the relation between ipo underpricing and litigation risk revisited: changes between 1990 and 2002

The Relation between IPO Underpricing and Litigation Risk Revisited: Changes between 1990and 2002Author(s): Yun (Ellen) ZhuSource: Financial Management, Vol. 38, No. 2 (Summer, 2009), pp. 323-355Published by: Wiley on behalf of the Financial Management Association InternationalStable URL: http://www.jstor.org/stable/40388675 .

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The Relation between IPO Underpricing and Litigation Risk Revisited: Changes

between 1990 and 2002 Yun (Ellen) Zhu*

This paper reexamines the litigation risk hypothesis of initial public offering (IPO) underpricing in different legal and economic environments. When litigation risk is reduced in the three-year period after the enactment of the Private Securities Litigation Reform Act of 1995, firms

' litigation risk

plays a less significant role in IPO underpricing strategy. Furthermore, underpricing deters more traditional IPO lawsuits compared to that effect in the pre- 199 5 period. In the period after that, however, there is another structural change in which firms again use underpricing as insurance against IPO lawsuits. This underpricing may actually have led to greater litigation relating to IPO allocation irregularities.

Initial public offerings (IPOs) typically experience a significant increase in the first day closing price from the offer price. Loughran and Ritter (2004) document a 15% first day return from 1990 to 1998. Ljungqvist (2007) groups theories of underpricing into four broad headings: 1) asymmetric information, 2) institutional reasons, 3) control considerations, and 4) behavioral approaches. One such theory, characterized as having an institutional basis, is the litigation risk hypothesis (LRH). This paper reassesses the effectiveness of this hypothesis in explaining IPO underpricing following the passage of the Private Securities Litigation Reform Act of 1995.

The LRH proposes that issuers and investment banks use underpricing as insurance against lawsuits, as lowering the offer price reduces both the probability of being sued and the damages that plaintiffs can recover (Ibbotson, 1975; Tinic, 1988; Hughes and Thakor, 1992; Hensler, 1995). Lowry and Shu (2002) argue that a simultaneous equations system is necessary since an IPO's litigation risk and underpricing are actually two interdependent endogenous variables. Their relationship can be expressed as two effects: 1) the insurance effect and 2) the deterrence effect. On one hand, issuers expecting higher litigation risk will underprice their IPOs more as a form of insurance against future lawsuits. On the other hand, issuers with higher IPO underpricing have a better chance of deterring lawsuits. They find evidence supporting both effects using the two-stage estimation method suggested in Maddala (1983). In this paper, I follow their approach to test the LRH in different legal and economic environments before and after 1995.

This paper is based on a chapter of my Ph.D. dissertation at Michigan State University. I am very grateful to my dissertation committee members, Ted Fee (cochair), Naveen Khanna (cochair), and Jennifer Marietta-Westberg for valuable suggestions and support. I appreciate the helpful comments of Sergey Barabanov, Alexander Butler, Carl Chen, Charles Hadlock, Fuad Hasanov, Wendy Jennings, Mohinder Parkash, Austin Murphy, Rina Ray, Rajeev Singhal, Jeffrey Wooldridge, Fei Xie, and especially the many constructive suggestions of William G. Christie (the editor) and one anonymous referee. I have also benefited from the comment of seminar participants at Michigan State University, Oakland University, Seattle University, University of Dayton, University of Toledo, Worcester Polytechnic Institute, the 2005 EFA meeting, and the 2005 FMA meeting. All remaining errors are my own.

* Yun (Ellen) Zhu is an Assistant Professor of Finance at Oakland University, Rochester, MI. Financial Management • Summer 2009 • pages 323 - 355



324 Financial Management • Summer 2009

On December 22, 1995, Congress enacted the Private Securities Litigation Reform Act of 1995 (Reform Act), which adopted a series of procedural hurdles to securities fraud class actions. Evidence indicates that firms' litigation risk is reduced in the post- 1995 period (Grundfest and Perino, 1997; Beatty, Drake, and Hogan, 2002; Perino, 2003; Bajaj, Mazumdar, and Sarin, 2003). Meanwhile, the economic environment changed significantly after 1995. During this period, the US stock market experienced a large boom and bust cycle featuring particularly unusual behavior from IPOs. There is also a structural change in what "IPO litigation" means after 1998. In 2001, a new type of lawsuit, IPO allocation cases, was filed in massive numbers. In order to see the impact of this changed legal and economic environment on the significance of LRH, I reexamine the LRH during this unique period and in these unique cases.

This paper presents four major results. First, when compared to the pre-1995 period, I find that firms' litigation risk plays a less significant role in their IPO pricing strategy in the three years after 1995 (1996-1998) through reduced litigation risk and a healthy stock market. Second, while firms' litigation risk is reduced in the three years following 1995, the deterrence effect becomes much stronger when compared to that in the pre-1995 period. Third, in the period after 1998, 1 find results that are consistent with the insurance effect; IPO firms do use IPO underpricing as insurance against IPO allocation lawsuits. Fourth, in the period after 1998, issuers underpricing their IPOs more heavily have no advantage in deterring IPO allocation lawsuits as I find IPO underpricing actually triggers these allocation cases. I conclude that the evidence indicates that LRH is very sensitive to the legal and economic environment. Issuers have other ways of handling litigation risk in IPOs rendering a broad and blunt instrument such as underpricing less necessary.

This paper contributes to the literature in three ways. First, I reexamine the LRH in different legal and economic environments. I find that the significance of the LRH changes along with variations in the litigation risk. Second, I test the LRH using a new type of lawsuit, IPO allocations cases, and find differing results from traditional IPO cases. Third, in addition to the two-stage estimation method, I use an alternative generated instrument approach developed in Wooldridge (2001), which is a better tool for coefficient estimation.

The rest of this paper is organized as follows. Section I discusses the related literature regarding the LRH and the Reform Act. Section II describes the data. Section III discusses the methodolo- gies. Section IV presents multivariate test evidence on the LRH using the sample of traditional IPO cases. Section V presents multivariate test evidence in connection with the LRH using a sample of IPO allocation cases. Section VI posits my conclusion.

I. Related Literature

A. Litigation Risk Hypothesis

Ibbotson (1975) was the first one to suggest that issuers and investment banks may use IPO underpricing as insurance against lawsuits. Tinic (1988) models expected legal liabilities as an increasing function of IPO underpricing and demonstrates that underpricing has increased following the enactment of the Securities Act of 1933, which is assumed to have increased firms' litigation risk. Hughes and Thakor (1992) and Hensler (1995) support the LRH by analyzing the trade-off between expected litigation cost and current revenue loss from underpricing in different model settings. Conversely, Prabhala and Puri (1999) argue that the findings in Tinic (1988) can be explained by differences in IPO risk instead of differences in litigation risk. Drake and Vetsuypens (1993) find that underpricing of sued IPOs is the same as that of nonsued IPOs. They conclude that underpricing does not deter lawsuits, which are typically triggered by unfavorable



Zhu « IPO Underpricing and Litigation Risk 325

news in the aftermarket. In addition, Ibbotson, Sindelar, and Ritter (1988), Alexander (1993), and Ritter (2003) oppose the LRH by arguing that the infrequency of IPO lawsuits and low settlement costs as compared to the considerable loss from underpricing barely make litigation avoidance an important justification for IPO underpricing. Keloharju (1993) challenges the LRH by finding significant IPO underpricing in Finland where issuers have almost no legal liability. Hanley and Hoberg (2008) indicate that IPO issuers strategically increase their disclosures instead of reducing the offer price as insurance against lawsuits when bad information is revealed.

In a recent paper, Lowry and Shu (2002) point out that IPO underpricing and litigation risk are actually two endogenously determined variables. They examine the LRH from two angles. First, issuers expecting higher litigation risk might use greater IPO underpricing as insurance against future lawsuits (the insurance effect). Second, more highly underpriced IPOs may deter further lawsuits (the deterrence effect). Using a simultaneous equations system, they support the LRH by finding both effects to be significant. Ljungqvist (2007) has concerns about the strength of their choice of instrumental variables. Following their model set up, I examine the LRH in the altered legal and economic environment that exists after 1995.

From a legal perspective, IPO-related class action lawsuits are mainly brought under Sections 11 and 12 of the Securities Act of 1933 and Rule 10b-5 of the Securities Exchange Act of 1934. For all of the Section 11 cases, plaintiffs' damages are calculated based on the difference between the offer price and either the price on lawsuit filing day or the sale price. Therefore, LRH supporters argue that lowering the offer price is likely to decrease both the probability of being sued and potential damages. Alexander (1993), however, points out that this argument ignores the fact that "investors can also, and almost invariably do, bring claims under the 1934 Act along with claims under the 1933 Act." The 1934 Act makes the LRH virtually ineffective as the damages under Rule 10b-5 are based on the shareholders' purchase price, which can be either the offer price or the aftermarket price. As a result, despite the amount that issuers' underprice their IPOs, they can still be sued as long as the aftermarket price is high enough to cover legal fees.

B. The Private Securities Litigation Reform Act of 1995

On December 22, 1995, Congress enacted the Private Securities Litigation Reform Act of 1995, which added Section 27(a)(3) to the Securities Act of 1933 and Section 21D(a)(3) to the Securities Exchange Act of 1934. This new law adopted a series of procedural obstacles to securities fraud class actions to discourage abusive lawsuits, thereby reducing firms' litigation risk. These obstacles include, but are not limited to the following:

1. The replacement of "joint and several liabilities" by "proportionate liability" reduces the plaintiffs' incentive to look for "deep pockets";

2. Plaintiffs' stay of discovery in a pending motion to dismiss reduces firms' defense costs; 3. A new lead plaintiff appointment process and the prohibition of bonus payments to lead

plaintiffs discourage lawyers from hiring "professional plaintiffs"; 4. A heightened pleading standard increases the cost of lawsuits; 5. A new 90-day bounce back rule prevents cases from rushing into courts; 6. The mandatory sanction of Rule 1 1 of the Federal Rules of Civil Procedure deters any party

from making frivolous lawsuits; 7. The comprehensive disclosure of the provisions of settlement and attorneys fees and the

limitation on attorneys' fees to a "reasonable percentage" of any damage award reduces attorneys' profits.




Evidence of decreased litigation risk following the Reform Act exists in both court practices and academic research. 1 Grundfest and Perino (1997) find that class action securities fraud litigation was filed at a rate of approximately 176 cases per year prior to the Reform Act. This rate dropped to 148 cases in 1996, a 16% drop in total litigation volume. Bajaj, Mazumdar, and Sarin (2003) find that there was an immediate drop in the number of federal cases, from 191 in 1995 to 1 19 in 1996. Although the number of state cases increased from 65 to 80, there was a drop in total cases, from 256 in 1995 to 199 in 1996. Perino (2003) uses data from 1996 to 2001 and draws a similar conclusion.

All studies listed above employ univariate tests. Since the Reform Act was designed to reduce firms' litigation risk, it may have changed the characteristics of IPO firms. Particularly, some small and risky companies that prefer staying private may go public with reduced litigation risk. Without controlling for firms' characteristics, these univariate comparisons cannot tell much about changes in litigation risk. To my knowledge, Beatty, Drake, and Hogan (2002) is the only paper that conducts both univariate and multivariate tests. They control for changes in the IPO market by estimating a logistic model of the probability that an IPO will be involved in lawsuits. The control variables include revenue, offer size, profitability, equity level, auditor type, high-tech indicator, market return, stock return volatility, and a post- 1995 indicator. They find the conditional probability of being sued decreases by 4.3% after 1995. Their results suggest that the litigation risk of IPO firms declined in the post- 1995 period. Of course, as pointed out in their paper, the litigation risk changes could also be attributed to structural changes in the economic environment in the later 1990s such as the booming stock market, accounting misrepresentations, analyst behavior to increase aftermarket prices, the internet bubble, and shifts in the structure of the investment banking industry. I study the LRH in this new legal and economic environment.

