Does Managerial Optimism Lead to Long-Run Underperformance? Evidence from Venture Capital-Backed IPOs. Jean-Sébastien Michel

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1 Does Managerial Optimism Lead to Long-Run Underperformance? Evidence from Venture Capital-Backed IPOs Jean-Sébastien Michel Current Version: February 15, 2010 Abstract In a sample of 777 venture capital-backed IPOs, I find that IPOs with more optimistic managers underperform IPOs with less optimistic managers by about 35% (30%) on an equal-weighted (value-weighted) basis in the 3 year period following the offer. Even relative to their style matched portfolio, the firms of the most optimistic managers underperform by about 40% (50%) on an equal-weighted (value-weighted) basis. These results are confirmed using a calendar-time risk-adjusted portfolio approach. Is the long-run underperformance a result of overinvestment or underinvestment? The evidence indicates that more optimistic managers tend to invest less than the IPOs with less optimistic managers and that this investment is sensitive to cash flows. Finally, managerial optimism is significantly and positively associated to first-day returns, suggesting that optimistic managers may also anchor on the middle price of the file price range. JEL classification: G12; G14; G24 Keywords: managerial optimism; long-run performance; underinvestment; initial public offering; venture capital; underpricing Assistant Professor of Finance, HEC Montréal, Université de Montréal, Montréal, Québec, H3T 2A7, Canada; jean-sebastien.michel@hec.ca; Phone: (514) ; Fax: (514) I would like to thank Walid Busaba, Ming Dong, Craig Dunbar, Steve Foerster, George Georgopoulos, Mark Kamstra, Elizabeth Maynes, Debarshi Nandy, Richard Smith and seminar participants at the 2009 European Financial Management Association meetings, the 2009 Financial Management Association meetings, HEC Montréal and Laval University for their very helpful comments.

2 1. Introduction In this paper, I find that IPOs with more optimistic managers underperform IPOs with less optimistic managers in the long-run. Moreover, the IPOs of the most optimistic managers underperform in the long-run when compared to a benchmark portfolio, while the IPOs of the least optimistic manager do not. Furthermore, firms with more optimistic managers invest less in research and development (R&D) and capital expenditures relative to firms with less optimistic managers. These results suggest that the underperformance of IPOs is in part driven by the underinvestment of the most optimistic managers relative to less optimistic managers. There is a large literature devoted to the long-run stock performance of initial public offerings. Ritter (1991) and Loughran and Ritter (1995) are among the first to document the long-run underperformance of IPOs. Ritter (1991) attributes the underperformance to an IPO market in which investors tend to be overoptimistic about the earnings potential of young growth firms. Other studies document additional patterns in long-run performance. For example, Brav and Gompers (1997) and Brav, Geczy, and Gompers (2000) find that underperformance is concentrated among nonventure capital-backed firms and small firms with low book-to-market ratios, and there is no general underperformance of IPO firms. Purnanandam and Swaminathan (2004) suggest that IPO investors pay too much attention to optimistic growth forecasts and too little attention to profitability in valuing IPOs, giving rise to overvaluation at the offer price and a long-run decline to fair value. Despite these and other studies on IPOs, the sources of differences in long-run underperformance remain unresolved. Why do some IPO firms underperform relative to others? Ritter and Welch (2002) suggest that overinvestment by optimistic managers may help explain some of the long-run underperformance. However, both overinvestment and underinvestment can lead to long-run underperformance. According to Heaton (2002), managers 1

3 who are optimistic about future projects overinvest by taking on negative net present value (NPV) projects that they perceive to be positive NPV projects. Alternatively, managers who are optimistic about assets in place underinvest, by declining positive NPV projects which require external financing, because they believe the market undervalues their company s stock. Both of these scenarios would lead to long-run underperformance. This study finds that IPOs with more optimistic managers underperform IPOs with less optimistic managers by about 35% on an equal-weighted basis in the 3 year period following the offer. On a value-weighted basis, firms of more optimistic managers underperform firms of less optimistic managers by about 30% over the same period. These returns are style-adjusted using a size and book-to-market reference portfolio. Indeed, even relative to their style matched portfolio, the firms of the most optimistic managers underperform by about 40% (50%) on an equal-weighted (value-weighted) basis. These results are confirmed using a calendar-time riskadjusted portfolio approach. Is the long-run underperformance a result of overinvestment or underinvestment? The evidence suggests that it is driven by underinvestment. The IPOs of more optimistic managers tend to invest less than the IPOs with less optimistic managers. The investment (research & development plus capital expenditures divided by assets) of more optimistic managers is significantly lower than for less optimistic managers for 4 of the 5 fiscal years after the offer. These results are robust to industry-adjusting and the inclusion of additional explanatory variables. I also find some evidence that investment is sensitive to cash flows, with high cash flow IPOs mitigating a portion of the underinvestment in some of the years following the offer. The main challenge in assessing the impact of managerial optimism on long-run performance is finding a reasonable measure of managerial optimism. I use the file-to-value ratio 2

