CEO overconfidence and corporate cash holdings

Journal Pre-proof CEO overconfidence and corporate cash holdings

Yenn-Ru Chen, Keng-Yu Ho, Chia-Wei Yeh PII:

S0929-1199(20)30021-3

DOI:

https://doi.org/10.1016/j.jcorpfin.2020.101577

Reference:

CORFIN 101577

To appear in:

Journal of Corporate Finance

Received date:

23 November 2018

Revised date:

22 November 2019

Accepted date:

11 January 2020

Please cite this article as: Y.-R. Chen, K.-Y. Ho and C.-W. Yeh, CEO overconfidence and corporate cash holdings, Journal of Corporate Finance(2020), https://doi.org/10.1016/ j.jcorpfin.2020.101577

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© 2020 Published by Elsevier.

Journal Pre-proof We are grateful to Lauren H. Cohen, Yanzhi Wang, and K. C. John Wei for their valuable comments and suggestions. The paper has benefited from comments from the conference participants at the 2015 Financial Management Association Annual Meeting, 2017 Asian Finance Association Meeting, 2017 International Conference and Annual Meeting of Taiwan Finance Association , and 2017 Taiwan Finance Symposium on Corporate Finance as well as seminar participants at National Taiwan University and National Central University.

CEO Overconfidence and Corporate Cash Holdings

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Department of Finance, National Chengchi University

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Department of Finance, National Taiwan University

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Yenn-Ru Chena, Keng-Yu Hob,* [email protected], Chia-Wei Yehb

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Corresponding author at: Depart ment of Finance, National Taiwan Un iversity, No.1, Roosevelt Road, Section 4, Taipei 10617, Taiwan.

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Abstract This study proposes chief executive officer (CEO) overconfidence to be an alternative explanation to corporate cash holdings. We find positive effects of CEO overconfidence

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on the level of cash holdings and the value of cash, which are mainly due to the investment environments faced by firms. The positive effects of CEO overconfidence on

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cash holdings level and cash value are barely affected by the traditional motives of cash holdings based on trade-off and agency theories. The analysis of cash sources further

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explains why firms with overconfident CEOs can aggressively pursue risky investments and maintain large cash holdings at the same time. Although the prior literature indicates

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that overconfident CEOs tend to avoid equity issues for their capital investments, the contribution to cash savings from equity is higher than that from debt. Additional robustness tests also support our empirical findings. Keywords: CEO overconfidence; Cash holdings; Value of cash.

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1. Introduction The cash literature shows that firms accumulate cash assets mainly for transaction and precautionary1 and agency motives 2 . Although the two motives are developed from different theories (the trade-off and agency theories, respectively), overemphasizing precautionary motive would be likely leading to agency problems because excess cash holdings provide managers with excess discretion (Opler, Pinkowitz, Stulz, and Williamson, 1999). However, the dynamics in economic conditions and business

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environments makes firms hold cash assets for the precautionary purpose more than agency motive (Bates, Kahle, and Stulz, 2009; McLean, 2011). Both theories to explain corporate cash holdings are based on what corporate cash could be used, but do not

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considered the belief of decision makers, who decide how to use the cash. In this study, we argue that CEOs’ attitude toward risky investments would also affect corporate cash

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holdings.

The literature documents the influence of CEO overconfidence on corporate

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financing and investment decisions (Malmendier and Tate, 2005; Malmendier and Tate, 2008; Malmendier, Tate, and Yan, 2011; Hirshleifer, Low, and Teoh, 2012; Ben-David,

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Graham, and Harvey, 2013). A common finding is that firms with overconfident CEOs (OC firms) tend to invest more if they have sufficient internal funds than firms without overconfident CEOs (non-OC firms). Since overconfident CEOs tend to either

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overestimate the investment payoffs or underestimate the investment risk, they have a

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disagreement on the firms’ equity value with outside investors and therefore would avoid external equity financing (Malmendier and Tate, 2005). When overconfident CEOs mainly invest new projects by internal funds, the capital spending should then greatly reduce the cash assets in OC firms. Overconfident CEOs are hired to conduct challenging and risky investments that may be otherwise not taken by non-overconfident CEOs because they tend to perform hard tasks rather than easy tasks. For instance, OC firms are found to have more R&D 1

Keynes (1936) p roposes three motives for holding cash: to have the ability to conduct daily operations (transaction motive), to have the ability to meet unexpected contingencies (precautionary motive), and to take advantage of future investment opportunities (speculative motive). Later studies tend to combine the speculative motive with the precautionary motive (e.g., Opler et al., 1999; Bates et al., 2009; McLean, 2011). Therefo re, in this paper, when we discuss the precautionary motive, we are actually considering the combination of the precautionary and speculative motives. 2 See Myers and Majluf, 1984; Jensen, 1986; Harford, 1999; Opler et al., 1999; Dittmar and Mahrt -Smith, 2007; Harford et al., 2008; Oler, 2008.

Journal Pre-proof spending and have better innovation outputs (Malmendier and Tate, 2008). Such high and persistent R&D expenses in OC firms require them to retain a certain level of cash holdings (Bates et al., 2009) because innovation involves higher level of idiosyncratic risk (Pastor and Veronesi, 2009). Taking the two effects together, overconfident CEOs could show positive effect on cash holdings to meet their investment pattern, or they could lead to negative effect on cash holdings due to overinvestment behavior. Preliminary summary statistics from the past literature show higher means of cash holdings for OC firms than for non-OC firms. We note that firm characteristic between

overconfidence on the level of cash holdings is unclear.

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OC firms and non-OC firms are different, so the motive of cash holdings between two types of firms could also be different. Without thorough analyses, the effect of CEO

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A more important question is whether the cash held by OC firms create or destroy firm value. There are two issues from the prior literature regarding the financing and

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investment decisions of OC firms. First, more debt issuances for OC firms’ investments needs due to the resistance to equity finance (Malmendier et al., 2011) would increase the

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financial risk of OC firms. Using debt financing in OC firms to support high risk taking could lead to the excessive risk taking and thus negatively affects firm value. Second, although corporate innovative activities involve higher risk, they also provide potential

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for future growth, and the equity market would offer premium to corporate innovation. Refusing to use equity financing and use debt financing could make the financial flexibility lower or lead to underinvestment, both making firm value lower. Therefore, if

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OC firms are able to accumulate cash to avoid the above mentioned issues, they should experience higher value of cash because firms with lower financial accessibility tend to

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have higher value of cash (Faulkendar and Wang, 2009; Denis and Sibilkov, 2010). However, the value of cash could be decreased with the existence of agency problems. When CEOs are holding large cash for their personal interests, they are likely to destroy firm value by engaging in value-decreasing investments, including mergers and acquisitions (M&As) 3 . The issue is whether the OC CEOs are free of agency problems. Malmendier and Tate (2008) find that overconfident CEOs are more likely to be involved in value-destroying M&As. However, they emphasize that overconfident CEOs, being different from traditional empire builders, believe that they act on the interests of shareholders and are more likely to personally invest in their firms. Such argument is consistent with Roll (1986), who suggests that overconfidence is not an agency problem because overconfident CEOs honestly believe that they are creating 3

See Jensen (1982), Harford (1999), and Richardson (2006).

Journal Pre-proof shareholder value as they are destroying it. Although no empirical studies directly examine this agency issue for OC firms, some other studies have similar reasoning. For instance, Goel and Thakor (2008) show theoretically that overconfident individual is more likely to win the intrafirm tournament of CEO position. If overconfident managers are prone to make value-decreasing decision for firms, one question will rise up, i.e., why firms hire overconfident individual as CEO. Hirshleifer et al. (2012) argue that overconfident managers will be more enthusiastic to risky and challenging projects because people are more likely to become overconfident

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on dealing with difficult tasks rather than easy tasks (Griffin and Tversky, 1992). They further show that firms with overconfident managers will have higher return volatility, heavier R&D expenditure, and greater innovation. Those firms also achieve in better

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innovation success. Their results supplement Gervais, Heaton, and Odean (2011) that firms in risky and highly- growth industry are prone to hire overconfident managers,

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implying that overconfident CEOs are more willing to take challenging and risky projects because they believe in their ability on creating value to their companies. In this study,

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we explore the agency issue as well as other cash holdings motives in OC firms by examining their level of cash holdings and value of cash. Covering a U.S. sample of 17,942 firm–year observations between 1992 and 2016,

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we first examine the effect of CEO overconfidence on cash holdings by adapting the models of Opler et al. (1999) and Bates et al. (2009). We find a positive effect of CEO overconfidence on level of cash holdings. This result indicates that although OC firms

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may invest more than non-OC firms, they have higher intention to hold more cash for their needs of investments. Maintaining a higher level of cash holdings provides the

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overconfident CEOs with more discretion on their future capital spending without the market monitoring. This finding is consistent with the CEO overconfidence literature where overconfident CEOs consider external financing costly and thus have a greater incentive to build up cash for unexpected needs. However, a high level of cash holdings could still lead to overinvestments in OC firms even if assuming no or low agency problems. Therefore, how high level of cash holdings in OC firms affect firm value becomes the key issue. We adapt the model of Faulkender and Wang (2006) for the marginal value of cash and find that the market values the additional dollar of cash accumulation higher for OC firms than for non-OC firms. This result indicates that the market considers OC firms to be more capable of creating value by using cash assets for future investments than non-OC firms. Following the CEO overconfidence literature, overconfident CEOs are hired to undertake risky and challenging projects that normally require large capital. With sufficient cash,

Journal Pre-proof overconfident CEOs would be able to create value to shareholders via the above behavior. As the findings show that CEO overconfidence has positive effects on the level of cash holdings and the value of cash, we then perform the channel analysis to verify that such positive effect is due to the investment environment. In innovative industries, the level of cash holdings and the value of cash is significantly higher for OC firms than for non-OC firms. However, in other industries, we do not find similar results. The finding indicates that the market values cash higher for OC firms in innovative industries because it allows overconfident CEOs to conduct risky investments. This finding is also

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consistent with Hirshleifer et al. (2012), in which the OC firms are more capable to transfer growth opportunities to firm value than non-OC firms in innovative industries, but not in other industries. The channel analysis indicates that the positive effects of CEO

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overconfidence on cash level and cash value are mainly due to the investment environment, significantly higher only for OC firms in innovative industries. The

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findings are sensible in that overconfident CEOs are more likely to be hired in the industries where challenging and risky investments persistently exist.

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We further examine whether the effects of CEO overconfidence on cash holdings and cash value would vary with the traditional motives of cash holdings: (1) growth

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opportunities (Tobin’s Q) for the transaction motive; (2) financial constraints (SA index)

cash

for

OC

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for the precautionary motive; (3) corporate governance (institutional ownership and E- index) for the agency motive. We contrast the level of cash holdings and the value of firms

between

high- transaction/precautionary

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low-transaction/precautionary (between well- governed and poorly-governed) groups to verify the effects of transaction/precautionary (agency) motive in explaining the effects of

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CEO overconfidence on corporate cash policies. Our empirical results show that the positive effect of CEO overconfidence on the level of cash holdings is only affected by a firm’s financial condition but the positive effect does not significantly vary with growth opportunity or corporate governance. The positive effect of CEO overconfidence on the value of cash does not vary with by all traditional motives of cash holdings. This finding is consistent with the argument in the CEO overconfidence literature that overconfident CEOs are less likely to pursue personal interests although they could sometimes undertake value-decreasing investments. The discussion of CEO overconfidence is often concentrated on the disagreement o f equity value between managers and outside investors, resulting in less equity issuance. Although Malmendier et al. (2011) clearly identify the equity issuance frequency is significantly less than the debt issuance frequency, the relative issue size is however not addressed in the literature. While OC firms are more likely to issue debt, the average

Journal Pre-proof leverage is however still smaller than non-OC firms (Deshmukh, Goel, and Howe, 2013). Meanwhile, the cash literature indicates that proportion of net proceeds saved as cash assets tends to be higher for equity issuances than debt issuances or internal cash flows (McLean, 2011). That is, following the pecking order theory, firms would be least in favor of equity issuances when they need capital for investments. However, when they do, the high issuing expenses would make the issue size larger than the capital needs of investments. As a result, the proportion of net proceeds saved as cash assets would be larger. We argue that although overconfident CEOs are less likely to issue equity, but

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when they do, they are likely to raise more money than needed, compared with non-overconfident CEOs. We adapt the model of McLean (2011) to examine the above prediction. We find that,

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consistent with the CEO overconfidence literature, OC firms rely greatly on internal cash flows and debt issuances rather than equity issuances. Nevertheless, non-OC firms shows

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similar pecking order as well. Although the size of debt issue and cash flows are higher for OC firms than non-OC firms, the size of equity issues exhibit similar pattern. That is,

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the scales of financing from all sources are higher for OC firms to support the nature of their higher investments than non-OC firms. Furthermore, we find that firms save larger proportion of net proceeds from equity issues than from debt issues, and this tendency is

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even higher for OC firms than for non-OC firms. Our empirical results confirm our prediction. In addition, the finding of saving larger proportions of net proceeds from all financing sources for OC firms than for non-OC firms helps to explain why OC firm can

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spend more on risky investments and still hold larger cash assets than non-OC firms. We also perform additional tests to mitigate the potential endogeneity concerns. By

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examining the CEO turnover sample, we have two main findings. First, firms are more likely to hire a succeeding CEO who has the same managerial overconfidence type as the proceeding CEOs. Second, cash flows and the lagged cash flows do not affect the type of CEO to be hired. By using CEO turnover as a quasi-exogenous event, we find that change in average excess cash is higher (lower) for firms which switch from a non-overconfident (overconfident) CEO to an overconfident (non-overconfident) one. Our findings from additional tests mitigate the concern of endogenous relation between corporate cash holdings and overconfident CEO selection. The study contributes to the CEO overconfidence literature as well as the cash literature. First of all, although Deshmukh et al. (2013) shows that OC firms will build up financial slacks by paying less dividends, it does not imply the effect of C EO overconfidence on cash holdings would always be positive because the capital spending in OC firms could also be higher than non-OC firms. In addition, the cash assets are not

Journal Pre-proof only accumulated internally from operations but could also from the net proceeds of external financings (McLean, 2011). Although overconfident CEOs tend to avoid equity financing, it does not indicate that equity financing will not happen in OC firms. Meanwhile, the leverage in OC firms is found to be higher than non-OC firms (Malmendier et al., 2011). This suggests that the negative relation between CEO overconfidence and dividend does not directly indicate high cash holdings in OC firms. Second, this study explains why and when accumulating cash in OC firms is more valuable than non-OC counterparts. The past literature suggests that OC firms could

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undertake value-decreasing projects when they have sufficient internal fund. Such value reduction is due to the overestimation of investment returns. As overconfident CEOs are hired to undertake challenging and risky investments but hesitate in raising external funds

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for investments, holding large cash in OC firms would be valuable because it can avoid the underinvestment problem. Giving up investment opportunities due to fund shortage

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could make OC firms losing market competitive power. Our findings verify the prediction by showing that OC firms in innovative industries experience higher value of

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cash than non-OC firms. Third, we link the psychology-based managerial behavior to the ratio nal-based managerial behavior in corporate decision making by examining whether the value of

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cash in OC firms vary with the firms’ transaction, precautionary, and agency motives. As the cash literature indicates, the cash is valued higher for the precautionary motive but lower for the agency motive. Although both the cash literature and the CEO

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overconfidence literature identify that both self- interested CEOs and overconfident CEOs would conduct more value-destroying M&As, their fundamental rationings are different,

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empire building for personal interests in the former and the belief in value creation in the later. Although overconfident CEOs may lead to value-decreasing investments, our analyses based on the cash holdings motives suggest that the main objective of overconfident CEOs is still more related to value maximization rather than the agency purpose. The remainder of this paper is organized as follows. Section 2 develops the hypotheses to be tested. Section 3 describes the data sources and variable definitions and provides summary statistics for the sample. Section 4 discusses the empirical analyses. Section 5 presents robustness tests. Section 6 concludes the paper.