II. Data

Data on US common stock IPOs issued from 1990 to 2002 are collected from the Thom- son Financial Securities Data (SDC). Closed-end funds, unit offerings, REITs, financial firms, reverse LBOs, ADRs, spin-offs, firms listed in the small capital market or the OTC market, and firms without exchange information are excluded. The sample ends in 2002, as I need at least three years after the offering date to collect lawsuit information. The list of IPO lawsuits is obtained from the Security Class Action Alert newsletter (SCAA), the Stanford Securi- ties Class Action Clearinghouse (http://securities.Stanford.edu), and the Initial Public Offering Securities Litigation website (http://www.iposecuritieslitigation.com). Case information is collected by searching these three resources and the Public Access to Court Electronic Records (PACER) (http^/pacer.psc.uscourts.gov), the Guardi and Co. class action administration website (http^/www.gilardi.com/allcases.html), company SEC filings, LexisNexis newswire, and LexisNexis legal research. An IPO firm is identified as sued if the class action lawsuits are related to its IPO.

Due to data limitations, my sample includes cases filed only in federal courts. Although this may bias my results, I believe the bias is minor for several reasons. As introduced in the last

'Courts appear to apply the Reform Act in their decisions. In Steckman et al v. Hart Brewing, Inc. et al, the court order states, "The Court also notes the impact of the ... Reform Act of 1995 .... Through this Act, Congress has encouraged the use of motions to dismiss. One of the salient features of the 1995 Reform Act is ... to protect against the abusive . . . lawsuits like this one 'with only faint hope that the discovery process might lead eventually to some plausible cause of action.'. . ." This case was dismissed with prejudice on December 24, 1996.




section, the overall lawsuit rate still decreases significantly after the enactment of the Reform Act, although some cases shift to state courts. Furthermore, state security laws are characterized by a great diversity of language and interpretation and apply only to transactions within states (Ratner, 1998). Damages that can be recovered from state courts are much smaller than those handed down from federal courts, thus, naturally deterring case shifts. Additionally, the majority of IPO cases are filed in federal courts as IPOs in my sample are typically offered and traded nationally.2

A. IPO Class Action Lawsuits in the Pre- and Post-1995 Periods

Table I lists the number of IPOs, the number and percentage of IPO lawsuits, and the average months between the offering month and the lawsuit filing month by issue year.3 I classify the IPO cases into two groups: 1) traditional IPO cases as shown in Panel A and 2) IPO allocation cases as illustrated in Panel B.4 Due to the three-year statute of limitations, the lawsuits related to 1993-1995 IPOs could be filed before or after the Reform Act enactment. Consequently, they may or may not be affected by the Reform Act since this law only applies to cases filed after December 22, 1995 (Lerach, 1998). To avoid this issue, I exclude 1994 and 1995 IPOs from my sample. 1993 IPOs are still included since the latest 1993 IPO case was filed before the enactment. The sample includes 1,000 IPOs issued from 1990 to 1993, and 1,883 IPOs issued from 1996 to 2002. Among them, 6.5% of the 1990-1993 IPOs and 4.1% of the 1996-2002 IPOs were sued under traditional IPO cases. Overall, the traditional IPO lawsuit rate dropped by 2.4% after 1995. Furthermore, this rate started to decrease in 1994 and 1995 and remained at a low level from 1996 to 2000. These results indicate that traditional IPO lawsuits were deterred for many years in the post- 1995 period, which is consistent with earlier research. Very few traditional IPO lawsuits were filed in 2001 and 2002, but the lawsuit percentage rate rebounded due to an even smaller number of IPOs in the bear market during these two years. In total, I find 143 traditional IPO cases (5%) in 1990-2002 (with 1994 and 1995 excluded). The robustness check results are statistically indifferent from those reported when I exclude 1993, 2001, and 2002 IPOs.

In 2001, there was an outbreak of IPO allocation lawsuits in the Southern District Court of New York around the time that New York State Attorney General Eliot Spitzer launched a broadside lawsuit against investment banks. As indicated in Panel B, only IPOs from 1998 to 2000 were exposed to this type of lawsuit. In my sample, there were 252 IPO allocation cases accounting for 27.8% of the 906 IPOs issued during these three years. Unlike traditional IPO cases that generally accuse the issuers of inflating the offer prices, these cases charge the underwriters and

2Beatty, Drake, and Hogan (2002) identify only 13 IPO state cases from 1991 to 1999. Given that their sample size is much larger than mine, I believe that the number of state cases left after my stricter screening process will be insignificant. 3 Since the number of truly eligible IPOs that can be sued must be closely determined by the raw return that the firm is experiencing in the aftermarket, I investigate both the full IPO sample and the eligible IPO samples that have negative cumulative returns within one year, two years, or three years after offering. All test results of eligible IPO samples are statistically similar to the results of a full sample as reported in this paper. 4 The traditional IPO case typically alleges that the IPO registration statement is materially false as it fails to disclose the issuer's improper accounting practice, the CEO's malpractice, and other important information. The IPO allocation case, however, alleges underwriters' laddering activity. Although issuers themselves may not be directly involved in these activities, they will be named as defendants along with the underwriters accused of omitting this information from the IPO registration statement.




Table I. Distribution of Sampie Firms across Years

The sample consists of initial public offerings (IPOs) issued between 1990 and 2002 that are available in the Thomson Financial Securities Data database. Closed-end funds, unit offerings, REITs, financial firms, reverse LBOs, ADRs, spin-offs, firms without exchange information, and firms listed in the small capital market or the OTC market are excluded. An IPO firm is identified as sued if the federal class action lawsuits related to its IPO are listed in the Security Class Action Alert newsletter, the Stanford Securities Class Action Clearinghouse (http://securities.Stanford.edu), and the Initial Public Offering Securities Litigation website (http://www.iposecuritieslitigation.com). Average months between IPO and filing of lawsuits are calculated as the average of months between the IPO offering month and the lawsuit filing month. Panel A illustrates the distribution of traditional IPO cases. Panel B demonstrates the distribution of IPO allocation cases. Traditional IPO cases allege the issuer's improper accounting practice and the CEO's malpractice, etc. IPO allocation cases are targeted at underwriters' and certain institutional owners' "laddering" activities.

Panel A. Traditional IPO Cases

IPO Issue Year # IPOs # Traditional % Traditional Average Months IPO Cases IPO between IPO and

Cases Filing of Traditional IPO Cases

1990 94 4 4.26% 14.25 1991 238 14 5.88% 11.21 1992 296 19 6.42% 14.42 1993 372 28 7.53% 13.07 Subtotal 1,000 65 6.50% 13.14 1994 323 10 3.10% 13.50 1995 361 18 4.99% 11.89 Subtotal 684 28 4.09% 12.46 1996 530 15 2.83% 13.07 1997 350 15 4.29% 12.40 1998 203 12 5.91% 10.08 1999 391 13 3.32% 17.85 2000 312 11 3.53% 12.45 2001 50 7 14.00% 16.71 2002 47 5 10.64% 12.00 Subtotal 1,883 78 4.14% 13.45 Total 3,567 171 4.79% 13.17 Total w/o 1994 & 1995 2,883 143 4.96% 13.31

Panel B. IPO Allocation Cases

IPO Issue #IPOs #IPO %IPO Average Months Year Allocation Allocation between IPO and

Cases Cases Filing of IPO Allocation Cases

Ï998 203 8 3.94% 35jÕÕ 1999 391 155 39.64% 24.75 2000 312 89 28.53% 16.58 Total 906 252 27.81% 22.19




some buyers with inflation of aftermarket prices.5 Consequently, IPOs with higher underpricing may be more likely to trigger IPO allocation cases, an action in direct opposition to the LRH's prediction regarding traditional IPO cases. Thus, I examine these two types of IPO lawsuits separately. In addition, instead of filing around 13 months after the offering date as in traditional IPO cases, IPO allocation cases were not filed until 2001. Therefore, although the number of IPO allocation cases was massive, the fact that they were filed in one year and almost exclusively in one location leads us to believe that they were unique events caused by the bear market and by the use of potential insider information by select lawyers and plaintiffs in Southern Manhattan.

Table II lists IPOs' case decisions and the average decision time length between the lawsuit filing month and the case decision month.6 For settled cases, I further present the average settlement amount and settlement/proceed ratio. Panel A indicates the characteristics of traditional IPO cases. About 66.2% of 65 cases filed prior to 1995 were settled, while 53.8% of the 78 cases filed following 1995 were settled. The settlement rate of traditional IPO cases declined by 12.4% and the average settlement/proceed ratio decreased by 1.6% from the pre- to the post- 1995 period. In contrast, the dismissal/termination rate increased 9% following 1995, which is consistent with Foster, Martin, Juneja, and Dunbar (2000). Furthermore, it took traditional IPO cases 2.8 more months to be settled and 1.4 more months to be dismissed by the courts in the post- 1995 period. Overall, my results support earlier studies that firms' risk exposure to traditional IPO cases was reduced and these cases were more difficult to be settled after 1995.

Panel B illustrates the decision information of IPO allocation cases. About 96.4% of 252 IPO allocation cases were settled with issuers within four years with a 2.94% average settlement/proceed ratio.7 These high settlement rates, lengthy decision times, and low average settlement/proceed ratios further confirm that IPO allocation cases were unique events. The low average settlement/proceed ratio is also consistent with the fact that the main targets of these cases were underwriters instead of issuers. From this point forward, I will concentrate on traditional IPO cases. IPO allocation cases will be studied separately in Section V.

5 A typical IPO allocation case such as Gene Meyers et al. v. Immersion Corporation et al. alleges violations of Sections 1 1 , 12(a)(2), and 15 of the Securities Act of 1933 and Section 10(b) of the Securities Exchange Act of 1934 and Rule 10b-5 promulgated there under. On November 12, 1999, Immersion issued an initial public offering at an offering price of $12 per share. Later that day, the price went up to $20 per share. During the Class Period, Immersion's common stock traded as high as $79 per share. The plaintiffs think this "impressive" performance was the result of the Defendants' unlawful practices. The complaint alleges that: 1) the Underwriter Defendants had solicited and received excessive and undisclosed commissions from certain investors in exchange for which the Underwriter Defendants allocated to those investors material portions of the restricted number of Immersion shares issued in connection with the Immersion IPO, and 2) the Underwriter Defendants had entered into agreements with customers whereby the Underwriter Defendants agreed to allocate Immersion shares to those customers in the Immersion IPO in exchange for which the customers agreed to purchase additional Immersion shares in the aftermarket at predetermined prices. The detailed information about IPO allocation cases can be found at http://www.iposecuritieslitigation.com andhttp^/securities.stanford.edu/IPO^ases/master.allegations.html. These cases were later consolidated and settled with a global settlement.

6The case decision month is based on the date of District court final judgment with prejudice, the date of preliminary judgment, the date on the settlement document from the Guardi and Co. class action administration website, the date listed in firms' SEC filings, or the case close date from court dockets.

7A11 settlement data with issuers are collected from the consolidated preliminary settlement order of August 2005, which is subject to potentially minor changes as the final decision is still pending. For underwriters, 10 big investment banks

agreed to a $1.4 billion settlement with the SEC in 2003. However, I was unable to locate data regarding the allocation of this settlement to each IPO allocation case.




