation in the financial securities industry Žnine cases..

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the whole sample is about 75% Žstandard deviation 12.69%. with the highest and lowest proportions being 98.5% and 1%, respectively.10 On average, companies with the highest proportion of retained ownership are from the hotel industry, and those with the lowest proportion are from the financial sector. The average proportion of shares allocated to Bumiputera investors is 44.45%. The mean and median management earnings forecast errors are 24.38% and 1.61%, respectively.11 The sample has an average operating history of about 20 years, with maximum and minimum values of 84 and 3 years, respectively,12 suggesting that in Malaysia, firms that go public have a long operating history. This is a result of strict listing requirements, and is similar to other countries in the region. For example, Kim et al. Ž1995. report a mean value of 19.63 years for the age of Korean IPOs. Firth Ž1997. reported 12 years average age for Singaporean IPOs. This is a much longer operating history from the average operating history of 6.46 years reported for US IPOs ŽRitter, 1991.. 3.2. Methodology We measure both the raw and market-adjusted initial returns using the conventional method where the initial return on the first day of trading is calculated as follows: MAIR i ,t s Ž Pi ,1 y Pi ,0 . rPi ,0 y Ž Ii ,1 y Ii ,0 . rIi ,0

Ž 1.

where MAIR i,t is the market index adjusted return of company ‘i’; Pi,1 is the closing price of company ‘i’ at the end of the first trading date; Pi,0 is the offer price of company ‘i’ Žtime index 0 refers to the last day of the subscription period.; Ii,1 is the KLSE Composite Index at the end of the first trading day and Ii,0 is the KLSE Composite Index on the last day of the subscription period of company ‘i’. The average time between the closing of applications and the first day of trading is about 32 days. Barber and Lyon Ž1997., Lyon et al. Ž1999., and Kothari and Warner Ž1997. document three main potential biases in the calculation of long-term returns: Ža. survivor bias, which may occur if failing firms are excluded from the sample, Žb. rebalancing bias, related to the calculation of cumulative returns, and Žc. skewness 10

Two outliers are Arab Malaysian First Property Trust, which offered for sale virtually all shares, and MBF Capital, which offered only about 1% of shares. 11 Forecast error ŽFE. s wŽActual ProfityForecast Profit.r
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bias due to the fact that long-term returns are typically skewed. In order to minimise these potential misspecifications, we evaluated long-term buy-and-hold market-adjusted compounded returns, cumulative abnormal returns, and wealth relatives for all IPOs in our sample. In addition, we calculated a skewness-adjusted t-statistic with bootstrapped p-values for 1-, 2- and 3-year buy-and-hold returns ŽLyon et al., 1999.. The benchmarks used are the value-weighted KLSE Composite Index and a portfolio of matching firms adjusted for industry and market values. The market adjusted Žabnormal. returns are calculated for each event month ‘t’ as ari ,t s ri ,t y rm ,t

Ž 2.

where ri,t is the return of company ‘i’ in event month ‘t’; rm,t is the return on the market index in event month ‘t’ and ari,t is the abnormal return for company ‘i’ in event month ‘t’. Each month consists of 21 trading days.13 The average marketadjusted return for a sample of ‘n’ companies in event month ‘t’ is defined as AR t s

1

n

Ý ari ,t .

Ž 3.

n is1

The cumulative abnormal return over T months starting from month t 0 is the summation of the average abnormal returns: T

CAR t 0 ,T s Ý AR t .

Ž 4.

tst 0

The buy-and-hold abnormal returns are calculated as T

T

R i ,t s Ł Ž 1 q ri ,t . y Ł Ž 1 q rm ,t . ts1

Ž 5.

ts1

where R i,t is the abnormal return of company ‘i’ in event month ‘t’ calculated on a compounded basis, ri,t is the return for company ‘i’ in event month ‘t’, and rm,t is the return of market index in event month ‘t’. Relative long-run performance of IPOs measured by wealth relatives is defined as WR s Ž 1 q average long run buy and hold return on the sample IPOs . r Ž 1 q average long run buy and hold return on benchmark firms . . Ž 6 . Wealth relatives greater Žlower. than one indicate superior Žinferior. performance of the sample IPOs to the performance of benchmark firms. In this paper we use two benchmarks: the value-weighted KLSE Composite Index, and a portfolio of 13

For example, the first trading month is from day 2 to 22, the second month comprises trading days from day 23 to 43, etc.

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matching firms from the same industries and with a similar market value to the sample IPOs. A portfolio of matching firms is created following the methodology adopted from Ritter Ž1991.. Firstly, we split firms from our sample according to prospectus dates into three groups. Sample IPO firms with prospectus dates from 1980–1984 were matched, in terms of industry and market value, with matching firms from 1980. IPOs from 1985–1989 are compared with matching firms from 1985, and 1990–1995 IPOs are matched with matching firms from 1990. Secondly, matching firms with closest market values and same four digit industry codes are chosen, and matching firms are used only once.14 Our matching sample does not include any recent IPOs.15 A similar industry code, instead of an exact one, would be used only when there was no firm with a similar market value within the same industry group, or there were no enough firms in the matching group to be able to find an exact industry code. Finally, the returns on the sample IPOs returns were calculated to begin and end on the same day as those on matching firms. For the evaluation of earnings forecasts, we apply error metrics that rely on historic earnings, which are known at the time the forecast was made, and are based on a comparison of predicted Žforecast. and realised Žactual. changes in earnings. This technique is defined by Theil and it is widely used in the literature on analysts earnings forecasts:16 PC i ,0 s Fi ,0 y Hi ,y 1 ,

Ž 7.

RC i ,1 s A i ,1 y Hi ,y 1 ,

Ž 8.

where, Fi,0 is a company ‘i’ earnings level forecast, for the end of next accounting year, made in the IPO prospectus Žtime 0.; Hi,y 1 is the last accounting year level of actual earnings Žtime y 1.; A i,1 is actual level of earnings for the company at the end of accounting year for which the forecast was made Žtime 1.. PC i,0 is the predicted change in earnings known at the time of IPO, and RC i,1 is the realised change in earnings for company ‘i’. This metrics has an easily interpreted economic meaning. Companies with a predicted change in earnings below that realised are cautious Žpessimistic. forecasters. If the predicted change in earnings is bigger than that realised, companies are regarded as optimistic. A predicted

14

All market values of IPOs are obtained from the PACAP database using end of year market value in the first year of trading. 15 This is achieved both by design of the matching procedure and by the size of our sample of IPOs. For example, IPOs coming to the market during 1985–1989 are matched with companies with similar market values and industry as in 1985. The 1985 matching firms are not IPOs, otherwise they would have been included in the 1985–1989 subsample of IPOs. We, however, have not included any of 1977–1980 IPOs in our matching portfolio for 1980–1985 subsample. 16 Theil Ž1966. as cited in Elton and Gruber Ž1995, p. 675..