Journal Pre-proof 2. Theories and empirical hypotheses 2.1. Literature reviews Corporate cash policies are determined by the motives based on the trade-off and agency theories. The trade-off theory suggests that firms build up cash for the transaction and precautionary motives (Opler et al., 1999). When firms have more business transactions, more investment opportunities, higher cost of cutting dividends or los ing financial accesses, or higher cash flows volatility, they have higher incentive to build up cash (Opler et al., 1999; Almeida, Campello, and Weisbach, 2004). Because the cash is built for the value creation purpose, the value of additional cash would certainly be

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higher under the transaction and precautionary motives (Faulkender and Wang, 2006; Denis and Sibilkov, 2010; Bates et al., 2011; Harford, Klasa, and Maxwell, 2014). Faulkender and Wang (2006) and Denis and Sibilkov (2010) find that the marginal value

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of cash tends to be higher in financially constrained firms than in unconstrained firms, especially when firms have more investment opportunities. Harford et al. (2014)

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investigate whether cash reserves enable firms to mitigate underinvestment problems due with shorter-maturity debt.

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to refinancing risk. Their findings suggest that larger cash holdings are valuable for firms In contrast, the agency theory suggests CEOs prefer to keep cash on hand because

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large cash assets provide CEOs with higher discretionary without being monitored by

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outside investors when they need capital for investments. The self- interested CEOs would then use the excess cash holdings to create personal benefits, such as empire building. Accordingly, holding cash would decrease firm value (Harford, 1999; Dittmar and

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Mahrt-Smith, 2007; Harford, Mansi, and Maxwell, 2008; Gao, Harford, and Li, 2013). Harford (1999) finds that cash-rich firms are more likely to attempt value-decreasing acquisitions. Dittmar and Mahrt-Smith (2007) find that poorly governed firms have a lower value of cash. Harford et al. (2008) find that poorly governed firms in the United States have smaller cash reserves than others because, instead of hoarding the excess cash, managers of poorly governed firms tend to spend it quickly on acquisitions and capital expenditures. Gao et al. (2013) find that public firms hold more cash than private firms and attribute the finding to the agency motive of cash holdings because public firms have lower precautionary motives than private firms do. CEO overconfidence represents a CEO’s belief on the future payoff and his/her attitude towards risk taking. O verconfident CEOs are likely to overestimate the future payoffs of investment projects and underestimate the risk of the projects, leading to a disagreement on firms’ equity value. As a results, overconfident CEOs tend to overinvest

Journal Pre-proof when the firms has abundant internal funds and underinvest when the investments require external financing (Malmendier and Tate, 2005). To finance for investment projects, OC firms tend to pay less dividend (Deshmukh, et al., 2013). Malmendier and Tate (2008) show that overconfident CEOs are more likely to undertake value-destroying M&As, a similar outcome of the agency problem of excess cash holdings (Harford, 1999; Richardson, 2006). These CEOs tend to believe they can control the outcomes of their investment projects and thus underestimate the likelihood of failure. Ben-David et al. (2013) conduct a survey on chief financial officer and find that overconfident managers

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tend to underestimate the volatility of future cash flows and follow more aggressive corporate policies, investing more and using more debt financing. Pikulina, Renneboog, and Tobler (2017) conduct an experiment on participants who acted as managers making

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investment decisions and find that overconfident subjects tend to choose higher investment levels in comparison with their moderately or less overconfident peers.

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From the empirical findings in the prior literature, the above discussed behaviors of overconfident CEO on corporate financing and investment decisions may make the OC

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firms’ cash policies explainable by the precautionary and agency motives. However, the fundamental theories between overconfidence and precautionary/agency motives are very different. The former is from psychology, while the latter two are within the scope of

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economics. Even if the agency motive is considered a CEO behavior, it is still built upon the economics theory with different objective functions. Therefore, it is necessary to explore and analyze the effect of CEO overconfidence on corporate cash holdings.

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Normally, CEOs have better information about the quality of investment projects. The information asymmetry between investors and CEOs would then determine the cost

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of financing. CEOs would have to evaluate the cost of capital and expected return of investment projects and decide whether the projects should be undertaken. Under the condition of no or low agency problem, the same project could be rejected by one CEO but accepted by another if the later believes this project’s payoffs to be higher than the costs. Such an optimum belief is due to the CEO’s confidence on higher investment payoffs or lower investment risk under his/her management. Although both types of CEOs are pursuing the best interests to firms, the final decisions could be very different. If a CEO is aware of a lower expected return than cost of capital for a project but still decides to go for it, then this is the agency problem of overinvestment. The CEO would like to pursue private benefits from this value-decreasing project. However, if the project was undertaken because the CEO believes the expected return to be greater than the cost of capital, then this is the overinvestment due to the overestimation of future payoff or underestimation of the project risk. That is, the same value-decreasing

Journal Pre-proof investment project could be chosen, but the rationales behind CEO behaviors are different. Are OC firms really better off than non-OC firms? Why would overconfident CEOs be hired? Goel and Thakor (2008), in a theoretical model, predict that well- governed firms are more likely to hire overconfident CEOs. Hirshleifer et al. (2012) argue that overconfident managers are more enthusiastic to risky and challenging projects because people are more likely to become overconfident on dealing with difficult tasks rather than easy tasks (Griffin and Tversky, 1992). They find that firms with overconfident managers

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have higher return volatility, heavier R&D expenditure and greater innovation. These managers also achieve in better innovation success. Their results supplement Gervais et al. (2011) that firms in risky and highly- growth industries are prone to hire overconfident

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managers. Based on these studies, we expect that overconfident CEOs are valued by the boards/shareholders of firms operating in challenging, risky, and innovative industries.

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When these conditions hold, OC firms should have more cash holdings and higher value

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of additional cash accumulated.

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2.2. Empirical predictions

Given that OC firms have higher capital needs for their investments and

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overconfident CEOs are more hesitate to use equity for financing needs (Malmendier and Tate, 2005), OC firms should maintain a higher level of cash holdings than non-OC firms do. However, since overconfident CEOs are likely to overinvest when they have

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sufficient financial slacks (Malmendier and Tate, 2005; Ben-David et al., 2013), OC firms

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could use more cash than they save, making the level of cash holdings lower compared to non-OC firms. The experimental analysis also indicates that overconfident CEOs tend to overinvest than non-OC counterparts (Pikulina, et al., 2017). Therefore, we suggest the following competing hypotheses: H1a: Overconfident CEOs tend to positively affect the level of cash holdings than non-overconfident CEOs; H1b: Overconfident CEOs tend to negatively affect the level of cash holdings than non-overconfident CEOs. The cash literature estimates the value of cash mostly following the model of Faulkender and Wang (2006), in which the excess stock returns are regressed on the change of cash holdings for any given year. The coefficient of the change of cash

Journal Pre-proof holdings is refer to as the (marginal) value of cash. As stated previously, the value of cash is determined by the motives of cash holdings. For firms in general, their projects’ NPVs would lean towards negative if the CEOs pursue personal interests. For OC firms, although they are still likely to undertake negative NPV projects, it is due to the gap between overconfident CEOs’ beliefs and outside investors’ expectations, rather than the value loss caused by the intended personal interests of the managers. Such disagreement could make firms drop value- increasing projects if overconfident CEOs avoid external financing (Malmendier and Tate, 2005).

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This underinvestment problem would generate an opportunity cost to firms as they lose the opportunities to create value and may also lead to lower competitiveness in the long run. By accumulating cash assets, firm could mitigate the underinvestment problem that

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might arise due to CEOs’ reluctance to raise external funds. Hirshleifer et al. (2012) show that firms with overconfident CEOs invest more in innovation and have more patent

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citations. This finding suggests that overinvestments made by overconfident CEOs are not induced by CEO self- interests. Given that OC firms may realize a higher NPV for the

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more challenging and risky investments than non-OC firms do, we therefore expect the cash available for their value pursuing investments would benefit their shareholders as well. We thus develop the following hypothesis:

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H2: CEO overconfidence has a positive effect on the value of additional cash saved.

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As stated previously, the overconfident CEOs are particularly hired to deal with challenging and risky investments. Because overconfident CEOs prefer hard tasks to easy

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ones, they may undertake investments that would not be undertaken by non-OC CEOs. Firms in innovative industries often face with higher risk and complicated investment decisions, requiring persistent capital and determined managerial capability. Hiring overconfident CEOs would thus be beneficial to firms in innovative industries. As a result, we suggest the following hypotheses: H3a: CEO overconfidence have a positive effect on the level of cash holdings in innovative industries in which more R&D investments are necessary. H3b: CEO overconfidence has a positive effect on the value of additional cash saved in innovative industries in which more R&D investments are necessary. The previous predictions are developed based on the theory of overconfidence to see how CEOs with such personal trait would affect the level of cash holdings and the value

Journal Pre-proof of cash. Nevertheless, to have a more comprehensive understanding, we investigate how the effects of CEO overconfidence on corporate cash policies vary with the motives of cash holdings that are based on fundamental theories, as discussed previous ly. Following the cash literature, we apply the conditions of a firm’s growth opportunity and financial constraint to estimate its transaction and precautionary motives. We further take into account for a firm’s corporate governance condition to estimate its agency motive. According to the discussion in the previous section, overconfident CEOs are hired to deal with hard tasks in risky and high-growth industries (Gervais et al., 2011).

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Firms with high growth opportunity have more investment decisions to make and require more capital for their investments. Given that overconfident CEOs hesitate to external financing, the higher transaction motive would then make those CEOs to hold even more

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cash. Without the cash, overconfident CEOs would have to give up the investment opportunities, which in turn will lead to lower long-term profitability. Therefore, the

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value of cash for OC firms should be higher if firms possessing growth opportunities than firms without growth opportunities.

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Similar argument can be applied to the condition of financial constraint. Firms with higher financial constraint have higher precautionary motive of cash holdings because they not only have to give up the investment opportunities (Faulkender and Wang, 2006;

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Denis and Sibilkov, 2010) but also have higher difficulty to defend against the shocks due to market dynamics (Bates et al., 2011). The value of cash for OC firms should be higher if firms are financially constrained, compared with financially unconstrained firms.

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Finally, the value loss of self- interested CEOs could be reduced via good governance mechanisms. Nevertheless, we argue that the size of value loss for

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overconfident CEOs may not be lowered by better corporate governance mechanisms because they believe the projects are value- increasing in the first place. Therefore, the level of cash holdings and the value of cash of OC firms should not vary with the condition of corporate governance. Based on all of the above, we develop the following hypotheses: H4a: The effects of overconfident CEOs on the level of cash holdings and the value of cash are higher when firms have higher transaction/precautionary motives, i.e. more growth opportunities and more financial constraints. H4b: The effects of overconfident CEOs on the level of cash holdings and the value of cash do not differ with the firms’ corporate governance condition.

Journal Pre-proof 3. Sample and data description 3.1. Sample The sample consists of firms in the United States with financial and executive compensation data from 1992 to 2016 available from Compustat and ExecuComp. To be included in our sample, firms are required to have positive assets and sales in a given year. Financial firms (Standard Industrial Classification, or SIC, codes 6000–6999) and utilities (SIC code 4900–4999) are excluded from the sample because they are more regulated and have more different industrial traits. Our sample construction process yields a firm– year panel of 17,942 observations for 1,967 unique firms. The following subsections

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provide detailed variable definitions.

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3.2. Measures of CEO overconfidence

Since CEO overconfidence cannot be observed directly, the related literature usually

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measures it based on the actions taken by CEOs. Following Campbell, Gallmeyer,

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Johnson, Rutherford, and Stanley (2011) and Hirshleifer et al. (2012), we measure CEOs’ overconfidence based on their executive options holding decisions. Unlike outsider investors, CEOs cannot trade their options or hedge the risk by short-selling their firms’

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stocks. Therefore, rational CEOs should exercise their exercisable executive options when they are sufficiently in the money. However, rather than exercising exercisable in-the- money options, overconfident CEOs are more prone to holding them longer,

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because they tend to overestimate the future profitability of their firms.

