Navigating turbulence: female CEOs and its impact on volatility during exceptional events. The case of the European insurance sector

In an increasingly volatile business environment, corporate governance plays a critical role in ensuring organizational resilience and performance. A key question in academic and professional debates is whether female leadership offers a competitive advantage in risk management and financial stability, particularly in strategic sectors like insurance. This sector is central to the financial system due to its exposure to systemic risks and its role in channeling savings and providing coverage. Risk management is thus a core element of insurers’ performance, making it relevant to examine how CEO gender may influence stock price volatility.

Analyzing insurers’ behavior during extraordinary events such as Brexit or the COVID-19 pandemic helps assess their resilience to exogenous shocks. In times of crisis, insurers must manage rising claims and adapt strategies to volatile conditions. Understanding stock market volatility during such periods is key to evaluating their stability and governance. This analysis also offers insights into the potential impact of future shocks, such as the global tariff war initiated by the United States in March 2025.

Stock market volatility, defined as price variation over time (Schwert, 1989), is a key indicator of market risk. It helps investors assess a firm’s risk exposure and overall market uncertainty. High volatility often leads to portfolio adjustments, while low volatility signals stability (Koch et al., 2024). Beyond macroeconomic factors like GDP or interest rates, volatility is also shaped by firm-specific variables such as dividends, ROA, cash flow expectations, and board composition (Baker and Wurgler, 2006; González-Sánchez and Morales de Vega, 2018).

In the insurance sector, effective risk management is key to profitability (Lonare et al., 2024). The AIG case during the 2008 crisis illustrates how poor risk control can threaten solvency and trigger systemic effects (Harrington, 2009; Wang et al., 2019). Despite this, few studies examine the CEO’s gender in relation to risk and volatility. As Li and Cheng (2023) note, female leadership may be linked to greater financial prudence and lower insolvency risk, yet this remains underexplored in the European insurance context.

The limited number of studies focused on the relationship between gender and financial risk in the broader financial sector, particularly banking, suggests that female CEOs tend to adopt more conservative strategies, with lower risk exposure and better long-term outcomes. Furthermore, their presence in executive positions promotes greater diversity of perspectives, thereby strengthening corporate governance and decision-making processes (Palvia et al., 2020; Barman and Mahakud, 2024).

The second objective of this study is to analyze volatility behavior during crisis periods, such as Brexit and the COVID-19 pandemic, and assess whether the CEO’s gender moderates insurers’ ability to navigate these events. Although there are some studies on the impact of Brexit on insurers’ performance (Müller and Reuse, 2022) and market responses to COVID-19 (Pulawska, 2021), no research to date has examined the interaction between these exogenous shocks and female leadership.

In this context, the FIEGARCH-X model offers a valuable methodological tool for estimating volatility, accounting for long memory, persistence, and asymmetric responses to negative shocks. Its use in analyzing CEO gender and exogenous crises provides a novel lens for understanding gender diversity and corporate strength. This study contributes to that line of research by proposing an innovative approach to assessing the impact of CEO gender on stock volatility in European insurers.

The structure of this paper is as follows: the second section reviews the literature on the relationship between female leadership, business risk, and volatility, as well as the financial impact of the Brexit and COVID-19 crises. The third section presents research hypotheses and details the sample, variables, and methodology. The fourth section discusses the empirical results of the model. Finally, the main conclusions are presented, along with some implications for future research.

The relationship between the presence of women on corporate boards and firm risk can be explained through various business theories. First, the Upper Echelons Theory posits that a firm’s strategies and policies are shaped by the individual preferences of its top executives, which are influenced by their values, psychological traits, knowledge, and experience (Hambrick and Mason, 1984). As such, the characteristics of board members, including gender, are critical in decision-making processes, information acquisition, and contingency management, all of which collectively influence firm performance. This implies that the proportion of women on the board may influence risk control, given that women tend to be more prudent and risk-averse (Palvia et al., 2020).

