Analyzing the Financial Performance of a Major Holding Company in Hong Kong SAR during the 2008-09 Global Financial Crisis and COVID-19 Period: A Comparative Study

Samson Poon

Chinese International School, Hong Kong SAR, China.

DOI: 10.4236/ib.2025.173009                

Abstract

This paper investigates the financial impacts of the Global Financial Crisis and the 2008 Financial Crisis on firm level financial performance in Hong Kong SAR using regression analysis and two sample t-tests. This study focuses on key financial indicators such as dividend (in $1000s HKD), net gearing, current ratio, net profit (in $1000s HKD), Return on Equity (ROE), EBITDA, net profit margin, earnings per share (EPS), and revenue (in $1000s HKD). The results show that the COVID-19 pandemic had more pronounced and statistically significant effects on firm level metrics compared to the 2008 financial crisis. Notably, during COVID-19, firms experienced a significant decline in profitability metrics such as ROE, EBITDA, EPS, and net profit, while showing an increase in dividend payout and revenue. Conversely, the financial crisis demonstrated limited statistically significant impacts, with only net gearing being the only figure being affected significantly during this period. These findings provide insight to policy-makers and investors, creating a nuanced analysis into the asymmetric effect of different shocks on company performance.

Keywords

COVID-19, Global Financial Crisis, Financial Performance, Regression Analysis, T-Test

1. Introduction

In recent years, the global economy has faced two major challenges: the 2008-09 Global Financial Crisis and the COVID-19 pandemic. These events had serious effects on businesses across global industries, including Hong Kong SAR. Understanding how companies perform during such crises is important for investors, managers, and policymakers. This paper looks at how the financial performance of a major holding company in Hong Kong SAR, Great Eagle Holdings Limited, was affected during both the crisis and pandemic, and illustrates how they continue to navigate a challenging environment, striking a balance between recovery and enduring issues, including high inflation, rising interest rates, and geopolitical unpredictability.

Great Eagle is a large and well-known company, providing a good example of how companies in the vast economy were affected by these global crises. Listed on the Hong Kong Stock Exchange in 1972, The Great Eagle Company, Limited was the holding company that the Group was established with in 1963 by the late Mr. Lo Ying Shek. Upon reorganization in 1990, the Group became known as Great Eagle Holdings Limited as a Bermuda-registered company.

Their total asset value is spectacular; of which, the most notable point is their owning of Langham hotels. In the hotel business, they own thirty-one properties with over eleven thousand rooms, meaning the Group’s international hotel portfolio is vast. Twenty-six of these properties are luxury hotels branded as The Langham or Cordis. In the fiscal year of 2024, the Group’s core profit after tax was around 1553 million Hong Kong dollars, and as of 31 December 2024, the net asset value (using the portion of net assets of Champion REIT and LHI) was about 63.03 billion Hong Kong dollars.

The research, combining regression analyses and t-tests, shows that an array of business financial variables was significantly impacted by the COVID-19 epidemic. Along with a minor improvement in the current ratio, which suggests improved short-term liquidity, there was a noticeable rise in revenue and dividends during the epidemic. Nonetheless, there were statistically significant drops in key profitability metrics like net profit, return on equity (ROE), EBITDA, net profit margin, and earnings per share (EPS), indicating that businesses had a difficult time sustaining profitability and operational effectiveness during this time. The 2008 financial crisis, on the other hand, had a less financial impact on businesses. Except for net gearing, which decreased during the crisis, indicating a decreased reliance on debt financing, the majority of financial metrics did not exhibit statistically significant changes. In the end, COVID-19 is shown as the more significant crisis that caused financial performance hindrance compared to the 2008 Global Financial Crisis, particularly in terms of profitability and financial ratios.

There are very few papers that take into account the effects of both COVID and the Global Financial Crisis. Additionally, many studies analyze the financial performances of publicly listed trading companies or financial companies, whereas this paper analyzes a holdings company, demonstrating the effects of global crises on the real economy. Under this holdings company in Hong Kong SAR, their portfolio encompasses global hotel chains, Langham; major F&B companies, Imperial Patisserie; home appliances, Top Tech; and more. Additionally, this paper uses the most updated data sets from a company, using essentially the latest available data.

After sustained growth, the Global Financial Crisis impacted the company’s hotel business significantly by late 2008, causing reduced demand and lower revenues. Hotel division revenue and EBITDA fell due to rebranding costs and weaker overall performance. Several planned hotel projects were delayed or halted due to market conditions. Net debt also surged HK$1033 million by year-end 2008, reversing a net cash position earlier in the year.

Despite these challenges, core profit rose 28.3% to HK$1150 million, driven mainly by increased investment income from Champion REIT and lower financial expenses. However, the outlook remained cautious amid limited visibility on the global downturn’s duration and severity.

In 2021, the COVID-19 pandemic and border closures continued to adversely affect the Group’s businesses. Operations of overseas hotels remained significantly hindered, though gradual relaxation of travel restrictions and efficient cost controls improved hotel performance compared to the previous year.

Nevertheless, the company’s strong year-end cash position and limited capital expenditure commitments provided protection against ongoing economic uncertainty. Demonstrating resilience through various economic ups and downs, Great Eagle Holdings Limited’s financial data provides valuable insights into the asymmetric effects of different worldwide economic shocks on company. Therefore, Great Eagle is undoubtedly a strong representative sample to investigate the financial impacts of the 2008 Global Financial Crisis and the COVID-19 pandemic on financial performance in Hong Kong SAR (Great Eagle Holdings Limited, 2025).

This paper proceeds as follows. Section 2 provides background information on the existing literature; Section 3 highlights the empirical findings; and Section 4 concludes the paper.

2. Literature Review

Table 1 presents a comprehensive literature review table, which will be summarized in the following section.

Various methodologies have been used to investigate the effects of the COVID-19 pandemic and the Global Financial Crisis on the financial performance of individual companies or groups of companies globally, such as Ordinary Least Squares (OLS) Regression (Achim et al., 2022; Shaharuddin et al., 2021; Nguyen et al., 2023; Khatib & Nour, 2021; Rababah et al., 2020; Golubeva, 2021), ANOVA and a Tukey test (Folger-Laronde et al., 2022), Non-Parametric Methodology (Nguyen, 2022), Panel Regression (Erdem, 2020; Kaakeh & Gokmenoglu, 2022), Differences in Differences Methodology (Zhang & Zheng, 2022; Jiang et al., 2021), Generalized Method of Moments (GMM) Methodology (Duguleană et al., 2024), Wilcoxon Signed Ranks Test (Qadri et al., 2023), and the Event Study Method (Abbas & Nainggolan, 2022). This study examines how COVID-19 and the Global Financial Crisis affected Hong Kong’s major holding companies’ financial performance using regression models and line graphs.