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The executive option moneyness is computed following Campbell et al. (2011). First, we estimate the average exercise price using a CEO’s aggregated options data from ExecuComp. We compute the average realizable value as the estimated value of the unexercised exercisable options (ExecuComp item OPT_UNEX_EXER_EST_VAL) divided by the number of unexercised exercisable options (ExecuComp item OPT_UNEX_EXER_NUM). We then subtract the average realizable value from the stock price at the fiscal year-end (Compustat item PRCC_F) and obtain the average exercise price of the exercisable options held by the CEO. The average percent moneyness of the options held by the CEO is then computed as the average realizable value divided by the average exercise price of the exercisable options. Following Hirshleifer et al. (2012), we classify CEOs as overconfident if they hold options that are over 67% in the money and classify CEOs as non-overconfident if they do not hold in- the-money options with moneyness greater than 67%. The variable

Journal Pre-proof Holder67 is an indicator variable that equals one if a firm is managed by an overconfident CEO and zero otherwise. Furthermore, once CEOs are classified as overconfident, they retain the same classification forward (from the year when they first held options more than 67% in the money) in the sample period. We also refer to the definition of Campbell et al. (2011), classifying CEOs as HighOptimism if they hold executive options that have moneyness greater than 100% at least twice during their tenure and as LowOptimism if they exercise executive options that have moneyness lower than 30% at least twice during their tenure. Those CEOs who are neither classified as

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HighOptimism nor LowOptimism are then classified as ModerateOptimism.4

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3.3. Summary statistics

Table 1 presents summary statistics for our sample.

Because Holder67,

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HighOptimism, ModerateOptimism, and LowOptimism are indicator variables, their mean

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values represent the proportion of firm–year observations that are managed by overconfident (or non-overconfident) managers. The variable Cash is defined as cash and cash equivalents scaled by total book assets. We measure firm size (Size) as the logarithm

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of total assets. The variable TobinsQ is widely used as a proxy for firms’ investment opportunities, which is defined as the firm’s market value divided by the book value of

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property, plant, and equipment, where the firm’s market value is computed using the

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market value of common equity plus the book value of debt minus the firm’s current assets. The variable CashFlow is measured as operating cash flow scaled by total assets, where operating cash flow is computed using earnings after interest, dividends, and taxes

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but before depreciation. Cash flow volatility, CashFlowVol, is measured as the standard deviation of industry median–adjusted operating cash flows over the previous eight quarters, where industries are classified using two-digit SIC codes. Net working capital, NWC, can be viewed as substitution for cash and is measured as the difference between current non-cash assets and current liabilities, scaled by total assets. The variable Leverage is computed as the ratio of total debt to total assets. Capital expenditures, CapitalExp, and acquisition expenditures, AcquisitionExp, are scaled by total assets; R&DExp is measured as R&D expenditures scaled by total sales and is set to zero when R&D expenditures are missing; and Dividend is an indicator variable that equals one if a firm pays cash dividends; Tenure is CEO tenure in years; CEODelta is the dollar change in CEO stock and option portfolio for 1% change in stock price; CEOVega is the dollar

4

We are unable to classify CEOs whose executive option data are not available in ExecuComp.

Journal Pre-proof change in CEO stock and option portfolio for a 1% change in stock return volatility. 5 To avoid outliers driving our results, we winsorize all continuous variables at the first and 99th percentiles. The mean and median of Cash for the sample firms are 0.146 and 0.083, respectively, and are both slightly lower than those of Bates et al. (2009) because we use a different sample period and mainly focus on Standard & Poor’s (S&P) 1500 firms due to the data coverage of ExecuComp. The mean value of Holder67 shows that about 63% of the sample firms are managed by overconfident CEOs and the remaining 37% are managed by non-overconfident CEOs, which is similar to the proportion of Hirshleifer et al. (2012).

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The mean value of Optimism also shows that about 25% of the sample firms are managed by HighOptimism CEOs, 41% are managed by ModerateOptimism CEOs, and the

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remaining 34% are managed by LowOptimism CEOs. In addition, the mean of Leverage

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for our sample firms is about 0.229, which is similar to the finding of Bates et al. (2009).

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[Insert Table 1 about here]

4. Empirical results

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4.1. CEO overconfidence and cash holdings

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Table 2 provides univariate comparisons of firm characteristics for subsamples based on CEO overconfidence. We employ Holder67 and Optimism as measures of CEO overconfidence. The preliminary results show that firms managed by overconfident CEOs

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tend to hold higher levels of cash, which is consistent with H1a. In addition, based on the mean and median difference tests, statistically significant differences are also found in other firm characteristics. Firms managed by overconfident CEOs tend to have a higher TobinsQ in comparison with firms managed by non-overconfident CEOs. This result suggests that firms with overconfident CEOs have better investment opportunities in the future and are likely to hold more cash for these. Finally, firms managed by overconfident CEOs seem to spend more on investments. They tend to have a higher CapitalExp and AcquisitionExp, which is consistent with the findings of Malmendier and Tate (2005, 2008). Our results further suggest that the proportion of firms that pay dividend is lower for firms that are managed by overconfident CEOs, which is similar to the findings of Deshmukh et al. (2013). 5

Core and Guay (2002) proposed CEODelta and CEOVega as measures of CEO incentives. We construct these measures following the method of Coles, Daniel, and Naveen (2006).

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[Insert Table 2 about here]

The preliminary results in Table 2 show that firms with overconfident CEOs tend to hold more cash. However, this finding could also be driven by other firm characteristics, since there are significant differences in firm characteristics related to ca sh holdings between the firms managed by overconfident CEOs and those managed by

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non-overconfident CEOs. Therefore, we conduct multivariate analyses to examine the relation between CEO overconfidence and the level of cash holdings by controlling for cash determinants proposed in previous literature. We adapt the cash holding models of

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Opler et al. (1999) and Bates et al. (2009) and include the CEO overconfidence indicator as an independent variable in our model. Table 3 presents the empirical results for the

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following regression:

(1)

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Cashi,t=β0 +β1 Overconfidencei,t+βControlVariablesi,t+FirmFE+YearFE+εit.

The dependent variable of the regression is Cash, which is defined as the ratio of cash

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and cash equivalents to total assets. The independent variables are the CEO

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overconfidence measures and the other firm characteristics, which include Size, TobinsQ, CashFlow, CashFlowVol, NWC, Leverage, CapitalExp, AcquisitionExp, R&DExp, and Dividend. We also control for CEO characteristics and incentives, such as Tenure,

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CEODelta, and CEOVega. Furthermore, we control for factors that vary over time but not across firms and factors that vary across firms but not over time by including year and firm fixed effects in the regression, to mitigate the omitted variable bias that firms choose to hire overconfident or non-overconfident CEOs for unobserved reasons which are likely to affect cash holdings. In model (1) of Table 3, we employ Holder67 as the measure for CEO overconfidence. The coefficient on Holder67 is 0.008, significant at the 1% level, after we control for other factors related to corporate cash holdings. This result implies that the cash-to-assets ratio is 0.008 higher for firms managed by overconfident CEOs, relative to other firms. Since the average cash-to-assets ratio for our sample is 0.146, the difference of 0.008 is economically significant. In model (2), we employ the Optimism measure and find the coefficient on HighOptimsm and ModerateOptimism are 0.020 and 0.011, respectively, both being significant at the 1% level. The coefficient on HighOptimism

Journal Pre-proof suggests that the cash-to-assets ratio is 0.020 (0.009) higher for firms with HighOptimism CEOs, in comparison to firms with LowOptimism (ModerateOptimism) CEOs, which is not only statistically but also economically significant. These results show that firms managed by overconfident CEOs have greater incentives to preserve funds in comparison with their non-overconfident counterparts, which is consistent with H1a. In addition, the coefficients on the other control variables are also consistent with the findings of Bates et al. (2009). Large firms and firms with more net working capital hold lower amounts of cash, because large firms have more property to liquidate when facing liquidity needs and non-cash working capital can also be easily converted into cash.

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Firms with a higher Tobin’s Q are considered to have more investment opportunities and those firms would reserve more cash for investment. In addition, if firms face more

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constraints on debt issuance, they would reduce their leverage and preserve more cash for

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negative effects on the level of cash holdings.

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future needs as well; thus, leverage has a negative effect on cash reserves. Cash o utflows, such as capital expenditures, acquisition expenditures, and R&D expenditures, have It is possible that our empirical findings could be biased due to misspecification of

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the model. Some confounding variables that affect firms to hire overconfident or non-overconfident CEOs are likely to affect cash holdings as well, which could cause

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spurious associations between the overconfidence measures and corporate cash holdings. To address this problem, we implement one-to-one nearest neighbor propensity score matching with replacement. To compute the propensity score, we first estimate a logistic

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regression model with a set of firm characteristics that should capture the likelihood that

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a given firm will hire or be managed by an overconfident CEO. Specifically, we consider CapitalExp, AcquisitionExp, R&DExp, and Dividend. We also require the matching firms to share the same industry and year as the firms managed by overconfident CEOs, where the industry are based on two-digit SIC codes. By using the propensity scores from the estimated logistic regression, we match each overconfident firm–year observation with a non-overconfident firm–year observation that minimizes the absolute value of the difference between propensity scores. To ensure that the overconfident and non-overconfident samples have extremely close propensity scores, we drop observations with bad matches.6 The regressions of model (1) is rerun for the matched samples in model (3) of Table 3. The coefficients on Holder67 remain positive and statistically significant in all the 6

Specifically, we use a threshold (or caliper) of 0.01. The results are robust to alternative thresholds of 0.015 and 0.005.

Journal Pre-proof matched samples. Therefore, the results of the matched samples remain consistent with H1a. We also use another definition of cash holdings, the logarithm of the ratio of cash to non-cash assets, for robustness. 7 The untabulated results are qualitatively similar to our main findings.

[Insert Table 3 about here]

4.2. CEO overconfidence and the value of cash

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In this subsection, we examine the influence of managerial overconfide nce on the value of cash holdings, following Faulkender and Wang (2006). Specifically, the authors

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estimate a regression of the annual excess return on the change in cash over the fiscal

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year with several control variables, including change in non-cash assets, change in earnings, change in R&D, change in interest expenses, change in dividends, net financing,

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lagged cash holdings, and market leverage. The regression model is specified as

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ExcessRet i,t=γ0 +γ1 △Cashi,t+γ2 Overconfidencei,t+ γ3 Overconfidencei,t×△Cashi,t+γControlVariablesi,t+ (2)

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FirmFE+YearFE+εit.

The dependent variable of the regression model is the excess stock return over the fiscal

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year, which is computed as the stock return over the fiscal year minus the return on its benchmark portfolio. The benchmark portfolios chosen are the Fama–French portfolios formed by independently sorting stocks on size and the book-to-market ratio. The coefficient on △Cash can be interpreted as the marginal value of cash to shareholders. In addition, to investigate the effect of CEO overconfidence on the marginal value of cash, we include the measures of CEO overconfidence and their interaction terms with △Cash in the model. The empirical results are presented in Table 4. In model (1) of Table 4, we employ Holder67 as the measure of CEO overconfidence. The coefficient on △Cash is less than one (0.908), being consistent with the finding in 7

Op ler et al. (1999) use the ratio of cash to non-cash assets as an alternative measure. However, Bates et al. (2009) point out the problem of ext reme outliers in the ratio of cash to non -cash assets for firms with most of their assets in cash. To address this problem, we fo llo w Bates et al. (2009) and use the logarithm of the ratio of cash to non-cash assets as an alternative measure for a robustness check.

Journal Pre-proof Faculkendar and Wang (2006) that the value of one dollar of cash saved is lower than one dollar. The key finding, the coefficient on the interaction term of Holder67 and △Cash, is positive (0.842) and significant at the 1% level, implying that the value of a dollar of cash to a firm with an overconfident CEO is $0.842 greater than to a similar firm with a non-overconfident CEO. This result indicates that market participants consider inc reases in cash holdings to be more valuable for firms managed by overconfident CEOs, which is consistent with H2. In model (2), we employ the Optimism measure. The coefficients on the interaction terms of HighOptimsm (ModerateOptimism) and △Cash remain positive

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and significant, which implies that a dollar of cash is $1.054 ($0.938) more valuable if the firm is managed by a HighOptimsm (ModerateOptimism) CEO. A dollar of cash is $0.116 more valuable for firms with highly optimistic CEOs than for t hose with

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moderately optimistic CEOs, although the difference is not statistically significant.

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We rerun the regression of model (1) for the propensity score matched sample in model (3) of Table 4. The coefficient on the interaction term of Holder67 and △Cash

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have similar result in the matched sample, which shows that overconfident CEOs

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increase the value of a dollar of cash held in firms by about $1.000. Therefore, the result of the matched sample remain consistent with H2.

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[Insert Table 4 about here]

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To summarize, we find that firms with overconfident CEOs tend to have a higher marginal value of cash than other firms. This finding indicates that the participants in

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capital markets view the increase in cash holdings as more valuable for firms with overconfident CEOs. One possible explanation for this finding is related to the costly external financing hypothesis in the CEO overconfidence literature. Holding larger cash could mitigate the underinvestment problem that might arise due to CEOs’ reluctance to raise external funds. Another possible explanation is that overconfident CEOs tend to invest more in innovation (Hirshleifer et al., 2012) and firms usually need a large amount of funds to proceed with their R&D projects. Therefore, larger cash holdings enable overconfident CEOs to produce more innovation activities, which is expected to benefit their firms in the future.

Journal Pre-proof 4.3. Channel analysis: Investment environment We expect the effect of CEO overconfidence on corporate cash policies to be more significant when firms are in innovative industries. Therefore, we split the sample to separately test the effect of CEO overconfidence on cash level and cash value for firms in innovative industries and for firms in other industries. We define an industry as innovative when the average R&D intensity for the industry is higher than the median across all industries in a given year. Table 5 shows the empirical results. In Panel A of Table 5, we show whether investment environment can explain the effect of CEO overconfidence on cash holdings. In models (1) and (2), the coefficient on

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Holder67 is positive and significant (0.012, t-stat = 3.6) for innovative industries and is negative and insignificant (-0.003, t-stat = -0.68) for other industries. The results suggest that overconfident CEOs’ incentive of cash holdings is higher when their firms are in

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innovative industries in which more R&Ds are necessary. Similarly, in models (3) and (4), we also find that the coefficients on HighOptimism and ModerateOptimism are

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statistically significant in the subsample of innovative industries but insignificant in the subsample of other industries. The difference between the HighOptimism and

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ModerateOptimism is significant at 1% level, i.e., extremely confident CEOs tend to hold more cash than moderately confident CEOs. We conduct similar regression analyses by

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focusing on the propensity score matched samples in models (5) and (6), and the results are qualitatively similar to those in models (1) and (2). Our findings indicate that challenging and risky investments in innovative industries is the key to make OC firms

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holding a higher level of cash than non-OC firms.