4 as such a measure. The numerator is the value of the firm at the filing date, and it represents the manager s appraisal of the firm s value. The denominator is the most recent valuation, given after a round of funding in the two years prior to the filing date by one of the venture capitalists backing the IPO, and it represents the firm s intrinsic value. Therefore, the file-to-value ratio represents how optimistic the manager s valuation is relative to the venture capitalist s valuation. However, the passage of time, the venture capital round financing received between the venture capital valuation date and the filing date, and changes in market conditions between the venture capital valuation date and the filing date, may potentially explain some of the variation in the file-to-value. Furthermore, Ivanov et al. (2008) find that IPOs with higher venture capitalist reputation tend to have better long-run performance than IPOs with lower venture capitalist reputation. I purge the file-to-value ratio of these potentially confounding effects in a first-stage regression, and use the residual from this regression as a second measure of managerial optimism. I find that overall, IPO firm managers tend to be very optimistic, in that they value the firm on average 3 times higher than the venture capitalist valuation. Furthermore, the file-to-value ratio is positively associated with CEO age and gender, characteristics which have been found to be associated with optimistic managers in the literature. Also, the file-to-value ratio is positively associated with short-term debt and negatively associated with the fraction of the firm sold at the offer, firm characteristics which have been found to be associated with managerial optimism. These findings suggest that managers with high file-to-value ratios are in fact more optimistic than managers with low file-to-value ratios. There are three other potential explanations for the results found in this paper. First, Stein (2003) notes that the optimistic manager described in this paper shares its predictions with 3

5 models of agency theory such as that of Jensen and Meckling (1976) or models of information asymmetry such as that of Myers and Majluf (1984). I include multiple independent variables to control for the empire-building manager s preference for presiding over a larger firm and the information asymmetry between the manager and investors. Second, optimistic managers unwittingly price their issue high because they overestimate their future cash flows or underestimate the discount rate, whereas market timing managers realize that their assets are overvalued in the market, and price their offer high to take advantage of this misvaluation. 1 I control for this alternate explanation by including firm and market-level variables of consumer and investor optimism, as well as uncertainty, all of which may be at the root of the misvaluation which managers would potentially take advantage of. Last, Teoh, Welch and Wong (1998a) show that long-run market performance can be driven by discretionary current accruals. Managers can increase current accruals by, for example, advancing recognition of revenues with credit sales before cash is received or by delaying the recognition of expenses when cash is advanced to suppliers. Discretionary current accruals are not independent of managerial optimism however. Teoh et al. (1998a) note that high discretionary current accruals may result from unintentional overoptimism by the managers about future cash flows. I nevertheless include their measure of discretionary current accruals and find that the results are not being driven by earnings management. This paper contributes to the IPO literature by documenting empirically for the first time a role for managerial optimism in explaining the long-run performance of IPOs. This relationship is driven by managers who are optimistic about assets in place and underinvest in their firm in the years after the offer. This is also the first time that underinvestment has been found in a 1 See Baker, Ruback and Wurgler (2007) for more detail about irrational managers. 4

6 sample of IPOs: this may not be surprising given these firms are precisely the types of firms which are likely to have insufficient internal funds to subsidize all of their prospective projects. The remainder of the paper is structured as follows. Section 2 reviews the literature and develops the hypothesis. Section 3 describes the data and summary statistics of the sample. Section 4 examines the link between the file-to-value ratio and managerial optimism. Section 5 presents buy-and-hold portfolio returns, cross-sectional return regressions and calendar-time portfolio regressions. Section 6 examines whether overinvestment or underinvestment may explain the long-run underperformance of optimistic managers by examining investment activities. Section 7 reports short-run return regressions, and Section 8 concludes. 2. Literature Review and Hypothesis Development Ritter (1991) and Loughran and Ritter (1995) are among the first to document long-run underperformance for IPOs. Ritter (1991) attributes the underperformance to an IPO market in which investors are periodically overoptimistic about the earnings potential of young growth firms. Brav and Gompers (1997) and Brav et al. (2000) find that the underperformance described in Loughran and Ritter (1995) is concentrated among nonventure capital-backed firms and small firms with low book-to-market. Purnanandam and Swaminathan (2004) suggest that IPO investors pay too much attention to optimistic growth forecasts and too little attention to profitability in valuing IPOs, giving rise to a long-run decline to fair value. One explanation for the underperformance of some IPOs is that investors are irrational, in that they are too optimistic or overconfident. These behavioural traits lead to overvaluation followed by long-run underperformance. The overvaluation is cause by optimistic investors who pay too much for shares in a firm. Alternatively, having overconfident investors (some of who 5