Table 1. Comprehensive literature summary.

Authors	Year	Country/Region	Variables	Main Findings (very concise)	Method	Dataset Period
Achim et al.	2022	Romania	ROE, ROA, Assets, Liquidity, Debt Ratios	Equity, liquidity, and size enhanced resilience; services hit hardest.	OLS	2019-2020
Shaharuddin et al.	2021	Malaysia	ROA, ROE, Leverage, Liquidity, CFO, Size	Liquidity and cash flows improved performance; leverage insignificant.	Multiple Regression	Q1 - Q2 2020
Nguyen et al.	2023	Vietnam	Z-score, Cash Holding, Size, Sales Growth	Higher cash reserves boosted stability, especially for larger firms.	OLS	2011 Q1 - 2020 Q3
Khatib and Nour	2021	Malaysia	ROA, ROE, EBIT, Governance, Leverage, Liquidity	Gender diversity helped; frequent board meetings hurt performance.	OLS	2019-2020
Rababah et al.	2020	China	ROA, Size, Leverage, Growth, Revenue	COVID-19 significantly impacted firms; preparedness essential.	OLS	2014-2020
Nguyen	2022	Vietnam	ROA, RTO, Current Ratio, Leverage	Logistics firms’ financial performance declined despite e-commerce growth.	Nonparametric	2019-2020
Folger-Laronde et al.	2022	Canada	Returns, Eco-Fund Ratings	Sustainability alone didn’t ensure financial resilience.	ANOVA, Tukey test	2019-2020
Golubeva	2021	Global	Firm impact, Sector, Size, Equity, Loans, Governance	Targeted sector support and governance reassessment needed.	OLS	May-July 2020
Erdem	2020	Global	Stock Returns, COVID-19 Data, Freedom Level	Freer countries faced milder stock market impacts.	Panel Regression	Jan-Apr 2020
Kaakeh and Gokmenoglu	2022	China	ROA, Environmental Scores, Size, Macro Indicators	Better environmental performance boosted financial results.	Panel Data	2017-2020
Qadri et al.	2023	South Asia	ROA, ROE, EPS, Asset & Debt Ratios	Banking sector declined during COVID-19; recovered with adaptation.	Wilcoxon Signed Ranks	2016-2021
Fu and Shen	2020	China	NROA, Size, Leverage, Growth	Energy firms negatively impacted; goodwill impairment increased risks.	Regression	2014-2020
Zhang and Zheng	2022	China	Tobin’s Q, Size, Leverage, Equity Share	Lockdowns and supply disruptions reduced profits.	Fixed Effect, Diff-in-Diff	2019 Q1 - 2021 Q2
Abbas and Nainggolan	2022	ASEAN	CAR, OCF, Assets, Liquidity, Debt	Liquidity and solvency mitigated negative market reactions.	Event Study	Jul 2019 - Mar 2020
Sun and Li	2021	China	ROA, ROE, Asset Turnover, Governance	Governance and state ownership mitigated efficiency losses.	OLS, Correlation	Q2 2019 - Q2 2020
Duguleană et al.	2024	Romania	ROA, Leverage, Size, Profit Margin	E-commerce firms thrived financially during COVID-19.	GMM	2005-2020
Jiang et al.	2021	China	Investment, Size, Cash Flow, Governance, SOE	COVID-19 reduced investment; cash flexibility improved resilience.	Propensity Score, Diff-in-Diff	Q4 2019 - Q1 2020
Makni	2022	Saudi Arabia	Profit, Investment, Revenue, Size, Cash Flow	Tourism and transport sectors severely impacted; quick recovery signs.	Regression	2009-2019
Hu and Zhang	2022	Global	COVID-19 Cases, ROA, Governance	Strong institutions and healthcare systems mitigated impacts.	Regression	Q1-Q3 2020
Boshnak et al.	2023	Saudi Arabia	ROA, ROE, Governance, Size, Leverage	Smaller boards, diversity, and lower leverage improved resilience.	Random Effects, OLS	2019-2020
Ahmad et al.	2022	Asia	ROA, Tobin’s Q, Working Capital Management	Firms adopted conservative working capital policies amid crises.	GMM, Correlation	2004-2020
Neacșu and Georgescu	2024	Bucharest	ROA, ROE, Leverage, Size	Larger firms and debt management aided resilience.	Panel Fixed Effect	2005-2022
Lee et al.	2024	US	ROA, Tobin’s Q, Leverage, Franchising, Cash	Hospitality firms benefited from franchising and cash holdings.	Panel Regression	2008 Q1 - 2009 Q2; 2020 Q1-Q4
Batrancea	2021	US	Profit Margins, Liquidity, Debt-to-Equity	Financial management key to resilience during crises.	Panel Data	2007 Q1 - 2020 Q3
Läger et al.	2025	Global	ROA, Tobin’s Q, Carbon Emissions	Lower carbon emissions improved financial performance during COVID-19.	Fixed-effects Regression	2007-2021
Fracasso and Jiang	2021	China	Firm Growth, Governance, Export, CEO status	Smaller, productive, well-governed firms performed better.	Cross-sectional, Fixed Effects	2007-2009
Kudlyak and Sánchez	2017	USA	Sales, Debt, Size, Leverage	Large firms suffered greater declines in 2007-09 crisis.	Fixed Effects, Diff-in-Diff	1958-2014 (focus 2007-09)

Return on Assets (ROA) (Kaakeh & Gokmenoglu, 2022; Qadri et al., 2023; Fu & Shen, 2020; Sun & Li, 2021) and Return on Equity (ROE) (Khatib & Nour, 2021; Jiang et al., 2021; Boshnak et al., 2023) are two important financial performance indicators often used in academic literature. ROA assesses a firm’s profitability relative to its total assets, while ROE evaluates a company’s ability to generate profit for its shareholders. Leverage (LEV) is a financial risk indicator that quantifies the proportion of a company’s financing derived from debt (Shaharuddin et al., 2021; Fu & Shen, 2020; Hu & Zhang, 2022).