Table II. Lawsuit Status and Resolution Characteristics

The case decision information is collected by searching the Security Class Action Alert newsletter, the Stanford Securities Class Action Clearinghouse (http://securities.Stanford.edu), the Initial Public Offering Securities Litigation website (http://www.iposecuritieslitigation.com), the Public Access to Court Elec- tronic Records (http^/pacer.psc.uscourts.gov), the Guardi and Co. Class Action Administration website (http^/www.gilardi.com/allcases.html), company SEC filings, LexisNexis newswire and LexisNexis legal research. Cases are categorized by IPO issue year from 1990 to 2002 (excluding 1994 and 1995). Average decision time length is the average number of months between the lawsuit filing month and the case decision month. Average settlement amount is calculated as the average of the total settlement fund amount. Average settlement/proceed ratio is calculated as the ratio of the average settlement amount to the IPO

proceeds raised. Panels A and B illustrate the characteristics of traditional IPO cases and IPO allocation cases.

Issue Settled Cases Dismissed or Pending Year Terminated Cases Cases

# Cases # Cases Average Average Average # Cases D/T Average # Cases Settled Decision Settlement Settlement/ Decision Pending

Time Amount Proceed Time Length ($millions) Ratio Length

Panel A. Traditional IPO Cases

1990 4 2 40.00 6.70 19.46% 2 12.00 0 1991 14 12 28.08 4.43 8.78% 2 7.50 0 1992 19 11 24.09 5.19 12.33% 7 15.57 1 1993 28 18 27.89 3.16 10.71% 9 17.67 1

Subtotal 65 43 27.53 4.19 11.08% 20 15.35 2 1996 15 8 24.75 3.70 7.23% 7 16.14 0 1997 15 11 33.82 5.53 10.64% 4 21.50 0 1998 12 7 29.57 6.49 16.12% 5 15.00 0 1999 13 2 33.00 7.05 7.03% 7 20.29 4 2000 11 8 33.63 7.36 7.45% 3 9.67 0 2001 7 4 29.75 7.63 6.66% 3 13.33 0 2002 5 2 21.00 2.03 3.79% 2 16.50 1

Subtotal 78 42 30.31 5.86 9.44% 31 16.71 5 Total 143 85 28.91 5.01 10.27% 51 16.18 7

Panel B. IPO Allocation Cases

1998 8 8 47.13 2.09 4.58% 0 0.00 0 1999 155 150 47.55 3.11 3.06% 0 0.00 5 2000 89 85 46.92 3.60 2.58% 0 0.00 4

Total 252 243 47.31 3.25 2.94% 0 0.00 9



Zhu » IPO Underpricing and Litigation Risk 331

B. Descriptive Statistics of Nonsued IPOs and Traditional IPO Cases in the Pre- versus Post-1995 Period

Descriptive statistics are illustrated in Table III.8 Panel A compares IPO characteristics in the pre- and post- 1995 periods with IPO allocation cases excluded. Panel B evaluates the characteristics of nonsued IPOs and traditional IPO cases in both pre- and post- 1995 periods. For the post- 1995 period, I primarily use the period 1996-1998 for traditional IPO cases to exclude the unusual boom and the bust periods that followed. The period after that is discussed separately in Sections IV and V and mainly focuses on IPO allocation cases since these are the cases that are the most relevant in this period.9 IPO firms' characteristics data are from the SDC and CRSP. The results in the pre- 1995 period are consistent with earlier findings; however, those in the post- 1995 period illustrate a different story.

Initial return is defined as the percentage change between the offer price (USPR) and the closing price. 10 As Panel A indicates, the average initial return significantly increases after 1995. Panel B demonstrates that the average initial return of traditional IPO cases is 6% larger than that of nonsued firms in the pre- 1995 period. However, this relationship does not appear in the new environment after 1995. There is no significant difference between the initial returns of nonsued IPOs and firms involved in traditional IPO cases in the post- 1995 period. The interpretation of these results is ambiguous due to the endogeneity of IPO underpricing and litigation risk. The multivariate tests in Section IV will offer interpretations that are more appropriate.

Price update is the percentage change between the midpoint of the filing price range (MFILE) and the offer price from SDC. As shown in Panel A, the price update level does not change much after 1995. Panel B shows traditional IPO cases have a higher price update than nonsued firms both prior to and following 1995, but the test's significance vanishes in the post- 1995 period. In other words, firms pricing more aggressively are more likely to be involved in traditional IPO lawsuits, but this likelihood decreases slightly after 1995.

The lead underwriter rank is the same as that used in Loughran and Ritter (2004). n Panel A indicates that IPOs are underwritten by more prestigious investment banks after 1995. Panel B demonstrates that IPOs involved in traditional IPO cases were underwritten by more prestigious investment banks in the pre- 1995 period. After 1995, however, there is no significant difference

8 From now on, only Section 11, 12, and Rule 10b-5 lawsuits are included in the sample as these cases are related to the IPO offer price and the LRH argument. Whether Section 11, 12, and Rule 10b-5 lawsuits should be considered together or whether Section 1 1 lawsuits should be considered separately is a matter for debate. My primary sample includes all IPO-related lawsuits under any of these three laws. I use Section 1 1 lawsuits separately as a robustness check. All test results of Section 1 1 samples are statistically similar to the results reported in this paper. I also use cases filed within two

years, one and one-half years, and one year after the IPO offering date because Lowry and Shu (2002) think "a lawsuit that occurs long after an IPO is more likely prompted by random stock price fluctuations that are not in the managers' information set at the time of IPO." All test results are statistically similar to the results of a full sample as reported in this paper. 9There were many things going on after 1998. First, Loughran and Ritter (2004) define the years 1999 and 2000 as the Internet bubble period. This included a 65% average IPO underpricing, more than four times the 15% found during the 1990-1998 period. In addition, there was a structural change in what "IPO litigation" meant after 1998. The stock market downturn in 2001 brought more than 300 "IPO allocation" lawsuits, more than double the total number of IPO lawsuits over my entire sample period. I think it is necessary to study this period and event separately. 1 following Lowry and Schwert (2004), to determine the closing price, I use the first available closing price data from CRSP within 14 calendar days after the offering. If CRSP data are not available, I obtain the closing price on the first

trading day (PRSDAY) from SDC. If that is still not available, initial return is equal to the percentage change between the offer price and the closing price one day after the offer (PCT1DAY) from SDC. 11 It is constructed in a way similar to Carter, Dark, and Singh (1998). The data are available on Dr. Ritter's web page (http://bear.cba.ufl.edu/ritter/ipodata.htm). I take the average when an IPO has more than one lead underwriter.




Table III. Descriptive Statistics of Nonsued IPOs and Traditional IPO Cases before and after 1995

The sample consists of 935 nonsued IPOs from 1990 to 1993 and 1,033 nonsued IPOs from 1996 to 1998. There are 41 IPOs from 1990 to 1993 and 40 IPOs from 1996 to 1998 involved in Section 11, 12, and Rule 10b-5 traditional IPO lawsuits. Some variables are based on fewer observations due to missing data. Initial return is the percentage change between the offer price and the first closing price. Price update is the percentage change between the midpoint of the filing price range in the prospectus and the offer price. Underwriter rank is the lead underwriter rank measure used in Loughran and Ritter (2004), with higher ranks representing higher quality underwriters. Market capitalization is the first closing price multiplied by the number of shares outstanding after offering in all markets. Proceeds raised are the offer price multiplied by the shares offered in all markets. Both market capitalization and proceeds raised are measured in millions of 1983 dollars using the Consumer Price Index. Standard deviation equals the standard deviation of daily returns during the first year starting one month after the IPO. Age is the difference between the firm's IPO offering year and the founding year. IPO firms are labeled as high-tech, venture capitalist backed, traded on the NYSE/AMEX, and with secondary offering in all markets according to the SDC classifications. Panel A compares IPO firms' characteristics in the pre-1995 period to that in the post- 1995 period. Panel B compares traditional IPO cases and nonsued firms in the pre-1995 period versus the post- 1995 period. The pre-1995 period represents the years 1990-1993. The post-1995 period represents the years 1996-1998.

Panel A. Pre-1995 Period vs. Post-1995 Period

Pre-1 995 Period Post-1 995 Period Wilcoxon Test Median Median f-test Mean Mean

(S^) (S.E1) Initial return 0.0652 0.0982 -4.0340***

0.1244 0.1644 -4.1064*** (0.0060) (0.0076)

Price update 0.0000 0.0000 1.0690 0.0042 -0.0033 0.7972 (0.0070) (0.0065)

Underwriter rank 8.0000 8.0000 -4.8920*** 6.8120 7.2774 -4.7909*** (0.0747) (0.0630)

Market capitalization 41 .00 74.20 - 1 1 .6590*** 173.00 254.00 -1.1093 (54.40) (49.90)

Proceeds raised 17.30 22.40 -7.4840*** 31.70 40.10 -2.1417** (1.89) (3.36)

Standard deviation 0.0407 0.0468 -7.7280*** 0.0439 0.0492 -6.4850*** (0.0006) (0.0006)

Age 8.0000 7.0000 5.1680*** 16.5259 13.5651 3.3138*** (0.6632) (0.6018)

% High tech 42.93% 52.28% % On NYSE/AMEX 15.57% 17.33% % Venture capitalist backed 48.62% 36. 1 9% % With secondary offering 41 .91% 35.88%

(Continued)



Zhu • IPO Underpricing and Litigation Risk 333

Fable III. Descriptive Statistics of Nonsued IPOs and Traditional IPO Cases before and after 1995 (Continued)

Panel B. Nonsued IPO Firms vs. Traditional IPO Cases in the Pre-1995 Period vs. Post-1995 Period

Pre-1 995 Period Post-1 995 Period

Nonsued Traditional Nonsued Traditional Wilcoxon IPOs IPOs IPOs IPOs Test

Cases Cases f-test

Median Median Wilcoxon Median Median Mean Mean Test Mean Mean

(S.E.) (S.E.) (-test (S.E.) (S.E.) Initial return 0.0625 0.1375 (2.4480)** 0.0962 0.1250 (0.2120)

0.1220 0.1773 (1.8617)* 0.1655 0.1372 0.7077 (0.0061) (0.0308) (0.0078) (0.0219)

Price update 0.0000 0.1000 (3.6490)*** 0.0000 0.0667 (1.5110) 0.0003 0.0949 (2.7407)*** (0.0044) 0.0254 (0.8637) (0.0071) (0.0249) (0.0066) (0.0279)

Underwriter rank 8.0000 8.0000 (2.9570)*** 8.0000 8.0000 (1.2210) 6.7620 7.9512 (3.2073)*** 7.2664 7.5625 (0.8910) (0.0772) (0.1813) (0.0644) (0.2959)

Market capitalization 39.10 67.90 (3.1270)*** 74.10 74.40 (0.5030) 175.00 121.00 0.1995 259.00 130.00 0.4862 (56.80) (25.80) (51.80) (23.80)

Proceeds raised 16.70 23.50 (3.4540)*** 22.30 23.70 (1.4530) 31.40 36.90 (0.5784) 40.00 44.30 (0.2448) (1.96) (5.33) (3.48) (8.16)

Standard deviation 0.0403 0.0482 (3.5030)*** 0.0462 0.0657 (5.1010)*** 0.0435 0.0514 (2.7712)*** 0.0485 0.0688 (6.5991)*** (0.0006) (0.0025) (0.0006) (0.0055)

Age 9.0000 7.0000 2.2960** 7.0000 7.5000 (0.4810) 16.8523 9.4634 2.2946** 13.5738 13.3421 0.0728 (0.6884) (1.5314) (0.6150) (2.9249)

% High tech 42.78% 46.34% 52.27% 52.50% %OnNYSE/AMEX 15.40% 19.51% 17.04% 25.00% % Venture capitalist 48.07% 60.98% 36.34% 32.50%

backed % With secondary 41.39% 53.66% 35.43% 47.50%

offering *** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level.

regarding the underwriter rank between nonsued IPOs and traditional IPO cases. As in Grundfest and Perino (1997), my results suggest that the incentive of plaintiffs and lawyers to look for a "deep pocket" gets much weaker after 1995.12

12The defendant's liability used to be "joint and several," which means one single "deep pocket" defendant might be liable for the entire amount of damages regardless of the individual's actual degree of fault. The Reform Act adopted proportionate liability under which each defendant is only liable for his or her percentage of total fault.




