The Effect of CEO-CFO Alumni Tie on the Application of Derivative Financial Instruments

The Effect of CEO-CFO Alumni Tie on the Application of Derivative Financial Instruments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Effect of CEO-CFO Alumni Tie on the Application of Derivative Financial Instruments Jing LIU This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6452281/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract Based on the economic practice in China, this paper empirically studies the effect of CEO-CFO alumni ties on the application of derivative financial instruments in listed firms. Empirical results show that the alumni tie between CEO and CFO has a positive effect on the application of derivative financial instruments. Heterogeneity tests show that the positive impact of CEO-CFO alumni ties on the application of derivative financial instruments mainly exists in listed firms with Chairman-CEO duality. Besides, individual characteristic similarity has a moderating effect, in the gender combination of male CEO – female CFO, the effect of CEO-CFO alumni tie on the application of derivative financial instruments is more pronounced, while the age difference will weaken the main effect. For the external environment, in environments of high economic policy uncertainty and a stable financial market, the positive impact of CEO-CFO alumni ties on the application of derivative financial instruments will be more pronounced. This research contributes to understanding the factors driving the use of derivative financial instruments and sheds light on the role of internal social relationships in corporate risk management practices. Business and commerce/Business and management Business and commerce/Finance Derivative Financial Instruments CEO-CFO Alumni Tie Economic Policy Uncertainty Similarity of Personal Characteristics 1. Introduction China is one of the major economies in the world, and its stability is of great significance (Liu, 2024a). At the microeconomic level, enterprises should conduct effective risk management and avoid triggering systemic risks to maintain stability. Among various risk management tools, derivative financial instruments are important tools that cannot be ignored and have grown exponentially worldwide in recent decades (Grima & Thalassinos, 2020). According to the International Swaps and Derivatives Association reports, 94% of the world’s 500 largest firms were trading derivative financial instruments in 2022 1 , while the ratio of Chinese firms listed in the world’s 500 largest firms that use derivative financial instruments is only 62% (Yang et al., 2023). Derivative financial instruments are both complex and specialized, requiring market participants to have a high level of financial literacy. However, if not used properly, derivative financial instruments can also be risky, leading to significant losses for listed firms. Thus, financial managers may be hesitant to make use of derivative financial instruments for the sake of their professional reputation (Khim & Liang, 1997). The relationship between key executives within the firm, especially the CEO and the CFO, can contribute to overcoming obstacles in applying derivative financial instruments in practice, especially in emerging markets highly embedded in social networks. Due to the complexity and specialization of derivative financial instruments, the CFO, as the professional, plays a crucial role in decision-making regarding the application of derivative financial instruments. Social relationships, such as alumni connections with the CEO of the firm, can influence the CFO’s enthusiasm and effectiveness in adopting derivative financial instruments. On the one hand, social relationships are proven to play an important role in promoting communication and enhancing trust (Grabner-Kräuter, 2009; Gaudeul & Giannetti, 2017; Liu, 2022). The close connection with the CEO can make it easier for the CFO to spread knowledge about derivative financial instruments among the manager team and gain support from the CEO. On the other hand, accurate estimation of the risk exposure and a comprehensive understanding of the corporate strategy is essential for effective hedging with derivative financial instruments. The social bond between the CEO and the CFO can contribute to these processes and promote the application of derivative financial instruments. Among social connections based on different kinds of social relationships, the alumni connection is an important social connection that significantly influences economic activities. Compared to general social connections, such as colleagues, alumni connections have stronger charisma and cohesion (Engelberg et al., 2013). Alumnus attended the same university and have been influenced by the same culture. This can form strong intra-group identities and close personal relationships (Liu, 2022). Besides, according to the statistical data from the Ministry of Education of the People’s Republic of China , the gross enrollment rate of higher education in China reached 57.8% in 2021 2 , and the education level of the people is at a high level. The alumni networks widely exist among businessmen, playing a particularly prominent role in economic activities, and becoming one of the most important social network relationships. Thus, the CEO-CFO alumni tie, as a typical personal connection between the CEO and the CFO, may significantly impact the application of derivative financial instruments. To study the impact of the CEO-CFO alumni tie on the application of derivative financial instruments, this paper takes A-share listed firms in China from 2010 and 2021 as research samples and tests the effect empirically. Empirical results show that the CEO-CFO alumni tie within the firm has a positive effect on the application of derivative financial instruments in emerging markets such as China, when the CEO also acts as the chairman of the firm, this positive effect can be more pronounced. Besides, characteristics similarity between the CEO and the CFO can influence the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Specifically, in the gender combination of male CEO – female CFO, the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments is more significant, while the age difference between the CEO and CFO will weaken the effect due to the generation gap. In addition, the external environment can influence the impact of the CEO-CFO alumni tie. For example, high economic policy uncertainty can strengthen the motivation to conduct risk management and a sound financial market can support the application of derivative financial instruments. Thus, high economic policy uncertainty and a sound financial market can strengthen the effect of the CEO-CFO alumni tie on the application of derivative financial instruments. This study has the following contributions. First, this paper studies the impact of the CEO-CFO alumni ties on the application of derivative financial instruments in emerging markets such as China. This research pays attention to the financial vision that the non-financial firms in emerging markets have a low ratio of derivative financial instruments usage, and enriches the literature on the driving factors of the application of derivative financial instruments. Second, prior literature on the social connections among economic participants mainly focuses on the social connections outside of the organization (Cohen et al., 2008; Cohen et al., 2010; El-Khatib et al., 2015). This research pays attention to the economic consequences of social connections within the firm and widens the research perspective on social connections. Third, this research can be of reference value in practice as well. This research finds that both the social connections within the firm, such as the CEO-CFO alumni tie, and the external environment, such as the financial market, can influence the application of derivative financial instruments. Thus, for more effective risk management, the government should further improve the financial market, and firms should strengthen internal communication and collaboration. The rest of the paper is organized as follows. Section 2 is hypothesis development. Section 3 describes the research design. Section 4 reports the empirical results and conducts robustness checks. Section 5 is further analysis, and finally, Section 6 concludes. 2. Hypothesis development Derivative financial instruments can be one of the crucial tools for firms to effectively manage risks and ensure stable operations. However, in emerging markets such as China, non-financial firms have limited adoption of derivative financial instruments, and the usage of derivative financial instruments for hedging is still not common at present (Yang et al., 2023). This phenomenon can be explained through external factors such as an underdeveloped derivative market (Oksana, 2014). At the same time, the internal factors, such as the characteristics of the management team, should not be ignored either. Prior literature finds that managers’ personal briefs and individual characteristics, such as risk-taking incentives, working experience, etc., can explain a large share of the application of derivative financial instruments beyond the firm (Rogers, 2002; Beber & Fabbri, 2012). However, prior studies on the effect of personal characteristics on the application of derivative financial instruments mainly focus on the CEO’s characteristics, while paying little attention to the relationships among the management team. As the financial expert, the CFO and his (or her) cooperation with the CEO cannot be ignored in the decision-making of the application of derivative financial instruments. On the one hand, as a complex tool for risk management, the efficient application of derivative financial instruments requires both financial expertise, which the CFO can provide, and comprehensive information on the firm’s risk distribution and corporate strategy, which the CEO can provide (Fleckenstein & Longstaff, 2020; Yang et al., 2023). The close personal relationship based on the alumni tie can contribute to efficient communication between the CEO and the CFO (High & Buehler, 2019; Liu, 2022). This communication makes it more likely for the key directors to adopt the derivative financial instrument as a risk management method, especially in emerging markets where derivatives are unpopular. On the other hand, the CEO-CFO alumni tie can contribute to the cooperation between the CEO and the CFO in the process of the application of derivative financial instruments (Houston et al., 2018). Successful utilization of derivative financial instruments necessitates more than just accurate calculation by financial professionals; it also demands thorough and precise data on the firm’s dynamic risk exposure. With the support of comprehensive information,, informed choices can be made regarding the selection and allocation of derivative financial instruments. This process calls for the close cooperation of the CEO and the CFO, which the CEO-CFO alumni tie can have a positive effect on. In addition, the derivative financial instrument is a double-edged sword and may cause loss in some cases (Wang, 2018; Yang et al., 2023). This potential loss may cause pressure from investors and directors on the board, and hurt the managers’ benefits, especially the CEO and the CFO. When the CEO and the CFO share an alumni tie, the cooperation can strengthen their disclosure power and ensure their career security to some extent (El-Khatib et al., 2015; Norbom & Lopez, 2016). This power can ease career anxiety and encourage managers to take the risk of derivative financial instruments. This leads to the main hypothesis in this paper: H1: Ceteris paribus, the alumni tie between the CEO and the CFO has a positive effect on the application of derivative financial instruments. 3. Data and methods 3.1 Sample selection and data sources Taking initial samples of Chinese A-share listed firms between 2010 and 2021, this paper employs the following sampling procedures. First, I delete financial company observations. Second, I delete observations with missing data used in the empirical tests. Ultimately, 6000 observations are left in regression analysis. The education information is handled connected from financial reports of the listed firms, and other data used in this paper is from the CSMAR database. Besides, to alleviate the undue influence of outliers, this paper winsorizes all the continuous variables at their bottom and top 1% percentiles. 