According to Human Capital Theory (Becker, 1964), board diversity fosters varied perspectives that enhance firm performance in complex environments. Resource Dependence Theory (Pfeffer and Salancik, 1978) also suggests that diverse profiles attract broader resources and investor interest. Prior research shows that greater female representation in senior management improves performance, innovation, CSR, and reputation, while reducing market risk (Valls-Martínez and Soriano Román, 2022).

Empirical evidence on female CEOs and firm performance remains mixed. Morales de Vega et al. (2025) find that firms led by women show stronger market growth and financial results. Francoeur et al. (2008) report positive abnormal returns in complex environments, while Faccio et al. (2016) highlight lower earnings volatility and higher survival rates. Peni and Vähämaa (2010) note more conservative earnings management among female CEOs. In contrast, Wolfers (2006), analyzing S&P 500 firms, finds no systematic differences in stock returns between male- and female-led companies.

Recent literature underscores the role of regulatory frameworks and behavioral traits in shaping insurers’ risk profiles. EIOPA’s stress tests and Solvency II guidelines offer key insights into how insurers respond to adverse conditions (EIOPA, 2020). These mechanisms help explain volatility dynamics. Behavioral finance studies show that male executives tend to be more overconfident, leading to riskier decisions (Huang and Kisgen, 2013). Gender-based differences in leadership and risk preferences, as noted by Adams and Funk (2012), support the idea that female CEOs may enhance financial stability, especially during crises.

According to Corradi et al. (2013), return volatility is countercyclical, meaning it tends to be higher during economic recessions and lower during periods of economic expansion. This behavior is attributed to the asymmetric response of risk premium to changes in economic conditions. The insurance sector experiences cycles of “hard” and “soft” markets, often triggered by external shocks that lead to increased volatility. Following major events that result in large payouts, insurers may face reduced capital levels, limiting their ability to underwrite new policies even as insurance demand increases (Owadally et al., 2018).

Handling volatility during a crisis is crucial for insurers to maintain solvency, manage capital effectively, and capitalize on market opportunities (Upreti and Adams, 2015). According to Pulawska (2021), volatility in the insurance sector during the COVID-19 pandemic became particularly significant. The pandemic adversely affected the functioning of the European insurance sector, leading to a decrease in the average return on assets (ROA) and solvency ratios in several countries (EIOPA, 2020). The overall risk exposure of the insurance sector rose due to the pandemic’s impact on economic activity and financial markets, contributing to the volatility observed during this period.

In the context of Brexit, the uncertainty generated by the United Kingdom’s exit from the European Union intensified financial risks, prompting insurers to adjust their risk management strategies. Paterson et al. (2024) highlighted that the overlap of Brexit with the COVID-19 pandemic heightened systematic risk across various economic sectors, creating a highly volatile investment environment that undermined investor confidence and destabilized the British market. Other European countries also faced their own challenges regarding economic and financial stability (Li and Cheng, 2023).

Previous studies in behavioral economics have identified significant differences between men and women (Li and Cheng, 2023). First, women exhibit greater risk aversion compared to men, particularly in financial investment risk profiles (Croson and Gneezy, 2009). Second, women tend to be less confident and optimistic than men in specific contexts, such as managing finances. Third, women are more closely associated with adherence to business ethics, as well as financial, accounting, and tax regulations (Barber and Odean, 2001).

For all these reasons, female executives, including CEOs, tend to exhibit greater risk aversion than their male counterparts (Faccio et al., 2016). This tendency can influence corporate decision-making, particularly in investment strategies and project management, by prioritizing financial stability and prudent decision-making. Female CEOs are less likely to commit to high-risk projects and more inclined to terminate underperforming initiatives early (Li and Cheng, 2023). These tendencies can translate into better business outcomes, lower leverage (Faccio et al., 2016) and reduced insolvency risk (Li and Cheng, 2023).