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change in earnings equal to that realised indicates a perfect forecast. In addition, this metrics can identify ‘optimists’ when they overestimate an increase in earnings as well as when they underestimate a reduction in earnings. In order to examine the patterns in forecast errors and to differentiate optimistic from pessimistic forecasts, we construct the Prediction Realisation Diagram ŽPRD..17 Forecast changes in earnings, defined in Eq. Ž7., are plotted along the vertical axis while actual changes in earnings, defined in Eq. Ž8., are plotted along horizontal axis. Perfect forecasts ŽPC i,0 y RC i,1 s 0. would be plotted along the line that lies at a 458 angle to the horizontal axis. The lines form six different sections, each representing a different pattern in forecast errors. Optimistic forecasts are found in Sections 1, 2, and 5 Žto the left of the 458 angle line. while pessimistic forecasts are found in Sections 3, 4 and 6 Žto the right of the 458 angle line.. A point lying in Section 1 of the PRD suggests that managers successfully forecast an increase in earnings, but overestimated the size of earnings, while those in Section 2 imply that managers correctly predicted a decrease in earnings but underestimated the size of the decrease. For points in Section 5 managers predicted that earnings would increase when they actually decreased. Sections 3, 4 and 6 are mirror images of Sections 1, 2 and 5. This means that Sections 3 and 4 indicate that managers were successful in forecasting an increase and a decrease in earnings, respectively, but were pessimistic about the change in the size of future earnings. Finally, in the case of points in Section 6 managers forecast a decrease in earnings when they actually increased.

4. Determinants of short-term performance 4.1. Underwriters reputation The evidence on the determinants of initial premiums is not conclusive ŽIbbotson and Ritter, 1995.. Evidence based on US data offers support for a negative relationship between size of the company and size of the issue, and the premiums ŽRitter, 1984; Ibbotson et al., 1988.. Beatty and Ritter Ž1986. found that riskier issues have greater underpricing, providing some evidence for Rock’s Ž1986. winner’s curse model. Negative relationship between premiums and the percentage of common stock held by outsiders was suggested by both Logue Ž1973. and Brennan and Franks Ž1995.. Product differentiation in the market for underwriting can be explained within the asymmetric information andror agency theory frameworks. From an agency theory perspective, selection of a high quality underwriter will reduce the high 17

Elton and Gruber Ž1995, p. 677..

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agency costs experienced by IPO firms. Alternatively, the choice of a high quality underwriter could be viewed as a signalling device where high quality underwriters will be selected by firms with more favourable information ŽTitman and Trueman, 1986.. Numerous studies on IPOs investigate the relationship between underwriter prestige and initial returns Žsee, for example, Beatty and Ritter, 1986; Johnson and Miller, 1988; Beatty and Welch, 1996; Carter et al., 1997; Paudyal et al., 1998.. On balance, the empirical evidence seems to suggest that underwriters with a better reputation tend to reduce the initial underpricing.18 This leads to the first hypothesis:

Hypothesis 1. Prestigious underwriters are associated with lower underpricing We test this hypothesis by constructing two portfolios on the basis of underwriters’ reputation. In the absence of an important agency andror signalling role of the underwriter, average Žmean and median. initial premiums of both portfolios should be similar. Several proxies to measure underwriters’ reputation have been used in the IPO literature Žsee Carter et al., 1997.. In this study we use the number of issues an investment bank has underwritten as lead manager since 1980. Twelve Malaysian investment banks have played a leading role in underwriting since 1980. However, only four of them have played a leading role for more than 20 new issues in our sample Ž28, 28, 24 and 23, respectively.. These banks were considered to be the most prestigious.19 Our measure of underwriter reputation is not without its limitations. It implies, for example, that the prestige level corresponds to the number of completed underwritings and implies that a reputation established before 1980 does not count.20 To overcome these problems we checked this criterion with the data for the income from underwriting fees and a bank’s position in Euromoney’s Bank Atlas for the best merchant banks worldwide. All AreputableB underwriters have been listed at least once among the top five Malaysian merchant banks in the Euromoney’s Bank Atlas, and can be found among the top five earners of underwriting fees in Malaysia during 1980–1995. Finally, all banks considered to be of high reputation are subsidiaries of banks selected to be core banks in the recent Malaysian NERP programme. 18 However, Johnson and Miller Ž1988. observe that this finding may be a consequence of the fact that more prestigious underwriters are involved with relatively lower risk IPOs. Beatty and Welch Ž1996. suggest that a negative relationship between the level of IPO underpricing and underwriters’ reputation may be reversed due to changes in the economic environment. 19 The four most reputable banks are Arab–Malaysian Merchant Bank, Malaysian International Merchant Bankers, Commerce International Asset Holdings, and Bumiputera Merchant Bankers. Together they led about 60% of the IPOs in our sample. 20 Given the relatively small number of IPOs in Malaysia during the 1970s relative to the number of IPOs during the mid 1980s and 1990s, this assumption seems to be acceptable.

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4.2. Forecast accuracy Prior research on management earnings forecasts finds a predictive content of these forecasts relative to actual earnings ŽHassell and Jennings, 1986; McNichols, 1989. and an association between the voluntary disclosure of management earnings forecasts and changes in market expectations. This is further reflected either in revisions of analysts earnings forecasts or in changes in share prices ŽLev and Penman, 1990; Baginski et al., 1993; Pownall et al., 1993.. Teoh et al. Ž1998. find evidence that issuers with unusually high accruals in the IPO year experience a poor stock return performance in the 3 years thereafter. There is, however, a paucity of research on the effect of management earnings forecasts on the financial performance of IPOs. This is partly due to the litigious environment in the US and some other countries that makes disclosure of management earnings forecasts in prospectuses extremely rare.21 Studies on management earnings forecasts in the IPO context are concentrated in countries with less a litigious environment Že.g. British Commonwealth countries.. Among these countries, the Malaysian market provides a rare test case in that disclosure of next financial year earning forecasts by management is mandatory in IPO prospectuses. Previous studies on the accuracy of earnings forecasts in IPO prospectuses suggest that managers seem to be cautious forecasters. Positive forecast errors prevail in studies for the UK, Malaysia, Canada, and Singapore ŽKeasey and McGuinness, 1991; Jelic et al., 1998; Clarkson et al., 1989; Firth et al., 1995, respectively.. Exceptions are New Zealand and Hong Kong where negative average forecast errors were reported ŽFirth and Smith, 1992; Selva et al., 1994, respectively.. The effect of management earnings forecasts on the financial performance of IPOs has received only modest attention in the literature. Clarkson et al. Ž1992. report the importance of management earning forecasts for market valuation of Canadian companies seeking a listing. Retained ownership and historical earnings are shown to be inferior to management earnings forecasts in market valuations. These findings are echoed in Firth Ž1997, 1998. who reports that the earnings forecasts play an important part in initial market valuations in New Zealand and Singapore, respectively. He finds that earnings forecasts are a major signal of IPO values Žmore important than retained ownership and historical earnings.. The accuracy of management earnings forecasts is a major explanatory variable of cumulative abnormal returns of Singaporean IPOs in the first year after the listing.