3.2 Key variables 3.2.1 Measures of the application of derivative financial instruments Following prior literature (Sinkey & Carter, 2000; Adznan & Nelson, 2015), this paper takes the disclosure of derivative financial instruments in the financial statements and notes to measure the application of financial derivatives. Specifically, the dependent variable Derivative is a dummy variable that equals one when the accounting items related to derivative financial instruments are not zero. The related items include arbitrage tools, effective part of cash–flow hedge profit and loss, derivative financial instruments, transaction monetary assets–derivative financial assets, transaction monetary assets–derivative tool, futures contracts, financial assets at fair value through profit or loss–derivative financial assets, and sound value flexible loss and profit–hedging. 3.2.2 Measures of the CEO-CFO alumni tie Following prior literature (Engelberg et al.,2013; Fang & Huang, 2017; Liu, 2022), this paper detects the personal relationship between the CEO and the CFO through the alumni tie. Specifically, if the CEO and CFO within the firm graduated from the same university or college, then they are defined to share an alumni tie. The independent variable Connected is a dummy variable that equals 1 if the CEO and CFO of the listed firm share an alumni tie, and 0 otherwise. 3.2.3 Control variables Control variables include the firm’s size ( Size ), asset-liability ratio ( Lev ), return on assets ( Roa ), book-to-market ratio ( BM ), age of the listed firm ( Age ), the ratio of operating net cash flow to assets ( CashFlow ), duality of CEO and the board chairman positions ( Dual ), the shareholding ratio of the largest shareholder ( Lshare ), whether the firm is a state-owned enterprise ( SOE ), number of the analysts following the firm in the year ( Follow ), and market competition ( HHI ). 3.3 Empirical model To empirically test the impact of CEO-CFO alumni tie on the application of derivative financial instruments, this paper employs Eq. ( 1 ) as follows: $$\:Prob[{Derivative}_{it}=1]={\beta\:}_{0}+{\beta\:}_{1}{Connect}_{it}+\sum\:{\beta\:}_{m}Controls+Year\:FE+Industry\:FE+\epsilon\:$$ 1 In Eq. ( 1 ), the subscripts i and t denote firms and years, respectively. The dependent variable is the application of the derivative financial instruments, proxied by the variable Derivative . The independent variable of interest is the alumni tie between the CEO and CFO, proxied by Connect . The firm’s characteristics that can impact the application of financial derivates are also controlled in Eq. ( 1 ). Besides, this paper also adopts year-fixed and industry-fixed effects in Eq. ( 1 ). 4. Empirical analysis 4.1 Descriptive statistics Table 1 presents descriptive statistics for the main variables. The mean value of the variable Derivative is 0.069, indicating that only about 6.9% of the non-financial listed firms use derivative financial instruments. The usage of derivative financial instruments is not common in China mainland. The mean value of the variable Connect is 0.088, indicating that in about 8.8% of listed firms of the sample, the CEO and CFO share an alumni tie and are closely connected. Table 1 Descriptive statistics Variables Mean SD Minimum Median Maximum Obs. Derivative 0.069 0.254 0.000 0.000 1.000 6000 Connect 0.088 0.283 0.000 0.000 1.000 6000 Size 22.00 1.301 19.846 21.763 26.100 6000 Lev 0.399 0.217 0.045 0.382 0.957 6000 Roa 0.037 0.077 -0.354 0.042 0.205 6000 BM 0.582 0.244 0.099 0.577 1.148 6000 Age 1.844 0.967 0.000 1.946 3.296 6000 CashFlow 0.042 0.072 -0.186 0.044 0.227 6000 Dual 0.334 0.472 0.000 0.000 1.000 6000 Lshare 33.888 14.716 9.310 31.250 74.890 6000 SOE 0.266 0.442 0.000 0.000 1.000 6000 Follow 1.436 1.197 0.000 1.386 3.784 6000 HHI 0.077 0.089 0.015 0.043 0.584 6000 4.2 Main results Table 2 presents the regression results of the impact of CEO-CFO alumni tie on the application of the derivative financial instruments. In Column ( 1 ) and Column ( 2 ), the coefficients of the variable Connect are both positively significant at the 5% level, indicating that the social connection between the CEO and CFO can be conducive to the application of derivative financial instruments. The regression results are consistent with the main hypothesis of this paper. Table 2 The impact of CEO-CFO alumni tie on the application of derivative financial instruments ( 1 ) ( 2 ) Derivative Derivative Connect 0.1673** 0.1971** (2.0175) (2.3294) Size 0.1813*** (5.0117) Lev 0.3996** (2.3778) Roa -0.1383 (-0.2893) BM 0.4581*** (2.8172) Age 0.0684* (1.9251) CashFlow 0.3693 (0.8182) Dual 0.1715*** (2.8957) Lshare 0.0039** (2.0380) SOE -0.2396*** (-3.2629) Follow 0.0769** (2.5229) HHI -1.5883*** (-3.5864) Constant -1.4983*** -5.4745*** (-57.5609) (-7.6850) Year FE Yes Yes Industry FE Yes Yes Pseudo R 2 0.0393 0.1074 Obs. 6,000 6,000 Notes : Z-statistics are reported in parentheses. *p < 0.10, **p < 0.05, ***p < 0.01 4.3 Robustness checks 4.3.1 Propensity score matching The ratio of firms with CEO-CFO alumni ties is 8.8% in the sample (see Table 1 ), indicating that in more than 90% of listed firms, the CEO and CFO do not share an alumni tie within the firm. In practice, large firms are more likely to employ professional executives who graduated from influential universities and form CEO-CFO alumni ties within the firm. To ease this endogeneity issue, this paper employs the research method of propensity score matching (PSM). Specifically, the PSM model is as follows: $$\:P(Connected=1)={\alpha\:}_{0}+{\alpha\:}_{1}{Controls}_{it}+\epsilon\:$$ 2 In Eq. ( 2 ), the matching factors include the firm features such as Size (natural logarithm of total assets), Lev (total liability divided by total assets), and SOE (dummy variable that equals 1 if the firm is a state-owned enterprise), and individual features such as Gender (dummy variable if the CEO or CFO is male), Age (the age of the CEO or CFO), and Education (the education degree of the CEO or CFO). Based on this, this paper conducts 1:1 yearly, industrially, nearest-neighbor matching with non-replacement, and gains the sub-sample after propensity score matching. Table 3 Column ( 1 ) presents the regression results of the sub-sample, and the regression results are consistent with the main findings. 4.3.2 Add city-fixed effect As the financial environment varies a lot among different areas in China, and the complex application of derivative financial instruments needs the support from financial environment, firms located in different areas may have systematic differences in the application of derivative financial instruments (Liu, 2024b). To address this issue, this paper adds the city-fixed to Eq. ( 1 ) and re-regresses the model. Table 3 Column ( 2 ) presents the regression results, and the regression results are consistent with the main findings. 4.3.3 Drop the firms located in Beijing or Shanghai Considering the high concentration of universities in Beijing and Shanghai, there is a higher likelihood of CEO-CFO alumni ties. At the same time, these cities are also key political and financial hubs with well-developed financial markets. This may lead to endogeneity issues arising from location factors. To address this issue, this paper excludes the firms located in Beijing and Shanghai as the sub-sample and re-regresses Eq. ( 1 ) in robustness tests. Table 3 Column ( 3 ) presents the regression results, and the regression results are consistent with the main findings. Table 3 Robustness checks ( 1 ) ( 2 ) ( 3 ) Sub-sample after PSM Add city-fixed effect Drop firms located in Beijing or Shanghai Derivative Derivative Derivative Connect 0.2668* 0.1831** 0.1547* (1.6920) (2.0516) (1.6560) Size 0.3109*** 0.2216*** 0.1967*** (2.7627) (5.7039) (5.1061) Lev 0.2112 0.3375* 0.3871** (0.3670) (1.8772) (2.1025) Roa -0.8279 -0.3874 0.1883 (-0.6032) (-0.7732) (0.3926) BM 0.3877 0.2852 0.4742*** (0.8103) (1.6420) (2.7331) Age -0.2029* 0.0592 0.0205 (-1.9402) (1.5080) (0.5290) CashFlow 1.6594 0.3085 0.2118 (1.1786) (0.6597) (0.4463) Dual 0.3778** 0.2088*** 0.2057*** (2.2938) (3.3670) (3.2140) Lshare 0.0041 0.0051** 0.0027 (0.7958) (2.5628) (1.2721) SOE 0.0180 -0.1789** -0.1726** (0.0809) (-2.1455) (-2.1530) Follow 0.0376 0.0632** 0.0827** (0.4068) (1.9912) (2.5100) HHI 1.7234 -1.8579*** -1.8131*** (0.9841) (-3.6990) (-3.8892) Constant -7.5849*** -6.3127*** -5.5833*** (-3.2048) (-8.1635) (-7.3127) Year FE Yes Yes Yes Industry FE Yes Yes Yes City FE - Yes - Pseudo R 2 0.1217 0.1599 0.1035 Obs. 538 6,000 4,701 Notes : Z-statistics are reported in parentheses. *p < 0.10, **p < 0.05, ***p < 0.01 5. Further analysis 5.1 Heterogeneity of the Chairman-CEO duality Prior literature indicates that having the CEO also serve as the chairman on the board can enhance decision-making efficiency (Galbraith, 2015). And the chairman-CEO duality can effectively motivate the CEO to adapt quickly to changes in the environment (Finkelstein & D’aveni, 1994). When the CEO also acts as the chairman, it can be easier for him (or her) to adopt derivative financial instruments and enhance the effect of CEO-CFO alumni tie on the application of derivative financial instruments. Thus, this paper tests the heterogeneity of the Chairman-CEO duality in further analysis. Specifically, this paper classifies the sample into the group of firms having the chairman act as the CEO, and the group of firms having the CEO separates from the chairman, and re-regresses Eq. ( 1 ), respectively. Table 4 presents the regression results. In the sub-sample of the firms having the CEO acts as the Chairman, the coefficient of the variable Connect is significantly positive (see Column ( 1 )), while in the sub-sample of the firms having the CEO separates from the Chairman, the coefficient of the variable Connect is positive but is not statistically significant (see Column ( 2 )). The regression results indicate that the Chairman-CEO duality can enhance the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments. Table 4 Heterogeneity of the Chairman-CEO duality ( 1 ) ( 2 ) The CEO acts as the Chairman The CEO separates from the Chairman Derivative Derivative Connect 0.2868* 0.1217 (1.9577) (1.1411) Size 0.2380*** 0.1561*** (3.4895) (3.6062) Lev 0.8812*** 0.0854 (2.9273) (0.4022) Roa -0.4584 -0.1629 (-0.6142) (-0.2627) BM 0.2799 0.6118*** (0.9908) (3.0632) Age 0.0504 0.0724* (0.7860) (1.6869) CashFlow -0.5550 1.1063* (-0.7587) (1.8803) Lshare 0.0066** 0.0032 (2.0777) (1.3712) SOE -0.5581*** -0.1454* (-2.6069) (-1.7822) Follow 0.1222** 0.0526 (2.3129) (1.3922) HHI 0.1019 -3.6915*** (0.1912) (-4.9104) Constant -7.6327*** -4.2579*** (-5.6297) (-5.1211) Year FE Yes Yes Industry FE Yes Yes Pseudo R 2 0.1435 0.1138 Obs. 1,967 3,953 Notes : Z-statistics are reported in parentheses. *p < 0.10, **p < 0.05, ***p < 0.01 5.2 Moderating effect of the individual characteristic similarity According to homosocial reproduction (Kanter, 1977; Liu, 2024a), similarities between individuals can improve mutual recognition and foster close relationships, while significant differences may lead to communication barriers and emotional conflicts stemming from negative discrimination and stereotypes. The individual characteristic similarities between the CEO and CFO can affect their communication and trust, this impact may lead to a moderating effect on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Thus, this paper further tests the moderating effect of individual characteristic similarity on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Specifically, this paper takes age and gender similarity as the main dimension of individual characteristics, and conducts the variable SameGender , a dummy variable that equals 1 if the CEO and CFO are both male or both female; and the variable AgeDiff to measure the age difference between the CEO and CFO. Based on this, this paper adds the interaction term of the CEO-CFO alumni tie and individual characteristics similarity ( Connect*SameGender, Connect*AgeDiff ) to Eq. ( 1 ), and re-regresses. Besides, this paper also conducts sub-sample tests based on the gender combination of CEO and CFO, and re-regresses respectively. Table 5 presents the regression results. In Column ( 1 ), the coefficient of the interaction term Connect*SameGender is negatively significant at the 1% level, indicating that gender similarity weakens the effect of CEO-CFO alumni tie on the application of derivative financial instruments. In the group of male CEO – male CFO, the coefficient of the interaction term Connect*SameGender