Market capitalization is the first closing price multiplied by the number of shares outstanding after the offering in all markets (OUTPF) from SDC. Proceeds raised equal the offer price multiplied by the shares offered in all markets (TOTSHSMIL) from SDC. Both market capitalization and proceeds are measured in millions of 1983 dollars using the Consumer Price Index. Panel A indicates that both size measures increase significantly after 1995. Panel B confirms that the median market capitalization of sued firms is $28.8 million more and the median proceeds of sued firms is $6.8 million more than those of nonsued firms in the pre-1995 period; however, the size differences become much smaller in the post- 1995 period. The test significance also disappears.

Stock volatility is the standard deviation of daily returns from CRSP during the first year, starting one month after the IPO. Panel A demonstrates that stock volatility significantly increases after 1995. This could reflect the higher uncertainty of the IPO market in the late 1990s. Panel B confirms that the standard deviation of traditional IPO cases is significantly higher than that of nonsued firms in both pre- and post- 1995 periods. This indicates that plaintiffs target firms with a steep price drop as those who may have been involved in wrong doing.

Age is the difference between IPO offering year and the firm's founding year, following Loughran and Ritter (2004). On average, IPO firms are 2.5 years younger after 1995. This might suggest that underwriters are willing to take younger firms public in the post- 1995 period. Panel B illustrates that traditional IPO cases are, on average, seven years younger than nonsued IPOs in the pre- 1 995 period suggesting that older firms seem subject to a reduced litigation risk. However, there is no significant age difference between the two groups in the post- 1995 period.

IPO firms are labeled as high-tech (HIGHTECHCODE), venture capitalist backed (VE), traded on the NYSE/AMEX (EXCHC), and with secondary offerings in all markets (TOTSECSHROMIL) according to SDC classifications. More high-tech firms go public in the post- 1995 period. High-tech firms are subject to more uncertainties, which may cause greater litigation risk. Consistent with this prediction, I find that the proportion of high-tech traditional IPO cases is higher than that of nonsued firms in both periods. Slightly more IPO firms choose to be listed on the NYSE/AMEX after 1995. Furthermore, IPOs listed on the NYSE/AMEX are more likely to be involved in traditional IPO cases in both periods. Approximately, 12% fewer IPOs are backed by venture capitalists after 1995. Additionally, prior to 1995, there were 13% more traditional IPO cases backed by venture capitalists than nonsued IPOs. However, there were 4% fewer traditional IPO cases backed by venture capitalists than nonsued IPOs in the post- 1995 period. This again reflects less "deep pocket" digging after 1995.

To create a proxy for the level of insider trading, I determine whether the IPO firms subsequently issued stock via a secondary offering. Panel A indicates that fewer IPOs have a secondary offering after 1995. This is consistent with the prospect theory of Loughran and Ritter (2004), who hypothesize that issuers concentrated more on aftermarket profit than on proceeds in the late 1990s. The signaling hypothesis states that insiders retaining a great portion of firm shares can signal firms' good quality (Leland and Pyle, 1977; Grinblatt and Hwang, 1989). Consistent with this hypothesis, the proportion of traditional IPO cases having a secondary offering is higher than that of nonsued IPOs.

In summary, IPO firms' litigation exposure to traditional IPO cases is reduced after 1995. I find lower settlement rates and settlement/proceeds ratios, higher dismissal rates, longer decision waiting time, and less "deep pocket" digging in the post- 1995 period. I also find that some major characteristics of IPO firms and traditional IPO cases changed after 1995. Therefore, I study LRH separately for the pre- and post- 1995 periods. Furthermore, I find that a new type of lawsuit, IPO allocation cases, was filed in large numbers during the 2001 bear market. I believe these cases are unique events because their characteristics, filing location, and dates of filing




are significantly different from those of traditional IPO cases. I study these cases separately in Section V.

III. Methods

I apply a simultaneous equations system approach to test the LRH. Under this model, the relationship between IPO underpricing and firms' litigation risk can be expressed as two simul- taneously decided effects: 1) the insurance effect and 2) the deterrence effect. On one hand, IPO firms expecting higher litigation risk underprice their IPOs by a greater amount. Conversely, IPOs with higher underpricing should have a lower probability of being sued after the offering. 13 While initial return is observed directly, litigation risk is observed only as a dichotomous variable, the lawsuit dummy. Hence, these two effects are captured by the following equations:

insurance effect: initial return = y' litigation risk* + ß'X' + /xi , (1)

deterrence effect: litigation risk* = y2 initial return + ßiX2 + £¿2, (2)

if litigation risk* > 0 0 otherwise

where

initial return = the amount of underpricing for IPO firm /; litigation risk* = the unobservable probability of litigation for IPO firm i;

X' = a vector of exogenous control variables for Equation (1); X2 = a vector of exogenous control variables for Equation (2);

lawsuit = dummy variable equal to 1 if firm i is sued, and 0 otherwise; /¿i and ß2 = unobservable i.i.d. bivariate normal error terms.

Equation (1) expresses the insurance effect of the LRH. I fail to reject the hypothesis if y 1 is significantly positive. Equation (2) expresses the deterrence effect of the LRH. I fail to reject the hypothesis if y2 is significantly negative. The LRH of IPO underpricing cannot be rejected only when both y ' and y 2 are significant and have the right signs. 14

13 These LRH predictions only apply to traditional IPO cases as all related literature was written before the occurrence of IPO allocation cases. As I discussed in Section II, IPO allocation cases accuse the underwriters and buyers of inflating the aftermarket prices. Consequently, IPOs with higher underpricing might trigger IPO allocation cases, and issuers expecting this type of litigation risk (if they can) might reduce IPO underpricing, an action in direct opposition to the LRH's prediction on traditional IPO cases. Thus, I study these two types of IPO lawsuits separately. 14Heckman (1978) suggests that the dummy endogenous variable model in Equation (1) might have "structural shift," where both the latent variable (litigation risk*) and their dichotomous realization (lawsuit) occur in the model simultane- ously. It is presented as follows: initial return = yx litigation risk* + S' lawsuit + Xxß' + ßL The null hypothesis of

structural shift is Hq. 5j =0. Following the estimation methods given by Maddala (1983), I find Si is not significantly different from zero when studying either traditional IPO cases or IPO allocation cases. Therefore, I believe there is no structural shift in the model.




According to Maddala (1983), the reduced forms of this simultaneous equations system are

initial return = T''X + vi (4)

litigation risk* = T'2X + v2, (5)

where

X = a vector of all exogenous variables in the system including instrumental variables; and vi and v2 = unobservable i.i.d. bivariate normal error terms.

Since litigation risk is observed only as a dichotomous variable, the lawsuit dummy, I can only estimate FI 2/(72, where o' = var(v2). Therefore, Equation (5) should be written as

litigation risk** = fl^atftwl *** = ^X + * = O2*X + v*. (6) a2 a2 or2

The structural Equations (1) and (2) are now written as

insurance effect: initial return = Y'Gi litigation risk** + ß'X' + Mi (7)

deterrence effect: litigation risk** = - infria/ retar« + - X2 -f - . (8) or2 a2 oi

A. Two-Stage Estimation Method Introduced by Maddala (1983)

I first estimate both effects (Equations (7) and (8)) using the two-stage estimation procedure recommended by Maddala (1983). For the insurance effect, the first-stage estimates Equation

A

(6) by probit maximum likelihood (ML) to obtain the index function U'X. The second-stage A

estimates Equation (7) by ordinary least squares (OLS) after substituting Tl*,X for litigation risk**. Parameters y'o2 and ß' are estimated here. For the deterrence effect, the first-stage

A estimates Equation (4) by OLS to obtain the linear projection function Yl^. The second-stage

A estimates Equation (8) by probit ML after substituting T'XX for the initial return. Parameters y ila 2 and ̂2/^2 are estimated here. The asymptotic covariance matrixes are given in Maddala (1983). I use the nonparametric bootstrap to obtain standard errors for coefficients. The drawback of this method is that coefficients y'9 y 2, and ̂2 are not identifiable, and I can only estimate scaled coefficients y ' a 2, 72/^2, and /?2/a2. In sPite of this, the regression coefficients are still consistent. I am able to test whether these coefficients are significantly different from zero and understand the statistical significance of both insurance and deterrence effects.

B. Generated Instrument Approach Introduced by Wooldridge (2001) I further use an arguably more applicable method to estimate the insurance effect. Given that the

endogenous variable (litigation risk*) in the insurance effect equation is observed as a dichotomous




variable (lawsuit), Equation (1) is called a dummy endogenous variable model (Heckman, 1978). I can estimate it using a generated instrument approach introduced by Wooldridge (2001).

The detailed procedure is as follows: 1) estimate Equation (6) by probit ML to obtain the A

fitted probabilities ^(n^^Q, which is the predicted probability of lawsuit = 1, and 2) using A

^(Ti^X) as a generated instrumental variable for litigation risk*, estimate Equation (1) by the two-stage least squares method (2SLS).15 The 2SLS in Step 2 is equivalent to the following two steps: 1) estimate the following Equation (9) by OLS to obtain the linear projection function A A A

^(Yl^X) + 0X', where litigation risk* is again observed as a dichotomous variable, the lawsuit A A a

dummy, and 2) estimate Equation (1) by OLS after substituting £3>(n*.X) + 0X' for litigation risk*. Parameters y i and ß ' are estimated here.

litigation risk* = Ç <$>(Û*2X) + 0Xx + r , (9)

where

r = unobservable i.i.d. normal error term.

In short, this approach is estimating Equation (1) by 2SLS using a generated instrumental vari- A

able 0(n*.X). As discussed in Wooldridge (2001), this approach offers estimators that are more efficient. There are two nice features of this approach as compared to the two-stage estimation method of Maddala (1983). First, I can actually estimate y' directly and avoid yia2. Second, I can ignore whether the specification of Equation (6) and the estimation of n*, are correct or not. Therefore, the 2SLS standard errors and test statistics are asymptotically valid (Wooldridge, 2001).

C. Instrumental Variables and Control Variables

In this subsection, I discuss instrumental variables and control variables. The descriptive statistics for most of these variables are listed in Table III. Table IV demonstrates the descriptive statistics of instrumental variables and matched sample proxies. Panel A compares the characteristics of these variables in the pre-1995 period to those in the post- 1995 period. Panel B compares traditional IPO cases and nonsued firms.