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In Panel B of Table 5, we show whether investment environment explains the effect of CEO overconfidence on the value of cash. In models (1) and (2), the coefficients on the interaction term of Holder67 and △Cash is positive and significant (0.712, t-state = 2.09) in model (1) for firms in innovative industries but is insignificant (0.529, t = 1.22) in model (2) for firms in other industries. The results suggest that the market value the additional dollar of cash saved $0.712 higher for OC firms than for non-OC firms in innovative industries, but the higher value of cash for OC firms than non-OC firms is not significantly observed in other industries. Models (3) and (4) show the regression results when we employ the Optimism measure. The coefficient of △Cash interacted with HighOptimism is positive and significant (1.078, t-state = 1.87), and the coefficient of △ Cash interacted with ModerateOptimism is also positive and significant (1.007, t-state = 3.01). The results indicate that a dollar of cash is worth $1.078 ($1.007) more for firms managed by HighOptimism (ModerateOptimism) CEOs than for firms with LowOptimism

Journal Pre-proof CEOs in innovative industries. Nevertheless, for firms in other industries, the market does not value differently for one dollar of cash saved by HighOptimism (ModerateOptimism) CEOs compared to LowOptimism CEOs. The results of Table 5 support our prediction in H3a and H3b. Firms in innovative industries face more risky and challenging investment decisions, and overconfident CEOs with the trait preferring hard tasks than easy tasks would be more capable to undertake risky investments than non-confident CEOs. Therefore, OC firms would have higher incentive of cash holdings than non-OC firms in innovative industries. The results, however, could be different in other industries because the investment opportunities may

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not be as many as those in innovative industries. An interesting thing to note is that the value of cash is not significantly higher for high-OC firms than for moderate-OC firms,

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although the level of cash holdings is significantly higher for high-OC firms than for

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moderate-OC firms. This finding suggests that the market prefer cash holdings for firms with moderately confident CEOs to that for firms with extremely confident CEOs in

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innovative industries because high-OC firms to may have even larger gap between CEOs’

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belief and market expectation on investment payoffs than moderate-OC firms.

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[Insert Table 5 about here]

4.4. Influences of cash holding motives on overconfident CEOs’ cash holdings

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After examining the channel to explain the effect of CEO overconfidence on the

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corporate cash policies, we link the traditional cash holdings theory to the psychology-based theory by examining whether the effects of CEO overconfidence on cash holdings would vary with different motives, as we hypothesize in H4a and H4b. The results are reported in Table 6. In Panel A of Table 6, we employ TobinsQ as a proxy for transaction motive of cash holdings as the high Q firms need more cash for their high level of investments. We split our sample firms into high and low TobinsQ subsamples by median. From models (1) and (2), the positive effect of OC CEOs on cash holdings is higher for high Q firms than for low Q firms, but the difference is not significant with p-value of 0.17. Similarly, the results in models (3) and (4) shows that the positive effects of HighOptimism (ModerateOptimism) CEOs on cash holdings are not significantly (p- value = 0.14) different between high Q firms and low Q firms. The results from models (5) and (6) are similar to those in models (1) and (2). The findings in Panel A indicate that the effects of

Journal Pre-proof CEO overconfidence on the level of cash holdings do not vary with a firms’ transaction motive of cash holdings. To verify the precautionary motive in explaining the corporate cash policies of overconfident CEOs, we examine whether firm financial constraint influences the effects of CEO overconfidence on corporate cash holdings. We adopt the SAIndex, proposed by Hadlock and Pierce (2010), to measure a firm’s financial constraint. The SAIndex value for each firm–year observation is calculated as

(3)

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SAIndex i,t=–0.737×SIZEi,t+0.043×SIZEi,t2 –0.040×AGEi,t,

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where SIZE is the logarithm of inflation-adjusted total assets, which is adjusted by the

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Consumer Price Index of 2004; and AGE is the number of years that the firm has been listed with non- missing stock prices in the Compustat database. Before the calculation,

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SIZE is winsorized at the logarithm of $4.5 billion and AGE is winsorized at 37 years. A

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higher SAIndex value implies that the firm is more likely to be financially constrained. To conduct the analyses, we sort the sample by SAIndex respectively in each year. For each year, firms with SAIndex in the top tercile are considered financially constrained (FC)

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and the firms in the remaining terciles are considered financially unconstrained (FU). We conduct the regression analyses on the subsamples of FC firms and FU firms separately. The results are reported in Panel B of Table 6. In models (1) and (2), the coefficients

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on Holder67 are 0.019 and 0.004, significantly different at the 1% level, indicating that

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the positive effect of CEO overconfidence on corporate cash holdings is more pronounced for financially constrained firms. Meanwhile, the result from models (3) and (4) show that the positive effect of HighOptimism significantly varies with the level of precautionary motive. Nevertheless, the positive effect of ModerateOptimism on cash holdings does not significantly vary with the level of precautionary motive. The results from models (5) and (6) are similar to those in models (1) and (2). The findings in Panel B indicate that the effects of CEO overconfidence on the level of cash holdings vary significantly with a firms’ precautionary motive of cash holdings. As stated in the first two sections, OC firms are likely to engage in value-decreasing M&As compared to non-OC firms. Although OC CEOs may not have intention to decrease firm value for personal interests, the outcome is however the same as the evidence of the agency theory in explaining cash holdings. Therefore, we adopt corporate governance to be an inverse proxy of agency problems and examine whether corporate

Journal Pre-proof governance influences the positive effect of CEO overconfidence on cash holdings. We split the sample firms into well- governed and poorly-governed subsamples based on two widely- used corporate governance measures. InstOwn is the first measure we employ, which is the percentage of shares held by institutional investors to total shares outstanding of a firm. Firms with higher proportion of shares held by institutional investors are considered to be heavier monitored by the capital markets. We also employ the entrenchment index, proposed by Bebchuk, Cohen, and Ferrell (2009), as an alternative measure for corporate governance. The EIndex is constructed by 6 different

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kinds of antitakeover provisions, which indicate that the managers are more entrenched and the corporate governance could be worse when they have more antitakeover amendments (higher EIndex). Following the definition of Johnson, Moorman, and

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Sorescu (2009), we classify firms with EIndex of 0 as well- governed, and firms with EIndex of 5 or more as poorly-governed. In Panel C of Table 6, we split our sample firms into high and low InstOwn

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subsamples by median. In models (1) and (2), the coefficients on Holder67 are 0.010 and

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0.007, which are not significantly different (p-value = 0.97), indicating that the effect of overconfident CEOs on the level of cash holdings does not vary with the institutional ownership. Similarly, in models (3) and (4), the coefficients on HighOptimism is not

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significantly different between the high InstOwn and low InstOwn subgroups (0.026 vs. 0.014, p-value = 0.49). Nevertheless, the coefficients on ModerateOptimism is significantly different between the high InstOwn and low InstOwn subgroups (0.016 vs.

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0.002), with a p-value of 0.10. The results in models (3) and (4) suggests that the agency issue is less likely to be a concern to OC CEOs’ cash policies when the level of CEO

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overconfidence is higher. The results from models (5) and (6) for the propensity score matched sub-samples are similar to those in models (1) and (2). The results in Panel D of Table 6 are for the E- index subsamples. As in panel C, the coefficients of CEO overconfidence (Holder67, HighOptimism, and ModerateOptimism) are not significantly different between low E-index and high E- index subsamples. Overall, the results in Panels C and D suggest that corporate governance condition have no significant impact on OC firms’ cash policies. As we predict, this finding is consistent with the argument of the CEO overconfidence literature that the overconfident CEOs do not possess agency concerns, such as empire building strategy. To the best of our knowledge, our finding is the first empirical evidence to such argument in the CEO overconfidence literature.

Journal Pre-proof [Insert Table 6 about here]

4.5. Influences of cash holding motives on the overconfident CEOs’ value of cash Similar to the Subsection 4.4, we examine the influences of cash holdings motives on the effects of overconfident CEOs on cash value in this subsection, and the results are reported in Table 7. Panel A shows the impact of growth opportunities. For each regression, we estimate the value of cash for OC firms by adding up the coefficients of

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△Cash and the interaction term of Holder67 and △Cash. We then contrast such value between high Q and low Q subsamples. From models (1) and (2), we find that the value of cash for OC firms is not significantly different although the numbers look very

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different (2.050 vs. 1.322, p-value = 0.12). Similarly, the HighOptimism firms’ value of cash is not significantly different between high Q and low Q firms (1.936 vs. 1.604,

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p-value = 0.11). Nevertheless, the ModerateOptimism firms’ value of cash is significantly

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different between high Q and low Q firms (1.757 vs. 1.397, p- value = 0.08). The findings show that value of cash for OC firms is marginally affected by the firms’ condition of growth opportunities. However, when we perform the analysis on the matched

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subsamples, the difference between high Q and low Q subsamples is insignificant (2.171 and 1.345, p-value = 0.74). Overall, the transaction motive of cash holdings might affect

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the OC firms’ value of cash, but with mixed results. Panel B of Table 7 shows the impact of financial constraint, a proxy of the

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precautionary motive. We employ SAIndex as the measure of financial constraint. For each regression, we estimate the value of cash for OC firms by adding up the coefficients

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of △Cash and the interaction term of Holder67 and △Cash. In models (1) and (2), although the value of cash for OC firms in financially constrained subsample is higher than that in unconstrained subsample, the difference is not significantly different (1.804 vs. 1.453, p- value = 0.11), indicating that the financial constraint does not affect the value of cash for OC firms. In models (3) and (4), the results remain the same when we change the overconfidence measure to HighOptimism and ModerateOptimism. The value of cash for HighOptimism (ModerateOptimism) firms is not significantly different between financially constrained firms and unconstrained firms (1.995 vs. 1.348, p-value = 0.47 for HighOptimism firms; 1.991 vs. 1.370, p-value = 0.34 for ModerateOptimism firms). When we perform the analysis on the matched subsamples, the difference on the value of cash for OC firms between financially constrained and unconstrained subsamples becomes larger, but the difference is insignificant (2.765 vs. 0.982, p-value = 0.53). The results in Panel B show that the precautionary motive of cash holdings does not affect

Journal Pre-proof how the market values the cash saved for OC firms, although it affects the OC firms’ cash holdings level as shown in Panel B of Table 6. To examine whether corporate governance influences the effect of CEO overconfidence on the value of cash, we conduct regression analyses on the subsamples of well- governed and poorly- governed firms. As in the previous subsection, we adopt institutional ownership and entrenchment index as two measures of corporate governance and report the results in Panels C and D, respectively. Both Panels C and D show that the value of cash for OC firms is not significantly different between the well- governed and poorly-governed subsamples. The results remain the same for different levels of CEO

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confidence, HighOptimism and ModerateOptimism, and for the propensity score matched sample. The findings in Panels C and D show that the agency motive of cash holdings

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does not affect how the market values the cash saved for OC firms.

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[Insert Table 7 about here]

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In summary, the findings in Tables 6 and 7 indicate that most of the cash holdings motives do not significantly affect the level of cash holdings and the value of cash for OC

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firms. These cash holding motives indeed show the significant effects on the level of cash holdings and the value of cash in our preliminary analysis (not tabulated), as in the past literature. However, when we consider the effect of CEO overconfidence, we cannot find

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significant difference between various levels of cash holdings motives on the overconfident CEOs’ cash level and cash value, except for a positive influence of

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precautionary motive on overconfident CEOs’ cash holdings. The overall findings support our argument that CEO overconfidence is an important alternative explanation to corporate cash policies.

4.6. Additional analysis: Sources of cash saving Although we have identified the positive effects of CEO overconfidence on the level of cash holdings and the value of cash, which are barely influenced by the traditional motives of corporate cash holdings, we have not yet understood why the OC firms can have aggressive investment strategies but still build up large cash holdings. As the cash literature suggests, cash can be saved from both internal cash flows and the proceeds of external financing. We therefore follow the model of McLean (2011) to examine the

Journal Pre-proof influence of CEO overconfidence on the source of cash. The regression model is specified as

△Cashi,t=α0 +α1 Overconfidencei,t+α2 Issuei,t+α3 Overconfidencei,t×Issuei,t+α4 Debt i,t +α5 Overconfidencei,t×Debt i,t+α6 CashFlowi,t+α7 Overconfidencei,t×CashFlowi,t +α8 Otheri,t+α9 Overconfidencei,t×Otheri,t+α10 Assetsi,t+εit.

(4)

The dependent variable of the regression model is the difference between cash at the end

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of the year and cash at the beginning of the year. Issue is the cash proceeds from equity issuance. Debt is the cash proceeds from debt sales. CashFlow is cash flow from operations. Other is all other cash sources, which include the sales of assets and

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investments. These measures are all scaled by lagged total assets. Assets is the logarithm of total assets. In addition, to investigate the effect of CEO overconfidence, we include

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the measures of CEO overconfidence and their interaction terms with the source of cash in the model. The empirical results are presented in Table 8.

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Panel A of Table 8 shows the summary statistics of the variables in the model in Equation (4), and Panel B presents the univariate comparisons for the subsamples based

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on different measures of CEO overconfidence. In Panel A, the means and medians of

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internal cash flows and debt issues are much larger than those of equity issues. This is consistent with the pecking order, firms rely on internal cash flows and debt for their operation and investments and issue equity only when necessary. In Panel B, although the

flows.