The current ratio (Nguyen, 2022; Abbas & Nainggolan, 2022), quick ratio, and cash ratio (Achim et al., 2022) are important liquidity metrics because they indicate how effectively a company can meet its short-term debt obligations. Additionally, firm size, generally measured as the logarithm of total assets (Shaharuddin et al., 2021; Nguyen et al., 2023; Fu & Shen, 2020; Rababah et al., 2020; Golubeva, 2021; Boshnak et al., 2023; Jie et al., 2021; Hu & Zhang, 2022), revenue growth rate (Makni, 2022; Nguyen et al., 2023; Rababah et al., 2020) and sales growth (Nguyen et al., 2023) are commonly included to capture the growth potential of firms.

Other notable variables include Tobin’s Q (Jiang et al., 2021; Boshnak et al., 2023), which links market valuation to a firm’s replacement cost, and Cash Flow (CFO) (Shaharuddin et al., 2021; Abbas & Nainggolan, 2022; Hu & Zhang, 2022). These indicators, along with governance-related variables like Board Size, Board Independence, and Audit Committee Characteristics (Khatib & Nour, 2021; Boshnak et al., 2023), provide a comprehensive view of a firm’s financial performance, risk profile, and governance structure, making them pivotal in analyzing corporate outcomes.

The studies reviewed span a wide range of geographical regions and levels of development. Of which, they have been separated and grouped into developing, developed, low income (LIC), middle income (MIC), low-middle income (LMIC), and high-income countries (HIC) or regions.

Numerous studies are undertaken in developing countries. Research conducted in Malaysia (Khatib & Nour, 2021; Shaharuddin et al., 2021), Vietnam (Nguyen et al., 2023; Nguyen, 2022), and China (Kaakeh & Gokmenoglu, 2022; Fu & Shen, 2020; Sun & Li, 2021) predominantly focusses on middle-income nations, classified by the World Bank as upper-middle-income economies (UMICs). In contrast, research from high-income countries (HICs), such as Canada (Folger-Laronde et al., 2022) and Saudi Arabia (Makni, 2022; Boshnak et al., 2023), often employs advanced metrics like Tobin’s Q, board governance variables, and environmental indicators, which signify the more sophisticated financial markets and developed regulatory frameworks in these affluent areas. Research focussing on global contexts (Golubeva, 2021; Hu & Zhang, 2022) provides an extensive perspective, often analysing cross-country comparisons or global trends, encompassing the impacts of COVID-19, political stability, and regulatory quality. Regionally, Asia constitutes the majority of the literature, predominantly originating from East Asia, particularly China, as well as Southeast Asia, including Malaysia and Vietnam. These regions are classified as LMICs and MICs, indicating their primary focus on growth, liquidity, and leverage. These are critical concerns for nations advancing in the development hierarchy. Research conducted in Romania (Achim et al., 2022; Duguleană et al., 2024), an upper-middle-income nation, indicates that Europe predominantly use traditional profitability metrics such as ROA, ROE, and liquidity ratios. This indicates that the financial systems in the region are maturing.

As mentioned, there are many papers available that investigates the effect of the COVID-19 pandemic on the financial performance on companies (Folger-Laronde et al., 2022; Sun & Li, 2021; Abbas & Nainggolan, 2022), and there are also many papers that investigate the effects of the Global Financial Crisis on the financial performances (Fracasso & Jiang, 2021; Kudlyak & Sánchez, 2017). However, there lack papers that investigates the effects of both events on the same control group (Ahmad et al., 2022; Neacșu & Georgescu, 2024; Lee et al., 2024).

The comprehensive literature summary table is presented below. The table provides extensive evidence on the method used in existing studies, the period, countries, sample, findings, and variables.

2.1. Case Study Scope

This study deliberately focuses on one flagship holding company rather than a cross-section of firms. Single-case designs may be used in this case’s shock-response finance research when the firm, Great Eagle, 1) is systemically important, given it represents the larger economy in Hong Kong SAR, and 2) publishes long, high-frequency histories, from 1980s to date (Table 2). The approach allows tight control over firm-specific factors and yields deep insight into within-firm dynamics, but it limits external validity. Therefore, results should not be generalised beyond comparable Hong Kong (SAR) property-hotel conglomerates without further testing of other companies.

Table 2. Descriptive statistics.

Variable	Obs	Mean	Std. Dev.	Min	Max
Dividend ($ in 1000s)
Financial Crisis Period	3	846,574	982066.35	240,961	1,979,669
COVID-19 Period	4	1,137,428	619606.92	584,053	2,025,835
Total Period	39	556372.92	678542.43	8338	3,153,453
Net Gearing
Financial Crisis Period	3	0.133	0.081	0.06	0.22
COVID-19 Period	4	0.29	0.079	0.196	0.369
Total Period	29	0.34	0.245	0.01	1
Revenue ($ in 1000s)
Financial Crisis Period	3	4296.946	408.345	3958.366	4750.433
COVID-19 Period	4	9064.345	1020.533	7830.429	10305.287
Total Period	40	4338.452	3229.985	62.513	10644.158
Net Profit ($ in 1000s)
Financial Crisis Period	3	1717.538	1968.578	71.67	3898.278
COVID-19 Period	4	−3645.247	6106.554	−12802.085	−410.814
Total Period	40	1648.358	3830.179	−12802.085	12788.931
Return on Equity (ROE)
Financial Crisis Period	3	0.076	0.087	0.003	0.173
COVID-19 Period	4	−0.044	0.074	−0.155	−0.006
Total Period	40	0.06	0.1	−0.155	0.531
EBITDA
Financial Crisis Period	3	0.63	0.665	0.12	1.382
COVID-19 Period	4	−0.136	0.606	−1.044	0.2
Total Period	40	0.691	0.755	−1.044	4.081
Net Profit Margin
Financial Crisis Period	3	0.415	0.47	0.015	0.932
COVID-19 Period	4	−0.363	0.587	−1.242	−0.046
Total Period	40	0.432	0.612	−1.242	3.148
Earnings Per Share (EPS)
Financial Crisis Period	3	2.837	3.273	0.12	6.47
COVID-19 Period	4	−3.34	5.736	−11.94	−0.25
Total Period	40	5.007	15.224	−11.94	95.16
Current Ratio
Financial Crisis Period	3	1.542	0.793	0.809	2.383
COVID-19 Period	4	1.45	0.329	1.115	1.9
Total Period	39	1.046	0.804	0.038	4.117

2.2. Empirical Analysis

Crisis-period coding

Global Financial Crisis (GFC): dummy = “1” for fiscal-years 2007, 2008, and 2009, “0” otherwise.