To estimate the insurance effect, I follow Lowry and Shu (2002) to use the matched turnover as an exogenous instrumental variable for litigation risk. Stock turnover equals [1 - 11^(1 - volume tradedf/total shares,)] with t = 0 as the IPO offering date. 16 Panel A indicates that the average IPO stock turnover significantly increases by 2% after 1995. Stock turnover should positively be related to the firms' litigation risk as shareholder damages are increasing with the number of shares traded at the allegedly misleading prices. Consistent with this theory, Panel B demonstrates that the average stock turnover of traditional IPO cases is significantly higher than that of nonsued IPOs. Since the post-IPO stock turnover is not in the managers' information set at the time of

15 This generated instrumental variable is uncorrelated with the error term ßu and highly correlated with the endogenous variable litigation risk*, so it meets both requirements for instrumental variables. 16 This turnover measure is a direct input in estimating damaged shares under the proportional trading model, which is widely accepted by courts as the appropriate way to calculate damages in class action lawsuits. For firms listing on NASDAQ, I divide the trading volume by a factor of two.




Table IV. Descriptive Statistics of Instrumental Variables and Matched Sample Proxies

The sample consists of 1,968 nonsued IPOs and 81 IPOs involved in traditional IPO lawsuits from 1990 to 1998 (with 1994 and 1995 excluded). Some variables are based on fewer observations due to missing data. Turnover is equal to [1 - Tl^22 (1 - volume traded,/total shares,] with the IPO offering date as t - 0. The matched sample consists of firms in the same three-digit, two-digit, one-digit, or zero-digit SIC code with market capitalization within 80%- 120% of the IPO firm's market capitalization at the close of the first trading day. Matched turnover is the average of matched firms' turnovers, which are based on daily returns over a one-year interval prior to the IPO offering date. Prior market return is the compounded value-weighted NYSE/AMEX/NASDAQ daily returns (including dividend) within 15 days prior to the IPO offering date. Matched SD is the average of matched firms' standard deviations, which are based on daily returns over a one-year interval prior to the IPO offering date. Panel A compares the IPO firms' characteristics in the pre-1995 period to that in the post- 1995 period. The pre-1995 period represents the years 1990-1993. The post- 1995 period represents the years 1996-1998. Panel B compares traditional IPO cases and nonsued firms in the whole sample period.

Panel A. Pre-1995 Period vs. Post-1995 Period

Pre-1995 Period Post-1995 Period Wilcoxon Test Median Median f-test Mean Mean

(S!E!) (S^) Turnover 0.6373 0.6475 -1.9950**

0.6258 0.6472 -2.3631** (0.0065) (0.0063)

Matched turnover 0.4826 0.5704 -11.1 740*** 0.4754 0.5555 -10.6527*** (0.0058) (0.0049)

Prior market return 0.0065 0.02 1 5 -9.6280*** 0.0068 0.0165 -7.7641*** (0.0007) (0.00 10)

Matched SD 0.0454 0.0475 -2.2360** 0.0476 0.0476 -0.1105 (0.0006) (0.0004)

Panel B. Nonsued IPO Firms vs. Sued IPO Firms

Nonsued IPOs Traditional IPOs Cases Wilcoxon Test Median Median f-test Mean Mean

(S^ (S^ Turnover 0.6354 0.7457 -4.3590***

0.6331 0.7326 -4.3012*** (0.0046) (0.0184)

Matched turnover 0.5297 0.5909 -3.6780*** 0.5146 0.5837 -3.4975*** (0.0040) (0.0145)

Prior market return 0.0116 0.0042 2.0830** 0.0122 0.0054 2.1079** (0.0006) (0.0032)

Matched SD 0.0465 0.0463 0.6600 0.0477 0.0454 1.2175 (0.0004) (0.0015)

*** Significant at the 0.01 level. ** Significant at the 0.05 level.




offering, the matched sample stock turnover (matched turnover) is further constructed.17 Lowry and Shu (2002) argue that the stock turnover of similar firms prior to the IPO should not directly affect the IPO initial return; therefore, matched turnover can be used as the instrumental variable for litigation risk. Table IV illustrates that matched turnover has characteristics similar to the IPOs' own stock turnover; hence, I believe it is a good proxy for the IPOs' stock turnover.

To estimate the deterrence effect, I follow Lowry and Shu (2002) to use prior market return as the exogenous instrumental variable for IPO initial return when studying traditional IPO cases. Prior market return is the compounded value-weighted NYSE/AMEX/NASDAQ daily returns within 15 days prior to the IPO offering date. As Loughran and Ritter (2002) have documented, this measure is significantly correlated with IPO underpricing. In addition, I agree that they are exogenous in estimating IPO firms' litigation risk as market returns prior to the IPO should not affect firms' litigation risk several months or years later. Panel A of Table IV indicates that prior market return is significantly higher in the post- 1995 period, which might reflect the issuers' stronger tendency to time their IPOs in the booming market of the late 1990s. Panel B confirms that nonsued IPOs have a slightly higher prior market return than traditional IPO cases.

Control variables are the common exogenous variables in both insurance and deterrence effects. I summarize their relationship with the IPO firms' litigation risk and IPO underpricing in this section. Ln(Market Cap) = the natural logarithm of market capitalization. The size of the firm should be positively related to litigation risk based on the "deep pocket" theory, but the relationship between size and initial returns could be mixed. With less information asymmetry, larger firms should have lower initial returns. Underwriters, however, may underprice bigger issues by a larger amount as it is harder to sell bigger issues (Michaely and Shaw, 1994). To control size, I use Ln(Market Cap) when studying traditional IPO cases.

UW rank denotes IPO lead underwriter rank. VC backed equals one if an IPO is venture capitalist backed and zero otherwise. The "deep pocket" theory suggests that the IPOs underwritten by more prestigious investment banks and/or backed by venture capitalists should have higher litigation risk. UW rank and VC backed should be negatively related to underpricing as higher rank underwriters and venture capitalists may disclose more information to protect their reputation (Ritter, 1984; Carter and Manaster, 1990; Michaely and Shaw, 1994). In the late 1990s, VC backed may be positively related to underpricing because they may retain shares for aftermarket profits (Loughran and Ritter, 2004).

Ln(l+Age) is the natural logarithm of (1+Age). NYSE-AMEX equals one if an IPO firm is listed on the NYSE or AMEX and zero otherwise. High-tech equals one if an IPO firm is classified as a high-tech firm in SDC and zero otherwise. With size controlled for in a multivariate regression, older firms and firms listed on NYSE/AMEX should have less litigation risk and underpricing because of their lower uncertainty levels and more publicly available information (Carter and Manaster, 1990). High-tech firms should have higher litigation risk and underpricing due to their higher uncertainty levels.

Insider selling equals one if an IPO firm has a secondary offering in IPO and zero otherwise. This dummy should be positively related to the IPO firm's litigation risk as insider selling makes it easier for plaintiffs to establish motive in lawsuits. It should be negatively related to the IPO underpricing since insider selling signals the poor quality of the issuing firm. In addition,

17For each IPO, I select firms with the same three-digit, two-digit, or one-digit SIC code and market capitalization within 80%- 120% of the IPO as the matched sample. If no matched firm is found, I select all firms with market capitalization within 80%- 120% of the IPO firm. For each matched firm in a particular IPO's matched sample, stock turnover is calculated based on its daily returns over a one-year interval prior to this IPO's offering date. This IPO's matched turnover is the average stock turnover of all matched firms in its matched sample. The correlation coefficient between the IPOs' own stock turnover and matched turnover is 0.15.



340 Financial Management * Summer 2009

insiders may have retained shares for aftermarket profits in the late 1990s (Loughran and Ritter, 2004).

Price update should be positively correlated with litigation risk since issuers that set offer prices more aggressively are more likely to be sued. There should be a positive relationship between price update and initial return as underwriters only partially update the offer price from the midpoint of filing range to compensate institutional investors through underpricing (Rock, 1986; Benveniste and Spindt, 1989).

Stock volatility should be positively related to litigation risk since lawsuits are typically filed after a steep drop in stock price. It should also be positively related to underpricing as high volatility is associated with high information asymmetry. Similar to stock turnover, IPOs' own stock volatility is not in the managers' information set at the time of offering. Therefore, matched sample standard deviation (matched SD) is used following Lowry and Shu (2002). 18 The correlation coefficient between matched SD and standard deviation is 0.24.

I also test the LRH using some alternative control variables. Loughran and Ritter (2004) reveal that SDC does not capture all dual class shares and CRSP only reports publicly traded shares. They also point out that SDC does not identify all the Internet firms. Their tech stock definition is also different from SDC's. 19 1 construct my market capitalization and high-tech dummy following Loughran and Ritter (2004) and rerun the tests. Results remain qualitatively unchanged from those previously presented.

In summary, X' includes all control variables plus the instrumental variables for initial return. X2 includes all control variables plus the instrumental variables for litigation risk. X is a vector of all exogenous variables in the simultaneous equations system (i.e., the union of X' andZ2).

IV. Empirical Results of Traditional IPO Cases

This section addresses the multivariate regression results of the LRH of IPO underpricing using the sample of traditional IPO cases. Section A examines the insurance effect. Section B examines the deterrence effect.

A. Insurance Effect Results

Table V illustrates the regression results of estimating Equations (7) and (1) using the two- stage estimation method in Maddala (1983) and the generated instrument approach in Wooldridge (2001). For all three panels, Column 1 shows the first-stage probit ML results of Equation (6), which is shared by both methods. Columns 2 and 3 demonstrate the second-stage regression results of the insurance effect using the two-stage estimation method and the generated instrument approach.

18The matched sample is the same one used for matched turnover. For each matched firm in a particular IPO's matched sample, standard deviation is calculated based on its daily returns over a one-year interval prior to this IPO's offering date. An IPO's matched SD is the average standard deviation of all firms in its matched sample. 19They use the number of postissue shares outstanding from CRSP for single-class IPOs and a variety of sources including Smart and Zutter (2003), SDC, CRSP, Dealogic, and the prospectus on EDGAR for dual class IPOs. They merge the Internet identifications from SDC, Dealogic, and IPOMonitor.com. These data are available on Dr. Jay Ritter's web page. Their tech stock includes these SIC codes: 3571, 3572, 3575, 3577, 3578 (computer hardware), 3661, 3663, 3669 (communications equipment), 3671, 3672, 3674, 3675, 3677-3679 (electronics), 3812 (navigation equipment), 3823, 3825-3827, 3829 (measuring and controlling devices), 3841, 3845 (medical instruments), 4812, 4813 (telephone equipment), 4899 (communications services), and 7371-7375, 7378, 7379 (software).




Table V. Insurance Effect Regression Results of Traditional IPO Cases

These regressions test the insurance effect of the litigation risk hypothesis using both the two-stage estimation method and the generated instrument approach, where litigation risk is treated as the endogenous variable. Panel A studies the pre-1995 period with a final sample size consisting of 922 IPOs issued between the years 1990 and 1993. Panel B studies the post- 1995 period with a final sample size consisting of 1,014 IPOs issued between the years 1996 and 1998. Column 1 is the first-stage probit ML regression. Column 2 is the second-stage OLS under the two-stage estimation method. Column 3 is the second-stage 2SLS under the generated instrument approach. Lawsuit = 1 if an IPO is involved in traditional IPO lawsuits between January 1990-December 2003, and 0 otherwise. Lawsuit Index = predicted index function from the first-stage probit ML regression. Ln(Market Cap) = the natural logarithm of market capitalization. UW rank = IPO lead underwriter rank. VC backed = 1 if an IPO is venture capitalist backed and 0 otherwise. Ln(l+Age) = the natural logarithm of (1+ Age). High tech = 1 if an IPO firm is in the high-tech industry and 0 otherwise. NYSE-AMEX = 1 if an IPO firm is listed on the NYSE or AMEX and 0 otherwise. Insider selling = 1 if an IPO firm has a secondary offering in the IPO process and 0 otherwise. All other variables are defined in earlier tables. The standard errors of the two-stage estimation method are calculated using the nonparametric bootstrap. All standard errors are reported in parentheses.