In exploring the link between CEO gender and stock price volatility, Li and Cheng (2023) found that companies with female CFOs tended to experience stock price declines compared to male-led firms. Additionally, Qayyum et al. (2021), analyzing a sample of U.S. public firms between 2006 and 2016, showed that companies led by female CEOs tend to experience lower stock price volatility than those led by men.

Accordingly, the first hypothesis is proposed:

According to Danielsson et al. (2018), rising market volatility is a strong signal of potential economic crises. Baker et al. (2019) and Gulen and Ion (2016) link high volatility to political uncertainty, which reduces investment and employment. Mele (2007) describe volatility’s countercyclical nature, rising in downturns and falling in expansions, driven by asymmetric risk premiums (Fama and French, 1989). During recessions, investors become more risk-averse and sensitive to changes in expected cash flows and dividends.

Khan et al. (2023) examined how the COVID-19 crisis influenced asymmetric volatility in financial markets, finding that volatility reacts more strongly to negative news. Similarly, Chowdhury et al. (2022) reported that U.S. markets during the pandemic responded sharply to adverse events like rising case numbers, triggering stock declines and increased uncertainty. This heightened sensitivity was linked to a long-term relationship between COVID-19 variables, economic policy uncertainty, and market volatility, suggesting that persistent negative news continued to influence investor behavior.

Brexit generated substantial uncertainty in UK and global markets, adversely affecting investment decisions. Ben Ameur and Louhichi (2022) reported a marked rise in volatility and spillover effects during 2015–2016, peaking around the referendum. Koch et al. (2024) noted another volatility spike following the activation of Article 50 in 2017. These episodes were driven by the interaction between news sentiments and market reactions, with investors responding strongly to Brexit-related developments. Hassan et al. (2024) found that “BrexitRisk” was negatively correlated with stock returns post-referendum, as firms most exposed to Brexit uncertainty experienced lower returns.

The impact of COVID-19 on UK firm volatility exceeded that of Brexit due to its global and health-related nature, which heightened market uncertainty. Elsayed and AbdElrhim (2021) found that markets reacted more strongly to COVID-19 fatalities, negatively affecting 24 of 30 sectors. Analyses of abnormal and cumulative abnormal returns showed that UK sectoral indices had favorable ARs before Brexit, suggesting market adaptation to political uncertainty and regulatory changes. In contrast, the pandemic triggered swift, widespread losses. Paterson et al. (2024) emphasize that unlike Brexit’s focus on trade, COVID-19 disrupted global supply chains, consumption, and labor markets, creating deeper and more varied uncertainty.

The relationship between CEO gender and stock price volatility during crises such as COVID-19 and Brexit reveals that companies led by female CEOs tend to experience lower stock price volatility. Faccio et al. (2016) argue that firms with female CEOs typically face lower insolvency risk and less volatility due to their more cautious and conservative risk management approach, which results in safer investment decisions and lower leverage, helping to mitigate shocks and performance fluctuations. Similarly, Li and Cheng (2023), analyzing a large sample of U.S. insurers between 2001 and 2017, found that female CEOs bring diverse perspectives and balanced decision-making, which helps avoid extreme outcomes.

Specifically, Thornton and Vasilakis (2024) found that during the COVID-19 pandemic, firms led by women achieved better financial results and increased firm value. Their analysis of 410 U.S. companies between 2019 and 2021 concluded that women-led firms were more profitable, better valued, and more risk-averse than those led by men during the crisis. Similar findings were reported in Germany (Sinha, 2023), where female-led companies outperformed male-led ones in both profitability and risk management in the pandemic year.

In this regard, the second and third hypotheses are as follows:

The sample focuses on analyzing European insurers listed in the EUROSTOXX 600 as of September 2024. The sample period spans from January 2013 to September 2024 (the sample period starts in 2013, when Bloomberg started reporting gender diversity data) and is based on daily data, resulting in 3,407 observations per insurer. All data, including both financial and gender diversity information, were obtained from the Bloomberg platform. Bloomberg has been chosen as the most suitable source of information for several reasons. Firstly, due to the variety of daily financial data it offers. Secondly, because it also provides ESG data, both collected from other sources and created by the Bloomberg platform itself.