is not statistically significant (see Column ( 2 )), while in the group of male CEO – female CFO, the coefficient of the interaction term Connect*SameGender is positively significant at the 1% level (see Column ( 3 )). That is, from the perspective of gender similarity, the gender combination of male CEO and female CFO can enhance the positive effect of CEO-CFO alumni tie on the application of derivative financial instruments. This may be because female CFOs are more cautious and risk aversion compared to their male peers (Lam, 2015; Zalata et al., 2019), and pay more attention to risk management. For the similarity of age, in Column ( 4 ), the coefficient of the interaction term is significantly negative, indicating that the age gap between the CEO and CFO will weaken the effect of CEO-CFO alumni tie on the application of derivative financial instruments. Table 5 The moderating effect of personal characteristic similarity ( 1 ) ( 2 ) ( 3 ) ( 4 ) Full sample Male CEO - male CFO Male CEO - female CFO Full sample Derivative Derivative Derivative Derivative Connect*SameGender -0.4604*** (-2.5783) Connect 0.5032*** 0.0838 0.5366*** 0.4097*** (3.4468) (0.8044) (3.3826) (3.2818) Connect*AgeDiff -0.0483*** (-2.6818) SameGender 0.0742 (1.2489) AgeDiff 0.0037 (0.7829) Size 0.1822*** 0.1514*** 0.2826*** 0.1829*** (5.0478) (3.3084) (3.9835) (5.0311) Lev 0.3857** 0.2905 0.5621* 0.4018** (2.2867) (1.3643) (1.7490) (2.3736) Roa -0.1556 -0.8445 1.8947** -0.1101 (-0.3265) (-1.4562) (2.1658) (-0.2278) BM 0.4608*** 0.5347** 0.5215* 0.4141** (2.8324) (2.5593) (1.6981) (2.5297) Age 0.0694* 0.0478 0.0616 0.0601* (1.9552) (1.0746) (0.9202) (1.6705) CashFlow 0.3879 0.7527 0.2449 0.3917 (0.8586) (1.3036) (0.3064) (0.8661) Dual 0.1752*** 0.2034*** -0.0170 0.1803*** (2.9566) (2.7652) (-0.1413) (3.0058) Lshare 0.0040** 0.0082*** -0.0044 0.0034* (2.0750) (3.4386) (-1.1782) (1.7683) SOE -0.2380*** -0.3796*** -0.0871 -0.2144*** (-3.2421) (-3.9753) (-0.5874) (-2.9072) Follow 0.0794*** 0.0854** 0.0202 0.0748** (2.6042) (2.2501) (0.3521) (2.4445) HHI -1.6137*** -1.1979** -1.3273 -1.4509*** (-3.6809) (-2.4704) (-1.1962) (-3.3472) Constant -5.5761*** -5.7634*** -6.8996*** -5.5299*** (-7.8456) (-6.4168) (-4.9763) (-7.7140) Year FE Yes Yes Yes Yes Industry FE Yes Yes Yes Yes Pseudo R 2 0.1096 0.1052 0.1669 0.1069 Obs. 6,000 3,784 1,618 5,934 Notes : Z-statistics are reported in parentheses. *p < 0.10, **p < 0.05, ***p < 0.01 The observations of groups female CEO – male CFO and female CEO – male CFO are too few to conduct regression. 5.3 Moderating effect of economic policy uncertainty One of the main reasons why non-financial firms use derivative financial instruments is to hedge against operational risks stemming from uncertainties. Economic policy uncertainty is an important factor influencing uncertainty and can affect the application of derivative financial instruments. Thus, this paper further tests the moderating effect of economic policy uncertainty on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Specifically, following the prior literature (Baker et al., 2016), this paper takes the South China Morning Post as the sample and employs a textual analysis method to measure the economic policy uncertainty, proxied by EPU . Based on this, this paper adds the interaction term of the CEO-CFO alumni tie and economic policy uncertainty ( Connect*EPU ) to Eq. ( 1 ). Table 6 presents the regression results. The coefficient of the interaction term Connect*EPU is positively significant at the 1% level, indicating that the economic policy uncertainty will strengthen the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments. That is, the external economic policy uncertainty can stimulate the CEO and CFO to work together and actively make use of derivative financial instruments for risk management. Table 6 Moderating effect of the economic policy uncertainty ( 1 ) Derivative Connect*EPU 0.1037*** (2.9051) Connect -0.2155 (-1.3182) EPU -0.0789** (-2.2431) Size 0.1980*** (5.3242) Lev 0.3750** (2.2218) Roa -0.1704 (-0.3556) BM 0.4276*** (2.6184) Age 0.0688* (1.9305) CashFlow 0.4118 (0.9126) Dual 0.1814*** (3.0513) Lshare 0.0038** (1.9703) SOE -0.2527*** (-3.4525) Follow 0.0622** (2.0188) HHI -1.6888*** (-3.7734) Constant -5.4262*** (-7.7340) Year FE Yes Industry FE Yes Pseudo R 2 0.1112 Obs. 6,000 Notes : Z-statistics are reported in parentheses. *p < 0.10, **p < 0.05, ***p < 0.01 5.4 Heterogeneity of the financial environment As a sophisticated derivative financial instrument, the application of derivative financial instruments necessitates specific conditions of the financial environment of the region where the firm is located. A sound financial environment can offer external support for understanding and applying derivative financial instruments. Thus, this paper further tests the heterogeneity of the financial environment. Specifically, following prior literature (Liu, 2022), this paper takes the score of the financial market environment in the Marketization Index of China’s Provinces: NERI Report 2021 (Wang et al., 2021) to measure the financial environment of the province where the firm located in. As the scores are not comparable before and after 2016, this paper classifies the sample into the group of weak financial environment and the group of sound financial environment based on the mean value of the financial market environment score of the year and re-regresses Eq. ( 1 ) respectively. Table 7 presents the regression results. In the sub-sample of weak financial environment, the coefficient of the variable Connect is not statistically significant (see Column ( 1 )), while in the sub-sample of sound financial environment, the coefficient of the variable Connect is significantly positive (see Column ( 2 )), indicating that the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments mainly exists in the sub-sample of sound financial environment, and the application of derivative financial instruments also rely on the support from external financial market. Table 7 Heterogeneity of the financial environment ( 1 ) ( 2 ) Weak financial environment Sound financial environment Derivative Derivative Connect 0.0574 0.2835** (0.4322) (2.4807) Size 0.2549*** 0.1421*** (5.0036) (2.5912) Lev 0.4215* 0.3952* (1.6459) (1.7267) Roa -0.4399 0.1372 (-0.6645) (0.1997) BM 0.1288 0.7831*** (0.5507) (3.2115) Age -0.0868 0.2353*** (-1.5550) (4.6674) CashFlow 1.0795* -0.2971 (1.6740) (-0.4540) Dual 0.1051 0.2097*** (1.1037) (2.6548) Lshare -0.0080*** 0.0124*** (-2.6750) (4.9594) SOE 0.1120 -0.6506*** (1.1606) (-4.9725) Follow 0.0916** 0.0473 (2.0431) (1.1089) HHI -2.0041*** -0.8457 (-3.4517) (-1.4977) Constant -6.5060*** -6.4050*** (-6.6381) (-5.9371) Year FE Yes Yes Industry FE Yes Yes Pseudo R 2 0.1319 0.1318 Obs. 3,001 2,999 Notes : Z-statistics are reported in parentheses. *p < 0.10, **p < 0.05, ***p < 0.01 6. Conclusion This paper empirically examines the impact of CEO-CFO alumni ties on the application of derivative financial instruments in China. The main findings are as follows: ( 1 ) The alumni tie between the CEO and CFO within the firm can contribute to the application of derivative financial instruments in emerging markets such as China, the research finding stands robust through a series of robustness checks. ( 2 ) The positive effect of CEO-CFO alumni tie on the application of derivative financial instruments mainly exists in listed firms with the Chairman-CEO duality, and the gender combination of male CEO – female CFO, while the generation gap between the CEO and the CFO can weaken the characteristic similarity and weaken the effect of alumni tie on the application of derivative financial instruments. ( 3 ) High economic policy uncertainty makes risk management necessary and has a positive moderating effect on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Besides, the application of derivative financial instruments needs support from external financial markets, and the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments mainly exists in listed firms located in areas with sound financial markets. Declarations Ethical Approval Ethical approval was not required as the study did not involve human participants. Informed Consent Informed consent was not required as the study did not involve human participants. Competing Interests The author declares no competing interests. Data Availability All data generated or analysed during this study are included in this published article [and its supplementary information files]. Author Contribution Conceptualization, JL; methodology, JL; software, JL; writing-original draft preparation, JL; writing-review and editing, JL. The author read and approved the final manuscript. The author has read and approved the re-submission of the manuscript. 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J Social Personal Relationships 36(3):719–740 Houston JF, Lee J, Suntheim F (2018) Social networks in the global banking sector. J Acc Econ 65(2/3):237–269 Kanter RM (1977) Men and Women of the Corporation. Basic Books, New York Khim EM, Liang DLK (1997) The use of derivative financial instruments in company financial risk management: The Singapore experience. Singap Manage Rev 19(2):17–44 Lam D (2015) Gender differences in risk aversion among Chinese university students. J Gambl Stud 31(4):1405–1415 Liu J (2022) Alumni network, CEO turnover, and stock price crash risk: Evidence from China. Cogent Econ Finance 10(1):1–25 Liu J (2024a) The impact of feminism-related public discussions on the promotion of female senior executives: evidence from China. Asian-Pac Econ Lit, 1 Liu J (2024b) The effect of local internet development on employees’ salary: Evidence from China. Emerg Markets Finance Trade 60(9):1986–1999 Nanda V, Silveri S, Wang K, Zhao L (2024) Executive compensation limits and executive turnover. Manage Sci 70(4):2382–2405 Norbom HM, Lopez PD (2016) Leadership and innovation: Informal power and its relationship to innovative culture. J Leadersh Stud 10(1):18–31 Oksana M (2014) Fractal Characteristics of World Market Commodity Derivatives. Revista Romana de Economie, 36–48 Rogers DA (2002) Does executive portfolio structure affect risk management? CEO risk-taking incentives and corporate derivatives usage. J Banking Finance 26(2/3):271 Sinkey JF Jr., Carter DA (2000) Evidence on the financial characteristics of banks that do and do not use derivatives. Q Rev Econ Finance 40(4):431 Wang M (2018) Credit default swaps on municipal bonds: A double-edged sword? Yale J Regul 35(1):301–323 Yang A, Li W, Teo BSX, Othman J (2023) The impact of financial derivatives on the enterprise value of Chinese listed companies: Moderating effects of managerial characteristics. Int J Financial Stud 11(1):2 Zalata AM, Ntim C, Aboud A, Gyapong E (2019) Female CEOs and core earnings quality: New evidence on the ethics versus risk-aversion puzzle. J Bus Ethics 160(2):515–534 Footnotes International Swaps and Derivatives Association (ISDA) website. ( https://www.isda.org/ ) accessed on 1 July 2022. http://www.moe.gov.cn/fbh/live/2022/54453/mtbd/202205/t20220517_628223.html Additional Declarations No competing interests reported. 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Introduction","content":"\u003cp\u003eChina is one of the major economies in the world, and its stability is of great significance (Liu, 2024a). At the microeconomic level, enterprises should conduct effective risk management and avoid triggering systemic risks to maintain stability. Among various risk management tools, derivative financial instruments are important tools that cannot be ignored and have grown exponentially worldwide in recent decades (Grima \u0026amp; Thalassinos, 2020). According to the International Swaps and Derivatives Association reports, 94% of the world\u0026rsquo;s 500 largest firms were trading derivative financial instruments in 2022\u003csup\u003e1\u003c/sup\u003e, while the ratio of Chinese firms listed in the world\u0026rsquo;s 500 largest firms that use derivative financial instruments is only 62% (Yang et al., 2023).