7 err on the optimistic side while others err on the pessimistic side) would lead to the same conclusion if the pessimistic investors are kept on the sidelines due to short sales constraints or limits to arbitrage. The subsequent long-run underperformance is the result of investors discovering the true firm value over time. Miller (1977) predicts that in the presence of shortsales constraints, the price of a firm tends to reflect the valuations of the most optimistic investors, and thus tend to be upward biased. 2 This is the case because pessimistic investors are forced out of the market when short-sales are not available. Therefore, greater divergence in investor beliefs about the firm s true value will lead to short-run overvaluation and long-run underperformance. Even when short-sales are allowed after the offer, the view of pessimistic investors may not be reflected in the prices in the short-run because there are limits to arbitrage in practice (see Shleifer and Vishny (1997)). Daniel, Hirshleifer and Subrahmanyam (1998) propose that overvaluation is due to investor overconfidence about the precision of their private information. Ljungqvist, Nanda and Singh (2006) model IPO pricing assuming the existence of a fraction of sentiment-driven investors who are overoptimistic about the prospects of the IPO firms. With regards to IPOs, both of these theories imply overvaluation, which when subsequently corrected, leads to poor long-run performance. A number of recent empirical papers lend support to the existence of irrational investors in IPO markets. 3 Another potential explanation for the long-run underperformance of some IPOs is that managers are irrational, in that they overestimate their future cash flows or underestimate the discount rate. Heaton (2002) finds in his theoretical paper that managers who are optimistic about future projects overinvest by taking on negative NPV projects that they perceive to be 2 Miller (1977) could be considered semi-rational in the sense that the source of the investor heterogeneity is not specified. 3 Derrien (2005), Cornelli, Goldreich and Ljungqvist (2006), and Houge, Loughran, Suchanek, and Yan (2001) are some examples. 6

8 positive NPV projects. Alternatively, managers who are optimistic about assets in place underinvest, by declining positive NPV projects which require external financing, because they believe the market undervalues their company s stock. Malmendier and Tate (2005) find both theoretically and empirically, that overconfident CEOs invest more when they have more cash at hand, but curtail investment when they require external financing. 4 Further, the sensitivity of investment to cash flow is strongest for CEOs of equity-dependent firms. Ritter and Welch (2002) suggest that the overinvestment caused by managerial optimism may be a source of longrun underperformance in IPOs. Loughran and Ritter (1997) find evidence of this by examining the operating performance of a sample of SEOs. They report that firms are investing in what the market views as positive NPV projects, but are in fact often negative NPV projects, suggesting that managers are just as overoptimistic about the future firms profitability as are investors. In a recent survey of chief financial officers, Brau, Ryan and DeGraw (2006) find that companies focusing on immediate growth opportunities (i.e. firms that are likely to overinvest) experience long-run underperformance, while those that focus on long-term growth do not. The goal of this paper is to examine whether managerial optimism can help to explain some of the differences in the long-run performance of IPOs. Managerial optimism is rooted in empirical psychology literature. In attribution theory 5, a high firm valuation is a confirmation of a firm s high worth, which in turn increases managerial confidence. A low firm valuation however is suppressed and as a result, managerial confidence falls modestly if at all. This leads managers to be overconfident. Further, managerial overconfidence is difficult to arbitrage because managerial decisions are concerned with assets such as human capital which cannot be 4 Overconfidence in Malmendier and Tate (2005) is equivalent to overoptimism in Heaton (2002), in that overconfident managers overestimate the returns to their investment projects and view external funds as unduly costly. 5 See Weinstein (1980) and Daniel et al. (1998) for examples. For applications in corporate finance, see Roll (1986), Boehmer and Netter (1997), Heaton (2002) and Malmendier and Tate (2005). 7

9 arbitraged away (Heaton (2002)). Greater overconfidence should also be associated with greater optimism since pessimistic managers are unable to bet against their firm, and so consequently they stay on the sidelines. The main challenge is determining a measure of managerial optimism. I use the file-to-value ratio as such a measure. The numerator is the value of the firm at the filing date, and represents the manager s appraisal of the firm s value. The denominator is the most recent valuation, given after a round of funding in the two years prior to the filing date by one of the venture capitalists backing the IPO, representing the firm s intrinsic value. Therefore, the file-to-value ratio represents how optimistic the manager s valuation is relative to the venture capitalist s valuation. Specifically, the file-to-value ratio (FTV) is given by: FTV V mgr / V vc = P file N file / V vc where P file is the middle point of the file range, N file is the shares outstanding prior to the offer plus shares filed and V vc is the venture capitalist valuation. The use of a recent valuation as an estimate of the current valuation is not new. The International Private Equity and Venture Capital Valuation Guidelines (2006) 6 list the Price of Recent Investment as one of the most widely used valuation methodologies, and recommend its use for firms with irregular or negative earnings. In particular, the Guidelines note: Where there has been any recent Investment in the Investee Company, the price of that Investment will provide a basis of the valuation. 7 6 These guidelines were developed by the Association Française des Investisseurs en Capital (AFIC), the British Venture Capital Association (BVCA), and the European Private Equity and Venture Capital Association (EVCA), and are available at 7 A Fund s Investment refers to all the financial instruments in an Investee Company held by the Fund. The term Investee Company refers to a single business or group of businesses in which a Fund is directly invested. The Fund is a generic term used to refer to any designated pool of investment capital targeted at private equity Investment, including those held by corporate entities, limited partnerships and other investment vehicles. 8