The sample comprises insurers from two countries: the United Kingdom and Switzerland. These two countries were selected because they are the only ones in which, at some point during the analyzed period, the CEO or equivalent position was held by a woman. To enhance the robustness of the results, the analysis not only compares the volatility behavior of each firm according to whether the CEO was a man or a woman but also includes a comparison with the remaining insurers from the EUROSTOXX 600 in these countries where the CEO was always a man.

Based on this information, the final sample includes 12 insurance companies ^[1] (7 from the United Kingdom: Phoenix Group Holings, Admiral Group, Hiscox, Direct Line, Aviva, Legal and General Group and Prudential; and 5 from Switzerland: Baloise Holding, Swiss Life Holding, Swiss Re, Zurich Insurance Group and Helvetia Holding), of which only 3 in the UK and 1 in Switzerland had a female CEO during the sample period. The sample size could not be expanded, as there are no additional European countries in the EUROSTOXX 600 with insurers that have had a female CEO or equivalent. The comparison between insurers within the same country ensures that the conditions under which insurance companies operate are more homogeneous.

The Bloomberg platform provides a total of 36 indicators related to gender diversity. However, for the purposes of this study, only the indicator “women as chairperson or equivalent BESG (Bloomberg Environmental, Social and Governance)” will be considered.

The daily closing stock prices of the insurers (Y_t) are non-stationary in both mean and variance. They are non-stationary in mean due to the presence of upward or downward trends depending on the sample period. Likewise, they are non-stationary in variance due to the varying dispersion of prices around the mean. For this reason, the analysis will be conducted using the first regular difference of prices over consecutive time periods in percentage terms, namely, the returns on insurers’ stock prices.

The returns of insurers’ stock prices (R_t = DLY_t) are characterized by a constant mean and volatility clustering (see Figure 1), as there are periods of heightened volatility alternating with others of lower volatility. The presence of these clusters highlights the need to apply volatility models capable of capturing this behavior, such as the FIEGARCH-X model, which is presented in the following section.

To analyze the dynamics of price volatility, in addition to returns, other variables will be included in the volatility equation. These variables are CEO_W, COVID-19 and Brexit.

Ceo_W represents the estimated probability of a woman being appointed as CEO based on explanatory variables reflecting insurers' characteristics. It is calculated using a logit model exclusively for the four companies (Admiral Group, Direct Line, Aviva and Swiss RE), which have had a female CEO at some point during the sample period analyzed. The purpose of this variable is to mitigate potential endogeneity between CEO appointments and firm performance or risk profile. In this sense, this variable is related to the appointment of a female CEO that is not directly correlated with volatility.

To test whether there are significant differences during crisis periods compared to the rest of the sample, two additional dummy variables have been created: COVID-19, which takes the value 1 in the year 2020, 2021 and 2022 and 0 otherwise. Brexit, which takes the value 1 from 2020 onwards and 0 in the preceding years.

The analysis of stock price volatility dynamics, both in general and specifically for insurers, is highly relevant, as it provides insights into the frequency and intensity of fluctuations in stock prices. This allows for risk assessment, since a highly volatile asset may attract investors seeking higher returns while assuming greater risk. Conversely, lower volatility may be more appealing to more conservative investors. In this regard, accurate modeling of volatility is essential for insurers to effectively manage risks, make informed decisions, and conduct strategic planning in a dynamic business environment.