\u003c/p\u003e\u003cp\u003eDerivative financial instruments are both complex and specialized, requiring market participants to have a high level of financial literacy. However, if not used properly, derivative financial instruments can also be risky, leading to significant losses for listed firms. Thus, financial managers may be hesitant to make use of derivative financial instruments for the sake of their professional reputation (Khim \u0026amp; Liang, 1997). The relationship between key executives within the firm, especially the CEO and the CFO, can contribute to overcoming obstacles in applying derivative financial instruments in practice, especially in emerging markets highly embedded in social networks. Due to the complexity and specialization of derivative financial instruments, the CFO, as the professional, plays a crucial role in decision-making regarding the application of derivative financial instruments. Social relationships, such as alumni connections with the CEO of the firm, can influence the CFO\u0026rsquo;s enthusiasm and effectiveness in adopting derivative financial instruments.\u003c/p\u003e\u003cp\u003eOn the one hand, social relationships are proven to play an important role in promoting communication and enhancing trust (Grabner-Kr\u0026auml;uter, 2009; Gaudeul \u0026amp; Giannetti, 2017; Liu, 2022). The close connection with the CEO can make it easier for the CFO to spread knowledge about derivative financial instruments among the manager team and gain support from the CEO. On the other hand, accurate estimation of the risk exposure and a comprehensive understanding of the corporate strategy is essential for effective hedging with derivative financial instruments. The social bond between the CEO and the CFO can contribute to these processes and promote the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003eAmong social connections based on different kinds of social relationships, the alumni connection is an important social connection that significantly influences economic activities. Compared to general social connections, such as colleagues, alumni connections have stronger charisma and cohesion (Engelberg et al., 2013). Alumnus attended the same university and have been influenced by the same culture. This can form strong intra-group identities and close personal relationships (Liu, 2022). Besides, according to the statistical data from the \u003cem\u003eMinistry of Education of the People\u0026rsquo;s Republic of China\u003c/em\u003e, the gross enrollment rate of higher education in China reached 57.8% in 2021\u003csup\u003e2\u003c/sup\u003e, and the education level of the people is at a high level. The alumni networks widely exist among businessmen, playing a particularly prominent role in economic activities, and becoming one of the most important social network relationships. Thus, the CEO-CFO alumni tie, as a typical personal connection between the CEO and the CFO, may significantly impact the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003eTo study the impact of the CEO-CFO alumni tie on the application of derivative financial instruments, this paper takes A-share listed firms in China from 2010 and 2021 as research samples and tests the effect empirically. Empirical results show that the CEO-CFO alumni tie within the firm has a positive effect on the application of derivative financial instruments in emerging markets such as China, when the CEO also acts as the chairman of the firm, this positive effect can be more pronounced. Besides, characteristics similarity between the CEO and the CFO can influence the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Specifically, in the gender combination of male CEO \u0026ndash; female CFO, the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments is more significant, while the age difference between the CEO and CFO will weaken the effect due to the generation gap. In addition, the external environment can influence the impact of the CEO-CFO alumni tie. For example, high economic policy uncertainty can strengthen the motivation to conduct risk management and a sound financial market can support the application of derivative financial instruments. Thus, high economic policy uncertainty and a sound financial market can strengthen the effect of the CEO-CFO alumni tie on the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003eThis study has the following contributions. First, this paper studies the impact of the CEO-CFO alumni ties on the application of derivative financial instruments in emerging markets such as China. This research pays attention to the financial vision that the non-financial firms in emerging markets have a low ratio of derivative financial instruments usage, and enriches the literature on the driving factors of the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003eSecond, prior literature on the social connections among economic participants mainly focuses on the social connections outside of the organization (Cohen et al., 2008; Cohen et al., 2010; El-Khatib et al., 2015). This research pays attention to the economic consequences of social connections within the firm and widens the research perspective on social connections.\u003c/p\u003e\u003cp\u003eThird, this research can be of reference value in practice as well. This research finds that both the social connections within the firm, such as the CEO-CFO alumni tie, and the external environment, such as the financial market, can influence the application of derivative financial instruments. Thus, for more effective risk management, the government should further improve the financial market, and firms should strengthen internal communication and collaboration.\u003c/p\u003e\u003cp\u003eThe rest of the paper is organized as follows. Section 2 is hypothesis development. Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e3\u003c/span\u003e describes the research design. Section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e4\u003c/span\u003e reports the empirical results and conducts robustness checks. Section \u003cspan refid=\"Sec17\" class=\"InternalRef\"\u003e5\u003c/span\u003e is further analysis, and finally, Section \u003cspan refid=\"Sec22\" class=\"InternalRef\"\u003e6\u003c/span\u003e concludes.\u003c/p\u003e"},{"header":"2. Hypothesis development","content":"\u003cp\u003eDerivative financial instruments can be one of the crucial tools for firms to effectively manage risks and ensure stable operations. However, in emerging markets such as China, non-financial firms have limited adoption of derivative financial instruments, and the usage of derivative financial instruments for hedging is still not common at present (Yang et al., 2023). This phenomenon can be explained through external factors such as an underdeveloped derivative market (Oksana, 2014). At the same time, the internal factors, such as the characteristics of the management team, should not be ignored either.\u003c/p\u003e\u003cp\u003ePrior literature finds that managers\u0026rsquo; personal briefs and individual characteristics, such as risk-taking incentives, working experience, etc., can explain a large share of the application of derivative financial instruments beyond the firm (Rogers, 2002; Beber \u0026amp; Fabbri, 2012). However, prior studies on the effect of personal characteristics on the application of derivative financial instruments mainly focus on the CEO\u0026rsquo;s characteristics, while paying little attention to the relationships among the management team. As the financial expert, the CFO and his (or her) cooperation with the CEO cannot be ignored in the decision-making of the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003eOn the one hand, as a complex tool for risk management, the efficient application of derivative financial instruments requires both financial expertise, which the CFO can provide, and comprehensive information on the firm\u0026rsquo;s risk distribution and corporate strategy, which the CEO can provide (Fleckenstein \u0026amp; Longstaff, 2020; Yang et al., 2023). The close personal relationship based on the alumni tie can contribute to efficient communication between the CEO and the CFO (High \u0026amp; Buehler, 2019; Liu, 2022). This communication makes it more likely for the key directors to adopt the derivative financial instrument as a risk management method, especially in emerging markets where derivatives are unpopular.\u003c/p\u003e\u003cp\u003eOn the other hand, the CEO-CFO alumni tie can contribute to the cooperation between the CEO and the CFO in the process of the application of derivative financial instruments (Houston et al., 2018). Successful utilization of derivative financial instruments necessitates more than just accurate calculation by financial professionals; it also demands thorough and precise data on the firm\u0026rsquo;s dynamic risk exposure. With the support of comprehensive information,, informed choices can be made regarding the selection and allocation of derivative financial instruments. This process calls for the close cooperation of the CEO and the CFO, which the CEO-CFO alumni tie can have a positive effect on.\u003c/p\u003e\u003cp\u003eIn addition, the derivative financial instrument is a double-edged sword and may cause loss in some cases (Wang, 2018; Yang et al., 2023). This potential loss may cause pressure from investors and directors on the board, and hurt the managers\u0026rsquo; benefits, especially the CEO and the CFO. When the CEO and the CFO share an alumni tie, the cooperation can strengthen their disclosure power and ensure their career security to some extent (El-Khatib et al., 2015; Norbom \u0026amp; Lopez, 2016). This power can ease career anxiety and encourage managers to take the risk of derivative financial instruments.\u003c/p\u003e\u003cp\u003eThis leads to the main hypothesis in this paper:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH1: Ceteris paribus, the alumni tie between the CEO and the CFO has a positive effect on the application of derivative financial instruments.\u003c/em\u003e\u003c/p\u003e"},{"header":"3. Data and methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Sample selection and data sources\u003c/h2\u003e\u003cp\u003eTaking initial samples of Chinese A-share listed firms between 2010 and 2021, this paper employs the following sampling procedures. First, I delete financial company observations. Second, I delete observations with missing data used in the empirical tests. Ultimately, 6000 observations are left in regression analysis. The education information is handled connected from financial reports of the listed firms, and other data used in this paper is from the CSMAR database. Besides, to alleviate the undue influence of outliers, this paper winsorizes all the continuous variables at their bottom and top 1% percentiles.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Key variables\u003c/h2\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1 Measures of the application of derivative financial instruments\u003c/h2\u003e\u003cp\u003eFollowing prior literature (Sinkey \u0026amp; Carter, 2000; Adznan \u0026amp; Nelson, 2015), this paper takes the disclosure of derivative financial instruments in the financial statements and notes to measure the application of financial derivatives. Specifically, the dependent variable \u003cem\u003eDerivative\u003c/em\u003e is a dummy variable that equals one when the accounting items related to derivative financial instruments are not zero. The related items include arbitrage tools, effective part of cash\u0026ndash;flow hedge profit and loss, derivative financial instruments, transaction monetary assets\u0026ndash;derivative financial assets, transaction monetary assets\u0026ndash;derivative tool, futures contracts, financial assets at fair value through profit or loss\u0026ndash;derivative financial assets, and sound value flexible loss and profit\u0026ndash;hedging.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e3.2.2 Measures of the CEO-CFO alumni tie\u003c/h2\u003e\u003cp\u003eFollowing prior literature (Engelberg et al.,2013; Fang \u0026amp; Huang, 2017; Liu, 2022), this paper detects the personal relationship between the CEO and the CFO through the alumni tie. Specifically, if the CEO and CFO within the firm graduated from the same university or college, then they are defined to share an alumni tie. The independent variable \u003cem\u003eConnected\u003c/em\u003e is a dummy variable that equals 1 if the CEO and CFO of the listed firm share an alumni tie, and 0 otherwise.