10 More recently, in the mergers and acquisitions literature, Cooney, Moeller and Stegemoller (2008) have used this valuation methodology to examine the effect of the revision in the valuation of a private target firm on the announcement effect of the acquiring firm. However, the International Private Equity and Venture Capital Valuation Guidelines (2006) also note the following in reference to the Price of Recent Investment valuation methodology, The validity of a valuation obtained in this way is inevitably eroded over time, since the price at which the Investment was made reflects the effects of conditions that existed when the transaction took place. In a dynamic environment, changes in market conditions, the passage of time itself and other factors will diminish the appropriateness of this valuation methodology as a means of estimating value at subsequent dates. As such, the passage of time, the venture capital round financing received between the venture capital valuation date and the filing date, and changes in market conditions between the venture capital valuation date and the filing date, may potentially explain some of the variation in the file-to-value. Furthermore, Ivanov et al. (2008) find that IPOs with higher venture capitalist reputation tend to have better long-run performance than IPOs with lower venture capitalist reputation. I purge the file-to-value ratio of these potentially confounding effects in a first-stage regression, and use the residual from this regression as a second measure of managerial optimism. Using file-to-value and residual file-to-value as measures of managerial optimism, I test the hypothesis that IPO firms with more optimistic managers underperform IPO firms with less optimistic managers. This paper contributes to the IPO literature by documenting empirically for 9

11 the first time the role of managerial optimism in explaining the long-run performance of some IPOs. Also, this paper shows that the relationship between managerial optimism and long-run underperformance is driven by managers who are too optimistic about assets in place and underinvest in their company in the years after the offer relative to less optimistic managers. There are three other potential explanations for the results found in this paper. First, Stein (2003) notes that the optimistic manager described in this paper shares its predictions with models of agency theory such as that of Jensen and Meckling (1976) or models of information asymmetry such as that of Myers and Majluf (1984). I include multiple independent variables to control for the empire-building manager s preference for presiding over a larger firm and the information asymmetry between the manager and investors. Second, optimistic managers price their issue at a high value because they overestimate their future cash flows or underestimate the discount rate. Market timing managers, on the other hand, realize that their assets are overvalued in the market, and price their offer high to take advantage of this misvaluation. The misvaluation in the market may be due to asymmetric information between managers and investors, as in Bayless and Chaplinsky (1996), overly optimistic investors, as in Teoh, Welch and Wong (1998a, 1998b), or waves of investor sentiment, as in Baker and Wurgler (2007) 8. I control for this alternate explanation by including firm and market-level variables of consumer and investor optimism, as well as uncertainty, all of which may be at the root of the misvaluation which managers would potentially take advantage of. Third, Teoh et al. (1998a) show that long-run market performance can be driven by discretionary current accruals. Managers can increase current accruals by, for example, advancing recognition of revenues with credit sales before cash is received or by delaying the 8 See Eckbo, Masulis and Norli (2007) for a review of security offerings and market timing. 10

12 recognition of expenses when cash is advanced to suppliers. The business conditions usually faced by a firm in its industry may justify some accrual adjustments. Given that these business conditions can be expected by investors, current accruals must therefore be decomposed into nondiscretionary current accruals (current accruals predicted by industry conditions) and discretionary current accruals (current accruals not predicted by industry conditions). Discretionary current accruals are not independent of managerial optimism however. Teoh et al. (1998a) note that high discretionary current accruals may result from unintentional overoptimism by the managers about future cash flows. I control for the possibility that managerial optimism may be related to earnings management by including discretionary current accruals as an explanatory variable. 3. Data and Summary Statistics 3.1. Data The initial sample is made up of 884 venture capital-backed IPO firms from 1987 to 2004, which have a venture capital post-round valuation available within three years of the filing date. The sample begins in 1987 because VC-backed IPOs with post-round valuations within three years of the filing date are sparse before this date, and ends in 2004 in order to allow for a 5-year period to calculate long-run performance. IPOs must be covered by the Center for Research in Security Prices (CRSP) within the first 30 days of the offer and also covered by Compustat, as well as have an offer price of at least $5 and have shares outstanding before the offer available, leaving 795 observations. Additionally, unit offerings, closed-end funds, American Depository Receipts (ADRs), Real Estate Investment Trusts (REITs), Shares of Beneficial Interest (SBIs) are eliminated. The final sample has 777 IPOs between 1987 and

13 Data on the IPOs of ordinary common shares are obtained from the Securities Data Company s (SDC) New Issues database. Data on venture capital-backed IPOs such as round-byround financing, post-round valuations, firm founding date, shares outstanding before the offer and the names of CEOs are obtained from the SDC s Venture Expert database. Share prices, returns, share codes and shares outstanding after the offer are obtained from CRSP. Accounting data are obtained from Compustat. Carter and Manaster (1990) underwriter reputation rankings updated by Professor Jay Ritter are obtained from Professor Jay Ritter s website. 9 Size and bookto-market portfolios as well as Fama and French (1993) factors are obtained from Professor Kenneth French s website. 10 Consumer sentiment is obtained from the Reuters/University of Michigan Surveys of Consumers 11, and investor sentiment is obtained from Professor Jeffrey Wurgler s website. 12 Finally, CEO age, gender and education are hand collected from Securities and Exchange Commission proxy filings. Definitions for all of the variables used in this paper can be found in the appendix. Throughout the paper the data will be winsorized at the 1 and 99% level to ensure that extreme outliers are not driving the results. However, the results remain qualitatively similar when the data is not winsorized Summary Statistics Table 1 reports the summary statistics of firm and market characteristics between the VC valuation date and the file date, as well as VC financing characteristics and VC and underwriter reputation. File-to-Value (FTV) is the ratio of the middle point of the filing range multiplied by the number of shares outstanding before the offer plus shares filed, to the venture capital firm's