There are numerous conditional heteroskedasticity models that can be used to model volatility. In the case of insurers, a FIEGARCH model will be used for several reasons. First, by incorporating fractional integration, this model captures the long memory of volatility, enabling a better representation of the persistence of shocks over time (Bentes, 2016). Another advantage of the FIEGARCH model is its ability to model non-stationary time series and its greater flexibility in describing volatility structures, making it particularly useful for financial analysis. Moreover, unlike other GARCH-type models, it captures the leverage effect or the asymmetric response of volatility, especially important in forecasting and risk management (González-Pla and Lovreta, 2022). This feature is highly relevant, as in financial markets, bad news typically increases volatility more than good news (Corradi et al., 2013; Mele, 2007). Although this phenomenon has been previously studied across different sectors, it has not yet been addressed in the insurance sector, thus representing a contribution to the literature while offering more accurate and robust volatility estimates in this context.

Another contribution of this study lies in determining whether volatility in European insurers differs depending on whether the CEO is a man or a woman. This variable is estimated to be using a logit model according to the company characteristics. The purpose of this variable is to evaluate the impact of gender on volatility, which may be relevant for investment and risk management decisions. Additionally, these differences are analyzed during two recent crises: the COVID-19 pandemic and Brexit. The financial crisis was excluded from the analysis because no women held CEO positions during that period. To determine whether significant differences exist, three dummy variables were incorporated into the variance equation of the FIEGARCH model, resulting in a FIEGARCH-X model. The first dummy variable is used to determine whether there are significant differences in volatility depending on the CEO’s gender. The second captures potential effects during the first year of the COVID-19 pandemic, and the third addresses the Brexit period. This approach aims to enhance the model’s accuracy and provide more robust estimates.

In specifying a FIEGARCH-X(1,d,1) model, it is essential to consider the following key equations, which allow for capturing long memory and asymmetry in volatility (Bollerslev and Mikkelsen, 1996):

1. The mean equation:

where: R_t represents the returns of each insurer at time t, calculated as the first difference of the logarithm of prices between two consecutive market days in percentage terms; μ is the constant of the mean equation and ε_t is the error term.

1. The error equation:

where: σ_t is the volatility at time t and z_t is the error term, which we assume to be white noise with a normal distribution.

1. The volatility equation:

Being: g $(zt−1)=ϕ(|zt−1σt−1|−E|zt−1σt−1|)$ + γ $zt−1σt−1$⁠;

where: $ϖ,α0,α1,α2,α3,β,$ ϕ y γ are the parameters of the model; $d$ is the integration factor; COVID-19 is a dummy variable created to observe the possible effect that the health crisis caused by COVID-19 may have had on volatility. Brexit is a dummy variable to capture the effect it has had on volatility since it came into force in 2020. CEO_W is a variable that captures the probability of a woman being appointed CEO of the insurers. This probability has been estimated using a logit model based on firm specific information obtained from Bloomberg, such as, profitability (ROA), firm size measured by total assets (Assets), risk (Leverage), board composition through the percentage of women on the board (% Board Women), and the assessment of gender diversity on boards (Board Gender Diversity).

First, a logit model was estimated to assess the probability that a woman is appointed CEO of an insurance company based on firm specific characteristics. The results for the four insurers in which a woman served as CEO at some point during the sample period are presented in Table 1.

The goodness of fit of the estimated models indicates that they classify appropriately, as the accuracy is high (the lowest value is 85.9%), and the Nagelkerke R² is above 0.8 in all cases. The results show that the variables with the greatest influence on the probability of a female CEO appointment are the insurer’s total assets and the percentage of women on the board.

Second, in order to determine if there are differences in the volatility behavior of European insurance companies in the EUROSTOXX 600 from the United Kingdom and Switzerland, as well as the impact of having a female CEO during certain periods, a FIEGARCH-X(1,d,1) model will be estimated. The results of the estimated model for the insurers from these two countries can be seen in Tables 2 and 3, respectively.