21

Debate on the information content and usefulness of management earnings forecasts has a long history in the US. Security Exchange Commission ŽSEC. has prohibited the disclosure for a long time, but was relaxed by the Safe Harbour Rule in 1973. Currently, the debate is intensified in relation to the valuation of IPOs in the information technology sector.

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Given the institutional arrangements in the Malaysian primary market, it is reasonable to assume that, in order to estimate an expected market price, investors might rely on the pricerearnings multiple and earnings forecasts by management. In the absence of any previous record regarding forecast accuracy, investors will tend to assess profit forecasts and will try to identify which of them are overly optimistic or overly pessimistic. If investors are successful in differentiating optimistic from pessimistic forecasts, then differences in the levels of premiums may be associated with forecast accuracy. Higher premiums would be more likely to be associated with pessimistic forecasts. In the case of optimistic forecasts, one would expect lower levels of underpricing.22 Thus:

Hypothesis 2. Optimistic forecasts are associated with lower initial returns. In order to examine this proposition, we construct two portfolios on the basis of forecast bias, viz. Ža. optimists and Žb. pessimists, and then perform parametric and non-parametric tests for differences in the portfolios’ average Žmean and median. returns. Finally, Hypotheses 1 and 2 have also been tested within the following cross-sectional model: MAIRs a q b 1 LnSIZEq b 2 AMU q b 3 LnAGEq b4 LnBVrMV q b5 OPTIMISTSq b6 INSIDERSq b 7 MARKET q b 8 DMULTIPLEq ´ .

Ž 9.

In the above equation, the market-adjusted initial return ŽMAIR. for each company is used as the dependent variable. In order to evaluate the association between underpricing and underwriters’ reputation, we introduce a dummy variable, taking a value of 1 if the company has been advised by one of four ‘reputable’ underwriters and 0 otherwise ŽAMU.. The association between forecast bias and the underpricing is examined by introducing a dummy variable ŽOPTIMISTS., taking a value of 1 for companies with a negative forecast error Žoptimists. and 0 for companies with a positive forecast error Žpessimists.. The variables for companies size ŽLnSIZE., operating history ŽLnAGE., retained ownership ŽINSIDERS., book to market value ratio ŽLnBVrMV., market sentiment prior to issues ŽMARKET., and demand multiple ŽDMULTIPLE. are included as control variables.

22

In extreme cases, the issue price could be above the initial listing price and a firm’s reputation and the cost of raising further capital may be adversely affected.

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5. Determinants of long-term performance Ibbotson and Ritter Ž1995. provide a detailed review of theories that have been proposed to explain the long-run underpricing of IPOs. For example, Welch Ž1989. sees underpricing as a signalling device, the main objective of which is to maximise the offer price of subsequent issues. Signalling costs Žunderpricing. will be prohibitively high for low quality firms. A testable implication of the Welch model is that firms with higher underpricing will make more Žsooner. subsequent issues. Also, the firms making subsequent issues would tend to have higher intrinsic values. Ritter Ž1991. presents Athe windows of opportunitiesB hypothesis according to which large cycles in volumes Žhot periods. indicate companies’ attempts to ‘time’ their IPOs. Shiller Ž1990. has introduced the impresario hypothesis, according to which underwriters Žacting as impresarios. deliberately underprice offerings in order to create excess demand. Consequently, when the excess demand is absorbed the market price will be reduced and the companies with biggest underpricing would have the lowest long-run returns. The Adivergence of opinionB hypothesis suggests long-run underperformance due to over-optimism of buyers in the presence of great uncertainty. The differences between optimists and pessimists would disappear with the release of more timely information about a company. Eventually this would lead to a drop in market price and underperformance in the long run ŽMiller, 1977; Levis, 1993.. Both of the above mentioned scenarios are consistent with Aover-reactionB hypothesis ŽRitter, 1991; De Bondt and Thaler, 1985, 1987., which suggests that companies with highest initial returns will have poorest long-term returns. The analysis of the determinants of long-term performance is particularly important in Malaysia because of the high level of over-subscription Žabout 27 times in our sample. and also the high degree of under-pricing reported on the new issues listed on the KLSE. It is plausible that the excess demand may lead to high and positive excess return in the short run, but once over-optimism disappears, in the long run Malaysian IPOs will underperform the market. To test for this possible market overreaction we construct two portfolios Žlow and high initial returns portfolios. on the basis of their initial performance Žcut-off point being the median initial return.. In the absence of initial over-optimism, the long-term returns of both portfolios should be similar and should not be significantly different from the market returns. This leads to the third hypothesis: Hypothesis 3. IPOs with highest initial returns will have lower long-term returns. A widely accepted theory on the relationship between underwriters’ reputation and the long-term performance of IPOs has not yet been developed. Most authors, however, hypothesise a positive relationship between the reputation and long-term performance. Fields Ž1995., for example, emphasises a possible role of banks Žand

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other institutional shareholders. in corporate governance. Chemmanur and Fulghieri Ž1994. propose that investors assess underwriters’ reputation by measuring the quality of firms advised by banks. The banks, therefore, build Žand protect. their reputation by being involved in IPOs of quality firms. Anecdotal evidence for this hypothesis is provided by the fact that some banks use the data on long-term performance of their clients in advertising.23 Empirical studies also indicate a less severe long-term underperformance of IPOs handled by more prestigious underwriters ŽMichaely and Wayne, 1994; Carter et al., 1997.. Thus: Hypothesis 4. There is a positive relationship between underwriters prestige and the long-term performance. Earnings forecasts are an important variable for valuation and as such often used by investors. Kim and Ritter Ž1999., for example, reported that PrE multiples using forecast earnings result in much more accurate valuations than multiples using historic earnings. The important consideration in this context is the ability of investors to use Žor choose not to use. and assess management earnings forecasts at the time they were disclosed. If investors rely on these forecasts but are not fully aware of degree of bias, then stock prices may reflect overly optimistic earnings predictions. Dechow et al. Ž1999. and Rajan and Serves Ž1997. pose the same question with regard to the role of financial analysts’ earnings forecasts around the time of new equity offerings in the pricing of IPOs in the US. For example, Rajan and Serves Ž1997. found that, in the long run, IPOs have a better stock performance when analysts ascribe low growth potential rather than high growth potential. They conclude that the anomalies may be partially driven by over-optimism. This result is echoed in Dechow et al. Ž1999., who found that analysts are systematically overly optimistic around new equity offerings. Furthermore, analysts’ overly optimistic forecasts seem to be reflected in the stock prices of issuing firms, suggesting that investors naively rely on analysts’ earnings growth forecasts. Similar evidence for management earnings forecasts is scarce due to limited data on such forecasts in many countries. The earnings forecasts furnished by the management in Malaysian IPO prospectuses provide vital information for prospective Malaysian investors. The accuracy of these forecasts cannot be verified at the time of listing. Thus, investors may initially rely on managers’ forecasts and may not be able to distinguish between optimistic and pessimistic forecasts to the extent that will significantly affect the degree of the initial premium of the two sub-samples Žpessimistic and optimistic forecasters.. The question we ask is: if managers are overly optimistic and investors naively believe their forecasts, do companies with the highest earnings 23

For example, see Deutsche Bank advert in Financial Times Ž2000, p. 6.. Forbes and the Wall Street Journal also provide tables on the correlation between underwriters’ reputation and IPO performance.