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e3.2.3 Control variables\u003c/h2\u003e\u003cp\u003eControl variables include the firm\u0026rsquo;s size (\u003cem\u003eSize\u003c/em\u003e), asset-liability ratio (\u003cem\u003eLev\u003c/em\u003e), return on assets (\u003cem\u003eRoa\u003c/em\u003e), book-to-market ratio (\u003cem\u003eBM\u003c/em\u003e), age of the listed firm (\u003cem\u003eAge\u003c/em\u003e), the ratio of operating net cash flow to assets (\u003cem\u003eCashFlow\u003c/em\u003e), duality of CEO and the board chairman positions (\u003cem\u003eDual\u003c/em\u003e), the shareholding ratio of the largest shareholder (\u003cem\u003eLshare\u003c/em\u003e), whether the firm is a state-owned enterprise (\u003cem\u003eSOE\u003c/em\u003e), number of the analysts following the firm in the year (\u003cem\u003eFollow\u003c/em\u003e), and market competition (\u003cem\u003eHHI\u003c/em\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Empirical model\u003c/h2\u003e\u003cp\u003eTo empirically test the impact of CEO-CFO alumni tie on the application of derivative financial instruments, this paper employs Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) as follows:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:Prob[{Derivative}_{it}=1]={\\beta\\:}_{0}+{\\beta\\:}_{1}{Connect}_{it}+\\sum\\:{\\beta\\:}_{m}Controls+Year\\:FE+Industry\\:FE+\\epsilon\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the subscripts \u003cem\u003ei\u003c/em\u003e and \u003cem\u003et\u003c/em\u003e denote firms and years, respectively. The dependent variable is the application of the derivative financial instruments, proxied by the variable \u003cem\u003eDerivative\u003c/em\u003e. The independent variable of interest is the alumni tie between the CEO and CFO, proxied by \u003cem\u003eConnect\u003c/em\u003e. The firm\u0026rsquo;s characteristics that can impact the application of financial derivates are also controlled in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Besides, this paper also adopts year-fixed and industry-fixed effects in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Empirical analysis","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Descriptive statistics\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents descriptive statistics for the main variables. The mean value of the variable \u003cem\u003eDerivative\u003c/em\u003e is 0.069, indicating that only about 6.9% of the non-financial listed firms use derivative financial instruments. The usage of derivative financial instruments is not common in China mainland. The mean value of the variable \u003cem\u003eConnect\u003c/em\u003e is 0.088, indicating that in about 8.8% of listed firms of the sample, the CEO and CFO share an alumni tie and are closely connected.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive statistics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMinimum\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMaximum\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eObs.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.069\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.088\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.846\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e26.100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.957\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.582\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.844\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCashFlow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLshare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33.888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e31.250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e74.890\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSOE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFollow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.436\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.784\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHHI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Main results\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the regression results of the impact of CEO-CFO alumni tie on the application of the derivative financial instruments. In Column (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) and Column (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), the coefficients of the variable Connect are both positively significant at the 5% level, indicating that the social connection between the CEO and CFO can be conducive to the application of derivative financial instruments. The regression results are consistent with the main hypothesis of this paper.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe impact of CEO-CFO alumni tie on the application of derivative financial instruments\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1673**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1971**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.0175)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.3294)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1813***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(5.0117)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3996**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.3778)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.1383\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-0.2893)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.4581***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.8172)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0684*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.9251)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCashFlow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3693\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.8182)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1715***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.8957)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLshare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0039**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.0380)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSOE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.2396***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-3.2629)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFollow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0769**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.5229)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHHI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.5883***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-3.5864)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConstant\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.4983***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-5.4745***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-57.5609)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-7.6850)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eYear FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIndustry FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudo R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0393\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1074\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eObs.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Z-statistics are reported in parentheses. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Robustness checks\u003c/h2\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e4.3.1 Propensity score matching\u003c/h2\u003e\u003cp\u003eThe ratio of firms with CEO-CFO alumni ties is 8.8% in the sample (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), indicating that in more than 90% of listed firms, the CEO and CFO do not share an alumni tie within the firm. In practice, large firms are more likely to employ professional executives who graduated from influential universities and form CEO-CFO alumni ties within the firm. To ease this endogeneity issue, this paper employs the research method of propensity score matching (PSM). Specifically, the PSM model is as follows:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:P(Connected=1)={\\alpha\\:}_{0}+{\\alpha\\:}_{1}{Controls}_{it}+\\epsilon\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), the matching factors include the firm features such as \u003cem\u003eSize\u003c/em\u003e (natural logarithm of total assets), \u003cem\u003eLev\u003c/em\u003e (total liability divided by total assets), and \u003cem\u003eSOE\u003c/em\u003e (dummy variable that equals 1 if the firm is a state-owned enterprise), and individual features such as \u003cem\u003eGender\u003c/em\u003e (dummy variable if the CEO or CFO is male), \u003cem\u003eAge\u003c/em\u003e (the age of the CEO or CFO), and \u003cem\u003eEducation\u003c/em\u003e (the education degree of the CEO or CFO). Based on this, this paper conducts 1:1 yearly, industrially, nearest-neighbor matching with non-replacement, and gains the sub-sample after propensity score matching. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Column (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) presents the regression results of the sub-sample, and the regression results are consistent with the main findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e4.3.2 Add city-fixed effect\u003c/h2\u003e\u003cp\u003eAs the financial environment varies a lot among different areas in China, and the complex application of derivative financial instruments needs the support from financial environment, firms located in different areas may have systematic differences in the application of derivative financial instruments (Liu, 2024b). To address this issue, this paper adds the city-fixed to Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and re-regresses the model. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Column (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) presents the regression results, and the regression results are consistent with the main findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e4.3.3 Drop the firms located in Beijing or Shanghai\u003c/h2\u003e\u003cp\u003eConsidering the high concentration of universities in Beijing and Shanghai, there is a higher likelihood of CEO-CFO alumni ties. At the same time, these cities are also key political and financial hubs with well-developed financial markets. This may lead to endogeneity issues arising from location factors. To address this issue, this paper excludes the firms located in Beijing and Shanghai as the sub-sample and re-regresses Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) in robustness tests. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Column (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) presents the regression results, and the regression results are consistent with the main findings.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRobustness checks\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSub-sample after PSM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdd city-fixed effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDrop firms located in Beijing or