14 valuation obtained within three years before the filing date. FTV is greater than 1 for about 91% of the sample, indicating that IPOs are highly valued by almost all managers at the file date. In fact, managers value their firm at 4.22 (2.75) times the venture capitalist value in mean (median). The VC valuation is obtained up to three years prior to the file date, however on average; it is obtained 344 days before the file date. In fact, for 61% of firms, the VC valuation is obtained within 1 year of the file date. Also, while firms receive about 9 million dollars in additional funding between the VC valuation date and the file date, 67% of firms receive no additional funding. As would be expected over the course of an average year, the S&P500 level and the consumer price index increase. Consumer sentiment also increases, but investor sentiment decreases insignificantly. In terms of financing characteristics, the VC valuation is obtained during the seed or early stage for 13% of firms, during the expansion stage for 48% of firms, and during the late stage for 31% of firms. On average, 7 different VC firms provide financing each company in the sample. These companies receive on average 4 rounds of financing for total financing of about 60 million dollars. Firms tend to retain high reputation underwriters, which is not surprising given this sample is entirely composed of VC-backed IPOs. When compared to all the VC-backed IPOs during the same period (not shown here), the underwriter reputation in this paper is actually quite representative. Figure 1 plots the mean and median file-to-value ratio and the number of IPOs for each year between 1987 and Aside from the first five years, in which there are only a total of 10 IPOs, File-to-Value remains fairly consistent through time: mean values vary from 2.28 to 4.86, while median values vary from 1.90 to Residual Managerial Optimism 13

15 Table 2 reports the coefficients from the regression of the file-to-value ratio on changes in firm and market conditions between the venture capital valuation date and the filing date (including the passage of time itself), as well as VC financing and VC and underwriter reputation. The goal of this regression, as mentioned in the last section, is to purge expected variations in File-to-Value, which are due to changes in market conditions or due to the impact of VCs and their financing strategy. The numbers in parentheses below the estimates are heteroscedasticity consistent t-statistics from an OLS regression. The cross-sectional relationship with File-to-Value (FTV) is formally tested using the following multivariate regression model: FTV i = β 0 + β 1 Ln(Nbr of Days i ) + β 2 Ln(Additional Funding i ) + β 3 ΔS&P500 i + β 4 ΔCPI i + β 5 ΔConsumer Sentiment i + β 6 ΔInvestor Sentiment i + β 7 VCREP i + β 8 Seed Stage i + β 9 Early Stage i + β 10 Expansion Stage i + β 11 Late Stage i + β 12 Ln(Nbr of Firms i ) + β 13 Ln(Nbr of Rounds i ) + β 14 Ln(Total Investment i ) + β 15 UWREP i + ε i All variables are described in detail in the appendix. Model 1 reports the impact of changes in firm and market characteristics on File-to- Value. As suggested in the caveats of this method of valuation, the farther away the venture capital valuation date is from the filing date, the greater the is the file-to-value ratio. The amount of venture capital funding received between the venture capital valuation date and the filing date is negatively related to File-to-Value. This may indicate that VCs are providing more funding to the firms in their portfolios that are not performing as well. To capture changes in market conditions, I include changes in the (i) level of the S&P 500; (ii) consumer price index; (iii) consumer sentiment index; and (iv) investor sentiment. Changes in the CPI are significantly and negatively related to changes in FTV. This result is somewhat counterintuitive. One potential 14

16 explanation is that demand for IPOs (or stocks in general) falls when the price of goods rises. Also significant is the positive impact of changes in investor sentiment. Model 2 reports the impact of VC financing, and VC and underwriter reputation on File-to-Value. I include the stage level of financing at the time of the VC valuation to capture firm growth. VC and underwriter reputation are included to pick up any certification effect. I also include the number of VC firms, the number of financing rounds and the total investment to capture differences in VC interest, staging and commitment, respectively. Stage level is insignificant for all stages. The number of rounds and total investment both predict significantly and negatively File-to-Value. This may indicate that VCs are providing more funding to the firms in their portfolios that are not performing as well. Lastly, more reputable underwriters do extract more value at the offer, while more reputable VCs do not. Model 3 incorporates all of the independent variables from models 1 and 2. The only remarkable difference in the coefficients from models 1 and 2 is that the coefficient on additional VC funding provided between the VC valuation date and the file date is now significantly positive when controlling for total funding. This suggests that funding provided near to the going public process does lead to a higher valuation at the offer. Throughout the rest of this paper, the residual from Model 3 will serve as a second measure of managerial optimism, which is purged of the effects of changes in market conditions and the impacts of venture capitalists and lead underwriters. 4. Managerial Optimism In this section, the link between the file-to-value ratio and managerial optimism is explored. In order to do this, I look at whether File-to-Value is related to some CEO and firm characteristics, which have been associated with managerial optimism in the literature. 15