COVID-19: dummy = “1” for fiscal-years 2019, 2020, 2021, and 2022, “0” otherwise.

These windows follow the fiscal year‐end of Great Eagle. All tables and tests below use exactly this coding.

Equations

$Y_i={\text{β}}_0+{\text{β}}_1\text{COVID-}19+{\text{ε}}_1$ (1)

$Y_i={\text{β}}_0+{\text{β}}_2\text{GFC}+{\text{ε}}_1$ (2)

When Y_i is the dependent variable for observation “I”, which refers to Dividend, Net Gearing, Revenue, Net Profit, Return on Equity, EBITDA, Net Profit Margin, Earnings per Share, and Current Ratio. β₀ is the constant term representing the expected value of the dependent variable when all independent variables are 0. β₁ is the coefficient for the COVID-19 pandemic. COVID-19 is a dummy variable, which takes 1 during the COVID-19 period and 0 otherwise. β₂ is the coefficient for the Global Financial Crisis (GFC). The GFC is another dummy variable, which takes 1 during the crisis period and 0 otherwise. The coefficient of β₁ and β₂ shows how much the dependent variable changes when the corresponding independent variable changes by 1 unit. ε₁ is the error term.

The line graphics of the variables for Global Financial Crisis and COVID-19 are presented below. Figures 1-9 foreshadow the regression results: profitability ratios plunge during COVID-19, while liquidity and leverage ratios show mixed patterns. In contrast, lines around the 2008-09 window are comparatively flat, except for a dip in net gearing. These visual cues motivate the formal tests that follow.

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Figure 1. Line graphics for net profit margin. (a) Global financial crisis period, (b) COVID-19 period.

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Figure 2. Line graphics for current ratio. (a) Global financial crisis period, (b) COVID-19 period.

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Figure 3. Line graphics for dividends ($ in 1000s). (a) Global financial crisis period, (b) COVID-19 period.

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Figure 4. Line graphics for earnings per share ($). (a) Global financial crisis period, (b) COVID-19 period.

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Figure 5. Line graphics for EBITDA ratio. (a) Global financial crisis period, (b) COVID-19 period.

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Figure 6. Line graphics for net gearing ratio. (a) Global financial crisis period, (b) COVID-19 period.

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Figure 7. Line graphics for net profit ($ in 1000s). (a) Global financial crisis period, (b) COVID-19 period.

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Figure 8. Line graphics for return on equity ratio. (a) Global financial crisis period, (b) COVID-19 period.

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Figure 9. Line graphics for revenue ($ in 1000s). (a) Global financial crisis period, (b) COVID-19 period.

Figure 1 represents the line graphics for net profit margin (NPM) over the time from 1980 to 2023. Panel (a). represents the global financial crisis period, while panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). There was a significant decline in NPM prior to both crises, followed by partial recovery. According to the data, from 1980 to 2007, the company maintained a relatively stable and positive net profit margin, with minor fluctuations. A significant spike occurred in 2007, representing the highest peak in the NPM during the observed period, likely associated with the Global Financial Crisis, which then fell during 2008. After 2008, the NPM showed greater volatility, with periods of both noticeable decline and recovery. Post-2008, there are visible dips below zero, including a dramatic drop to its historical lowest around 2020-2021, which is likely associated with the COVID-19 pandemic’s economic impact (Figure 1).

Figure 2 illustrates the line graphics for Current Ratio (CR) from 1980 to 2023. Panel (a). represents the Global Financial Crisis period, while panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). In Panel (a), there seems to be an increase in current ratio, starting at a dip that rises up to a spike during the end of the observation period. Possibly, during the financial crisis, the company focused on maintaining short-term financial position by accumulating liquidity. Hence, their current ratio is seemingly unaffected by the Global Financial Crisis. Conversely, in Panel (b), there is a moderate decline in current ratio, which persisted past the focus period, suggesting potential liquidity problems. The graph shows a steady decline in the current ratio starting just before 2020, reaching its lowest point in 2021, likely due to reduced cash flow and increased liabilities during the pandemic.

Figure 3 shows the line graphics for Dividends (in $1000s) from 1980 to 2023. Panel (a) represents the Global Financial Crisis period, while panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). During both periods, dividends experienced notable fluctuations. The first observable increase is during 2005, where it experienced a sharp jump prior to the 2007, but falls into a steep decline between 2006 and 2007. Then, it peaked again during the observed Global Financial Crisis period only to fall again by the end of 2009, remaining relatively flat for a few years after. Despite fluctuations between years, there is an upward trend towards COVID-19. Dividends first increased into 2020, then experienced sharp decline into the next year, where it flattened out, and then finally declined further. Recovery is not observed.

Figure 4 exemplifies the line graphics for Earnings Per Share (EPS) from 1980 to 2023. Panel (a) represents the Global Financial Crisis period, while Panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). In the late 1980s, there was a notable spike in EPS where there may be many reasons contributing to this surge; of which, one was that the late 1980s marked a period of rapid economic growth in Hong Kong SAR, as it emerged as a global financial hub. In the first observed period, Global Financial Crisis, there are minor fluctuations, often not varying by much. However, during the COVID period, there is a significant decrease into a negative EPS, the first in company recorded history since 1980.

Figure 5 describes the line graphics for EBITDA Ratio from 1980 to 2023. Panel (a) represents the Global Financial Crisis period, while panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). Prior to the early 2000s, the EBITDA ratio fluctuated relatively small, between 0 and 1, until certain anomaly periods, early 2000s towards 2005, where it surged far greater than before. The factors that may contribute to this spike, may be that the business faced disruptions in operations, reduced consumer demand, increased cost of production, supply chain issues, and workforce limitations. At the beginning of the observed Global Financial Crisis period, there is a rise in EBITDA, only to fall to a trough during the observed period; however, there was prompt recovery during, and after, the period, rising to a flat post-crisis. Then, during COVID period, there is an obvious and sharp decrease into a negative ratio, suggesting the first time the company’s operational earnings were insufficient to cover its operating expenses.