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forecasts, at the time of the offering, tend to have the poorest stock price aftermarket performance? If this was the case, one could conclude that investors initially believed management’s earnings forecasts Žand overreacted. and were subsequently disappointed when less-than-expected earnings were achieved. One would expect that the higher the forecast error, the greater the effect on the long-term performance and in particular, prices for overly optimistic companies may be reduced. Thus: Hypothesis 5. There is a negative relationship between long-term returns and upward bias in management earnings forecasts. We test this hypothesis by constructing two portfolios on the basis of forecast bias. In the absence of initial over-optimism andror if investors do not rely on forecasts in their valuation of IPOs, the long-run performance of both portfolios should be similar and should not be significantly different from the market returns. According to the impresario hypothesis, however, investors’ disappointment could be directed to other variables, such as initial premium and the underwriters’ reputation. In addition, within a signalling framework, management profit forecasts may be an alternative Žor additional. signal to retained ownership ŽClarkson et al., 1992; Firth, 1998.. It is important, therefore, to include initial premium, underwriters’ reputation, and retained ownership as control variables in following cross-sectional models for long-term returns: MACR 1 s a q b 1 AMU q b 2 MAIRq b 3 OPTIMISTSq b4 INSIDERS q b5 LnSIZEq ´ ,

Ž 10 .

MACR 2 s a q b 1 AMU q b 2 MAIRq b 3 OPTIMISTSq b4 INSIDERS q b5 LnSIZEq ´ ,

Ž 11 .

MACR 3 s a q b 1 AMU q b 2 MAIRq b 3 OPTIMISTSq b4 INSIDERS q b5 LnSIZEq ´ .

Ž 12 .

One- ŽMARC 1 ., two- ŽMACR 2 . and three- ŽMACR 3 . year market adjusted buy-and-hold returns for each company are used as the dependent variables. Explanatory variables, AMU, MAIR, OPTIMISTS, INSIDERS, and LnSIZE are the same as in Eq. Ž9..

6. Results 6.1. Short-term performance Table 2, Panel A reports the initial returns of the 182 Malaysian new issues in 1980–1995. Average Žmean and median. raw and market-adjusted initial returns

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Table 2 Panel A: Average Žmean and median. raw ŽIR. and market-adjusted initial returns ŽMAIR. IR Ž%.

MAIR Ž%.

Mean

Median

Std. dev.

Mean

Median

Std. dev.

99.25 w0.00x

79.04 w0.00x

88.48

99.04 w0.00x

78.75 w0.00x

88.23

No. of firms

No. of firms

Returns- 0% 2 2 0%-Returns- 50% 66 66 50%-Returns-100% 40 45 Returns)100% 74 69 Total 182 182 Average returns are calculated on an equally weighted basis. P-values Žin brackets. indicate the level of significance for the two-tailed T and Wilcoxon tests of meanrmedians 0 vs. meanrmedian/ 0. Distribution of raw and market-adjusted initial returns by number of firms. Panel B: Market-adjusted initial returns stratified by year of listing Year

Total gross proceeds

Mean

Median

Std. dev.

Min

Max

N

1980 23,182 102.53 102.53 4.40 99.41 105.64 2 1981 70,606 172.10 159.78 113.78 70.84 298.01 4 1982 205,754 78.22 75.41 34.02 32.86 113.28 5 1983 130,949 230.10 217.39 142.64 78.69 596.59 10 1984 81,107 157.00 135.28 87.16 20.16 313.00 11 1985 200,289 157.61 93.19 140.30 54.36 384.87 5 1986 27,867 41.73 45.32 24.24 9.14 67.17 4 1987 295,385 87.61 87.74 59.19 24.08 176.17 7 1988 112,925 36.22 39.85 31.00 y7.77 75.44 6 1989 862,691 65.28 59.41 41.61 4.98 128.33 10 1990 3,338,551 61.91 39.48 65.92 y61.35 246.79 20 1991 697,572 43.11 21.21 56.59 y65.80 203.01 25 1992 4,704,581 51.94 27.04 79.24 y20.75 396.96 28 1993 640,831 111.06 85.13 83.72 7.09 301.26 13 1994 2,219,870 150.57 136.55 61.40 39.07 289.09 19 1995 1,959,797 87.25 96.94 52.94 y4.64 159.53 13 Total 182 Total gross proceeds and number of IPOs in RM Ž000. based on sample statistics; Gross proceeds are in real terms Žnominal proceeds deflated by consumer price index for the year.; Pearson correlation for previous year MAIR and current year gross proceedssy0.35.

are positive and statistically significant at 1% level using both t-test and Wilcoxon Signed tests. This is consistent with empirical evidence both internationally and for Malaysia. The reported level of underpricing Ž99%. is higher than reported in

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most studies.24 It appears that underpricing was exceptionally high during the ‘hot issue’ periods during 1983–1985 and during 1993–1995 ŽTable 2, Panel B.. The cycles in volume allow investors to predict next year’s volume using the current year’s number of IPOs with a relatively high degree of accuracy.25 The persistence of the average initial returns is not strong.26 Low correlation coefficients between current year volumes and previous year’s premiums give no evidence that initial returns lead volume.27 Construction, Industrial Products, and Trading and Services are the sectors with the highest level of underpricing Ž110.62%, 107.62%, and 97.72%, respectively.. Hotels, Plantations and Finance display the lowest marketadjusted initial premiums: 51.85%, 53.19% and 64.43%, respectively.28 Results reported in Table 3, Panel A suggest that underwriters with a better reputation tend, on average, to increase initial underpricing. This contradicts results reported in studies on underwriters’ role in other countries Že.g. Beatty and Ritter, 1986; Carter et al., 1997.. However, results of both parametric and non-parametric tests reveal no significant differences between average returns of IPOs underwritten by reputable underwriters and IPOs underwritten by less reputable underwriters. Data on forecasts of earnings changes was available for 151 companies. The forecasts were stated as a single figure Že.g. profit will be RM 10 million., and the average forecast horizon was 8 months, with the shortest forecast horizon at 2 months and the longest 16 months. As presented in the PRD ŽFig. 1., there were 65 IPOs with optimistic forecasts ŽSections 1, 2 and 5 of the diagram. and 86 companies with pessimistic forecasts ŽSections 2, 4 and 6 of the diagram.. Seventeen companies from the sample predicted the wrong direction of changes in earnings ŽSections 5 and 6 of the diagram.. The most common mistake made by the management with correct directional forecasts was to underestimate the size of the increase in earnings Ž75 companies.. The management of 46 companies correctly forecast an increase in earnings but overestimated the size of the increase. Among those which correctly predicted a decrease in earnings, six were over-pessimistic ŽSection 4 of the diagram., and seven companies underestimated the size of the decrease ŽSection 2 of the diagram.. 24

Since average initial returns are computed using equal weights on all IPOs, the reported level of underpricing may be slightly overstated. For example, lower-priced issues in our sample tend to be underpriced by more in the short run. The average market-adjusted return on IPOs with an offering price of less than RM 1.80 Žmedian value. was 105%, whereas the average initial return on IPOs with an offering price of RM 1.80 or more was 49%. Similar results were reported for US data in Ibbotson et al. Ž1988.. 25 The first-order autocorrelation of annual number of IPOs in Table 2 ŽPanel B. is 0.67. 26 The first-order autocorrelation of annual average raw initial returns is y0.03. 27 The correlation between previous year market-adjusted initial returns and current year gross proceeds in Table 2 ŽPanel B. is y0.35. Unreported Pearson correlation for previous year raw initial returns and current year number of issues is y0.49. 28 Initial premium for Trusts, based on one company only, was 34%.