Shanghai\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2668*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1831**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1547*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.6920)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.0516)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1.6560)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3109***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2216***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1967***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.7627)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(5.7039)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(5.1061)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3375*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.3871**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.3670)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.8772)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.1025)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.8279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.3874\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1883\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-0.6032)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-0.7732)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.3926)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3877\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4742***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.8103)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.6420)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.7331)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.2029*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0592\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0205\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-1.9402)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.5080)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.5290)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCashFlow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.6594\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.2118\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.1786)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.6597)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.4463)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3778**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2088***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.2057***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.2938)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.3670)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(3.2140)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLshare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0051**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0027\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.7958)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.5628)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1.2721)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSOE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0180\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.1789**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.1726**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.0809)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-2.1455)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-2.1530)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFollow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0632**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0827**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.4068)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.9912)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.5100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHHI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.7234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.8579***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.8131***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.9841)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-3.6990)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-3.8892)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConstant\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7.5849***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-6.3127***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-5.5833***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-3.2048)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-8.1635)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-7.3127)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eYear FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIndustry FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCity FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudo R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1599\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1035\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eObs.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e538\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,701\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Z-statistics are reported in parentheses. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"5. Further analysis","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Heterogeneity of the Chairman-CEO duality\u003c/h2\u003e\u003cp\u003ePrior literature indicates that having the CEO also serve as the chairman on the board can enhance decision-making efficiency (Galbraith, 2015). And the chairman-CEO duality can effectively motivate the CEO to adapt quickly to changes in the environment (Finkelstein \u0026amp; D\u0026rsquo;aveni, 1994). When the CEO also acts as the chairman, it can be easier for him (or her) to adopt derivative financial instruments and enhance the effect of CEO-CFO alumni tie on the application of derivative financial instruments. Thus, this paper tests the heterogeneity of the Chairman-CEO duality in further analysis. Specifically, this paper classifies the sample into the group of firms having the chairman act as the CEO, and the group of firms having the CEO separates from the chairman, and re-regresses Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), respectively.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the regression results. In the sub-sample of the firms having the CEO acts as the Chairman, the coefficient of the variable \u003cem\u003eConnect\u003c/em\u003e is significantly positive (see Column (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)), while in the sub-sample of the firms having the CEO separates from the Chairman, the coefficient of the variable \u003cem\u003eConnect\u003c/em\u003e is positive but is not statistically significant (see Column (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)). The regression results indicate that the Chairman-CEO duality can enhance the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHeterogeneity of the Chairman-CEO duality\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe CEO acts as the Chairman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe CEO separates from the Chairman\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2868*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1217\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.9577)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.1411)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2380***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1561***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(3.4895)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.6062)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8812***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0854\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.9273)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.4022)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.4584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.1629\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-0.6142)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-0.2627)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2799\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.6118***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.9908)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.0632)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0504\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0724*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.7860)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.6869)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCashFlow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.5550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.1063*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-0.7587)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.8803)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLshare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0066**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.0777)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.3712)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSOE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.5581***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.1454*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-2.6069)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-1.7822)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFollow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1222**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0526\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.3129)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.3922)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHHI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.6915***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.1912)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-4.9104)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConstant\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7.6327***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-4.2579***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-5.6297)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-5.1211)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eYear FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIndustry FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudo R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1435\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1138\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eObs.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,953\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Z-statistics are reported in parentheses. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Moderating effect of the individual characteristic similarity\u003c/h2\u003e\u003cp\u003eAccording to homosocial reproduction (Kanter, 1977; Liu, 2024a), similarities between individuals can improve mutual recognition and foster close relationships, while significant differences may lead to communication barriers and emotional conflicts stemming from negative discrimination and stereotypes. The individual characteristic similarities between the CEO and CFO can affect their communication and trust, this impact may lead to a moderating effect on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003eThus, this paper further tests the moderating effect of individual characteristic similarity on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Specifically, this paper takes age and gender similarity as the main dimension of individual characteristics, and conducts the variable \u003cem\u003eSameGender\u003c/em\u003e, a dummy variable that equals 1 if the CEO and CFO are both male or both female; and the variable \u003cem\u003eAgeDiff\u003c/em\u003e to measure the age difference between the CEO and CFO. Based on this, this paper adds the interaction term of the CEO-CFO alumni tie and individual characteristics similarity (\u003cem\u003eConnect*SameGender, Connect*AgeDiff\u003c/em\u003e) to Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and re-regresses. Besides, this paper also conducts sub-sample tests based on the gender combination of CEO and CFO, and re-regresses respectively.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the regression results. In Column (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), the coefficient of the interaction term \u003cem\u003eConnect*SameGender\u003c/em\u003e is negatively significant at the 1% level, indicating that gender similarity weakens the effect of CEO-CFO alumni tie on the application of derivative financial instruments. In the group of male CEO \u0026ndash; male CFO, the coefficient of the interaction term \u003cem\u003eConnect*SameGender\u003c/em\u003e is not statistically significant (see Column (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)), while in the group of male CEO \u0026ndash; female CFO, the coefficient of the interaction term \u003cem\u003eConnect*SameGender\u003c/em\u003e is positively significant at the 1% level (see Column (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)). That is, from the perspective of gender similarity, the gender combination of male CEO and female CFO can enhance the positive effect of CEO-CFO alumni tie on the application of derivative financial instruments. This may be because female CFOs are more cautious and risk aversion compared to their male peers (Lam, 2015; Zalata et al., 2019), and pay more attention to risk management. For the similarity of age, in Column (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), the coefficient of the interaction term is significantly negative, indicating that the age gap between the CEO and CFO will weaken the effect of CEO-CFO alumni tie on the application of derivative financial instruments.