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mean and median of equity issues are both smaller than other two sources, equity issues are significantly higher for OC firms than non-OC firms, so are debt issues and cash Panel C presents the results of Equation (4). McLean (2011) refers the coefficients of Issue, Debt, and CashFlow as the saving rates from each sources of cash. The interaction of overconfidence measure (Holder67, HighOptimism, or ModerateOptimism) with each source of cash is the additional saving rate for OC firms compared to non-OC firms. The significant and positive coefficients of the interaction between overconfidence measure and Issue (Debt) of cash indicate that OC firms save a higher proportion of net proceeds from equity (debt) issues than non-OC firms. We further note that, although equity issues are avoided by OC firms compared to debt issues, if issued, OC firms would issue more capital than needed and save a larger proportion of net proceeds than non-OC firms. In addition, although the statistics in Panel B shows a larger size of debt issues than equity

Journal Pre-proof issues, the results in Panel C show that OC firms rely greatly on equity issues for their cash saving. We estimate the contribution of equity issues for one dollar of cash saving by adding the coefficient of Issue and the coefficient of Issue interacted with overconfidence measure multiplied by the mean of Issue in Panel B, The contribution of equity issues (0.563 + (0.195 × 0.032) = $0.569) is much higher than that of debt issues ((0.029 + (0.038 × 0.134) = $0.034)) and that of internal cash flows ((0.214 + (0.082 × 0.114) = $0.223)). The results in Table 8 not only provide a consistent finding with the literature that OC firms use more debt issues and internal cash flows rather than equity issues to support

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their investments but also reveal that the equity issues in OC firms (although smaller than debt issues and cash flows) are still larger than those in non-OC firms. This is in line with

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our conjecture that equity is also an important source of capital for OC firms as their

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innovations could be highly valued by the market. The higher contribution of equity issues to the cash saving than other sources provide a sensible argument to the fact why

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OC firms could have higher cash holdings than non-OC firms while they also invest more

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than non-OC firms.

5.1. Cash flows

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5. Robustness tests

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[Insert Table 8 about here]

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We recognize that our analyses might be subject to endogeneity concerns. An arguable issue here is whether firms are managed by overconfident CEOs or by non-overconfident CEOs might not be determined exogenously. As we mention earlier, it is possible that firms choose to hire overconfident or non-overconfident CEOs for reasons that are difficult to observe, and the omitted variables could bias the empirical results. There is also a concern that firms with a higher percentage of cash may tend to hire overconfident CEOs, which leads to the reverse causality. To deal with these endogeneity problems, we incorporate the interactive terms of contemporaneous (and lagged) cash flow and overconfidence measure in the model in Equation (1), and the empirical results are shown in Table 9. The coefficients of CEO overconfidence remain positive and significant in all overconfidence measures, consistent with the results in Table 3. However, the coefficients of OC interacted with cash flo ws or lagged cash flows are negative and insignificant. This results indicate that the level of firms’ cash flows in

Journal Pre-proof recent years do not affect the effect of overconfidence on cash holdings. Moreover, the cash flows in recent years do not determine corporate cash holdings. Therefore, the challenge that cash flows might simultaneously affect the firms’ decisions on hiring overconfident CEOs and cash holdings should not be an issue to our study.

[Insert Table 9 about here]

5.2. CEO turnover

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To deal with the concern of the above reverse causality further, we directly investigate whether firms with high cash holdings are more likely to hire an

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overconfident CEO when there is a turnover. Specifically, we estimate a logit model and

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test whether cash holdings prior to CEO turnovers can explain the probability of hiring overconfident CEOs. The dependent variable is the overconfidence measure of the

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succeeding CEO after turnover, and the independent variables are those prior to the CEO

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turnover, including cash holdings, firm characteristics, and overconfidence measure of the previous CEO. The empirical results are presented in Panel A of Table 10. The coefficients on the cash holdings are insignificant in both models (1) and (2), which

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provide no evidence that firms with high cash holdings may increase the probability to hire an overconfident CEO. In addition, the coefficients on the overconfidence measures are both positive and significant in models (1) and (2), suggesting that the succeeding

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CEOs are likely to be the same managerial overconfidence type as the proceeding CEOs.

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We also use the CEO turnover as the quasi-exogenous event. Following Galasso and Simcoe (2011), we examine a within- firm analysis of treatment effects before and after firm changes in CEO to confirm whether the effect of CEO overconfidence on corporate cash holdings is still significantly positive. This method, being similar to a difference-in-difference estimation, compares the difference in average excess cash before and after CEO turnovers as well as between treatment and control groups. Panel B of Table 10 presents the results. The treated samples are firms whose non-overconfident (overconfident) CEOs are replaced by overconfident (non-overconfident) CEOs. For the control samples, a firm changes its CEO, but the managerial overconfidence type remains the same. The results show that change in average excess cash is higher (by 0.003) for firms with new overconfident CEOs, and it is lower (by -0.029 with 1% significance level) for firms with new non-overconfident CEOs. As a result, our empirical finding of the impact of CEO overconfidence on cash holdings is robust to endogeneity concerns.

Journal Pre-proof

[Insert Table 10 about here]

5.3. Alternative CEO overconfidence measure The option-based overconfidence measure are widely used in related literature. However, once a manager holds in-the-money executive options with moneyness greater than 67% (or 100%), that manager will be identified as overconfident, which implicitly

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assumes this kind of managerial trait does not change over time and it might not be reasonable to believe people behave similarly at different stages of life. We construct an alternative measure of CEO overconfidence following Banerjee, Humphery-Jenner, and

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Nanda (2015). This variable, Confidence, is a continuous measure of the moneyness of a CEO’s exercisable executive options, which is measured as the average realizable value

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scaled by the stock price at the fiscal year-end. Use of this variable allows the overconfidence measure to vary over time. For the robustness of the empirical results, we

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further construct an indicator variable based on Confidence, ConfidenceTop, an indicator variable that equals one if a firm’s Confidence measure is in the top quartile in a specific year and zero otherwise.

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Table 11 shows the regression results of Equation (1) when using Confidence and ConfidenceTop as the measures of CEO overconfidence for robustness tests. In models (1) and (2), the regression coefficients on Confidence and ConfidenceTop are 0.031 and

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0.012, respectively, both significant at the 1% level. In models (3) and (4), we focus on the propensity score matched sample, which is constructing based on the indicator

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variable ConfidenceTop; the coefficient on Confidence and ConfidenceTop are 0.027 and 0.010, which are also significant at the 5% level and 10% level, respectively. Overall, the empirical results in Table 11 are similar to those in Table 3, which are consistent with H1a, and suggest that firms with overconfident managers tend to hold more cash.

[Insert Table 11 about here]

We further examine the effect on the value of cash when using Confidence and ConfidenceTop, and the results are presented in Table 12. Similar to the results in Table 4, the coefficients on the interaction terms of Confidence (ConfidenceTop) and △Cash are positive and significant, which indicates that firms with overconfident CEOs tend to have

Journal Pre-proof a higher marginal value of cash. Therefore, the results in Table 12 remain consistent with H2.

[Insert Table 12 about here]

6. Conclusion This study proposes CEOs’ beliefs and attitudes toward risky investments (CEO overconfidence) to be an alternative explanation to corporate cash policies, in addition to

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the trade-off theory and agency theory. Although the findings in the prior literature that OC firms tend to spend more on R&D and risky investments and have more innovation

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outputs make the OC CEOs prone to have higher transaction/precautionary motives of

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cash holdings, the background of these firm-specific findings is mainly due to the investment environment where OC firms are operated, i.e., external industrial attributes

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rather than internal firms characteristics. In addition, while both cash-rich firms and OC

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firms are likely to engage in value-destroying M&As, overconfident CEOs do not do so intentionally for personal interests. We find positive effects of overconfident CEOs on the level of cash holdings and the

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value of cash, and such positive effects are due to the investment environment where OC firms face. For innovative firms, R&D spending and risky investments require high and persistent capital. Furthermore, overconfident CEOs are more capable of dealing with

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these difficult challenges than

non-overconfident counterparts.

As a results,

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Overconfidence is the key to drive the motive of holding cash for CEOs. Moreover, the positive effect of CEO overconfidence on the level of cash holdings is only affected by a firm’s financial condition but not growth opportunity or corporate governance. The positive effect of CEO overconfidence on the value of cash is not affected by all traditional motives of cash holdings. By linking the psychology-based theory and economic-based theory, the impact of CEO overconfidence on cash holdings is clearly distinguishable from other traditional motives. The analysis of cash sources allows us to understand why OC firms hold more cash when they also invest more than non-OC firms. Although equity issues are avoided by overconfident CEOs, once issued, OC firms tend to issue larger amount and then save a larger proportion of net proceeds from equity issuance. A larger contribution to cash saving from equity issues than from debt issues indicates the importance of equity issuance to OC firms’ cash policies.

Journal Pre-proof Finally, we understand that it is not easy to entirely remove the endogenous concerns in this research question. However, we have done several reasonable robustness tests to

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na

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ro

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mitigate the endogenous problems. All additional analyses provide us with higher confidence to the empirical findings we document in this study.

Journal Pre-proof References Almeida, H., Campello, M., Weisbach, M., 2004. The cash flow sensitivity of cash. Journal of Finance 59, 1777-1804. Banerjee, S., Humphery-Jenner, M., Nanda, V., 2015. Restraining overconfident CEOs through improved governance: Evidence from the Sarbanes–Oxley Act. Review of Financial Studies 28, 2812-2858. Bates, T. W., Kahle, K. M., Stulz, R. M., 2009. Why do U.S. firms hold so much more cash than they used to? Journal of Finance 64, 1985-2021.

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Bebchuk, L., Cohen, A., Ferrell, A., 2009. What matters in corporate governance? Review of Financial Studies 22, 783-827.

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Ben-David, I., Graham, J. R., Harvey, C. R., 2013. Managerial miscalibration. Quarterly

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Campbell, T. C., Gallmeyer, M., Johnson, S. A., Rutherford, J., Stanley, B. W., 2011.

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CEO optimism and forced turnover. Journal of Financial Economics 101, 695-712. Coles, J., Daniel, N., Naveen, L., 2006. Managerial incentives and risk-taking. Journal of

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Financial Economics 79, 431-468.

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Core, J., Guay, W., 2002. Estimate the value of employee stock option portfolios and their sensitivities to price and volatility. Journal of Accounting Research 40, 613-630. Denis, D. J., Sibilkov, V., 2010. Financial constraints, investment, and the value of cash

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holdings. Review of Financial Studies 23, 247-269.

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Deshmukh, S., Goel, A. M., Howe, K. M., 2013. CEO overconfidence and d ividend policy. Journal of Financial Intermediation 22, 440-463. Dittmar, A., Mahrt-Smith, J., 2007. Corporate governance and the value of cash holdings. Journal of Financial Economics 83, 599-634. Faulkender, M., Wang, R., 2006. Corporate financial policy and the value of cash. Journal of Finance 61, 1957-1990. Galasso, A., Simcoe, T. S., 2011. CEO overconfidence and innovation. Management Science 57, 1469-1484. Gao, H., Harford, J., Li, K., 2013. Determinants of corporate cash policy: Insights from private firms. Journal of Financial Economics 109, 623-639. Gervais, S., Heaton, J. B., Odean, T., 2011. Overconfidence, compensation contracts, and capital budgeting. Journal of Finance 66, 1735-1777.

Journal Pre-proof Goel, A. M., Thakor, A. V., 2008. Overconfidence, CEO selection, and corporate governance. Journal of Finance 63, 2737-2784. Griffin, D., Tversky, A., 1992. The weighing of evidence and the determinants of confidence. Cognitive Psychology 24, 411-435. Hadlock, C. J., Pierce, J. R., 2010. New evidence on measuring financial constraints: Measuring beyond the KZ index. Review of Financial Studies 23, 1909-1940. Harford, J., 1999. Corporate cash reserves and acquisitions. Journal of Finance 54, 1969-1997.

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Harford, J., Klasa, S., Maxwell, W., 2014. Refinancing risk and cash holdings. Journal of Finance 69, 975-1012.

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Harford, J., Mansi, S. A., Maxwell, W. F., 2008. Corporate governance and firm cash

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holdings in the US. Journal of Financial Economics 87, 535-555. Hirshleifer, D., Low, A., Teoh, S. H., 2012. Are overconfidence CEOs better innovators?

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compensation structure. Journal of Financial Economics 119, 533-558.

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Jensen, M. C., 1986. Agency costs of free cash flow, corporate finance, and takeovers. American Economic Review 76, 323-329. Johnson, S. A., Moorman, T. C., Sorescu, S., 2009. A reexamination of corpo rate

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Keynes, J. M., 1936. The General Theory of Employment, Interest and Money. Macmillan Cambridge University Press, New York. Malmendier, U., Tate, G., 2005. CEO overconfidence and corporate investment. Journal of Finance 60, 2661-2700. Malmendier, U., Tate, G., 2008. Who makes acquisitions? CEO overconfidence and the market's reaction. Journal of Financial Economic 89, 20-43. Malmendier, U., Tate, G., Yan, J., 2011. Overconfidence a nd early- life experiences: The effect of managerial traits on corporate financial policies. Journal of Finance 66, 1687-1733. McLean, R. D., 2011. Share issuance and cash savings. Journal of Financial Economics 99, 693-715.

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experimental approach. Journal of Corporate Finance 43, 175-192.

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Roll, R., 1986. The hubris hypothesis of corporate takeovers. Journal of Business 59,

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Table 1. Summary statistics

25th Percentile 0.000 0.000 0.000 0.000 0.027 6.288 0.813 0.057 0.004 -0.015 0.081 0.022 0.000 0.000 0.000 3.000 85.286 19.051

re

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0.626 0.253 0.409 0.338 0.146 7.396 4.885 0.084 0.011 0.073 0.229 0.056 0.032 0.033 0.512 7.444 617.136 135.628

Standard Deviation 0.484 0.435 0.492 0.473 0.165 1.535 10.861 0.088 0.013 0.144 0.184 0.053 0.066 0.056 0.500 6.816 1455.981 222.663

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Holder67 HighOptimism ModerateOptimism LowOptimism Cash Size TobinsQ CashFlow CashFlowVol NWC Leverage CapitalExp AcquisitionExp R&DExp Dividend Tenure CEODelta CEOVega

Mean

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Variable

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This table presents summary statistics. The sample consists of 17,942 firm–year observations from 1992 to 2016 fro m 1,967 firms in the United States with financial data and executive compensation data available fro m Co mpustat and ExecuCo mp. The variable Holder67 is an indicator variable that equals one if the firm is managed by an overconfident CEO and zero otherwise. Fo llo wing Hirshleifer et al. (2012), a CEO is classified as overconfident in the first fiscal year the CEO holds exercisable executive options that have moneyness greater than 67% and retains the same classification forward in the sample period. Fo llo wing Campbell et al. (2011), HighOptimism is an indicator variable that equals one if the CEO holds executive options that have moneyness greater than 100% at least twice during their tenure; Low Optimism is an indicator variable that equals one if the CEO exercises executive options that have moneyness lower than 30% at least twice during their tenure; and ModerateOptimism is an indicator variable that equals one if the CEO is not classified as HighOptimism or LowOptimism. Cash is cash and cash equivalents scaled by total assets; Size is the logarithm of total assets; TobinsQ is the firm’s market value div ided by the book value of property, p lant and equip ment, where the firm’s market value is computed using the market value of co mmon equity plus the book value of debt minus the firm’s current assets; CashFlow is the operating cash flow scaled by total assets, where the operating cash flow is co mputed using earnings after interest, dividends, and taxes but before depreciation; CashFlowVol is the standard deviation of industry median–adjusted operating cash flows over the previous 10 years, where industries are classified using two -digit SIC codes; NWC is the difference between current non-cash assets and current liabilit ies, scaled by total assets; Leverage is the ratio of total debt to total assets; CapitalExp is capital expenditures scaled by total assets; AcquisitionExp is acquisition expenditures scaled by total assets; R&DExp is R&D expenditures scaled by total sales and zero when this value is missing; Dividend is an indicator variable that equals one if the firm pays cash dividends and zero otherwise; Tenure is CEO tenure in years; CEODelta is the dollar change in CEO stock and option portfolio for 1% change in stock price; CEOVega is the dollar change in CEO stock and option portfolio for a 1% change in stock return volatility. CEODelta and CEOVega are stated in $ thousands in 2016. All continuous variables are winsorized at the first and 99th percentiles.