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Table 3 Panel A: Average initial returns by underwriters reputation IR Ž%. N High reputation Low reputation Differences

MAIR Ž%. Mean

Median

Std. dev.

Mean

Median

Std. dev.

101 70

99.99 78.89 90.95 100.08 79.09 89.57 91.62 73.68 75.89 91.07 76.57 73.99 8.37 6.21 9.01 2.52 Ž0.65. Ž5943. Ž0.72. Ž5940. w0.51. w0.81x w0.47x w0.80x Average returns are calculated on an equally weighted basis. Test statistics Žin parentheses. and p-values Žin brackets. indicate the level of significance for the differences in mean Ž t-test. and median ŽMann–Whitney test. raw ŽIR. and market-adjusted initial returns ŽMAIR. for IPOs with highly reputed underwriters Žhigh reputation. vs. raw and market-adjusted initial returns for IPOs with less highly reputed underwriters Žlow reputation.. In order to examine the robustness of the results, we tested the hypothesis that differences in median raw and market-adjusted returns are significantly different from zero using the Mood’s median test. The hypothesis is rejected at 5% level for both, raw or market-adjusted returns. Panel B: Average initial returns for optimists and pessimists IR Ž%. N Pessimists Optimists Differences

MAIR Ž%. Mean

Median

Std. dev.

Mean

Median

Std. dev.

86 65

97.70 76.23 100.85 97.94 74.85 100.23 84.18 57.86 86.22 82.62 54.36 85.18 13.52 18.37 15.32 20.49 Ž0.89. Ž6604. Ž1.01. Ž6631. w0.38x w0.38x w0.31x w0.33x Average returns are calculated on an equally weighted basis. Test statistics Žin parentheses. and p-values Žin brackets. indicate the level of significance for the differences in mean Ž t-test. and median ŽMann–Whitney test. raw ŽIR. and market-adjusted initial returns ŽMAIR. for IPOs with optimistic forecasts vs. raw and market-adjusted initial returns for IPOs with pessimistic forecasts. In order to examine the robustness of the results, we tested the hypothesis that differences in median raw and market-adjusted returns are significantly different from zero using Mood’s median test. The hypothesis is rejected at 5% level for both, raw or market-adjusted returns.

Both mean raw and market-adjusted initial returns are, on average, higher for pessimists than for optimists ŽTable 3, Panel B.. However, t-test indicates that the mean initial returns for ‘optimists’ and ‘pessimists’ Žboth for raw and market-adjusted returns. are not significantly different. Non-parametric Mann–Whitney Test confirms that there is no significant difference between medians for ‘optimists’ and ‘pessimists’. Consequently, investors seem unable to predict a bias in forecast accuracy. This result is consistent with findings by Firth and Smith Ž1992. for IPOs in New Zealand, which has similar mandatory earnings forecasts in IPO prospectuses. To check for the robustness of our results we identified optimists and pessimists using the percentage forecast error ŽFE. as an alternative error metrics. Companies

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Fig. 1. Prediction Realisation Diagram. RC i,1 and PC i,0 in RM Ž000.; RC i,1 s A i,1 y Hi,y 1 sRealised change in earnings for company ‘i’; PC i,1 s Fi,0 y Hi,y 1 s Forecast change in earnings for company ‘i’; Hi,y 1 s Last accounting year actual level of earnings; A i,1 s Actual level of earnings for company ‘i’ at the end of accounting year for which the forecast was made; Fi,0 sCompany’s ‘i’ earnings level forecast for the end of next accounting year, made in the IPO prospectus; Optimistic forecasts to the left of PC i,0 yRC i,0 line ŽSections 1, 2 and 5.; Pessimistic forecasts to the right of PC i,0 yRC i,0 line ŽSections 3, 4 and 6.; Section 1ssuccessfully forecast an increase in earnings; Section 2 ssuccessfully forecast a decrease in earnings; Section 3ssuccessfully forecast an increase in earnings; Section 4 ssuccessfully forecast a decrease in earnings; Section 5s forecast an increase in earnings when they actually decreased; Section 6 s forecast a decrease in earnings when they actually increased.

with a negative FE reported profits lower than forecast Žoptimists. while those with a positive FE exceeded their forecast profits Žpessimists.. The mean FE is positive, which confirms our earlier findings that, on average, managers were cautious forecasters.29 The unreported results confirm our earlier findings on absence of statistically significant difference between average Žmean and median. initial returns between optimists and pessimists.30

29 These findings are also consistent with evidence presented for UK, Malaysia, Canada and Singapore in previous studies on management earnings forecasts. 30 We also compared average returns for companies from top and bottom deciles by forecast error. The average returns for top decile Žpessimists. were 84.48% while average returns from bottom decile Žoptimists. were 103.57%. P-values of the two-sample paired t-test for difference in mean returns, however, suggest no statistically significant difference between mean returns. Results available upon request.

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6.2. Long-term performance Table 4 reports the average market-adjusted returns and cumulative abnormal returns ŽCAR t . for 36 months after the offerings of the IPOs. The CAR t is significantly positive from month 7 through to month 36. Buy-and-hold returns are statistically significant and positive in month 6 and remain positive until month 36 ŽTable 5, Panel A.. The results remain robust after we account for skewness bias, by calculating a skewness-adjusted t-statistic with bootstrapped p-values. These findings contradict typical findings in the IPO literature where significant negative long-run performance is documented. The buy-and-hold returns were always higher than CAR t , except for months 34, 35, and 36. Our sample firms are, on average, bigger than matching firms in all deciles except one. There were several outliers in our sample with very large market values, namely the biggest privatised companies: Malaysian International Shipping, Telecom Malaysia, Tenaga Nasional and Petronas Gas. About 42% of our sample firms were matched with firms with the same four-digit industry code and 39% with firms with the same three digits in the industry code. For 21 firms we had to look for a firm with a similar industry Ždifferent four-digit industry code.. None of our sample or matching firms has been de-listed or taken over during the relevant period. Wealth relatives have been calculated without adjusting for betas. The average beta for the sample is 1.241 and the average beta for matching firms is also above 1 Ž1.271..31 The time series patterns of betas are also similar.32 The difference in betas does not seem to be significant to an extent that would affect our conclusions. As shown in Table 5 ŽPanel B., wealth relatives bigger than 1 were found after 1, 2 and 3 years after IPOs, when market index was used as a benchmark. This has been confirmed for years 1 and 2, using market-adjusted and raw returns for the sample and matching firms. However, it seems that the sample firms on average underperform the matching firms 3 years after the IPO. The long-term returns for low and high initial return portfolios and the p-values of t-statistics of differences in the mean returns of the two portfolios are reported in Table 6. Consistent with the overreaction hypothesis, the portfolio of IPOs with low initial returns outperforms the portfolio of those with high initial returns. The difference between the mean initial returns is statistically and economically significant starting from month 12 up to month 36. Twelve months following official listing the difference reaches over 18%, after 2 years it has become 62.7% and after 3 years it is just below 63%. These results are in line with those reported