Figure 6 shows the line graphics for Net Gearing Ratio from 1980 to 2023. Panel (a). represents the Global Financial Crisis period, while panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a). and COVID-19 period in Panel (b). The Net Gearing Ratio grew significantly from late 1990s to 2003. With the lower revenue and cash flow disruption, the company may have borrowed more to maintain operations. But it then began falling at the same rate it grew until 2008, suggesting a recovery period. Even during the Global Financial Crisis period, the company maintained a ratio below 20%, signifying more conservative spending habits. During COVID, there was a moderate increase in Gearing Ratio, which indicates higher financial risk because the company relied more on debt for funding.

Figure 7 expresses the line graphics for Net Profit (in $1000s) from 1980 to 2023. Panel (a) represents the Global Financial Crisis period, while panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). Prior to the Global Financial Crisis, there was a significant jump in net profit, but during the period, there was no significant effect on the variable. Conversely, just before the COVID-19, net profit actually hit its peak in 2017; nonetheless, after 2017, net profit began a drastic decline until the only negative net profit in the company’s recorded financial history since 1980. Considering the decline began before the COVID period, this suggests alternative factors initially contributed to a decline in net profit, which was further exacerbated by the effects of COVID-19. There are several reasons, including lower sales, increased operating costs, decreased demand, disruptions in business operations, etc., contributing to the substantial decline in net profit.

Figure 8 exhibits the line graphics for Return on Equity Ratio (ROE) from 1980 to 2023. Panel (a) represents the Global Financial Crisis period, while Panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). The behavior between ROE and net profit is similar, showing an anomaly early 2000s and a minor significance during the Global Financial Crisis. However, just before COVID, ROE reached a smaller peak in 2017; likewise, it then stooped to the only negative net profit in the company’s recorded financial history since 1980, reaching a trough in 2020. This shows the lowered company profitability and financial challenges the company faced during COVID-19.

Figure 9 displays the line graphics for Revenue ($ in 1000s) from 1980 to 2023, showing a clear upward trend over the observed period. Panel (a) represents the Global Financial Crisis period, while panel (b). represents the COVID-19 period. The red dash line indicates the Global Financial Crisis period in Panel (a) and COVID-19 period in Panel (b). Throughout the years, revenue steadily increased, with some dips and fluctuations during the Global Financial Crisis, which were insignificant given the instant recovery and rise almost 3 years after. This reflects the company’s long-term growth trajectory. Just before the COVID-19 period, shown in Panel (b)’s red dash lines, there was a slight dip in revenue, but it then rose again, only to again drop tremendously following 2020. This was likely due to reduced business operations, lower consumer spending, and economic disruptions caused by the pandemic. Post-COVID, the graph shows a steady recovery as revenue climbed back up, where this upward recline indicates a return to more stable operations and possibly improving market conditions.

2.3. Data

Appendix presents the source and financial performance indicators of Great Eagle Holdings Limited used in the paper. The variables include Dividend (in $1000s HKD), Net Gearing, Current Ratio, Net profit (in $1000s HKD), Return on Equity (ROE), EBITDA, Net Profit Margin, Earnings Per Share, and Revenue (in $1000s HKD).

2.3.1. Descriptive Statistics

Table 2 provides descriptive statistics for various financial indicators used in the analysis. The Dividend has 39 observations with a mean of 556372.92 and a standard deviation of 678542.43, ranging from a minimum of 8338 to a maximum of 3,153,453. For the financial crisis period, the Dividend has 3 observations with a mean of 846,574, standard deviation of 982066.35, and a range from 240,961 to 1,979,669. During the COVID-19 period, 4 observations show a mean of 1,137,428, a standard deviation of 619606.92, and a range from 584,053 to 2,023,855. In both Global Financial Crisis and COVID periods, the dividend increased from the overall mean.

Net Gearing has 29 observations with a mean of 0.34 and a standard deviation of 0.245, ranging from a minimum of 0.01 to a maximum of 1. During the financial crisis period, there are 3 observations with a mean of 0.133, a standard deviation of 0.081, and a range from 0.06 to 0.22. For the COVID-19 period, there are 4 observations with a mean of 0.29, a standard deviation of 0.079, and a range from 0.196 to 0.369. Both crisis periods show a decrease in the net gearing ratio.

Revenue has 40 observations with a mean of 4338.452 and a standard deviation of 3229.985, ranging from a minimum of 62.513 to a maximum of 10644.158. For the financial crisis period, there are 3 observations with a mean of 4296.946, a standard deviation of 408.345, and a range from 3958.366 to 4750.433. During the COVID-19 period, there are 4 observations with a mean of 9064.345, a standard deviation of 1020.533, and a range from 7830.429 to 10036.287. For revenue, during the financial crisis, it decreased by 1%, from 4338.452 to 4296.946. However, for COVID, it rose by more than double the overall mean.

Net Profit has 40 observations with a mean of 1648.358 and a standard deviation of 3830.179, ranging from a minimum of −12802.085 to a maximum of 12788.931. For the financial crisis period, there are 3 observations with a mean of 1717.578, a standard deviation of 1968.578, and a range from 71.67 to 3898.278. During the COVID-19 period, there are 4 observations with a mean of 3645.527, a standard deviation of 6106.554, and a range from −12802.085 to 4190.814. For net profit, the mean during the Global Financial Crisis period is greater than the overall mean and is even substantially larger during the COVID period. Like revenue, the net profit mean during COVID is more than double the overall mean value. However, it should be observed that the minimum value in all observations occurred during the COVID period with a negative value at −12802.085. This shows that there was a net loss during then, and during this period, this company generated no return.

Return on Equity (ROE) has 40 observations with a mean of 0.06 and a standard deviation of 0.1, ranging from a minimum of −0.155 to a maximum of 0.531. For the financial crisis period, there are 3 observations with a mean of 0.076, a standard deviation of 0.087, and a range from 0.003 to 0.173. During the COVID-19 period, there are 4 observations with a mean of −0.044, a standard deviation of 0.074, and a range from −0.155 to −0.006. The mean is observably greater during the Global Financial Crisis. On the other hand, during COVID, the mean for ROE is −0.044, a negative value, significantly lower than the overall observations’ mean. This follows in accordance with the net profit, indicating that if there is a net loss as mentioned earlier, the ROE will consequently be negative.