Based on the results obtained from the FIEGARCH(1,d,1) model, it is observed that the impact of the constant in the mean equation is generally greater for Swiss insurers than for those in the UK. In all Swiss insurers, the constant in the mean equation (μ) is positive, statistically significant, and small in magnitude, close to zero, whereas for UK insurers it is only significant in the case of Admiral Group. However, the opposite occurs with the constant in the variance equation (ϖ): for all UK insurers, it is positive and statistically significant, while for Swiss insurers it is only significant for Swiss Life Holding and Boloise Holding. Furthermore, the estimated values are smaller in Swiss firms compared to those in the UK, implying that a substantial constant impact contributes to explaining volatility variability in UK insurers.

The parameter α₀, which reflects how past errors influence current volatility, is not significant for the insurers analyzed, except for Prudential (UK) and Swiss Life Holding (Switzerland). Regarding the parameter β, which captures volatility inertia, that is, the influence of past volatility on current volatility, it is statistically significant for all Swiss insurers and for most UK insurers, except Admiral Group and Direct Line Insurance Group. This parameter is positive and close to 1 in most cases, indicating that current volatility in UK and Swiss insurers is strongly affected by past volatility. In other words, volatility is highly persistent: when high in one period, it tends to remain high in the next; when low, it tends to remain low. Additionally, for UK firms, this persistence is lower in companies that, at some point in time, were led by a female CEO (Admiral Group, Direct Line Insurance Group, and Aviva).

To understand the long memory of volatility in UK and Swiss insurers included in the EUROSTOXX 600, it is essential to examine the estimated value of the d parameter. This value is significant for all insurers except for Helvetia Holding (Switzerland), indicating the presence of long memory in volatility, meaning that the effects of volatility shocks persist over a prolonged period. This implies that volatility is not only influenced by recent shocks, but also by those that occurred in the more distant past, highlighting the relevance of using the FIEGARCH-X model. Furthermore, for all Swiss insurers (except for Swiss RE and Helvetia holding which is slightly above 0.5), the d value falls within the range 0<d<0.50, indicating that volatility is long-memory and stationery. Thus, the effects of volatility shocks are persistent but may eventually dissipate. The same applies to UK insurers, except for Direct Line, Aviva and Prudential, where d is slightly above 0.5, suggesting that past volatility has a stronger influence on current volatility due to more persistent shocks.

With respect to the leverage effect or asymmetric volatility response (γ), this parameter is negative and significant for all Swiss insurers and for most UK insurers, except Direct Line Insurance Group. Although there are no major differences in asymmetric volatility behavior between the two countries, the leverage effect tends to be smaller in insurers that were led by a woman at some point during the sample period. Moreover, volatility tends to increase with larger market shocks, as the parameter ϕ is positive and significant in all firms except Admiral Group.

According to the results, periods characterized by a higher likelihood of female CEO appointments exhibit significantly lower levels of volatility. Although the parameter α₁ is not statistically significant, it is negative for the UK firms (Admiral Group, Direct Line Insurance Group, and Aviva) and for the Swiss firm Swiss Re. This suggests that Hypothesis 1 cannot be confirmed, as volatility did decline under female leadership, but the differences between UK and Swiss companies are not statistically significant. If significant, the estimated values would indicate that average volatility in the UK insurers may have declined between −0.18 and −0.72 points during periods characterized by a high probability of female CEO appointments, compared to the rest of the sample period. In Swiss Re, the estimated decline would be around 0.58 points. This may be since female CEOs adopt more conservative, informed, and risk-averse strategic decisions or that investors and the market perceive female-led firms as more stable, thus contributing to lower volatility.

Regarding volatility behavior during the COVID-19 health crisis, volatility increased across all firms. As shown in Figure 3, which presents estimated volatilities under the FIEGARCH(1,d,1) model, volatility in some firms even tripled, or more, in companies such as Hiscox, Legal and General Group, Prudential (UK), and Helvetia Holding (Switzerland). Several general factors may explain this surge in volatility: the pandemic affected all sectors and generated widespread uncertainty about the global economic future, leading to changes in investment and consumption decisions. Additionally, travel and trade restrictions disrupted imports and exports, creating instability in financial markets. In the case of insurers, factors such as increased claims (especially in life and health insurance) due to rising illness and mortality rates also contributed to volatility. Moreover, lockdowns and restrictions challenged business continuity, complicated customer service and risk management. In fact, containment measures and reduced economic activity temporarily altered loss patterns across several lines of insurance.