Median 1.000 0.000 0.000 0.000 0.083 7.295 1.894 0.087 0.007 0.066 0.214 0.040 0.001 0.005 1.000 5.000 213.654 56.474

75th Percentile 1.000 1.000 1.000 1.000 0.207 8.419 4.662 0.121 0.013 0.159 0.333 0.070 0.029 0.045 1.000 10.000 550.007 153.182

N 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942 17,942

Table 2. Univariate comparison

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This table presents the univariate comparisons for the subsamples based on different measures of CEO overconfidence. The variables are as defined in Table 1. CEODelta and CEOVega are stated in $ thousands in 2016. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Panel A: Holder67

Panel B: Optimism

0.178

0.109

0.132

Size

7.217

7.114

7.629

TobinsQ

9.915

4.182

4.025

CashFlow

0.108

0.109

0.090

CashFlowVol

0.012

0.007

0.010

NWC

0.067

0.060

Leverage

0.202

0.175

CapitalExp

0.064

AcquisitionExp

0.038

R&DExp

0.038

Dividend

0.405

Tenure

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t-statistic 12.06*** -5.76*** 22.48*** 16.68*** -2.24** -0.19 -10.56*** 6.41*** 8.11*** 3.98*** -14.64*** 44.40*** 23.81*** 6.12***

Difference (H−L) t-statistic Wilcoxon Z

Wilcoxon Z 10.92*** -5.83*** 34.89*** 24.33*** -2.95*** -0.26 -11.50*** 5.14*** 7.39*** 2.71*** -14.56*** 51.52*** 45.42*** 6.05***

Difference (H−M ) t-statistic Wilcoxon Z

0.076

0.140

0.078

11.35***

11.43***

7.535

7.249

7.095

-1.06

-1.09

2.004

2.158

0.978

31.89***

0.090

0.057

0.070

26.76***

0.006

0.013

0.008

-5.00***

0.078

0.068

0.072

0.069

-1.84*

0.225

0.217

0.254

0.241 -13.39***

0.045

0.054

0.040

0.051

0.036

0.003

0.033

0.003

0.025

0.000

0.008

0.029

0.006

0.035

0.004

2.51**

3.83***

9.44***

5.32***

0.000

0.597

1.000

0.491

0.000

-8.87***

-8.84***

-20.69***

-20.33***

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Cash

LowOptimism (N = 6,056) M ean M edian

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ModerateOptimism (N = 7,346) M ean M edian

Difference

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Variable

HighOptimism (N = 4,540) M ean M edian

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Variable Cash Size TobinsQ CashFlow CashFlowVol NWC Leverage CapitalExp AcquisitionExp R&DExp Dividend Tenure CEODelta CEOVega

Holder67 = 0 (N = 6,713) Mean Median 0.127 0.072 7.482 7.381 2.561 1.228 0.069 0.076 0.012 0.007 0.074 0.068 0.248 0.234 0.052 0.038 0.026 0.001 0.031 0.005 0.583 1.000 4.670 3.000 287.511 115.746 122.476 51.913

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Holder67 = 1 (N = 11,229) Mean Median 0.158 0.091 7.345 7.248 6.275 2.422 0.092 0.094 0.011 0.007 0.073 0.065 0.218 0.201 0.058 0.041 0.035 0.002 0.035 0.006 0.470 0.000 9.103 7.000 814.195 307.090 143.491 60.178

14.69***

13.17***

-14.65***

-14.36***

51.28***

25.03***

30.15***

37.29***

12.86***

19.49***

-8.10***

9.50***

10.29***

-2.26**

-4.19***

-3.80***

-14.55***

-6.98***

-10.64***

11.73***

11.53***

9.14***

7.33***

10.40***

10.54***

3.94***

0.79

8.480

7.000

7.582

6.000

6.500

4.000

14.89***

20.92***

7.02***

9.34***

CEODelta

1,086.419

425.718

592.344

252.048

295.403

98.830

26.40***

49.08***

15.88***

20.44***

CEOVega

118.587

46.658

167.851

79.560

109.318

42.740

2.34**

2.93***

-11.30***

-17.67***

Journal Pre-proof

Table 3. CEO overconfidence and cash holdings

This table presents the regression results of Eq. (1) for the fu ll sample and the matched sample fro m 1992 to 2016. Observations are at the firm–year level. We match each treated firm–year observation (firm with an overconfident CEO) with a control firm–year observation (firm without an overconfident CEO) in the same industry and year, using Holder67. Each matched sample includes treated observations and their matched peers with a similar propensity score, which is computed based on CapitalExp, AcquisitionExp, R&DExp, and Dividend. The dependent variable is Cash, which is defined as the ratio of cash and cash equivalents to total assets. The remaining variables are as defined in Tab le 1. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. The p -values [in brackets] of Wald test for the difference between the estimated coefficients of HighOptimism and ModerateOptimism are p resented in the table as well. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Sample Model Holder67

Full Sample (1) 0.008*** (2.91)

(2)

p-value of High −Moderate Size

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TobinsQ

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CashFlow

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CashFlowVol NWC

Log(1+Tenure) Log(1+CEODelta) Log(1+CEOVega) Firm Fixed Year Fixed N Adjusted R2

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Dividend

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R&DExp

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Leverage

AcquisitionExp

-0.039*** (-10.19) 0.001** (2.16) -0.056** (-2.32) -0.090 (-0.89) -0.267*** (-13.89) -0.099*** (-8.20) -0.343*** (-9.93) -0.203*** (-15.75) -0.306*** (-3.24) 0.007 (1.44) -0.007*** (-4.32) 0.006*** (4.18) -0.001 (-0.60) Yes Yes 17,942 0.809

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ModerateOptimism

CapitalExp

0.020*** (5.87) 0.011*** (4.79) [0.00]*** -0.038*** (-9.95) 0.000** (2.00) -0.062** (-2.55) -0.090 (-0.89) -0.267*** (-14.03) -0.097*** (-7.99) -0.351*** (-10.16) -0.206*** (-16.01) -0.303*** (-3.20) 0.007 (1.51) -0.006*** (-3.68) 0.004** (2.57) 0.000 (0.23) Yes Yes 17,942 0.810

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HighOptimism

Matched Sample (3) 0.013*** (3.23)

-0.043*** (-8.18) 0.001*** (2.60) -0.051 (-1.50) -0.160 (-1.08) -0.289*** (-10.66) -0.088*** (-5.14) -0.389*** (-6.93) -0.245*** (-10.73) -0.301** (-2.42) 0.010 (1.56) -0.008** (-2.58) 0.005** (2.17) 0.001 (0.62) Yes Yes 12,504 0.835

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Table 4. CEO overconfidence and value of cash

This table presents the regression results of Eq. (2) for the fu ll sample and the matched sample fro m 1992 to 2016. Observations are at the firm–year level. The dependent variable is ExcessRet, wh ich is the excess stock return over the fiscal year, co mputed as the difference between the firm’s annual stock return and its benchmark portfolio return. All the change variables are co mputed as annual change over the fiscal year divided by the lagged market value of equity. The variable Earnings is earnings before ext raordinary items p lus interest, deferred tax credits, and investment tax credits; NetFinancing is the total equity issuance minus repurchases plus debt issuance minus debt redemption, scaled by the lagged market value of equity; and Leverage is the market leverage, which is calcu lated as total debt over the sum of total debt and the market value of equity. All continuous variables are winsorized at the first and 99th percentiles. The measures of CEO overconfidence are defined as in Table 1. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. The p-values [in brackets] of Wald test for the difference between the estimated coefficients of HighOptimism×△ Cash and ModerateOptimism×△Cash are presented in the table as well. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Full Sample

Holder67 Holder67×△Cash

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HighOptimism

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HighOptimism×△Cash ModerateOptimism

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ModerateOptimism×△Cash

△Dividend NetFinancing Leverage Cash i,t-1 Log(1+Tenure) Log(1+CEODelta) Log(1+CEOVega) Firm Fixed Year Fixed N Adjusted R2

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△InterestExp

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△R&DExp

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p-value of High−Moderate △NonCashAssets △Earnings

(2) 0.751*** (2.61)

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(1) 0.908*** (3.49) -0.024 (-0.86) 0.842*** (2.86)

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Sample Model △Cash

0.153*** (2.64) 0.313*** (5.28) -1.428 (-1.35) -1.660 (-1.64) -0.803 (-1.10) -0.111 (-0.88) -0.810*** (-6.17) 1.498*** (9.96) -0.029 (-1.64) 0.126*** (7.53) -0.043*** (-4.15) Yes Yes 12,881 0.273

0.085** (2.33) 1.054** (2.10) 0.063** (2.54) 0.938*** (2.97) [0.82] 0.148** (2.52) 0.304*** (4.98) -1.802* (-1.71) -1.748* (-1.72) -0.957 (-1.30) -0.106 (-0.83) -0.752*** (-5.61) 1.478*** (9.87) -0.031* (-1.82) 0.108*** (6.52) -0.036*** (-3.40) Yes Yes 12,881 0.274

Matched Sample (3) 0.774 (1.46) -0.047 (-1.04) 0.996** (1.98)

0.076 (0.76) 0.372*** (3.73) -0.514 (-0.29) -2.599 (-1.37) -0.160 (-0.14) 0.084 (0.35) -0.838*** (-4.73) 1.737*** (6.81) 0.006 (0.20) 0.149*** (5.58) -0.047*** (-3.17) Yes Yes 8,920 0.360

Journal Pre-proof

Table 5. Effects of investment environments

This table presents the regression results of Eq. (1) for the full samp le and the matched samp le fro m 1992 to 2016. The observations are at the firm–year level. The dependent variable is Cash, which is defined as the ratio of cash and cash equivalents to total assets. Firms are classified in the subsample of innovative industry if they belong to an industry which has industry average R&D intensity greater than the med ian in a given year; otherwise, firms are classified in the subsample of other industry. The remaining control variab les are as defined in Tab le 1 and Table 4. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. The p-values [in brackets] of Wald test for the differences between the estimated coefficients of HighOptimism and ModerateOptimism and between the estimated coefficients of HighOptimism× △Cash and ModerateOptimism×△Cash are presented in the table as well. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Panel A: Effect of OC on the Level of Cash Holdings Innovative Industry (1) 0.012*** (3.60)

Model Holder67

Full Sample Other Innovative Industry Industry (2) (3) 1.494*** 0.334 (3.28) (1.05) -0.025 (-0.34) 0.529 (1.22) 0.112** (2.48) 1.078* (1.87) 0.069** (2.38) 1.007*** (3.01) [0.90] Yes Yes Yes Yes Yes Yes 2,803 9,708 0.267 0.282

na

Panel B: Effect of OC on the Value of Cash

re

Yes Yes Yes 13,682 0.812

lP

p-value of High−Moderate Controls Firm Fixed Year Fixed N Adjusted R2

-p

ModerateOptimism

Sample

Innovative Industry (1) 0.640** (2.29) -0.019 (-0.59) 0.712** (2.09)

Jo

ur

Model △Cash

Holder67×△Cash

Other Industry (4)

ro

HighOptimism

Holder67

Full Sample Other Innovative Industry Industry (2) (3) -0.003 (-0.68) 0.026*** (5.91) 0.014*** (4.68) [0.00]*** Yes Yes Yes Yes Yes Yes 3,798 13,682 0.702 0.813

of

Sample

HighOptimism HighOptimism×△Cash ModerateOptimism ModerateOptimism×△Cash p-value of High−Moderate Controls Firm Fixed Year Fixed N Adjusted R2

Yes Yes Yes 9,708 0.281

0.004 (0.77) 0.004 (1.26) [0.87] Yes Yes Yes 3,798 0.702

Other Industry (4) 1.574*** (3.38)

0.055 (0.73) 0.496 (0.74) 0.082 (1.35) 0.331 (0.58) [0.82] Yes Yes Yes 2,803 0.267

Matched Sample Innovative Other Industry Industry (5) (6) 0.014*** 0.005 (3.08) (0.60)

Yes Yes Yes 10,730 0.834

Yes Yes Yes 1,454 0.728

Matched Sample Innovative Other Industry Industry (5) (6) 0.686 2.255*** (1.15) (3.16) -0.052 -0.052 (-1.06) (-0.39) 0.893 0.848 (1.63) (0.85)

Yes Yes Yes 7,583 0.372

Yes Yes Yes 1,085 0.294

Journal Pre-proof

Table 6. The influence of transaction/precautionary/agency motives of cash holdings on the effect of CEO overconfidence on cash holdings This table presents the regression results of Eq. (1) for the full samp le and the matched samp le fro m 1992 to 2016. The observations are at the firm–year level. The dependent variable is Cash, which is defined as the ratio of cash and cash equivalents to total assets. In Panel A, firms are classified in the subsample of h igh TobinsQ if their TobinsQ are greater than the sample median in a given year; otherwise, firms are classified in the subsample of low TobinsQ. In Panel B, firms are classified in the subsample of high SAIndex (financially constrained) if their SAIndex are in the top tercile in a given year; otherwise, firms are classified in the subsample of lo w SAIndex (financially unconstrained). InstOwn is the percentage of shares held by institutional investors to total shares outstanding of a firm. In Panel C, firms are classified in the subsample of high InstOwn if their institutional ownership are greater than the med ian in a given year; otherwise, firms are classified in the subsample of low InstOwn. In Panel D, firms are classified in the subsample of low EIndex if their entrenchment index equal to 0; and are classified in the subsample of h igh EIndex if their entrenchment index are greater than or equal to 5. The remain ing control variables are as defined in Tab le 1. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. The p-values [in brackets] of Wald test for the difference between the estimated coefficients are presented in the table as well. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively.