17 Specifically, I examine three CEO characteristics (gender, age and education) and three firm characteristics (short-term debt, long-term debt and the fraction of the firm sold in the IPO), all of which are associated with managerial optimism. Barber and Odean (2001) find that men tend to be more overconfident than women in that they overestimate the precision of their information. This leads them to turn over their portfolios more often and, given trading costs, leads to worse market performance. For entrepreneurs, greater overconfidence should be associated with more optimism since pessimistic entrepreneurs are unable to sell-short their venture, and so consequently they stay on the sidelines. Landier and Thesmar (2009) argue that entrepreneurs with more experience and higher education enjoy a larger outside option on the labour market, which translate into more optimism. However, education could also lead to lower optimism if it gives entrepreneurs a big picture view. Both Heaton (2002) and Landier and Thesmar (2009) find a pecking order of financing when managers are optimistic. Optimistic managers prefer to use internal funds first, debt second (short-term debt before long-term debt) and equity last. According to this pecking order, more optimistic managers raising financing through an IPO must have more debt, especially short-term debt. Further, if optimistic managers overestimate future cash flows of assets in place, they will believe that their firm is undervalued by capital markets and will restrict the fraction they sell in their company. Table 3 examines the CEO and firm characteristics of high, mid and low File-to-Value portfolios, as well as a high minus low File-to-Value zero-investment portfolio and all IPOs. Panel A reports the results for raw File-to-Value (FTV) portfolios, while Panel B reports the results for residual File-to-Value (RFTV) portfolios. The numbers in parentheses are t-statistics based on simple t-tests for differences in means. In terms of CEO characteristics, high FTV (RFTV) firms have 3% (5%) more male CEOs than low FTV (RFTV) firms. Further, high FTV 16

18 (RFTV) firms tend to have slightly older CEOs than low FTV (RFTV) firms, although the age differences are not significant. Last, high FTV (RFTV) firms have less educated CEOs than low FTV (RFTV) firms. As for firm characteristics, high FTV (RFTV) firms sell 5% (6%) less of the company at the IPO than low FTV (RFTV) firms. High FTV (RFTV) firms also have more short and long-term debt when compared to low FTV (RFTV) firms. Taken together, this evidence suggests that high File-to-Value firms do indeed have more optimistic CEOs than low File-to- Value firms. Given that these variables may be correlated, I will examine their marginal impact in the multivariate analysis below. Table 4 uses cross-sectional analysis to determine the relationship between managerial characteristics and File-to-Value. Columns 1 and 2 examine the impact of managerial optimism on raw File-to-Value ratio and on Residual File-to-Value, respectively. The cross-sectional relationship with the FTV in column 1 is formally tested using the following multivariate regression model: FTV i = β 0 + β 1 GENDER i + β 2 Ln(CEO Age i ) + β 3 EDUCATION i + β 4 Fraction Sold i + β 5 STD/A i + β 6 LTD/A i + ε i All variables are described in detail in the appendix. A notable difference from the univariate results in Table 3 is that CEO age becomes significant. Economically, a 10% increase in the CEO s age would lead to a 6% increase in File-to-Value. Another difference is that CEO education becomes much less significant while short-term debt becomes more significant. Finally, long-term debt becomes insignificant. All independent variable coefficients, except for long-term debt, support the idea that File-to-Value measures managerial optimism. It is possible that long-term debt also represents the loss of autonomy for CEOs, a trait that is associated with 17

19 more optimism by Landier and Thesmar (2009). As such, optimistic CEOs with a desire for autonomy may shy away from long-term debt in order to retain control of the future cash flows which they overestimate, even though long-term debt is a less costly option than outside equity. The cross-sectional relationship with RFTV in column 2 is formally tested using the same multivariate regression model as above, except that RFTV is the dependent variable. As in the case regression on FTV, CEO age becomes positive and highly significant, while long-term debt becomes negative. Another notable difference is that the fraction of the company sold at the IPO becomes even more economically significant when compared to the univariate results. In particular, a 10% decrease in Fraction Sold is associated with a 16.4% increase in RFTV. The results from this section indeed support the idea that File-to-Value captures managerial optimism. 5. Managerial Optimism and Long-Run Market Performance This section examines whether there is a relationship between managerial optimism and long-run market performance. I find that IPOs with more optimistic managers underperform IPOs with less optimistic managers in the 3-5 years following the offer. Fama (1998) and Brav et al. (2000) make the point that equal-weighting a portfolio s returns gives more weight to small stocks relative to their capitalization in the market, and therefore leads to more severe bad-model problems. 13 They also point out that returns which are value-weighted more accurately capture the total wealth effects experienced by investors. For these two reasons, we examine both equal and value-weighted portfolio returns. As will be shown, this result is robust to a style-adjusted 13 Bad-model problems refer to the asset pricing model not being a complete description of expected returns, or the sample, which is period specific, not reflecting the true model s predictions. 18