Brexit, however, did not contribute uniformly to increased volatility among insurers. As shown in Tables 2 and 3, the estimated α₃ parameter is positive but not statistically significant for all firms. It is significant in the cases of Hiscox and Direct Line Insurance Group (UK) and Swiss Re and Helvetia Holding (Switzerland), where volatility increased by approximately, 13% and 29% respectively, relative to the average for the rest of the period (ceteris paribus). This suggests that Brexit did not cause a significant effect on volatility for most firms. Nevertheless, comparing both crises shows that in all firms the impact of COVID-19 was greater than that of Brexit, which supports Hypothesis 2.

Generally speaking, the estimated parameter values for Swiss insurers are lower than those for UK insurers. This may be explained, in part, by the fact that, as non-EU members, Swiss insurers have less direct exposure to regulatory and economic changes affecting UK insurers. In addition, Switzerland is known for its political and economic stability, which may provide a more predictable and less volatile environment. Moreover, Swiss insurers tend to be more geographically diversified, which helps mitigate risks associated with Brexit-related uncertainty.

Thus, according to the results obtained, a relevant finding is that insurers led by a female CEO during the COVID-19 or Brexit crises show slightly lower parameter values related to these events compared to insurers led by male CEOs. This supports Hypothesis 3, suggesting that female CEOs have a moderating effect on volatility by reducing the impact of crisis events. Figure 2 presents the interrelations among the hypotheses proposed and tested.

Finally, Figure 3 illustrates the differences in volatility behavior across the various periods analyzed. As previously mentioned, one of the key moments in which a substantial increase in volatility occurred was during the COVID-19 crisis, an effect further intensified by Brexit. The rise in volatility resulting from COVID-19 and Brexit led to the implementation of measures aimed at mitigating the increase in uncertainty in the insurance sector, uncertainty that hampers decision-making not only for companies but also for investors, as stock price declines negatively impacted their wealth. Moreover, this surge in volatility has heightened the perceived market risk, potentially resulting in higher risk premiums for policyholders.

This innovative analysis of the insurance sector in countries where, at some point in time, the CEO or equivalent has been a woman suggests that female leadership may help mitigate the negative impact of crises. It may also assist in better risk assessment and support informed strategic decisions that protect both the company and its clients.

In the insurance sector, operating in a volatile environment requires the ability to adapt swiftly and seize emerging opportunities that provide a significant competitive advantage, while maintaining solvency and financial stability through sound investment strategies. Analyzing volatility dynamics enables insurers to tailor their products and marketing strategies in response to evolving market needs.

The main objective of this study was to analyze the behavior of stock price volatility in the European insurance sector based on the gender of the person holding the CEO position, with a particular focus on the role of women in top executive roles during exceptional events such as Brexit and the COVID-19 pandemic. To this end, a FIEGARCH-X(1,d,1) model was estimated, which allows for the capture not only of long memory and volatility persistence but also of the asymmetric response to adverse events. This methodology was applied to a sample of 12 insurance companies from the United Kingdom and Switzerland, two European countries that are not members of the European Union, listed in the EUROSTOXX 600 between 2013 and 2024, selected on the basis that they had, at some point, a female CEO or equivalent.

The empirical results indicate, first, that in the periods during which insurers were led by a female CEO, stock price volatility tended to decrease. However, this finding is not statistically significant, likely due to the limited number of female CEOs in European insurers, thus only partially confirming Hypothesis 1.