of

Panel A: TobinsQ

Model Holder67 p-value of FC−FU HighOptimism p-value of FC−FU ModerateOptimism p-value of FC−FU Controls Firm Fixed Year Fixed N Adjusted R2

-p

Full Sample High Low High Low SAIndex SAIndex SAIndex SAIndex (1) (2) (3) (4) 0.019*** 0.004 (2.61) (1.49) [0.04]** 0.033*** 0.014*** (4.51) (3.90) [0.04]** 0.015*** 0.009*** (2.75) (3.73) [0.44] Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 5,933 11,985 5,933 11,985 0.829 0.785 0.830 0.785

Jo

Sample

ur

p-value of HighQ−LowQ Controls Firm Fixed Year Fixed N Adjusted R2

Matched Sample High Low TobinsQ TobinsQ (5) (6) 0.017** 0.011** (2.51) (2.31) [0.28]

re

p-value of HighQ−LowQ ModerateOptimism

lP

p-value of HighQ−LowQ HighOptimism

na

Model Holder67

Panel B: SAIndex

Full Sample High Low High Low TobinsQ TobinsQ TobinsQ TobinsQ (1) (2) (3) (4) 0.011*** 0.004 (2.26) (1.24) [0.17] 0.024*** 0.013*** (4.13) (3.08) [0.14] 0.012*** 0.008*** (2.81) (3.23) [0.49] Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 8,980 8,962 8,980 8,962 0.811 0.787 0.811 0.788

ro

Sample

Yes Yes Yes 6,811 0.835

Yes Yes Yes 5,693 0.833

Matched Sample High Low SAIndex SAIndex (5) (6) 0.028*** 0.008** (2.80) (2.02) [0.04]**

Yes Yes Yes 4,861 0.851

Yes Yes Yes 8,131 0.820

Journal Pre-proof

Panel C: Institutional Ownership

p-value of WellGov−PoorGov HighOptimism p-value of WellGov−PoorGov ModerateOptimism p-value of WellGov−PoorGov Controls Firm Fixed Year Fixed N Adjusted R2

of

Model Holder67

Full Sample High Low High Low InstOwn InstOwn InstOwn InstOwn (1) (2) (3) (4) 0.010** 0.007 (2.08) (0.93) [0.97] 0.026*** 0.014 (4.50) (1.56) [0.49] 0.016*** 0.002 (4.11) (0.44) [0.10]* Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 7,384 3,243 7,384 3,243 0.813 0.833 0.815 0.833

ro

Sample

Panel D: Entrenchment Index

Full Sample High Low EIndex EIndex (2) (3) 0.013* (1.85)

Model Holder67

[0.61]

lP

p-value of WellGov−PoorGov HighOptimism

na

p-value of WellGov−PoorGov ModerateOptimism

Yes Yes Yes 844 0.868

ur

Jo

p-value of WellGov−PoorGov Controls Firm Fixed Year Fixed N Adjusted R2

-p

Low EIndex (1) 0.002 (0.16)

re

Sample

0.024 (1.63)

High EIndex (4)

Matched Sample High Low InstOwn InstOwn (5) (6) 0.009 0.013 (1.24) (1.11) [0.41]

Yes Yes Yes 5,473 0.852

Yes Yes Yes 2,198 0.867

Matched Sample Low High EIndex EIndex (5) (6) -0.003 0.008 (-0.15) (0.63) [0.99]

0.023** (2.44) [0.94]

0.011 (1.10)

0.012* (1.88) [0.88]

Yes Yes Yes 1545 0.849

Yes Yes Yes 844 0.869

Yes Yes Yes 1545 0.850

Yes Yes Yes 527 0.885

Yes Yes Yes 1108 0.880

Journal Pre-proof

Table 7. The influence of transaction/precautionary/agency motives of cash holdings on the effect of CEO overconfidence on cash value

Panel A: TobinsQ

△Cash+OC×△Cash p-value of HighQ−LowQ HighOptimism HighOptimism×△Cash △Cash+OC×△Cash

ro

-p

Jo

p-value of HighQ−LowQ ModerateOptimism

ModerateOptimism×△Cash △Cash+OC×△Cash p-value of HighQ−LowQ Controls Firm Fixed Year Fixed N Adjusted R2

Yes Yes Yes 6,332 0.275

Low TobinsQ (4) 0.842*** (2.87)

re

Holder67×△Cash

lP

Holder67

Full Sample Low High TobinsQ TobinsQ (2) (3) 0.990*** -0.042 (3.70) (-0.06) -0.032 (-0.80) 0.332 (1.07) 1.322 [0.00]***

na

Model △Cash

High TobinsQ (1) 0.361 (0.65) -0.036 (-0.65) 1.689*** (2.68) 2.050 [0.00]*** [0.12]

ur

Sample

of

This table presents the regression results of Eq. (2) for the full samp le and the matched samp le fro m 1992 to 2016. The observations are at the firm–year level. The dependent variable is ExcessRet, which is the excess stock return over the fiscal year, co mputed as the difference between the firm’s annual sto ck return and its benchmark portfo lio return. In Panel A, firms are classified in the subsample of h igh TobinsQ if their TobinsQ are greater than the sample median in a given year; otherwise, firms are classified in the subsample of low TobinsQ. In Panel B, firms are classified in the subsample of high SAIndex (financially constrained) if their SAIndex are in the top tercile in a g iven year; otherwise, firms are classified in the subsample of lo w SAIndex (financially unconstrained). InstOwn is the percentage of shares held by institutional investors to total shares outstanding of a firm. In Panel C, firms are classified in the subsample of high InstOwn if their institutional ownership are greater than the median in a given year; otherwise, firms are classified in the subsample of low InstOwn. In Panel D, firms are classified in the subsample of lo w EIndex if their entrench ment index equal to 0; and are classified in the subsample of high EIndex if their entrench ment index are g reater than or equal to 5. The remaining control variables are as defined in Table 4. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. The p-values [in brackets] of Wald test for the difference between the estimated coefficients are presented in the table as well. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively.

Yes Yes Yes 6,549 0.311

0.069 0.054 (1.11) (1.22) 1.978** 0.762 (2.12) (1.36) 1.936 1.604 [0.01]** [0.00]*** [0.11] 0.028 0.051* (0.61) (1.69) 1.800*** 0.555 (2.87) (1.44) 1.758 1.397 [0.00]*** [0.00]*** [0.08]* Yes Yes Yes Yes Yes Yes 6,332 6,549 0.276 0.312

Matched Sample High Low TobinsQ TobinsQ (5) (6) -0.334 1.358** (-0.25) (2.57) -0.095 -0.055 (-1.10) (-0.86) 2.505** -0.013 (2.00) (-0.03) 2.171 1.345 [0.01]*** [0.00]*** [0.74]

Yes Yes Yes 4,825 0.370

Yes Yes Yes 4,095 0.484

Journal Pre-proof

Panel B: SAIndex Sample

High SAIndex (1) 1.264** (2.38) -0.066 (-0.86) 0.540 (0.97) 1.804 [0.00]*** [0.11]

Model △Cash Holder67 Holder67×△Cash △Cash+OC×△Cash p-value of FC−FU HighOptimism

Full Sample Low High SAIndex SAIndex (2) (3) 0.692*** 0.802 (2.63) (1.44) -0.006 (-0.19) 0.761** (2.17) 1.453 [0.00]***

ro

△Cash+OC×△Cash

-p

p-value of FC−FU ModerateOptimism

re

ModerateOptimism×△Cash

Yes Yes Yes 8,638 0.249

Jo

ur

na

Yes Yes Yes 4,243 0.307

lP

△Cash+OC×△Cash p-value of FC−FU Controls Firm Fixed Year Fixed N Adjusted R2

0.153* (1.87) 1.193 (1.36) 1.995 [0.02]** [0.47] 0.067 (1.13) 1.189** (2.34) 1.991 [0.00]*** [0.34] Yes Yes Yes 4,243 0.310

Matched Sample High Low SAIndex SAIndex (5) (6) 2.123*** 0.021 (2.85) (0.03) 0.060 -0.080* (0.51) (-1.71) 0.642 0.961 (0.82) (1.61) 2.765 0.982 [0.00]*** [0.03]** [0.53]

0.048 (1.14) 0.737 (1.49) 1.348 [0.00]***

of

HighOptimism×△Cash

Low SAIndex (4) 0.611** (2.03)

0.057** (1.99) 0.759* (1.82) 1.370 [0.00]*** Yes Yes Yes 8,638 0.249

Yes Yes Yes 3,132 0.458

Yes Yes Yes 5,788 0.321

Journal Pre-proof

Panel C: Institutional Ownership Sample Model △Cash Holder67 Holder67×△Cash △Cash+OC×△Cash p-value of WellGov−PoorGov HighOptimism

Matched Sample High Low InstOwn InstOwn (5) (6) 0.547 -0.353 (0.72) (-0.31) -0.037 -0.240 (-0.49) (-1.26) 1.056 0.619 (1.50) (0.42) 1.603 0.266 [0.00]*** [0.85] [0.73]

Jo

ur

p-value of WellGov−PoorGov Controls Firm Fixed Year Fixed N Adjusted R2

-p

△Cash+OC×△Cash

re

ModerateOptimism×△Cash

lP

p-value of WellGov−PoorGov ModerateOptimism

na

△Cash+OC×△Cash

ro

of

HighOptimism×△Cash

Full Sample High Low High Low InstOwn InstOwn InstOwn InstOwn (1) (2) (3) (4) 1.288*** 0.318 1.209*** -0.239 (2.86) (0.48) (2.77) (-0.33) 0.018 -0.172 (0.38) (-1.48) 0.109 0.515 (0.23) (0.78) 1.397 0.833 [0.00]*** [0.27] [0.49] 0.164*** 0.131 (2.99) (0.93) -0.328 1.052 (-0.36) (1.20) 0.881 0.813 [0.33] [0.37] [0.46] 0.070* 0.074 (1.69) (0.82) 0.499 1.833*** (1.02) (2.72) 1.708 1.594 [0.00]*** [0.02]** [0.27] Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 5,342 2,296 5,342 2,296 0.268 0.329 0.270 0.332

Yes Yes Yes 3,903 0.396

Yes Yes Yes 1,562 0.539

Journal Pre-proof

Panel D: Entrenchment Index Sample Model △Cash Holder67 Holder67×△Cash △Cash+OC×△Cash p-value of WellGov−PoorGov HighOptimism

High EIndex (4) -0.805 (-1.05)

Matched Sample Low High EIndex EIndex (5) (6) 1.059 0.428 (0.53) (0.32) -0.133 0.141 (-0.27) (0.82) 0.232 1.572 (0.07) (1.11) 1.291 2.000 [0.63] [0.09]* [0.64]

0.089 (0.73) 2.819** (2.32) 2.014 [0.06]*

△Cash+OC×△Cash

ro

of

HighOptimism×△Cash

Full Sample Low High Low EIndex EIndex EIndex (1) (2) (3) 2.420** 0.402 2.003 (2.07) (0.54) (1.31) -0.033 -0.045 (-0.15) (-0.39) -0.334 0.979 (-0.29) (1.16) 2.086 1.381 [0.05]* [0.03]** [0.93] 0.426 (1.32) 0.527 (0.23) 2.530 [0.18]

p-value of WellGov−PoorGov ModerateOptimism

[0.94]

-p

-0.045 (-0.23) -0.055 (-0.04) 1.948 [0.06]*

ModerateOptimism×△Cash

Jo

Yes Yes Yes 1,197 0.392

lP

na

Yes Yes Yes 594 0.136

ur

p-value of WellGov−PoorGov Controls Firm Fixed Year Fixed N Adjusted R2

re

△Cash+OC×△Cash

0.025 (0.29) 2.846*** (3.72) 2.041 [0.00]***

[0.23] Yes Yes Yes 594 0.148

Yes Yes Yes 1,197 0.406

Yes Yes Yes 369 0.294

Yes Yes Yes 846 0.439

Journal Pre-proof

Table 8. CEO overconfidence and sources of cash accumulations This table presents the empirical results of source of cash analysis following McLean (2011). Panel A presents summary statistics. △Cash is the difference between cash at the end of the year and cash at the beginning of the year. Issue is the cash proceeds fro m share issuance. Debt is the cash proceeds from debt sales. CashFlow is cash flow fro m operations. Other is all other cash sources, which include the sales of assets and investments. All these measures are scaled by lagged total assets. Assets is the logarithm of total assets. All continuous variables are winsorized at the first and 99th percentiles. Panel B presents the univariate co mparisons for the subsamples based on different measures of CEO overconfidence. Panel C presents the regression results of the extension of Eq . (4) for the full sample and the matched sample fro m 1992 to 2016. The observations are at the firm–year level. The dependent variable is △Cash. The measures of CEO overconfidence are as defined in Table 1. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Panel A: Summary statistics

lP

Panel B: Univariate comparison Holder67 = 1 (N = 10,172) Mean Median 0.028 0.005 0.032 0.008 0.134 0.022 0.114 0.115 0.045 0.000

ModerateOptimism (N = 6,670) M ean M edian

1.000 0.000 0.000 0.000 0.004 0.006 0.021 0.105 0.000 7.288

Holder67 = 0 (N = 5,916) Mean Median 0.006 0.002 0.017 0.004 0.105 0.021 0.080 0.090 0.038 0.001