EBITDA has 40 observations with a mean of 0.691 and a standard deviation of 0.755, ranging from a minimum of −1.044 to a maximum of 4.081. For the financial crisis period, there are 3 observations with a mean of 0.63, a standard deviation of 0.665, and a range from 0.12 to 1.382. During the COVID-19 period, there are 4 observations with a mean of −0.136, a standard deviation of 0.606, and a range from −1.044 to 0.2. EBITDA decreased for both financial crisis and COVID-19 period, but it turns negative during the latter, producing the overall minimum value. Despite the lower mean, the company still was positive during financial crisis, generating positive operational profits. Conversely, during COVID-19, the company didn’t generate enough revenue to cover operating expenses, taking an operational loss during the pandemic. There is a clear impact of COVID on the operational profit, which was more severe than the financial crisis.

Net Profit Margin has 40 observations with a mean of 0.432 and a standard deviation of 0.612, ranging from a minimum of −1.242 to a maximum of 3.148. For the financial crisis period, there are 3 observations with a mean of 0.415, a standard deviation of 0.47, and a range from 0.015 to 0.932. During the COVID-19 period, there are 4 observations with a mean of −0.363, a standard deviation of 0.587, and a range from −1.242 to −0.046. Like EBITDA, it is again positive for financial crisis period and negative for COVID-19 though both were still lower than the overall mean. The company operated at a loss during the COVID-19 period, and again, COVID-19 had a much more significant impact than the Global Financial Crisis.

Earnings Per Share (EPS) has 40 observations with a mean of 5.007 and a standard deviation of 15.224, ranging from a minimum of −11.94 to a maximum of 95.16. For the financial crisis period, there are 3 observations with a mean of 2.837, a standard deviation of 3.273, and a range from 12 to 6.47. During the COVID-19 period, there are 4 observations with a mean of 3.34, a standard deviation of 5.736, and a range from −11.94 to 0.25. The company maintained a positive EPS during the financial crisis period, meaning they generated profit per share despite the crisis environment. However, during COVID-19, the EPS was negative, indicating the company suffered losses per share, meaning COVID directly affected shareholder returns.

Finally, Current Ratio has 39 observations with a mean of 1.046 and a standard deviation of 0.804, ranging from a minimum of 0.038 to a maximum of 4.117. For the financial crisis period, there are 3 observations with a mean of 1.542, a standard deviation of 0.793, and a range from 0.809 to 2.383. During the COVID-19 period, there are 4 observations with a mean of 1.45, a standard deviation of 0.329, and a range from 1.115 to 1.9. It should be observed the means are 1.542 and 1.45 for financial crisis and COVID period, respectively, greater than the overall mean. The company generated enough current assets to cover short term liabilities during both the financial crisis and COVID period. The company maintained a happy liquidity position in both events.

2.3.2. Findings

Equations (1) and (2) are estimated by regression analysis, and the results are reported below.

Table 3(a) presents the results of four different regression models during the COVID-19 period. The dependent variables are “Dividend,” “Net Gearing,” “Revenue,” and “Net Profit.” Each column corresponds to a distinct model, with explanatory variables such as COVID-19, in which a dummy variable takes “1” during the COVID period and “0” otherwise. If the results are statistically significant at the 1% level, we indicated by (***), the 5% level (**), and the 10% level (*).

Table 3. (a) Regression analysis panel A for COVID-19, (b) Regression analysis panel A for financial crisis.

(a)
VARIABLES	(1)		(2)	(3)	(4)
	Dividend		Net Gearing	Revenue	Net Profit
COVID-19	647461.371**		−0.057	5250.991***	−5881.784**
	(297730.108)		(0.064)	(672.956)	(2762.707)
Constant	489966.629***		0.348***	3813.353***	2236.536***
	(112998.105)		(0.053)	(497.306)	(522.191)
Observations	39		29	40	40
R-squared	0.086		0.007	0.244	0.218
(b)
VARIABLES		(1)	(2)	(3)	(4)
		Dividend	Net Gearing	Revenue	Net Profit
FC		314384.500	−0.230***	−44.872	74.789
		(488207.432)	(0.063)	(592.955)	(1157.779)
Constant		532189.500***	0.364***	4341.818***	1642.749**
		(11527.026)	(0.049)	(559.098)	(658.749)
Observations		39	29	40	40
R-squared		0.016	0.085	0.000	0.000

Robust standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.

In model 1 and model 3, the COVID-19 pandemic is positively associated with Dividend and Revenue with a coefficient of 647461.371 and 5250.991, respectively, suggesting that the COVID-19 period has a statistically positive effect on both variables.

For model 2, during COVID-19, there are no statistically significant differences in Net Gearing, meaning the impact may be deemed negligible. However, for model 4, the COVID-19 pandemic is negatively associated with Net Profit with a coefficient of −5881.784, suggesting that the COVID-19 period has a statistically negative effect on Net Profit.

Table 3(b) presents the results of four different regression models during the Financial Crisis (FC) period. The dependent variables are “Dividend,” “Net Gearing,” “Revenue,” and “Net Profit.” Each column corresponds to a distinct model, with explanatory variables such as FC, in which a dummy variable takes “1” during the Financial Crisis period and “0” otherwise. If the results are statistically significant at the 1% level, we indicated by (***), the 5% level (**), and the 10% level (*).

In model 1 and model 4, the Financial Crisis period is positively associated with Dividend and Net Profit with a coefficient of 314384.500 and 74.789, respectively. However, those are not statistically significant, suggesting that the Financial Crisis period has no statistically significant effect on Dividend and Net Profit.

In model 2, Financial Crisis period has a statistically significant effect on Net Gearing, with a coefficient of −0.230, indicating a negative association. However, for model 3, the Financial Crisis had a negative effect on Revenue. But, given that the model has no statistical significance, the effects on Revenue cannot be statistically attributed to the Financial Crisis period.

Table 4(a) presents the results of five different regression models during the COVID-19 period. The dependent variables are “Return on Equity (ROE),” “EBITDA,” “Net Profit Margin,” “Earnings per Share (EPS),” and “Current Ratio” Each column corresponds to a distinct model, with explanatory variables such as COVID-19, in which a dummy variable takes “1” during the COVID period and “0” otherwise. If the results are statistically significant at the 1% level, we indicated by (***), the 5% level (**), and the 10% level (*).