20 benchmark as well as value-weighting. Empirical p-values are also reported since the sample distribution of buy-and-hold returns tends to be highly misspecified in long-run event studies Cross-Sectional Univariate Analysis Table 5 reports the equal and value-weighted buy-and-hold returns of high, mid and low File-to-Value portfolios, as well as a high minus low File-to-Value zero-investment portfolio and all IPOs, for 3 and 5-Year periods after the offer. Panel A reports results for raw File-to-Value (FTV) portfolios, while Panel B reports results for residual File-to-Value (RFTV) portfolios. The numbers in parentheses are t-statistics based on simple t-tests for differences in means. The raw buy-and-hold return (BHR) is the IPO firm's buy-and-hold return using monthly returns, starting the month after the offer, and ending 3 and 5 years after the offer, or the on the delisting date, whichever is earlier. 15 The style-adjusted buy-and-hold return (SBHR) is the difference between the IPO firm's BHR and the BHR from an equal-weighted portfolio matched on size and bookto-market. On an equal-weighted basis, all of the high File-to-Value portfolios significantly underperform the low File-to-Value portfolios, even when a style-adjusted portfolio is used as a reference. Moreover, the decrease in market performance is monotonic across portfolios. The strongest underperformance overall can be found in the 3-year buy-and-hold returns: high FTV (RFTV) firms underperform low FTV (RFTV) firms by 34.1% (36.0%) on a style-adjusted basis. These numbers are significant at the 5% level with both the t-statistics and the empirical p- values. Further, high FTV firms underperform significantly relative to their style benchmark, while low FTV firms do not. On a value-weighted basis, the results are slightly lower than those which use equal-weighting, but are nevertheless significant at the 5% level with both the t- 14 See Purnanandam and Swaminathan (2004, p. 829) for a description of this procedure. Briefly, using empirical p- values preserves the skewness, time-series autocorrelation and cross-sectional properties of the original sample, all of which are at the root of the misspecification of long-run returns. 15 I use the delisting returns if these are available in CRSP after the delisting date. 19

21 statistics and the empirical p-values. 16 The strongest underperformance overall can again be found in the 3-year buy-and-hold returns: high FTV (RFTV) firms underperform low FTV (RFTV) firms by 28.2% (27.5%) on a style-adjusted basis. One difference with equal-weighted portfolios is that all value-weighted FTV (RFTV) portfolios underperform significantly relative to their style benchmark, suggesting that size and book-to-market are inadequate risk controls Cross-Sectional Multivariate Analysis Table 6 uses cross-sectional analysis to determine the impact of File-to-Value on longrun style-adjusted returns, controlling for firm, offer and market characteristics that have been found to influence long-run market performance. In particular, the dependent variables included are mainly to control for firm size (VCV, Assets, Sales), asymmetric information and uncertainty (File Range, Age, TECH, NASDAQ, NYSE), misvaluation (Consumer Sentiment, Investor Sentiment, BV/VCV) and earnings management (DCA). The cross-sectional relationship with long-run style-adjusted returns is tested using the following multivariate regression model: SBHR i = β 0 + β 1 FTV i + β 2 Ln(VCV i ) + β 3 Ln(Assets i ) + β 4 Ln(Sales i ) + β 5 File Range i + β 6 Ln(1+AGE i ) + β 7 TECH i + β 8 NASDAQ i + β 9 NYSE i + β 10 Consumer Sentiment i + β 11 Investor Sentiment i + β 12 BV/VCV i + β 13 VCREP i + β 14 UWREP i + β 15 DCA i + β 16 PADJ i + β 17 FDRET i + ε i All variables are described in detail in the appendix. The numbers in parentheses below the estimates are heteroscedasticity consistent t-statistics from an OLS regression. Model 1 uses raw File-to-Value (FTV) as the measure of managerial optimism, while Model 2 uses residual File- 16 One exception is the 3-year value-weighted BHR differential between high and low FTV portfolios, which has an empirical p-value of I will examine calendar-time Fama-French risk-adjusted portfolios in Section 5.3 in order to address this issue. 20

22 to-value (RFTV). Predicted File-to-Value (PTV) is also included in Model 2 to make it comparable to Model 1. I first examine the impact of the file-to-value ratio on 3-year BHRs in columns 1 and 2. Overall, I find a negative and significant relationship between File-to-Value and style-adjusted buy-and-hold returns. Economically, a one standard deviation increase in FTV (RFTV) leads to a 15.0% (14.2%) decrease in style-adjusted returns. For 5-year BHRs in columns 3 and 4, there is a stronger and more significant negative relationship between File-to- Value and long-run returns. Economically, a one standard deviation increase in FTV (RFTV) leads to a 23.9% (22.7%) decrease in style-adjusted returns. The venture capital valuation and Assets seem to capture some additional size effect not captured by the style-adjustment. Sales however are positively and significantly related to style-adjusted returns. It is possible that controlling for assets, the marginal impact of sales actually represents better accounting performance. Surprisingly, firm age has no relationship with 3-year SBHRs, and has a significantly negative relationship with 5-year SBHRs. This is inconsistent with Ritter s (1991) finding that finds a significantly positive relationship between firm age and buy-and-hold returns. The difference is due to the subsample of VC-backed IPOs examined in this paper, which are about twice as large and 9 years older than in the overall sample of IPOs. Discretionary current accruals lead to lower SBHRs as expected, although this relationship is not significant. Lastly, first-day returns are significantly and negatively associated with SBHRs, but only in the 3-year results, suggesting that some of the long-run underperformance may be caused by initial overvaluation Calendar-Time Portfolio Analysis The evidence presented up to now shows that high File-to-Value IPOs underperform low File-to-Value IPOs in the 3-5 years following the offer. These tests, which controlled for 21