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe moderating effect of personal characteristic similarity\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFull sample\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMale CEO - male CFO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMale CEO - female CFO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFull sample\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect*SameGender\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.4604***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-2.5783)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5032***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0838\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5366***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4097***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(3.4468)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.8044)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(3.3826)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.2818)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect*AgeDiff\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.0483***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(-2.6818)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSameGender\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0742\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.2489)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAgeDiff\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.7829)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1822***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1514***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.2826***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1829***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(5.0478)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.3084)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(3.9835)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(5.0311)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3857**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5621*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4018**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.2867)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.3643)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1.7490)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(2.3736)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.1556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.8445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.8947**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.1101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-0.3265)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-1.4562)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.1658)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(-0.2278)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.4608***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.5347**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5215*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4141**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.8324)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.5593)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1.6981)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(2.5297)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0694*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0601*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.9552)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.0746)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.9202)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.6705)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCashFlow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.2449\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3917\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.8586)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.3036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.3064)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.8661)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1752***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2034***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1803***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.9566)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.7652)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-0.1413)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.0058)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLshare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0040**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0082***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0034*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.0750)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.4386)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-1.1782)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.7683)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSOE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.2380***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.3796***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0871\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.2144***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-3.2421)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-3.9753)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-0.5874)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(-2.9072)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFollow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0794***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0854**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0748**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.6042)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.2501)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.3521)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(2.4445)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHHI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.6137***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.1979**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.3273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.4509***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-3.6809)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-2.4704)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-1.1962)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(-3.3472)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConstant\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-5.5761***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-5.7634***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-6.8996***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-5.5299***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-7.8456)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-6.4168)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(-4.9763)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(-7.7140)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eYear FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIndustry FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudo R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1069\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eObs.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,784\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5,934\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Z-statistics are reported in parentheses. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe observations of groups female CEO \u0026ndash; male CFO and female CEO \u0026ndash; male CFO are too few to conduct regression.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e5.3 Moderating effect of economic policy uncertainty\u003c/h2\u003e\u003cp\u003eOne of the main reasons why non-financial firms use derivative financial instruments is to hedge against operational risks stemming from uncertainties. Economic policy uncertainty is an important factor influencing uncertainty and can affect the application of derivative financial instruments. Thus, this paper further tests the moderating effect of economic policy uncertainty on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Specifically, following the prior literature (Baker et al., 2016), this paper takes the \u003cem\u003eSouth China Morning Post\u003c/em\u003e as the sample and employs a textual analysis method to measure the economic policy uncertainty, proxied by \u003cem\u003eEPU\u003c/em\u003e. Based on this, this paper adds the interaction term of the CEO-CFO alumni tie and economic policy uncertainty (\u003cem\u003eConnect*EPU\u003c/em\u003e) to Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the regression results. The coefficient of the interaction term \u003cem\u003eConnect*EPU\u003c/em\u003e is positively significant at the 1% level, indicating that the economic policy uncertainty will strengthen the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments. That is, the external economic policy uncertainty can stimulate the CEO and CFO to work together and actively make use of derivative financial instruments for risk management.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eModerating effect of the economic policy uncertainty\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect*EPU\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1037***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.9051)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.2155\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-1.3182)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEPU\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.0789**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-2.2431)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1980***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(5.3242)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3750**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.2218)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.1704\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-0.3556)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.4276***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.6184)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0688*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.9305)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCashFlow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.4118\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.9126)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1814***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(3.0513)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLshare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0038**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.9703)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSOE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.2527***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-3.4525)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFollow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0622**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.0188)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHHI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.6888***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-3.7734)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConstant\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-5.4262***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-7.7340)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eYear FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIndustry FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudo R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1112\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eObs.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6,000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Z-statistics are reported in parentheses. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e5.4 Heterogeneity of the financial environment\u003c/h2\u003e\u003cp\u003eAs a sophisticated derivative financial instrument, the application of derivative financial instruments necessitates specific conditions of the financial environment of the region where the firm is located. A sound financial environment can offer external support for understanding and applying derivative financial instruments. Thus, this paper further tests the heterogeneity of the financial environment. Specifically, following prior literature (Liu, 2022), this paper takes the score of the financial market environment in the \u003cem\u003eMarketization Index of China\u0026rsquo;s Provinces: NERI Report 2021\u003c/em\u003e (Wang et al., 2021) to measure the financial environment of the province where the firm located in. As the scores are not comparable before and after 2016, this paper classifies the sample into the group of weak financial environment and the group of sound financial environment based on the mean value of the financial market environment score of the year and re-regresses Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) respectively.