For all models except model 5, Current Ratio, the COVID-19 pandemic has a statistically significant negative effect on all dependent variables. ROE has a coefficient of −0.117, EBITDA has a coefficient of −0.920, Net Profit Margin has a coefficient of −0.884, and lastly, EPS has a coefficient of −9.275, suggesting that the COVID-19 period has a statistically negative effect on these respective variables.

For model 5, the COVID-19 pandemic has a statistically significant positive effect on the current ratio. There was a substantial decline in nearly all dependent variables but current ratio during the pandemic, where the most considerable impact is observed with EPS.

Table 4. (a) Regression analysis panel B for COVID-19, (b) Regression analysis panel B for financial crisis.

(a)
VARIABLES	(1)	(2)	(3)	(4)	(5)
	ROE	EBITDA	Net Profit Margin	EPS	Current Ratio
COVID-19	−0.117***	−0.920***	−0.884***	−9.275**	0.451**
	(0.037)	(0.295)	(0.277)	(3.675)	(0.204)
Constant	0.072***	0.783***	0.521***	5.935**	0.999***
	(0.016)	(0.121)	(0.093)	(2.648)	(0.142)
Observations	40	40	40	40	39
R-squared	0.125	0.137	0.193	0.034	0.030
(b)
VARIABLES	(1)	(2)	(3)	(4)	(5)
	ROE	EBITDA	Net Profit Margin	EPS	Current Ratio
FC	0.017	−0.067	−0.018	−2.347	0.538
	(0.045)	(0.346)	(0.250)	(3.070)	(0.407)
Constant	0.059***	0.696***	0.434***	5.183*	1.004***
	(0.017)	(0.128)	(0.104)	(2.631)	(0.135)
Observations	40	40	40	40	39
R-squared	0.002	0.001	0.000	0.002	0.033

Robust standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.

Table 4(b) presents the results of five different regression models during the Financial Crisis period. The dependent variables are “Return on Equity (ROE),” “EBITDA,” “Net Profit Margin,” and “Earnings per Share (EPS),” and “Current Ratio.” Each column corresponds to a distinct model, with explanatory variables such as “FC”, in which a dummy variable takes “1” during the Financial Crisis period and “0” otherwise. If the results are statistically significant at the 1% level, we indicated by (***), the 5% level (**), and the 10% level (*).

In model 1 and model 5, there is a positive correlation between Financial Crisis and the variables ROE and Current Ratio. Meanwhile, there is a negative correlation in the other three variables, models 2, 3, and 4, EBITDA, Net Profit Margin, and EPS, respectively. For all models, there is no statistical significance observed for ROE, EBITDA, Net Profit Margin, EPS, or Current Ratio; every dummy variable did not have an asterisk related. This indicates that the Financial Crisis period does not have significant effects on the dependent variables.

The mean value of the Dividend during the non-COVID-19 period is 489.966, and the mean value of the Dividend during the COVID-19 period is 1137.428. The T value shows −1.85, indicating that the difference “dif” in dividends is statistically significant at a 10-percentage level. At the same time, the “p-value” is 0.07, which is less than 0.10, suggesting that the difference between dividends during COVID and non-COVID eras is statistically significant. It is clear that Dividend payments dramatically increased during the COVID-19 period (Table 5).

Table 5. (a) Two-sample t-test results for COVID-19, (b) Two-sample t-test results for financial crisis.

(a)
Two-sample t-test with equal variances
	obs1	Non-Covid	Mid-Covid	dif	St Err	t-value	p-value
Dividend (in $1000s HKD)	35	489.966	1137.428	−647.462	346.982	−1.85	0.070
Net Gearing	25	0.348	0.29	0.058	0.134	0.45	0.671
Current Ratio	35	1.000	1.45	−0.451	0.423	−1.05	0.294
Net profit (in $1000s HKD)	36	2236.537	−3645.247	5881.784	1808.842	3.25	0.003
ROE	36	0.072	−0.044	0.117	0.05	2.35	0.025
EBITDA	36	0.783	−0.136	0.919	0.374	2.45	0.018
Net Profit Margin	36	0.521	−0.363	0.884	0.293	3	0.005
Earnings Per Share	36	5.934	−3.34	9.274	7.988	1.15	0.253
Revenue (in $1000s HKD)	36	3813.353	9064.345	−5250.992	1499.554	−3.5	0.001
(b)
Two-sample t-test with equal variances
	obs1	Non-FC	During-FC	dif	St Err	t-value	p-value
Dividend (in $1000s HKD)	36	532189.500	846,574	−314384.5	409981.72	−0.75	0.448
Net Gearing	26	0.363	0.134	0.23	0.145	1.6	0.126
Current Ratio	36	1.004	1.542	−0.538	0.481	−1.1	0.271
Net profit (in $1000s HKD)	37	1642.748	1717.538	−74.79	2329.283	−0.05	0.975
ROE	37	0.059	0.076	−0.017	0.061	−0.3	0.779
EBITDA	37	0.697	0.63	0.067	0.459	0.15	0.885
Net Profit Margin	37	0.434	0.416	0.018	0.372	0.05	0.961
Earnings Per Share	37	5.183	2.837	2.347	9.251	0.25	0.801
Revenue (in $1000s HKD)	37	4341.818	4296.946	44.871	1964.294	0.001	0.982

Note: pooled-variance t-test; see “Justification”.

The mean value of net gearing during the non-COVID-19 period is 0.348. The mean value of the Net Gearing during the non-COVID-19 period is 0.348, and the mean value of the Dividend during the COVID-19 period is 0.29. The T value shows 0.45, indicating that the difference “dif” in net gearing is not statistically significant at a 10-percentage level. At the same time, the “p-value” is 0.671, which is far greater than 0.10, suggesting that the difference between Net Gearing during COVID and non-COVID eras is not statistically significant. The mean values between non-COVID and COVID periods are not distinguishable and are almost similar, showing no statistical differences.