31

All betas are taken from the Datastream database, and are based on 5-year Ž1992–1997. monthly returns. 32 Unreported average betas for the first 3 years after IPO show that betas are getting lower with the length of the time since offering. This is consistent with results reported in Ritter Ž1991..

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Table 4 Average and cumulative abnormal returns for Malaysian IPOsa Month

No. of firms b

Negative AR t

Positive AR t

AR t Ž%.

T-stat.c

CAR t Ž%.

T-stat.c

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 182 181 179 177 176 175 175 174 172

101 95 105 97 100 81 87 99 100 103 103 98 105 100 112 97 90 84 102 94 91 98 90 102 91 91 99 99 86 104 92 93 91 98 89 100

81 87 77 85 82 101 95 83 82 79 79 84 77 82 70 85 92 98 80 88 91 84 92 80 91 91 83 83 95 75 85 83 84 77 85 72

y0.180 0.392 y0.335 0.461 y0.043 2.882 1.993 0.844 0.068 0.825 0.888 1.178 y0.045 1.394 y1.070 1.256 1.460 2.586 y1.024 1.300 2.479 0.191 1.932 y1.577 1.213 0.279 1.020 1.472 2.002 0.023 1.408 0.028 1.110 y0.532 0.661 y1.710

y0.157 0.539 y0.469 0.559 y0.053 3.264 1.979 0.979 0.082 0.682 0.884 1.038 y0.053 1.404 y0.964 1.053 1.388 2.361 y0.991 1.071 1.927 0.185 1.289 y1.740 1.184 0.276 0.847 1.226 1.825 0.017 1.371 0.022 0.819 y0.489 0.597 y1.314

y0.180 0.212 y0.123 0.338 0.295 3.177 5.170 6.014 6.082 6.907 7.795 8.973 8.928 10.322 9.251 10.507 11.967 14.553 13.529 14.828 17.308 17.499 19.430 17.853 19.066 19.345 20.365 21.837 23.839 23.862 25.271 25.298 26.408 25.876 26.537 24.826

y0.166 0.156 y0.078 0.189 0.150 1.490 2.262 2.475 2.371 2.564 2.768 3.058 2.930 3.270 2.836 3.123 3.456 4.088 3.703 3.960 4.514 4.462 4.849 4.365 4.570 4.549 4.702 4.953 5.301 5.190 5.379 5.287 5.421 5.235 5.277 4.842

a

Average returns are calculated on an equally weighted basis without initial premiums. Data from 22–36 months are missing for companies that came to the market during 1993–1995 period. c The t-statistic for AR t is computed for each month as AR t Ž n t . rSDt , where AR t is the average adjusted return for month ‘t’, n t is the number of observations in month ‘t’, and SDt is the cross-sectional standard deviation of the adjusted returns for month ‘t’; The t-statistics for the cumulative average adjusted return in month ‘t’ is computed as CAR t Ž n t . rCSDt ,where n t is the b

'

'

'

number of firms trading in each month, and CSDt is computed as CSDt s w t varq2 Ž t y1 . cov x , where ‘t’ is the event month, var is the average Žover 36 months. cross-sectional variance, and cov is the first-order autocovariance of the AR t series ŽRitter, 1991..

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Table 5 Panel A: Average raw IPO buy-and-hold returns ŽRAW., KLSE index buy-and-hold returns ŽKLSE. and market-adjusted IPO buy-and-hold returns ŽMACR. Holding period

N

RAW

KLSE

MACR

1 week 2 weeks 3 weeks 1 month 2 months 3 months 6 months 12 months

182 182 182 182 182 182 182 182

0.63 0.44 0.92 0.80 2.96 3.98 12.57 25.04

0.33 0.63 0.59 0.71 2.27 3.41 7.98 12.22

0.30 y0.19 0.33 0.09 0.69 0.57 4.59 12.82

T-stat.

P-value

0.36 0.720 y0.20 0.840 0.29 0.780 0.07 0.940 0.43 0.670 0.31 0.760 1.88 0.061 2.69 0.008 Ž3.44. w0.000x 18 months 182 46.63 21.27 25.36 2.79 0.006 24 months 182 54.09 28.32 25.77 3.23 0.002 Ž4.25. w0.000x 30 months 178 64.01 35.72 28.29 2.83 0.005 36 months 171 63.83 41.85 21.98 2.24 0.027 Ž2.73. w0.004x All returns in percentages. MACRs are computed as buy-and-hold market-adjusted compounded returns using the KLSE Index as a benchmark, as in Eq. Ž5.. P-values for two-tailed t-test of mean MACR s 0 vs. mean/ 0 indicate statistical significance of returns at 1% in months 12, 18, 24, 30, and 36. Skewness-adjusted t-statistic are Žin parentheses. with bootstrapped p-values Žin brackets.. Panel B: Wealth relatives Year

MACR

MMACR

RAW

MRAW

KLSE

WR1

WR2

WR3

1 12.82 12.19 25.04 24.43 12.22 1.052 1.025 2.049 2 25.77 24.59 54.09 52.93 28.32 1.048 1.022 1.910 3 21.98 22.18 63.83 64.41 41.85 0.991 0.991 1.525 WR1s wealth relative ratio for our sample buy-and-hold market-adjusted compounded returns ŽMACR. and the matching sample buy-and-hold market-adjusted compounded returns ŽMMACR.; WR2 s wealth relative ratio for our sample buy-and-hold compounded raw returns ŽRAW. and the matching sample buy-and-hold compounded raw returns ŽMRAW.; WR3s wealth relative ratio for our sample compounded raw returns and the Kuala Lumpur Stock Exchange Composite Index returns ŽKLSE..

by Paudyal et al. Ž1998. for a sample of 95 Malaysian IPOs. The results provide support for the findings of Ritter Ž1991. and suggest that initial abnormal returns could be partly due to over-optimism in the IPO market. The results of the long-term performance of IPOs segregated by underwriters’ reputation and their statistical significance are also reported in Table 6. The findings reveal that IPOs underwritten by more reputed underwriters provide higher long-term returns Žwith the exception of the 24th month. than IPOs underwritten by less reputed underwriters. The difference is significant for the 3rd,