23 systematic risks in the case of event-time style-adjusted returns, still have some limitations. In this section, I report calendar-time risk-adjusted performance of high, medium and low File-to- Value portfolios as well as a high minus low File-to-Value zero-investment portfolio. These tests avoid the autocorrelation problems present in overlapping returns and account for crosscorrelation among returns across clustered events. I examine these performance measures over the first 3 and 5 years after the IPO. While the sample is composed of subset of VC-backed firms going public from 1987 to 2004, I only begin to examine portfolio performance in 1996 and end in 2006 because I require that enough firms be in each portfolio in order to make reliable inferences. Calendar-time risk-adjusted returns (FF-α) are obtained using Fama and French (1993) three-factor regressions involving the equal-weighted monthly calendar time returns of IPO portfolios. IPOs can remain in the sample for the holding period after which time they drop out. More specifically, for the 3 and 5-year holding periods, the monthly portfolios are constructed as follows: IPOs are assigned to one of high, medium, or low File-to-Value portfolios as they become public, and stay in their respective portfolios for 3 and 5 years, respectively. The monthly returns used to run the Fama-French three-factor regression are the equal and valueweighted monthly returns for each File-to-Value portfolio. The risk-adjusted return is the intercept from this regression. Table 7 reports the results of these regressions for equal-weighted portfolios, the intercepts of which can be interpreted as the risk-adjusted monthly abnormal returns for 3 and 5- year holding periods. Panel A reports results for raw File-to-Value (FTV), while Panel B shows results for residual File-to-Value (RFTV). Overall, I find no underperformance on a risk-adjusted basis in this sample of VC-backed IPOs (All IPOs). In Panel A, the intercept for the high minus 22

24 low FTV zero-investment portfolio is 0.69% in the 3-year horizon and -1.10% in the 5-year horizon (significant at the 1% level), indicating that the high FTV portfolio underperforms the low FTV portfolio by about 25% ( ) over a 3-year period and by about 66% ( ) over a 5-year period. The 3-year results are consistent with the style-adjusted buy-and-hold return differentials found in Table 5. However, the 5-year results are much greater in magnitude than the style-adjusted buy-and-hold return differentials found in Table 5. This difference may be due to the fact that I require a sufficient number of observations to implement the calendar-time approach, which restricts the sample to as mentioned above. Overall, the change in abnormal return is monotonic across portfolios. Panel B presents results that are similar to those in Panel A. The underperformance for the high minus low RFTV portfolio is slightly larger in magnitude than for the high minus low FTV portfolio in the 3-year results, but slightly smaller in the 5-year results. Economically, the high RFTV portfolio earns about 31% ( ) less than the low RFTV portfolio in the 3-year horizon, and about 56% ( ) less in the 5-year horizon. Table 8 reports the results of the calendar-time regressions for value-weighted portfolios. Panel A reports results for raw File-to-Value (FTV), while Panel B shows results for residual File-to-Value (RFTV). Again, on the overall sample, I find no underperformance on a riskadjusted basis in this sample of VC-backed IPOs (All IPOs). In Panel A, the intercept for the high minus low FTV zero-investment portfolio is 1.74% in the 3-year horizon and -1.15% in the 5-year horizon, indicating that the high FTV portfolio underperforms the low FTV portfolio by about 63% ( ) over a 3-year period and by about 69% ( ) over a 5-year period. Both the 3-year and 5-year results are much greater in magnitude than the value-weighted style-adjusted buy-and-hold return differentials found in Table 5. As mentioned above, this 23

25 difference may be due to the fact that I require a sufficient number of observations to implement the calendar-time approach, which restricts the sample to as mentioned above. When examining the individual portfolios, we can see that high FTV firms underperform significantly on a risk-adjusted basis, while low FTV firms do not. Hence, the underperformance in the high minus low hedge portfolio is driven by the underperformance of high FTV firms rather than the outperformance of low FTV firms. This supports the idea that optimistic managers are destroying value rather than the idea that conservative managers are creating value. Economically, high FTV firms underperform on a risk-adjusted basis by 40% in the 3-year horizon and by 69% in the 5-year horizon. As with the equal-weighted results of Table 7, the change in abnormal return is monotonic across portfolios. Panel B presents results that are similar to those in Panel A. One difference is that the underperformance for the high minus low RFTV portfolio is larger in magnitude than the high minus low FTV portfolios in the 5-year results. 6. Managerial Optimism and Long-Run Investment In this section, long-run investment is analyzed to determine whether the long-run return differentials found in the last section might be the result of overinvestment or underinvestment on the part of optimistic managers. Recall from Section 2 that managers who are optimistic about future projects overinvest by taking on negative NPV projects that they perceive to be positive NPV projects. Alternatively, managers who are optimistic about assets in place underinvest by declining positive NPV projects which require external financing because they believe the market undervalues their company s stock. Therefore, I also examine the sensitivity of this relationship to cash flow. The evidence that will be provided supports the latter interpretation. 24