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e presents the regression results. In the sub-sample of weak financial environment, the coefficient of the variable \u003cem\u003eConnect\u003c/em\u003e is not statistically significant (see Column (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)), while in the sub-sample of sound financial environment, the coefficient of the variable \u003cem\u003eConnect\u003c/em\u003e is significantly positive (see Column (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)), indicating that the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments mainly exists in the sub-sample of sound financial environment, and the application of derivative financial instruments also rely on the support from external financial market.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHeterogeneity of the financial environment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeak financial environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSound financial environment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eDerivative\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConnect\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0574\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2835**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.4322)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.4807)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSize\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2549***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1421***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(5.0036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.5912)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLev\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.4215*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3952*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.6459)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.7267)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRoa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.4399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1372\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-0.6645)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.1997)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7831***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0.5507)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.2115)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.0868\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2353***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-1.5550)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(4.6674)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCashFlow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0795*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.2971\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.6740)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-0.4540)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDual\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2097***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.1037)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.6548)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLshare\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.0080***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0124***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-2.6750)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(4.9594)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSOE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.6506***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(1.1606)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-4.9725)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFollow\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0916**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0473\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(2.0431)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.1089)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHHI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.0041***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.8457\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-3.4517)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-1.4977)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eConstant\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-6.5060***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-6.4050***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(-6.6381)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(-5.9371)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eYear FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIndustry FE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudo R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1318\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eObs.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Z-statistics are reported in parentheses. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis paper empirically examines the impact of CEO-CFO alumni ties on the application of derivative financial instruments in China. The main findings are as follows: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The alumni tie between the CEO and CFO within the firm can contribute to the application of derivative financial instruments in emerging markets such as China, the research finding stands robust through a series of robustness checks. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The positive effect of CEO-CFO alumni tie on the application of derivative financial instruments mainly exists in listed firms with the Chairman-CEO duality, and the gender combination of male CEO \u0026ndash; female CFO, while the generation gap between the CEO and the CFO can weaken the characteristic similarity and weaken the effect of alumni tie on the application of derivative financial instruments. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) High economic policy uncertainty makes risk management necessary and has a positive moderating effect on the relationship between the CEO-CFO alumni tie and the application of derivative financial instruments. Besides, the application of derivative financial instruments needs support from external financial markets, and the positive effect of the CEO-CFO alumni tie on the application of derivative financial instruments mainly exists in listed firms located in areas with sound financial markets.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was not required as the study did not involve human participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was not required as the study did not involve human participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, JL; methodology, JL; software, JL; writing-original draft preparation, JL; writing-review and editing, JL. 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J Banking Finance 26(2/3):271\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSinkey JF Jr., Carter DA (2000) Evidence on the financial characteristics of banks that do and do not use derivatives. Q Rev Econ Finance 40(4):431\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang M (2018) Credit default swaps on municipal bonds: A double-edged sword? Yale J Regul 35(1):301\u0026ndash;323\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang A, Li W, Teo BSX, Othman J (2023) The impact of financial derivatives on the enterprise value of Chinese listed companies: Moderating effects of managerial characteristics. Int J Financial Stud 11(1):2\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZalata AM, Ntim C, Aboud A, Gyapong E (2019) Female CEOs and core earnings quality: New evidence on the ethics versus risk-aversion puzzle. J Bus Ethics 160(2):515\u0026ndash;534\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e International Swaps and Derivatives Association (ISDA) website. (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.isda.org/\u003c/span\u003e\u003cspan address=\"https://www.isda.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) accessed on 1 July 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.moe.gov.cn/fbh/live/2022/54453/mtbd/202205/t20220517_628223.html\u003c/span\u003e\u003cspan address=\"http://www.moe.gov.cn/fbh/live/2022/54453/mtbd/202205/t20220517_628223.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Derivative Financial Instruments, CEO-CFO Alumni Tie, Economic Policy Uncertainty, Similarity of Personal Characteristics","lastPublishedDoi":"10.21203/rs.3.rs-6452281/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6452281/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBased on the economic practice in China, this paper empirically studies the effect of CEO-CFO alumni ties on the application of derivative financial instruments in listed firms. Empirical results show that the alumni tie between CEO and CFO has a positive effect on the application of derivative financial instruments. Heterogeneity tests show that the positive impact of CEO-CFO alumni ties on the application of derivative financial instruments mainly exists in listed firms with Chairman-CEO duality. Besides, individual characteristic similarity has a moderating effect, in the gender combination of male CEO \u0026ndash; female CFO, the effect of CEO-CFO alumni tie on the application of derivative financial instruments is more pronounced, while the age difference will weaken the main effect. For the external environment, in environments of high economic policy uncertainty and a stable financial market, the positive impact of CEO-CFO alumni ties on the application of derivative financial instruments will be more pronounced. This research contributes to understanding the factors driving the use of derivative financial instruments and sheds light on the role of internal social relationships in corporate risk management practices.\u003c/p\u003e","manuscriptTitle":"The Effect of CEO-CFO Alumni Tie on the Application of Derivative Financial Instruments","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-17 13:53:52","doi":"10.21203/rs.3.rs-6452281/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-20T15:46:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-14T03:49:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-12T13:50:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-05T05:02:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294957492770842786133199941593429259565","date":"2025-08-04T21:22:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-04T11:58:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116847469860293011777112873661746389149","date":"2025-08-04T11:00:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224624598857246522759954752979992662661","date":"2025-08-02T13:02:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-29T01:20:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272232488981181896848198901450378952993","date":"2025-07-26T00:14:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209889617033112959110300384265233177707","date":"2025-07-18T02:18:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-15T07:57:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-13T09:20:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-13T09:14:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-06T18:54:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-04-15T07:47:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1af30f32-d5fd-4174-8d77-6705261bed3f","owner":[],"postedDate":"July 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":51604601,"name":"Business and commerce/Business and management"},{"id":51604602,"name":"Business and commerce/Finance"}],"tags":[],"updatedAt":"2026-04-21T13:54:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-17 13:53:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6452281","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6452281","identity":"rs-6452281","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}