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Table 6 Initial returns, underwriter reputation, and long-run performance of Malaysian IPOs Mean market-adjusted buy-and-hold returns are reported in percentages. The market-adjusted buy-andhold returns are estimated using Eq. Ž5.. For underwriters’ reputation Žlow and high., portfolios are formed on the basis of the reputation of the underwriters. Underwriters’ reputation is measured on the basis of frequency of engagement in underwriting Žas a lead underwriter. during 1980–1995. P-values indicate the level of significance for the test of differences Žh1 sh 2 vs. h1 /h 2 . in mean Ž t-test. and median ŽMann–Whitney test. market-adjusted buy-and-hold returns for IPOs with highly reputed underwriters Žhigh reputation. and IPOs with less highly reputed underwriters Žlow reputation.; The median market-adjusted initial return is chosen as a cut-off point for low and high market-adjusted initial returns ŽMAIRs. portfolios. P-values indicate the level of significance for the test of differences Žh1 sh 2 vs. h1 /h 2 . in mean Ž t-test. and median ŽMann–Whitney test. market-adjusted buy-and-hold returns for IPOs with high MAIRs and IPOs with low MAIRs. Holding period

1 month 2 months 3 months 4 months 5 months 6 months 7 months 8 months 9 months 10 months 11 months 12 months 18 months 24 months 30 months 36 months

Underwriters reputation Low

High

y2.23 y2.45 y3.23 y4.87 y5.69 y1.68 1.70 2.45 4.45 3.96 3.62 12.05 18.79 29.13 20.57 23.39

1.52 2.35 3.22 4.62 4.76 7.42 9.34 11.24 10.41 13.23 12.97 12.32 32.65 25.63 37.53 27.04

t-test p-value

MW p-value

MAIRs Low

High

t-test p-value

MW p-value

0.150 0.140 0.082 0.021 0.022 0.059 0.160 0.140 0.360 0.190 0.190 0.980 0.440 0.850 0.410 0.860

0.126 0.161 0.091 0.007 0.005 0.021 0.077 0.068 0.123 0.183 0.096 0.186 0.364 0.347 0.237 0.461

y0.60 1.10 2.30 1.87 3.61 7.90 9.16 9.49 10.24 9.70 14.83 22.20 45.02 57.01 65.00 53.34

0.7 0.3 y1.2 0.89 y0.15 1.3 5.12 6.74 5.76 9.84 4.95 4.18 6.2 y5.7 y9.2 y9.6

0.600 0.800 0.340 0.810 0.410 0.180 0.460 0.640 0.470 0.980 0.16 0.049 0.035 0.000 0.000 0.001

0.243 0.497 0.653 0.520 0.972 0.957 0.706 0.712 0.880 0.955 0.281 0.168 0.172 0.000 0.000 0.001

4th, 5th and 6th month following official listing. The results are not consistent with the findings reported by Paudyal et al. Ž1998. and Carter et al. Ž1997., who report that IPOs underwritten by reputable underwriters are better long-term investments in Malaysia and US, respectively. The results reported in Table 7 report that ‘pessimists’ outperform ‘optimists’ during the first 12 months following official listing. The difference between the mean returns of the two portfolios is significantly different from zero for months 1, 2, 3, 5, 6 and 10 Ž10% level or better.. The fact that the relationship between forecast accuracy and the long-term performance of Malaysian IPOs does not extend beyond the 10-month period could be due the fact that the average forecast horizon is only 8 months as reported earlier. The median returns for ‘pessimists’ are higher than for ‘optimists’ in all months. The difference between the median

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481

Table 7 Long-run performance measured by market-adjusted buy-and-hold returns stratified by forecast errors Mean, median and standard deviation of market-adjusted buy-and-hold returns are reported in percentages. The market-adjusted buy-and-hold returns are estimated using Eq. Ž5.. Companies with optimistic management earnings forecasts are located in segments 1, 2 and 5 of the Prediction Realisation Diagram. P-values indicate the level of significance for the test of differences Žh1 sh 2 vs. h1 /h 2 . in mean Ž t-test. and median ŽMann–Whitney test. market-adjusted buy-and-hold returns for IPOs with optimistic earnings forecasts and IPOs with pessimistic earnings forecasts. Months 1 2 3 4 5 6 7 8 9 10 11 12 18 24 30 36

Optimists Mean Median

Std. dev.

Pessimists Mean Median

Std. dev.

t-test p-value

MW p-value

y4.49 y5.06 y3.74 y3.51 y5.18 y3.11 0.15 1.26 1.59 y1.81 2.94 8.58 31.00 34.41 41.95 36.14

15.85 21.11 23.18 26.04 28.82 30.89 35.13 39.58 44.36 36.98 46.31 83.44 182.35 155.28 190.11 177.45

1.96 3.20 2.69 2.52 3.55 6.17 8.01 9.24 9.23 14.83 12.96 14.06 22.57 21.12 26.67 23.52

16.22 21.22 23.02 25.42 26.11 29.04 35.24 37.12 38.80 55.68 46.67 49.30 69.99 65.33 91.07 95.43

0.015 0.019 0.092 0.160 0.057 0.062 0.175 0.208 0.270 0.028 0.191 0.638 0.720 0.519 0.550 0.614

0.049 0.003 0.041 0.118 0.015 0.019 0.079 0.061 0.079 0.026 0.068 0.027 0.057 0.095 0.168 0.194

y9.46 y10.98 y9.92 y10.37 y13.00 y10.63 y9.74 y9.15 y10.46 y7.60 y9.85 y10.28 y12.56 y18.32 y16.76 y20.96

1.20 y0.38 y2.11 y0.03 0.27 2.72 5.84 2.75 0.04 2.00 1.83 7.18 2.69 7.29 2.17 1.08

returns of the two portfolios is statistically significant in all months except for months 4, 30 and 36. Firth Ž1998. reports a positive relationship between percentage earnings forecast error and the first year performance of Singaporean IPOs. In order to be able to compare our results with the results of this study, we repeated our calculations using the percentage forecast error ŽFE.. The results remain robust and are consistent with Firth Ž1998..33 ‘Pessimists’ outperform ‘optimists’ during the first 15 months following official listing. The difference between the mean returns of the two portfolios is significantly different for months 1, 3, 6, 7, 10 and 11 Ž10% level or better.. The medians are statistically different for all months except for month 36. In order to check for robustness of our results, we compared average first year returns for top and bottom deciles of IPOs in our sample by forecast error. The companies in the top decile are companies with highest positive forecast errors Ž‘over-pessimists’.. The companies in bottom decile are companies with the lowest negative forecast errors Ž‘over-optimists’.. Average first year market-adjusted buy-and-hold returns for ‘over-pessimists’ and ‘over-optimists’ are 32.66% 33

Unreported results available upon request.