Panel A. Pre-1995 Period (90-93)

Variable First Stage Second Stage (Dep. = Initial Return)

(Dep. = Lawsuit) Two-Stage Estimation Generated IV Approach Lawsuit Index 0.0818***

(0.0271) Lawsuit 0.8055*

(0.4581) Matched turnover 1 .2613**

(0.5210) Prior market return -3.7505 1 .4940*** 1 .4047***

(3.7748) (0.2340) (0.3466) Ln(marketcap) 0.0077 0.0168*** 0.0173**

(0.0819) (0.0061) (0.0085) UWrank 0.1274** -0.0238*** -0.0187***

(0.0638) (0.0061) (0.0061) VC backed 0.1100 -0.0138 -0.0118

(0.1858) (0.0126) (0.0184) Ln(l+Age) -0.2454*** -0.0099 -0.0130

(0.0923) (0.0075) (0.0133) Hightech -0.1567 0.0205** 0.0200

(0.1854) (0.0104) (0.0179) NYSE-AMEX 0.1510 -0.0428*** -0.0418*

(0.2252) (0.0149) (0.0234) Insider selling 0.1236 0.0166 0.0212

(0.1634) (0.0112) (0.0166) Price update 0.7829** 0.2560*** 0.2632***

(0.3362) (0.0587) (0.0520) Match SD 0.8769 -1.3265*** -1.2171**

(5.4235) (0.3229) (0.4957) Intercept -3.0311** 0.2252 -0.0095

(1.4515) (0.1382) (0.1436) Pseudo R2 (adj R2) 0. 1095 0.2737

(Continued)




Table V. Insurance Effect Regression Results of Traditional IPO Cases (Continued)

Panel B. Post-1995 Period (96-98)


(Dep. = Lawsuit) Two-Stage Estimation Generated IV Approach Lawsuit Index 0.0950**

(0.0465) Lawsuit 1.1066

(0.7838) Matched turnover 0. 8899

(0.5861) Prior market return -4.4172** 0.7467*** 0.7245*

(2.2400) (0.2850) (0.4018) Ln(market cap) 0.0303 -0.0089** -0.0090

(0.0502) (0.0040) (0.0063) UWrank -0.0951 0.0495*** 0.0497***

(0.0972) (0.0122) (0.0115) VC backed -0.0804 -0.0143 -0.0144

(0.1741) (0.0151) (0.0214) Ln(l+Age) -0.0151 -0.0137*** -0.0134

(0.0789) (0.0049) (0.0095) Hightech -0.0460 0.0169 0.0165

(0.1756) (0.0120) (0.0209) NYSE-AMEX 0.2493 -0.1099*** -0.1091***

(0.2212) (0.0229) (0.0313) Insider selling 0. 1 996 -0.027 1 -0.0263

(0.1556) (0.0170) (0.0236) Price update 0.6197 0.4721*** 0.4739***

(0.3940) (0.0591) (0.0658) Match SD 5.7433 -0.7349 -0.5988

(7.9674) (0.6714) (1.0316) Intercept -1.0656 -0.4197* -0.6462***

(1.8214) (0.2206) (0.2190) Pseudo R2(aájR2) 0.0404 0.3503

***Significantatthe0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level.

1. Pre-1995 Period

Panel A studies the pre-1995 period using matched turnover as the instrumental variable for litigation risk. I find results similar to Lowry and Shu (2002). With other characteristics remaining the same, the predicted probability of IPO firms being involved in traditional IPO cases increases by 0.08% at the 5% significance level if matched turnover increases by 1%. The chi-square statistic of matched turnover is 5.86, which suggests that it is a strong instrument for litigation risk. The second-stage regression results of both methods suggest that the IPO firms' expected litigation risk has a significant positive effect on IPO initial return in the pre-1995 period. The coefficient of the lawsuit index function in Column 2 is 0.08, which is much smaller than the 0.81 of lawsuit in Column 3. This difference is reasonable because the two-stage estimation



Zhu * IPO Underpricing and Litigation Risk 343

method identifies y 'Oi while the generated instrument approach identifies y ' itself. With a 1% increase in the firm's litigation risk, this IPO firm will increase its IPO underpricing by 0.81%. Therefore, I find results consistent with the insurance effect of the LRH in Lowry and Shu (2002) that pre-1995 IPO firms do use IPO underpricing as insurance against traditional class action lawsuits.

Other regression results of the two methods are very close in every aspect as both methods identify ß' directly. These results are similar to the findings in the literature. A 1% increase in market return prior to the offering date leads to a 1.4% increase in the initial return. In support of Michaely and Shaw (1994) who state that the underwriter might offer underpricing to institutional investors in return for selling a large bulk of shares, I find that IPOs with larger market capitalization have a significantly higher initial return. Consistent with the information asymmetry hypothesis and lower uncertainty levels, IPOs of older firms and IPOs underwritten by prestigious investment banks have a lower initial return. Due to higher uncertainty levels, the initial return of high-tech IPOs is 2% higher than that of other IPOs, and the initial return of IPOs listed on NASDAQ is 4% higher than that of IPOs listed on NYSE/AMEX. When an IPO issuer adjusts the offer price 1% higher than the midpoint of the filing range, the initial return increases by 0.3%. This suggests that underwriters only partially update the offer price to compensate institutional investors for them to reveal more information.

2. Post-1995 Period

Panel B studies the three-year period after 1995 (from 1996 to 1998) that excludes IPO allocation cases and the unusual boom and bust period that followed. I find these results different from those in the pre-1995 period. The significance of matched turnover is decreased. The second- stage regression results suggest that the effect of the IPO firms' expected litigation risk on IPO initial return is less statistically significant as compared to the results in the pre-1995 period. There is no statistical significance at all, especially for the generated IV approach in Panel B. My results suggest that firms' litigation risk plays a less significant role in IPO pricing strategy after 1995 with reduced litigation risk and a healthy stock market.

My other regression results are similar to the findings in the literature. IPOs underwritten by prestigious investment banks have a significantly higher initial return after 1 995 . This is consistent with the allegation that insiders, including issuers and underwriters, are involved in IPO laddering for future aftermarket profits in the late 1990s. As in Panel A, I again find that an increase in market return prior to the offering date leads to a significant increase in initial return. Consistent with the information asymmetry hypothesis and lower uncertainty levels, IPOs of larger firms and older firms have a significantly lower initial return. Due to higher uncertainty levels, the initial return of IPOs listed on NASDAQ is 1 1% higher than that of IPOs listed on NYSE/AMEX. When an IPO issuer adjusts the offer price 1% higher than the midpoint of the filing range, the initial return increases by 0.47%. This suggests that underwriters only partially update the offer

price to compensate institutional investors for them to reveal more information.

B. Deterrence Effect Results

Table VI illustrates the regression results of estimating Equation (8) using the two-stage estimation method in Maddala (1983). For both panels, the first two columns use the full sample. The second two columns use the sample excluding dismissed/terminated cases because Lowry and Shu (2002) argue that these cases should not be brought to court in the first place and, hence, should not be included in the tests. Columns 1 and 3 are the first-stage results of Equation (4). Columns 2 and 4 are the second-stage regression results of the deterrence effect.




Table VI. Deterrence Effect Rearession Results of Traditional IPO Cases

These regressions test the deterrence effect of the litigation risk hypothesis using the two-stage estimation method, where initial return is treated as the endogenous variable. Panel A studies the pre-1995 period with a final sample size consisting of 922 IPOs issued between the years 1990 and 1993 and 909 observations after dropping dismissed/terminated (D/T) cases. Panel B studies the post- 1995 period with a final sample size consisting of 1 ,0 1 4 IPOs issued between the years 1 996 and 1 998 and 1 ,000 observations after dropping D/T cases. The first two columns illustrate the regression results under the full sample. The second two columns demonstrate the regression results under the subsample after dropping D/T cases. Columns 1 and 3 indicate the first-stage OLS regression results. Columns 2 and 4 illustrate the second-stage probit ML regression results. Predicted initial return = predicted value from the first-stage OLS regression. All other variables are defined in earlier tables. The standard errors of the two-stage estimation method are calculated using the nonparametric bootstrap. All standard errors are reported in parentheses.

Panel A. Pre-PSLRA Period (90-93)

Variable Full Sample Drop D/T Cases

First Stage Second Stage First Stage Second Stage (Dep. = Initial (Dep. = (Dep. = Initial (Dep. =

Return) Lawsuit) Return) Lawsuit) Predicted initial return -3.1588 -1.2989

(2.4123) (3.5711) Prior market return 1.1873*** 1.1 785***

(0.2302) (0.2307) Matched turnover 0.1031*** 1.5870*** 0.1117*** 1.0733*

(0.0334) (0.4977) (0.0335) (0.5880) Ln(market cap) 0.0175*** 0.0628 0.0174*** -0.0570

(0.0058) (0.0850) (0.0058) (0.0905) UWrank -0.0133*** 0.0852 -0.0134*** 0.1366*

(0.0033) (0.0694) (0.0033) (0.0728) VC backed -0.0048 0.0948 -0.0068 -0.0609

(0.0124) (0.2189) (0.0124) (0.2100) Ln(l+Age) -0.0299*** -0.3399*** -0.0310*** -0.2476*

(0.0060) (0.1032) (0.0061) (0.1313) Hightech 0.0077 -0.1324 0.0068 -0.1338

(0.0124) (0.1639) (0.0124) (0.1896) NYSE-AMEX -0.0305* 0.0547 -0.0305* 0.1703

(0.0156) (0.2619) (0.0157) (0.2752) Insider selling 0.0267** 0.2079 0.0282** 0.0860

(0.0112) (0.1975) (0.0113) (0.2460) Price update 0.3200*** 1.7936* 0.3139*** 1.0617

(0.0260) (0.9620) (0.0261) (1.2143) Match SD -1.2549*** -3.0869 -1.2768*** 0.7613

(0.3459) (6.6041) (0.3458) (6.2634) Intercept -0.0226 -3.1024** -0.0207 -1.7298

(0.0987) (1.3494) (0.0993) (1.4903) Pseudo R2(adjR2) 0.2737 0.1095 0.2731 0.0749

(Continued)




Table VI. Deterrence Effect Regression Results of Traditional IPO Cases {Continued)

Panel B. Post-PSLRA Period (96-98)



Return) Lawsuit) Return) Lawsuit) Predicted initial return - 13.5053* -20.0472**

(7.3874) (9.0772) Prior market return 0.327 1 * 0.3 1 97*

(0.1910) (0.1934) Matched turnover 0.0845* 2.0317*** 0.0869* 2.7532***

(0.0449) (0.7400) (0.0453) (0.9718) Ln(marketcap) 0.0404*** 0.4511 0.0404*** 0.6893*

(0.0078) (0.3027) (0.0079) (0.3567) UWrank -0.0060 -0.0510 -0.0063 -0.0725

(0.0039) (0.0688) (0.0040) (0.0674) VC backed -0.0219 -0.3763 -0.0218 -0.6903***

(0.0140) (0.2314) (0.0142) (0.2610) Ln(l+Age) -0.0151** -0.2195 -0.0154** -0.2644*

(0.0063) (0.1363) (0.0064) (0.1560) Hightech 0.0125 0.1229 0.0133 0.0940

(0.0142) (0.1678) (0.0144) (0.2461) NYSE-AMEX -0.0862*** -0.9155 -0.0870*** -1.5332*

(0.0186) (0.6598) (0.0188) (0.8744) Insider selling -0.0082 0.0895 -0.0066 -0.0521

(0.0130) (0.1746) (0.0132) (0.2317) Price update 0.5310*** 7.7913* 0.5330*** 11.5173**

(0.0331) (4.0565) (0.0333) (4.9303) Match SD -0.1893 3.1870 -0.2096 9.5716

(0.6311) (6.8648) (0.6357) (6.8809) Intercept -0.5209*** -8.1011** -0.5176*** -11.7658**

(0.1464) (3.9890) (0.1474) (4.8306) Pseudo i?2(adjtf2) 0.3503 0.0404 0.3526 0.0723

*** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level.

1. Pre-1995 Period

Panel A studies the pre-1995 period using prior market return as the instrumental variable for initial return. I find results similar to Lowry and Shu (2002). With other characteristics remaining the same, Columns 1 and 3 demonstrate that the IPOs' initial return increases by 1.2% when the market return prior to the offering date increases by 1%. The coefficient of prior market return is significant at the 1% level suggesting that it is a strong instrumental variable for initial return. The second-stage regression results of both samples suggest that IPO underpricing reduces an IPO firm's litigation risk in the pre-1995 period. Although the coefficients of predicted initial return are insignificant, the signs from both samples are in the correct direction. These results are consistent with the findings in Lowry and Shu (2002).