Second, in relation to Hypothesis 2, the impact of the COVID-19 crisis on volatility was significantly greater than that of Brexit. The analysis reveals that during 2020, marked by the global health emergency, all insurers in the sample experienced substantial increases in volatility, in some cases even tripling. In contrast, while Brexit also led to an increase in volatility, it was more limited and concentrated in specific insurers such as Hiscox, Direct Line Insurance Group, Helvetia Holding and Swiss Re.

Regarding the interaction between volatility and female CEOs during the COVID-19 and Brexit periods, the findings confirm that CEO gender exerts a moderating effect on volatility behavior. This dampening effect confirms Hypothesis 3, likely due to more cautious management practices and strengthened market confidence. Lower volatility is critical for insurers, as it enhances financial stability and allows firms to maintain a solid foundation for fulfilling long-term obligations. Moreover, it reduces the risk of substantial losses during periods of heightened market volatility, safeguarding company assets and ensuring solvency. This stability also attracts risk-averse investors seeking safety and consistency, improving the company’s market reputation and enhancing its ability to raise capital. While less volatile stocks may not offer high returns, they tend to provide more stable and predictable performance over time.

This study contributes to literature on several levels. First, it offers novel empirical evidence on a sector that has been underexplored from the perspective of gender leadership, namely, the European insurance industry. Second, it provides a robust and replicable methodology to estimate the impact of CEO gender on stock market volatility in complex environments. Lastly, it emphasizes the importance of continuing to explore the relationship between gender diversity and corporate resilience, especially in sectors where risk management is a core function.

Despite the limited literature on insurance companies, this study highlights the critical role of the insurance sector in economic stability and financial protection. It provides a safety net that enables individuals and firms to manage risk and plan for the long term with confidence. Additionally, it promotes saving and investment by offering products that help people plan for retirement and manage their finances effectively. By facilitating entrepreneurship and innovation, insurers contribute to economic development by allowing firms to operate with greater security and take calculated risks. In times of crisis, insurers offer crucial financial support, helping to mitigate economic damage and support recovery.

Therefore, the findings of this study may be useful not only for decision-makers within insurance companies but also for institutional investors, regulators, and financial analysts. Promoting gender diversity in corporate governance and executive leadership is not only ethically and reputationally valuable but may also translate into lower risk exposure and improved crisis response, a particularly relevant factor in today’s environment of heightened economic and financial uncertainty.

The study also underscores the need for continued research into the role of female leadership in ensuring the financial stability of insurance companies, especially in times of crisis. A particularly relevant line of future research would be to analyze the impact of new global economic disruptions, such as the trade war initiated by the United States in March 2025. This emerging conflict, ongoing at the time of writing, threatens to disrupt international capital flows, increase political uncertainty, and have significant effects on strategic sectors such as finance, and insurance in particular. Evaluating how insurers respond to this new source of instability will enhance our understanding of the role of leadership diversity in complex scenarios and in the proactive management of corporate risk.

This study is subject to several limitations. Firstly, the sample size, while encompassing a range of European insurance companies, may not fully represent the entire sector, particularly smaller firms or those outside the EUROSTOXX 600 index. Additionally, not all European insurance companies listed on the EUROSTOXX 600 report all the information analyzed in this study to Bloomberg. This has forced us to analyze only the ones which had a female CEO at some point during the period. It should be emphasized that this limitation does not invalidate the results obtained in the study. In future studies another sector or geographical area will be analyzed to check if this situation changes.

Future research could explore other financial or non-financial sectors to gain a broader understanding of how diversity impacts performance. This approach can help identify sector-specific and cultural factors that enhance or hinder the benefits of diversity, leading to more tailored and effective diversity policies and practices.

We are grateful for the comments made by Irma Martínez-García, Ph.D., in her role as discussant at both the 5th Boca-ECGI Corporate Finance and Governance Conference and the XIII Iberoamerican Academy of Management Conference. We also gratefully acknowledge the financial support provided by the Cátedra Universidad San Pablo CEU–Mutua Madrileña and the Cátedra USPCEU–MOEVE.