LowOptimism (N = 5,312) M ean M edian

75th Percentile 1.000 1.000 1.000 1.000 0.038 0.017 0.135 0.152 0.009 8.402

N 16,088 16,088 16,088 16,088 16,088 16,088 16,088 16,088 16,088 16,088

Difference t-statistic 9.84*** 8.48*** 7.27*** 18.35*** 3.37***

Wilcoxon Z 8.85*** 22.66*** 2.52** 23.78*** -1.30

Variable

HighOptimism (N = 4,106) M ean M edian

△Cash

0.056

Jo

ur

na

Variable △Cash Issue Debt CashFlow Other

Median

of

0.632 0.255 0.415 0.330 0.020 0.026 0.124 0.102 0.042 7.386

25th Percentile 0.000 0.000 0.000 0.000 -0.016 0.002 0.000 0.064 0.000 6.283

ro

Holder67 HighOptimism ModerateOptimism LowOptimism △Cash Issue Debt CashFlow Other Assets

Standard Deviation 0.482 0.436 0.493 0.470 0.137 0.111 0.245 0.115 0.129 1.527

-p

Mean

re

Variable

Difference Difference (H−L) (H−M ) t-statistic Wilcoxon Z t-statistic Wilcoxon Z

0.011

0.013

0.003

0.002

0.001

16.79***

16.25***

14.19***

12.09***

Issue

0.050

0.011

0.020

0.007

0.017

0.003

11.98***

36.24***

12.24***

15.90***

Debt

0.147

0.015

0.118

0.026

0.112

0.019

6.65***

CashFlow

0.143

0.140

0.112

0.110

0.058

0.076

33.87***

41.71***

15.03***

21.25***

Other

0.049

0.000

0.038

0.001

0.043

0.001

1.95*

-3.20***

4.12***

-3.17***

1.12

5.68***

-1.33

Journal Pre-proof

Panel C: Regression Sample Model Holder67

Full Sample (1) -0.021*** (-3.27)

(2)

HighOptimism

-0.036*** (-2.97) -0.011* (-1.84) 0.554*** (9.74)

ModerateOptimism Issue

0.563*** (8.77) 0.195*** (2.95)

Holder67×Issue HighOptimism×Issue

0.222*** (3.36) 0.091 (0.81) 0.011 (1.21)

0.029** (2.44) 0.038* (1.87)

Holder67×Debt

-p

HighOptimism×Debt ModerateOptimism×Debt

0.214*** (5.64) 0.082* (1.70)

re

CashFlow

lP

Holder67×CashFlow HighOptimism×CashFlow

Other Holder67×Other HighOptimism×Other

Firm Fixed Year Fixed N Adjusted R2

Jo

ModerateOptimism×Other

ur

na

ModerateOptimism×CashFlow

Assets

ro

Debt

of

ModerateOptimism×Issue

-0.065** (-2.22) 0.055 (1.64)

0.008** (2.34) Yes Yes 16,088 0.398

0.107*** (3.19) 0.018 (1.38) 0.186*** (6.26)

0.188*** (2.68) 0.063 (1.36) -0.079*** (-4.27)

0.086** (2.03) 0.071** (2.09) 0.008** (2.52) Yes Yes 16,088 0.407

Matched Sample (3) -0.008 (-0.83)

0.641*** (6.74) 0.189* (1.93)

0.042* (1.82) 0.088** (2.33)

0.276*** (4.60) 0.022 (0.29)

-0.038 (-1.02) 0.006 (0.16)

0.012** (2.35) Yes Yes 11,127 0.485

Journal Pre-proof

Table 9. CEO overconfidence, cash flows, and cash holdings

This table presents the regression results of the extension of Eq. (1) for the full sample and the matched sample fro m 1992 to 2016. Observations are at the firm–year level. The dependent variable is Cash, which is defined as the ratio of cash and cash equivalents to total assets. The remaining variables are as defined in Table 1. The t -statistics (in parentheses) are based on standard errors robust to clustering by firm. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Sample Model Holder67

Full Sample (1) 0.012** (2.02) -0.053 (-1.37) 0.009 (0.26)

Holder67×CashFlow Holder67×CashFlow i,t-1

(2)

HighOptimism

of

HighOptimism×CashFlow

ro

HighOptimism×CashFlow i,t-1 ModerateOptimism

-p

ModerateOptimism×CashFlow

re

ModerateOptimism×CashFlow i,t-1 Size

CapitalExp AcquisitionExp R&DExp Dividend Log(1+Tenure) Log(1+CEODelta) Log(1+CEOVega) Firm Fixed Year Fixed N Adjusted R2

ur

Leverage

Jo

NWC

na

CashFlow

CashFlowVol

-0.037*** (-8.68) 0.000* (1.86) -0.026 (-0.84) -0.015 (-0.50) -0.138 (-1.14) -0.279*** (-12.80) -0.095*** (-6.72) -0.342*** (-8.95) -0.200*** (-13.97) -0.351*** (-3.15) 0.008 (1.58) -0.008*** (-3.97) 0.008*** (4.39) -0.001 (-1.03) Yes Yes 14,798 0.817

lP

TobinsQ

CashFlow i,t-1

0.023*** (3.18) -0.077* (-1.71) 0.040 (0.88) 0.013** (2.54) -0.064 (-1.47) 0.049 (1.29) -0.036*** (-8.53) 0.000* (1.66) -0.035 (-1.31) -0.033 (-1.12) -0.135 (-1.11) -0.279*** (-13.01) -0.092*** (-6.56) -0.348*** (-9.18) -0.205*** (-14.35) -0.349*** (-3.12) 0.008 (1.64) -0.006*** (-3.29) 0.005*** (2.87) -0.000 (-0.27) Yes Yes 14,798 0.818

Matched Sample (3) 0.017** (2.36) -0.045 (-0.93) -0.029 (-0.56)

-0.038*** (-6.63) 0.001** (2.37) -0.039 (-0.92) -0.006 (-0.12) -0.240 (-1.45) -0.315*** (-10.48) -0.091*** (-4.60) -0.382*** (-5.91) -0.235*** (-9.75) -0.364*** (-2.66) 0.015** (2.07) -0.008** (-2.44) 0.006*** (2.58) 0.000 (0.25) Yes Yes 10,351 0.844

Journal Pre-proof

Table 10. Level of cash holdings and succeeding CEO after CEO turnover This table presents the empirical results of CEO turnover. Panel A presents the logit regression results of prior cash on the CEO overconfidence after turnover. Holder67 and HighOptimism are emp loyed as dependent variables. The variab les are as defined in Table 1. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. In Panel B, the treated samples are firms whose non-overconfident (overconfident) CEOs are rep laced by overconfident (non-overconfident) CEOs. For the control samples, a firm changes its CEO but the managerial overconfidence type remains the same. AvgExcessCash is the average excess cash during the CEO’s tenure, where the excess cash is de fined as the difference between the firm’s cash and the industry median in a given year. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Panel A: Effect of prior cash on the CEO overconfidence Holder67 = 1 (1) 0.177 (0.16) 0.742*** (2.77)

Holder67 i,t-1 HighOptimism i,t-1

-p

TobinsQ i,t-1 CashFlow i,t-1

re

CapitalExp i,t-1

lP

AcquisitionExp i,t-1 R&DExp i,t-1

Jo

ur

na

Dividend i,t-1 Industry Fixed Year Fixed N Pseudo R2

-0.106 (-1.47) 0.018 (1.13) 4.214 (1.33) -1.139 (-0.34) -0.583 (-0.26) -5.479 (-1.39) 0.044 (0.18) Yes Yes 650 0.199

ro

Size i,t-1

HighOptimism = 1 (2) -2.299 (-1.41)

of

Dependent Variable Model Cash i,t-1

1.692*** (4.40) -0.129 (-1.22) -0.006 (-0.27) 9.385** (2.49) -0.563 (-0.10) -1.177 (-0.42) -5.089 (-0.96) -0.099 (-0.25) Yes Yes 520 0.273

Panel B: CEO turnover and the subsequence change in cash

Sample of Treated (A) Sample of Controls (B) Difference (A-B)

Turnover from Non-Overconfidence to Overconfidence Change in AvgExcessCash N 0.002 31 -0.001 140 0.003

Turnover from Overconfidence to Non-Overconfidence Change in AvgExcessCash N -0.012*** 318 0.017*** 105 -0.029***

Journal Pre-proof

Table 11. Alternative measures of CEO overconfidence and cash holdings This table presents the regression results of Eq. (1) with alternative OC p ro xy for the full samp le and the matched sample fro m 1992 to 2016. Observations are at the firm–year level. The dependent variable is Cash, which is defined as the ratio of cash and cash equivalents to total assets. The variab le Confidence is a continuous measure of the moneyness of a CEO’s exercisable executive options, which is measured as the average realizable value scaled by the stock p rice at the fiscal year-end, where the average realizable value is co mputed by divid ing the estimated value of all the unexercised exercisable options by the number of options. The variable ConfidenceTop is an indicator variable that equals one if a firm’s Confidence measure is in the top quartile of the year and zero otherwise. The remaining variab les are as defined in Table 1. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Full Sample (1) 0.031*** (5.68)

CashFlow CashFlowVol NWC

lP

Leverage CapitalExp

Log(1+CEODelta) Log(1+CEOVega) Firm Fixed Year Fixed N Adjusted R2

ur

Log(1+Tenure)

Jo

Dividend

na

AcquisitionExp R&DExp

-p

TobinsQ

-0.037*** (-9.85) 0.000* (1.71) -0.064*** (-2.65) -0.090 (-0.89) -0.266*** (-13.92) -0.096*** (-7.92) -0.349*** (-10.10) -0.208*** (-16.17) -0.303*** (-3.21) 0.007 (1.58) -0.005*** (-3.23) 0.003* (1.83) 0.001 (0.86) Yes Yes 17,942 0.810

re

Size

0.012*** (4.73) -0.038*** (-10.05) 0.000* (1.93) -0.058** (-2.41) -0.095 (-0.94) -0.266*** (-13.87) -0.098*** (-8.13) -0.346*** (-10.07) -0.205*** (-15.91) -0.306*** (-3.24) 0.007 (1.57) -0.006*** (-3.54) 0.005*** (3.19) 0.000 (0.17) Yes Yes 17,942 0.810

ro

ConfidenceTop

(2)

Matched Sample (3) (4) 0.027** (2.00) 0.010* (1.75) -0.052*** -0.052*** (-7.37) (-7.37) 0.000 0.000* (1.56) (1.72) -0.096** -0.091** (-2.38) (-2.25) -0.366* -0.363* (-1.77) (-1.75) -0.332*** -0.332*** (-8.34) (-8.30) -0.068*** -0.070*** (-2.81) (-2.90) -0.448*** -0.445*** (-5.37) (-5.33) -0.270*** -0.267*** (-8.67) (-8.53) -0.342*** -0.342*** (-2.60) (-2.60) 0.016 0.017 (1.54) (1.57) -0.004 -0.005 (-1.20) (-1.35) 0.005 0.007 (1.01) (1.42) 0.000 -0.001 (0.07) (-0.19) Yes Yes Yes Yes 6,242 6,242 0.832 0.831

of

Sample Model Confidence

Journal Pre-proof

Table 12. Alternative measures of CEO overconfidence and the value of cash This table presents the regression results of Eq. (2) with alternative OC p ro xy for the full samp le and the matched sample fro m 1992 to 2016. Observations are at the firm–year level. The dependent variable is ExcessRet, which is the excess stock return over the fiscal year, co mputed as the difference between the firm’s annual stock return and its benchmark portfo lio return. The variable Confidence is a continuous measure of the moneyness of a CEO’s exercisable executive options, wh ich is measured as the average realizab le value scaled by the stock p rice at the fiscal year-end, where the average realizable value is co mputed by div iding the estimated value of all the unexercised exercisable options by the number of options. The variable ConfidenceTop is an indicator variable that equals one if a firm’s Confidence measure is in the top quartile of the year and zero otherwise. The remaining variables are as defined in Tab le 4. The t-statistics (in parentheses) are based on standard errors robust to clustering by firm. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively.

Confidence

ro

Confidence×△Cash

-p

ConfidenceTop ConfidenceTop×△Cash

re

△NonCashAssets

lP

△Earnings △R&DExp

Cash i,t-1 Log(1+Tenure) Log(1+CEODelta) Log(1+CEOVega) Firm Fixed Year Fixed N Adjusted R2

ur

Leverage

Jo

NetFinancing

na

△InterestExp △Dividend

Full Sample (1) (2) 0.703*** 1.136*** (2.69) (5.05) 0.387*** (7.19) 2.059*** (3.10) 0.086*** (3.06) 0.865* (1.91) 0.142** 0.150** (2.43) (2.54) 0.297*** 0.303*** (4.87) (4.86) -1.762* -1.636 (-1.68) (-1.52) -1.609 -1.741* (-1.58) (-1.69) -0.962 -0.873 (-1.28) (-1.17) -0.145 -0.120 (-1.14) (-0.94) -0.616*** -0.758*** (-4.65) (-5.68) 1.474*** 1.479*** (9.86) (9.79) -0.022 -0.029* (-1.34) (-1.73) 0.069*** 0.105*** (4.29) (6.43) -0.012 -0.030*** (-1.15) (-2.94) Yes Yes Yes Yes 12,881 12,881 0.279 0.274

Matched Sample (3) (4) 0.718 1.238** (1.04) (2.29) 0.306** (2.51) 2.947** (2.08) 0.079 (1.24) 1.525** (2.03) 0.070 0.073 (0.33) (0.35) 0.460*** 0.470*** (4.06) (4.28) -0.222 0.444 (-0.13) (0.24) -0.052 -0.296 (-0.02) (-0.11) -1.056 -1.164 (-0.63) (-0.70) 0.349 0.383 (0.83) (0.91) -0.846** -0.954*** (-2.46) (-2.80) 1.980*** 1.962*** (5.02) (5.02) -0.027 -0.034 (-0.60) (-0.73) 0.086** 0.110*** (2.03) (2.58) -0.014 -0.029 (-0.56) (-1.12) Yes Yes Yes Yes 4,413 4,413 0.335 0.333

of

Sample Model △Cash

Journal Pre-proof

Highlights

of ro -p re lP na ur



CEO overconfidence is an alternative explanation to corporate cash holdings. The positive effects of CEO overconfidence on the level of cash holdings and the value of cash are mainly due to the investment environments faced by firms. The positive effects of CEO overconfidence on cash holdings level and cash value are barely affected by the traditional motives of cash holdings based on trade-off and agency theories.

Jo

 