Other regression results are similar to the earlier findings. The coefficient on the matched turnover is positive and significant confirming that turnover is an important determinant of securities litigation. IPOs solicited by higher ranking investment banks tend to have higher litigation risk, potentially revealing one motivation for plaintiffs' "deep pocket" digging activity. Possibly because older firms are less uncertain and have lower information asymmetry, IPOs issued by older firms have a lower probability of being involved in traditional IPO cases than those issued by younger firms. IPOs with a 1% higher price update have a 0. 12% higher litigation risk demonstrating that issuers setting the offer price more aggressively are more likely to be sued. Other coefficients in the regression are not significant.

2. Post-1995 Period

Panel B studies three-year period after 1995 (from 1996 to 1998) that excludes the IPO allocation cases and the unusual boom and bust period that followed. I find results different from those in the pre-1995 period. The coefficient of prior market return is significant at the 1% level suggesting that it is a strong instrumental variable for initial return. With other characteristics remaining the same, the IPOs' initial return increases around 0.3% when the market return prior to the offering date increases by 1%. Panel B also demonstrates a significant deterrence effect in the post- 1995 period. While IPO underpricing increases by 1%, its litigation risk reduces by about 1%. When the firm's litigation risk is reduced in the post- 1995 period, the deterrence effect becomes much stronger as compared to that in the pre-1995 period.

Based on the estimation results in Panel B Column 2, 1 find the probability of getting involved in traditional IPO cases is 3.6% for IPOs issued in the post- 1995 period. I further calculate the predicted litigation risk of these IPOs using the estimated coefficients from the pre-1995 period in Panel A Column 2.20 That calculation indicates that these IPOs from the post-1995 period would be subject to a 5.2% probability of involvement in traditional IPO lawsuits if the legal and economic environment were not changed. This risk is much higher than the actual post- 1995 period litigation risk of 3.6%. These testing results remain qualitatively unchanged after dropping dismissed/terminated cases. I again confirm that IPO firms do experience lower litigation risk after 1995.

Other regression results are similar to the earlier findings. The coefficient on the matched turnover is positive and significant confirming that turnover is an important determinant of securities litigation. IPOs with larger market capitalization have higher litigation risk, which may indicate that plaintiffs are seeking to take advantage of firms' "deep pockets." IPOs backed by venture capitalists tend to have lower litigation risk. When compared with IPOs issued by younger firms, the IPOs issued by older firms have a lower probability of being involved in traditional IPO cases, possibly because these businesses have less uncertainty and less information asymmetry. IPOs listed on NYSE/AMEX have a 0.04% lower probability of being involved in traditional IPO cases than those listed on NASDAQ. IPOs with a 1% higher price update have a 0.5% higher litigation risk indicating that issuers setting their offer price more aggressively are more likely to be sued. Other coefficients in regression are not significant.

20The index function is as follows: Lawsuit Index = -3.1024 - 3.1588 x Predicted Initial Return + 0.0628 x Ln(Market Cap) - 0.3399 x Ln(l+Age) - 0.1324 x High tech + 0.2079 x Insider selling + 0.0948 x VC backed + 0.0547 x NYSE-AMEX + 1.793612 x Price update - 3.0869 x Match SD + 0.0852 x UW rank + 1.5870 x Match turnover.




C. Results in the Post-1995 Period Including the Boom and Bust Periods (1996-2002)

I further test the LRH in the post- 1995 period including the extreme volatile boom and bust periods (1 996-2002). 21 When markets become more volatile in the bubble and bust periods, I find that the IPO firms' expected litigation risk has a more economically significant insurance effect on IPO initial return when compared to the results in the pre-1995 period. With a 1% increase in firm's litigation risk, this IPO firm will increase its IPO underpricing by 2.19% on average from 1996 to 2002, which is larger than the 0.8% in the pre-1995 period. These results indicate that firms do worry about litigation risk in the volatile market and again use IPO underpricing as insurance against traditional class action lawsuits. The deterrence effect results in this period are unclear. I find that IPO underpricing is positively related to litigation risk in the full sample and negatively related to litigation risk when the D/T cases are dropped. The results in both samples are insignificant. When the market becomes more volatile in the bubble and bust periods, using underpricing to deter traditional class action lawsuits doesn't seem to be an effective strategy anymore. In fact, in the next section, I find that IPO underpricing actually triggers a new type of lawsuit, IPO allocation cases.

V. Empirical Results of IPO Allocation Cases

This section addresses the multivariate regression results of the LRH of IPO underpricing using the sample of IPO allocation cases. Section A offers the descriptive statistics of IPO allocation cases. Section B examines the insurance effect, while Section C examines the deterrence effect.

A. Descriptive Statistics of IPO Allocation Cases

Descriptive statistics of IPO allocation cases are shown in Table VII. For IPO allocation cases, I only study the internet bubble period of 1999-2000 as these two years are the most relevant. The average initial return of firms involved in IPO allocation cases is 107% higher than that of nonsued firms consistent with the allegation nature of these cases. These IPOs also demonstrate an aggressive pricing strategy. The average price update of IPOs involved in these cases is 34% higher than that of nonsued firms. Consistent with the fact that the targets of IPO allocation cases are large underwriters instead of issuers, the average underwriter rank of these IPOs is significantly higher than that of nonsued IPOs. For firms involved in IPO allocation cases, the median market capitalization is more than four times that of nonsued firms. The proceeds difference is much smaller. The extremely high market capitalization of firms involved in IPO allocation cases could be caused by laddering activities of underwriters and some institutional buyers in the aftermarket. The stock volatility of firms involved in IPO allocation cases is 1% higher than that of nonsued firms. These firms are also significantly younger than nonsued IPOs. About 94% of IPO allocation cases involve high-tech firms. IPOs listed on the NYSE/AMEX are less likely to be involved in IPO allocation cases. I find nearly all IPO allocation cases involve the high-tech IPOs listed on the NASDAQ. Seventy-five percent of IPO allocation cases are IPOs backed by venture capitalists. The proportion of firms involved in IPO allocation cases that have a secondary offering is only 8%, reflecting the notion that insiders in these firms are more interested in getting the aftermarket profit.

21 Detailed tables are available upon request. I also test the LRH in the boom and bust periods only (1999-2002). Results are not significant due to the small sample size of traditional IPO lawsuits in these two years.




Table VII. Descriptive Statistics of IPO Allocation Cases

The sample consists of 435 nonsued IPOs from 1999 to 2000. There are 244 IPOs involved in the IPO allocation cases. Some variables are based on fewer observations due to missing data. UW premium is each underwriter's average excess IPO initial return to market return in the past year. Overhang is the ratio of retained shares to issued shares. All other variables are defined in Tables III and IV

Nonsued IPOs IPO Allocation Cases Wilcoxon Test f-test

Median Mean (S.E.) Median Mean (S.E^T Initial return 0.1417 1.1583 -16.3610***

0.3109 1.3800 -17.3383*** (0.0253) (0.0698)

Price update 0.0000 0.3125 -12.5320*** 0.0394 0.3828 -13.1027*** (0.0132) (0.0260)

Underwriter rank 8.0000 9.0000 -7.5290*** 7.8732 8.6910 -7.4295*** (0.0779) (0.0382)

Market capitalization 154.00 552.00 - 1 1 .5640*** 444.00 1,230.00 -3.8474*** (122.00) (162.00)

Proceeds raised 35.70 48.10 -6.7000*** 67.80 65.30 0.1784 (9.70) (3.93)

Standard deviation 0.0737 0.0837 -6.3830*** 0.0751 0.0843 -4.9224*** (0.0013) (0.0010)

Age 5.0000 4.0000 4.4630*** 9.1968 6.0905 0.5260*** (0.5697) (0.5260)

UW premium 0.0217 0.2024 -6.6390*** 0.0593 0.2254 -6.7058*** (0.0160) (0.0190)

Overhang 2.8592 4.1978 -4.1180*** 3.6256 5.2904 -4.5879*** (0.1844) (0.3569)

% High tech 80.92% 93.99% % on NYSE/AMEX 8.05% 1 .29% % Venture capitalist backed 54.94% 74.68% % With secondary offering 17.01% 8.15% Turnover 0.6737 0.8639 -8.5950***

0.6714 0.8143 -8.8073*** (0.0102) (0.0112)

Matched turnover 0.6989 0.7743 -9.1880*** 0.6617 0.7571 -7.8809*** (0.0080) (0.0071)

Prior NASDAQ return -0.0020 0.0354 -4.7860*** -0.0011 0.0328 -5.1477*** (0.0041) (0.0048)

Matched SD 0.0644 0.0625 0.8170 0.0619 0.0613 0.4735 (0.0009) (0.0009)

*** Significant at the 0.01 level.




In estimating the insurance effect for IPO allocation cases, I again follow Lowry and Shu (2002) to use the matched turnover as an exogenous instrumental variable for litigation risk. The average stock turnover of IPO allocation cases is significantly higher than that of nonsued IPOs. To estimate the deterrence effect for IPO allocation cases, I use prior NASDAQ return as the instrumental variable for the IPO initial return since nearly 90% of the IPOs issued from 1999 to 2000 are listed on the NASDAQ. Prior NASDAQ return is the compounded value-weighted NASDAQ daily returns within 15 days prior to the IPO offering date. Table VII demonstrates that firms involved in IPO allocation cases have significantly higher prior NASDAQ return than nonsued firms have.

Most control variables used in studying IPO allocation cases are the same as those used in studying traditional IPO cases with a few exceptions. To control size, I use the natural logarithm of proceeds raised because the market capitalization of IPO allocation cases may have been manipulated by underwriters through laddering activities and may not accurately represent the IPO firms' size.