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Table 8 Multivariate regression analysis of cross-sectional variation in initial and long-run returns MAIR s a q b 1 LnSIZEq b 2 AMUq b 3 LnAGEq b4 LnBVrMVq b5 OPTIMISTSq b6 INSIDERS q b 7 MARKETqDMULTIPLEq ´ ; MACR 1,2,3 s a q b 1 AMUq b 2 MAIRq b 3 OPTIMISTSq b4 INSIDERSq b5 SIZEq ´ ; T-statistics computed using White Ž1980. heteroskedasticity-consistent estimate of the standard errors of the coefficients in parenthesis; LnAGEs ln Ž1qlength of operating history.; AMUs1 for highly reputed underwriters, 0 otherwise; LnSIZEs ln ŽTotal Assets.; OPTIMISTSs1 if FE - 0, 0 otherwise; MARKET s% change in KLSE Index for 3 months prior to subscription; INSIDERS s % of retained ownership; MAIR s market-adjusted initial returns; MACR 1,2,3 s market-adjusted buy and hold returns for respective years; DMULTIPLEs times oversubscribed; LnBVrMVs Net tangible assets per sharer1st day closing price. MAIR

MACR 1

MACR 2

MACR 3

0.09 0.06 Ž0.54. y0.17 Žy1.54.

0.43 y0.09 Žy0.82. 0.01 Ž0.02. y0.07 Žy1.37. 0.31 Ž0.60.

0.60 0.04 Ž0.21. y0.05 Žy0.25. y0.24 Žy2.68. ) ) ) 1.10 Ž1.73. )

2.12 0.06 Ž0.28. 0.01 Ž0.03. y0.30 Žy1.89. ) 0.29 Ž0.46.

y0.04 Žy1.28.

y0.08 Žy1.41.

y0.15 Žy2.03. )

162 2.14 0.64

162 6.68 2.23 )

151 6.41 1.99 )

Intercept OPTIMISTS AMU MAIR INSIDERS LnBVrMV LnSIZE MARKET LnAGE DMULTIPLE

y0.59 Žy1.37. y0.71 Ž0.00. ) ) ) 0.02 Ž0.59. 0.01 Ž2.02. ) ) y0.01 Žy0.16. 0.01 Ž3.54. ) ) )

N R 2 Ž%. F

136 51.40 16.79 ) ) )

)

10% significance. 5% significance. ))) 1% significance. ))

and y0.10%, respectively. The difference between average Žmean. returns is statistically significant at 1% level.34 The results give further support for our Hypothesis 5. 6.3. Results of multiple regression models The results of the multiple regression model for MAIRs are shown in Table 8. The regression explains 51.40% of the variation in market-adjusted initial returns.35 The LnBVrMV, MARKET and DMULTIPLE variables have the expected signs and are highly significant suggesting that initial valuation is driven by BVrMV ratios, market sentiment, and levels of oversubscription. A negative coefficient for INSIDERS suggests lower underpricing for companies with high percentage of 34

P-value for two-sample two-tail paired t-test is 0.012. The difference between average 2- and 3-year returns is not statistically significant. 35 P-value for two-sample two-tail paired t-test is 0.012. The difference between average 2- and 3-year returns is not statistically significant.

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retained ownership. The coefficient for LnSIZE is positive but not statistically significant. The coefficient for OPTIMISTS is positive Žthough not statistically significant., thus confirming our findings that investors are not able to differentiate between biased and unbiased earnings forecasts prior to listings. The coefficient for AMU is negative, though not statistically significant. The lack of statistical significance may indicate a lack of competitive pressure in the Malaysian underwriting market or it could be due to our choice for the proxy for underwriters’ reputation. Regressions for long-term returns in years 1 to 3 are also reported in Table 8. Overall model fit is low with adjusted R 2 ranging from 2.14% to 6.68%. Coefficients for MAIR are, as expected, negative in all years and significant in years 2 and 3 after listing Žat 1% and 10%, respectively.. This result lends support to our ‘over-reaction’ hypothesis. AMU has an expected positive sign Žin years 1 and 3. though not statistically significant. Companies with a higher percentage of retained ownership seem to perform better in the long run. The coefficient for INSIDERS is positive in all years and significant in year 2 Žat 10% level.. The coefficients for LnSIZE are negative and statistically significant in year 3 Ž10% level., suggesting poor performance of big Malaysian companies in the long run. The coefficient for OPTIMISTS has an expected negative sign Žbut not statistically significant. in regression for 1 year buy-and-hold returns. 7. Conclusions Our results suggest that, on average, Malaysian IPOs are underpriced Ž99%. and that underpricing was greatest in the early 1980s and during the ‘hot issue’ period in 1993–1995. The cycles in volume seem to allow investors to predict the next year’s volume using the current year’s number of IPOs with a relatively high degree of accuracy. As expected, market-adjusted initial returns are, on average, higher for companies with highly reputed underwriters and with cautious earnings forecasts than for their counterparts with less highly reputed underwriters and optimistic forecasts. The differences in average Žmean and median. initial returns between respective sub-samples, however, are not statistically significant. Wealth relatives bigger than one were found after 1, 2 and 3 years after IPOs, when market index was used as a benchmark. This has been confirmed for years 1 and 2, using market-adjusted and raw returns for the sample and matching firms. However, the sample firms, on average, slightly underperform the matching firms 3 years after the IPO. The long-run after-issue performance measured by average buy-and-hold market-adjusted compounded returns for 6, 12, 24, and 36 months are found to be positive and significantly different from zero. The results remain robust after we account for skewness bias, by calculating a skewness-adjusted t-statistic with bootstrapped p-values. Cumulative abnormal returns are positive and statistically significant in all months, from month 7, up to 36 months after the IPOs. Overall, our findings on the long-run performance contradict the consensus

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of the IPO literature that documents a significant negative long-run performance in other countries. The results of our analysis on determinants of long-term returns reveal that companies with higher initial returns underperform those with low initial returns. The difference in average returns between these two groups of companies is statistically significant in all months from 1 up to 3 years after the IPO. The results do not give evidence that offers underwritten by more prestigious underwriters are better long-term investments as compared to those underwritten by less prestigious underwriters. Lack of support for our hypotheses on the underwriters role in valuation of IPOs raises concerns about the role of Malaysian banks in the primary market, particularly in the light of ongoing reforms in the banking sector.36 Finally, we find that companies with optimistic management earnings forecasts underperform their more cautious counterparts during the first 12 months after the IPOs. The results suggest that aftermarket returns, up to 1 year after listing, are at least partially driven by management earnings forecasts disclosed in IPO prospectuses.

Acknowledgements We would like to thank conference participants at the 1998 Asia-Pacific Finance Association and Nippon Finance Association Joint Conference in Tokyo, the 1998 National Taiwan University Finance Conference in Taipei, Wolfgang Aussenegg and Mike Theobald for helpful comments. We would like especially to thank Kalok Chan Žthe editor. and an anonymous referee for numerous constructive suggestions. Mr. Dean Flavell’s research assistance is gratefully acknowledged.

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