I further use UW premium and overhang to control the unique characteristics of IPO allocation cases. Each IPO's UW premium is the average of its lead underwriters' premiums, while each lead underwriter's premium is the average of its excess IPO initial returns relative to market returns in the past year (Hoberg, 2008). UW premium reflects lead underwriters' recent IPO pricing strategy. Hoberg (2008) indicates that it is positively related to IPO initial return. I believe it should also be positively related to the litigation risk of getting involved in IPO allocation cases since these cases concentrate on the underwriters' laddering activities. Consistent with this projection, Table VII indicates that the UW premium of IPO allocation cases significantly exceeds that of nonsued firms by 17%.

Stock overhang is the ratio of retained shares to issued shares (Barry, 1989). Loughran and Ritter (2004) find it has a significantly positive impact on IPO initial return in 1999 and 2000. 1 think this impact could mainly come from laddering activities since issuers could take advantage of aftermarket profits with higher overhang. As shown in Table VII, firms involved in IPO allocation cases retain 1.6 more shares than nonsued firms do for each share offered.

B. Insurance Effect Results

Table VIII illustrates the regression results of estimating Equations (7) and (1) using the two- stage estimation method in Maddala (1983) and the generated instrument approach in Wooldridge (2001). Column 1 shows the first-stage probit ML results of Equation (6), which is shared by both methods. Columns 2 and 3 demonstrate the second-stage regression results of the insurance effect using the two-stage estimation method and the generated instrument approach.

IPO allocation cases are studied using matched turnover as the external instrumental variable for litigation risk. With other characteristics remaining the same, the predicted probability of IPO firms being involved in IPO allocations cases increases by 0.98% at the 1% significance level if matched turnover increases by 1%. The chi-square statistic of matched turnover is 1 1.03. The second-stage regression results of both methods suggest that IPO firms' expected litigation risk has a significant positive effect on IPO initial return. With a 1% increase in firms' litigation risk of exposure to IPO allocation cases, this IPO firm will increase its IPO underpricing by 0.45% during the bubble period. Therefore, I find results consistent with the insurance effect of the LRH that IPO firms do use IPO underpricing as insurance against IPO allocation lawsuits.

Other regression results are consistent with earlier findings regarding IPOs in this period ( 1 999- 2000). The initial return of IPOs backed by venture capitalists is 17% higher than that of other IPOs. Firms that retain 1% more of the postissue shares in the IPO have a 0.03% increase in initial




Table Vili. Insurance Effect Regression Results of IPO Allocation Cases

These regressions test the insurance effect of the litigation risk hypothesis using both the two-stage estimation method and the generated instrument approach, where litigation risk is treated as the endogenous variable. It studies the IPO allocation case with a final sample size consisting of 395 IPOs issued in the years 1999-2000. Column 1 is the first-stage probit ML regression. Column 2 is the second-stage OLS under the two-stage estimation method. Column 3 is the second-stage 2SLS under the generated instrument approach. Lawsuit = 1 if an IPO is involved in IPO allocation lawsuits between January 1 999 and December 2003, and 0 otherwise. All other variables are defined in earlier tables. The standard errors of the two-stage estimation method are calculated using the nonparametric bootstrap. All standard errors are reported in parentheses.


(Dep. = Lawsuit) Two-Stage Estimation Generated IV Approach Lawsuit Index 0.2351*

(0.1229) Lawsuit 0.4772*

(0.2864) Matched turnover 2.51 86***

(0.7582) Prior NASDAQ return 2.2570** 0.3898 0.5274

(0.9844) (0.4927) (0.4597) Ln(proceeds) 0.0010 -0.1060* -0.0981*

(0.1322) (0.0614) (0.0586) UWrank 0.1407 0.0418 0.0631

(0.1515) (0.0692) (0.0657) VC backed 0.2404 0.1430* 0.1701**

(0.1660) (0.0777) (0.0789) Ln(l+Age) -0.1742 0.0021 -0.0201

(0.1102) (0.0526) (0.0506) Hightech 0.2598 0.0256 0.0666

(0.2618) (0.1230) (0.1153) NYSE-AMEX -0.5531 0.0894 -0.0400

(0.5761) (0.1338) (0.1893) Insider selling -0.1510 -0.1167* -0.1121

(0.2230) (0.0660) (0.1012) Price update 1.4771*** 1.1996*** 1.3871***

(0.2957) (0.2329) (0.1685) Match SD -10.6448 -3.8001 -3.7804

(6.5091) (3.0916) (2.4571) UW premium 0.7536** 0.0229 0.0784

(0.2968) (0.1887) (0.1489) Overhang 0.0114 0.0280** 0.0298***

(0.0190) (0.0123) (0.0088) Intercept (3.1080) 2.1270* 1.4782

(2.5830) (1.1535) (1.1362) Pseudo R2(ad)R2) 0.2740 0.5133 0.5530 *** Significant at the 0.01 level.

"Significant at the 0.05 level. * Significant at the 0.10 level.




Table IX. Deterrence Effect Regression Results of IPO Allocation Cases

These regressions test the deterrence effect of the litigation risk hypothesis using the two-stage estimation method, where initial return is treated as the endogenous variable. It studies the IPO allocation case with a final sample size consisting of 395 IPOs issued in the years of 1999 and 2000 and 390 observations after dropping D/T cases. The first two columns show the regression results under full sample. The second two columns show the regression results under the subsample after dropping D/T cases. Columns 1 and 3 show the first-stage OLS regression results. Columns 2 and 4 show the second-stage probit ML regression results. All variables are defined in earlier tables. The standard errors of the two-stage estimation method are calculated using the nonparametric bootstrap. All standard errors are reported in parentheses.



Return) Lawsuit) Return) Lawsuit) Predicted initial return 2.4523*** 2.1413**

(0.9473) (0.9490) Prior NASDAQ return 0.9203** 0.9754**

(0.4450) (0.4513) Lawsuit growth rate 0.5920* 1.0668 0.6204** 1.1162

(0.3085) (1.0691) (0.3114) (0.9857) Ln(proceeds) -0.1058* 0.2605 -0.1108* 0.2612*

(0.0614) (0.1681) (0.0619) (0.1422) UWrank 0.0749 -0.0429 0.0787 -0.0445

(0.0677) (0.1918) (0.0681) (0.1612) VC backed 0.1996** -0.2489 0.2028** -0.2083

(0.0788) (0.2275) (0.0795) (0.2622) Ln(l+Age) -0.0389 -0.0788 -0.0311 -0.1247

(0.0508) (0.1321) (0.0530) (0.1295) Hightech 0.0866 0.0473 0.0911 0.0795

(0.1181) (0.3211) (0.1209) (0.3329) NYSE-AMEX -0.0406 -0.4536 -0.0092 -0.7432**

(0.1969) (0.3722) (0.2053) (0.3519) Insider selling -0.1522 0.2222 -0.1510 0.1790

(0.1057) (0.2773) (0.1074) (0.3038) Price update 1.5468*** -2.3161 1.5461*** -1.8278

(0.1166) (1.5950) (0.1175) (1.5298) Match SD -6.3022** 4.8101 -6.5395** 3.9918

(2.8463) (8.4532) (2.8706) (9.5254) UW premium 0.2000 0.2631 0.2207 0.1630

(0.1407) (0.3071) (0.1451) (0.3716) Overhang 0.0307*** (0.0639) 0.0306*** (0.0517)

(0.0089) (0.0392) (0.0090) (0.0364) Intercept 1.3964 -6.5325** 1.4244 -6.3862**

(1.1845) (2.8240) (1.1919) (3.0429) Pseudo R2(zd)R2) 0.5133 0.2740 0.5153 0.2721 *** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level.




return. The initial return of IPOs with no secondary offering is 1 1% higher than that of IPOs with secondary offerings. These results are all consistent with the findings in Loughran and Ritter (2004) that insiders including issuers and venture capitalists may have retained shares for future aftermarket profits in the late 1990s. Consistent with the information asymmetry hypothesis, IPOs of larger firms have a significantly lower initial return. Price update is again significantly positively related to initial return suggesting that underwriters only partially update the offer price to compensate institutional investors for their information revealing. Other coefficients in regression are not significant.

C. Deterrence Effect Results

Table IX illustrates the regression results of estimating Equation (8) using the two-stage estimation method in Maddala (1983). For both panels, the first two columns use the full sample. The second two columns use the sample excluding dismissed/terminated cases. Columns 1 and 3 are the first-stage results of Equation (4). Columns 2 and 4 are the second-stage regression results of the deterrence effect.

IPO allocation cases are studied using the prior NASDAQ return as the instrumental variable for initial return. With other characteristics remaining the same, Columns 1 and 3 indicate that the IPOs' initial return increases by 0.9% when the NASDAQ return prior to the offering date increases by 1%. The coefficient of prior NASDAQ return is significant at the 5% level in both columns suggesting that it is a strong instrumental variable for initial return.

The second-stage regression results of IPO allocation cases are interesting and different from traditional IPO cases. I find IPO underpricing is positively related to litigation risk at the 1% significance level. While IPO underpricing increases by 1%, its litigation risk of exposure to IPO allocation cases increases by about 0.95%. These findings suggest that IPO underpricing cannot deter, but actually trigger the IPO allocation cases, which is consistent with the nature of these cases. That is, shareholders blame the underwriters and institutional buyers inflate the aftermarket prices. Therefore, I conclude that issuers underprice their IPOs more heavily have no advantage in deterring IPO allocation lawsuits.

IPOs with larger proceeds tend to have higher litigation risk, which may indicate the plaintiffs' intentions of digging into these firms' "deep pockets." IPOs listed on the NASDAQ have a 0.2% higher probability of being involved in IPO allocation cases than those listed on the NYSE/AMEX. This is not surprising as most IPO allocation cases are related to high-tech IPOs listed on the NASDAQ. IPOs underwritten by investment banks that tend to set higher excess initial returns are more likely to be involved in IPO allocation cases, consistent with underwriters' laddering activities (Hao, 2007). However, the coefficient of UW premium is not significant. Other coefficients in the regression are not significant.

VI. Conclusion

The litigation risk hypothesis of IPO underpricing posits that issuers underprice IPOs in an effort to avoid costly litigation and that underpricing should be greater for issuers with ex ante higher levels of litigation risk. This paper reexamines this hypothesis for IPO samples in the varying legal and economic environment before and after 1995.

Evidence has indicated that firms' litigation risk is reduced in the three years after 1995 when the Private Securities Litigation Reform Act was enacted. Meanwhile, the economic environment also changed significantly after 1995. The big boom and bust experienced by the US stock market




was accompanied by particularly unusual behavior from IPOs. There is also a structural change in what IPO litigation means after 1998. I observe the appearance of a new type of lawsuit, as massive numbers of IPO allocation cases were filed in 2001. In order to see the impact of this changed legal and economic environment on the significance of LRH, I reexamine the LRH during this unique period and in these unique cases.

When litigation risk is reduced in the three years after 1995 (1996-1998), I find that firms' litigation risk plays a less significant role in IPO pricing strategy, and underpricing does deter traditional IPO cases when compared to that effect in the pre-1995 period. In the period after 1998, I find that IPO firms do use underpricing as insurance against IPO allocation lawsuits; however, issuers underpricing their IPOs more heavily cannot deter, but actually trigger the IPO allocation lawsuits. I conclude that the evidence of the LRH is very sensitive to the legal and economic environment. Issuers probably have other ways of handling litigation risk in IPOs, more so today than before, rendering a broad and blunt instrument such as underpricing less necessary (Hanley and Hoberg, 2008; Liu, Sherman, and Zhong, 2008). ■

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the relation between ipo underpricing and litigation risk revisited: changes between 1990 and 2002

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