The mean value of the Current Ratio during the non-COVID-19 period is 1.000, and the mean value during the COVID-19 period is 1.45. The T value shows −1.05, indicating that the difference “dif” in the current ratio is not statistically significant at a 10-percentage level. At the same time, the “p-value” is 0.294, which is greater than 0.10, suggesting that the difference between the Current Ratios during COVID and non-COVID periods is not statistically significant. The mean values between the non-COVID and COVID periods are not distinguishable and are almost similar, showing no statistical differences.

The mean value of Net Profit (in $1000s HKD) during the non-COVID-19 period is 2236.537, and the mean value during the COVID-19 period is −3645.247. The T value shows 3.25, indicating that the difference “dif” in net profit is statistically significant at a 1-percentage level. The “p-value” is 0.003, less than 0.01, suggesting that the difference between Net Profits during COVID and non-COVID periods is statistically significant. It is clear that the net profit drastically decreased during the COVID-19 period.

The mean Return on Equity value during the non-COVID-19 period is 0.072, and the mean value during the COVID-19 period is −0.044. The T value shows 2.35, indicating that the difference “dif” in return on Equity is statistically significant at a 5-percentage level. The “p-value” is 0.025, less than 0.05, suggesting that the difference between return on Equity during COVID and non-COVID periods is statistically significant. Return on Equity notably decreased during the COVID-19 period.

The mean value of EBITDA during the non-COVID-19 period is 0.783, and the mean value during the COVID-19 period is −0.136. The T value shows 2.45, indicating that the difference “dif” in EBITDA is statistically significant at a 5-percentage level. The “p-value” is 0.018, less than 0.05, suggesting that the difference between EBITDA during COVID and non-COVID periods is statistically significant. EBITDA dropped significantly during the COVID-19 period.

The mean value of Net Profit Margin during the non-COVID-19 period is 0.521, and the mean value during the COVID-19 period is −0.363. The T value shows 3.0, indicating that the difference “dif” in net profit margin is statistically significant at a 1-percentage level. The “p-value” is 0.005, less than 0.01, suggesting that the difference between net profit margin during COVID and non-COVID periods is statistically significant. As such, observe that net profit margins were significantly reduced during COVID-19.

The mean value of Earnings Per Share during the non-COVID-19 period is 5.934, and the mean value during the COVID-19 period is −3.34. The T value shows 1.15, indicating that the difference “dif” in earnings per share is not statistically significant at a 10-percentage level. The “p-value” is 0.253, more substantial than 0.10, suggesting that the difference between earnings per share during COVID and non-COVID periods is not statistically significant. The mean values between the non-COVID and COVID periods do not change significantly.

The mean value of Revenue (in $1000s HKD) during the non-COVID-19 period is 3813.353, and the mean value during the COVID-19 period is 9064.345. The T value shows −3.5, indicating that the difference “dif” in Revenue is statistically significant at a 1-percentage level. The “p-value” is 0.001, less than 0.01, suggesting that the difference between Revenue during COVID and non-COVID periods is statistically significant. Revenue increased dramatically during the COVID-19 period.

The mean value of the Dividend during the Non-FC period is 532189.500, and the mean value of the Dividend during the FC period is 846,574. The T value shows −0.75, indicating that the difference “dif” in dividends is not statistically significant at a 10-percentage level. At the same time, the “p-value” is 0.448, which is greater than 0.10, suggesting that the difference between Dividends during the FC and Non-FC eras is not statistically significant. The mean values between the Non-FC and FC periods are highly distinguishable and during the financial crisis period is significantly lower.

The mean value of Net Gearing during the Non-FC period is 0.363, and the mean value during the FC period is 0.134. The T value shows 1.6, indicating that the difference “dif” in net gearing is not statistically significant at a 10-percentage level. At the same time, the “p-value” is 0.126, which is greater than 0.10, suggesting that the difference between Net Gearing during FC and Non-FC periods is not statistically significant. The mean values between the Non-FC and FC periods are similar, showing no statistical differences.

The mean value of the Current Ratio during the Non-FC period is 1.004, and the mean value during the FC period is 1.542. The T value shows −1.1, indicating that the difference “dif” in the current ratio is not statistically significant at a 10-percentage level. At the same time, the “p-value” is 0.271, which is greater than 0.10, suggesting that the difference between Current Ratios during FC and Non-FC periods is not statistically significant. The mean values between the Non-FC and FC periods do not differ significantly.

The mean value of Net Profit (in $1000s HKD) during the Non-FC period is 1642.748, and the mean value during the FC period is 1717.538. The T value shows −0.05, indicating that the difference “dif” in net profit is not statistically significant at a 10-percentage level. The “p-value” is 0.975, which is far greater than 0.10, suggesting that the difference between Net Profits during FC and Non-FC periods is not statistically significant. The mean values between the Non-FC and FC periods are almost identical and show no statistical differences.

The mean Return on Equity (ROE) value during the non-FC period is 0.059, and the mean value during the FC period is 0.076. The T value shows −0.3, indicating that the difference “dif” in return on equity is not statistically significant at a 10-percentage level. The “p-value” is 0.779, which is greater than 0.10, suggesting that the difference between ROE during FC and Non-FC periods is not statistically significant. Return on Equity remained relatively unchanged during the FC period.

The mean value of EBITDA during the Non-FC period is 0.697, and the mean value during the FC period is 0.63. The T value shows 0.15, indicating that the difference “dif” in EBITDA is not statistically significant at a 10-percentage level. The “p-value” is 0.885, which is greater than 0.10, suggesting that the difference between EBITDA during FC and Non-FC periods is not statistically significant. EBITDA levels between the Non-FC and FC periods are nearly identical.

The mean value of Net Profit Margin during the Non-FC period is 0.434, and the mean value during the FC period is 0.416. The T value shows 0.05, indicating that the difference “dif” in net profit margin is not statistically significant at a 10-percentage level. The “p-value” is 0.961, which is greater than 0.10, suggesting that the difference between Net Profit Margins during FC and Non-FC periods is not statistically significant. Net Profit Margins remained stable across the two periods.

The mean value of Earnings Per Share during the Non-FC period is 5.183, and the mean value during the FC period is 2.837. The T value shows 0.25, indicating that the difference “dif” in earnings per share is not statistically significant at a 10-percentage level. The “p-value” is 0.801, which is greater than 0.10, suggesting that the difference between Earnings Per Share during FC and Non-FC periods is not statistically significant. The mean values between the two periods do not show significant changes.

The mean value of Revenue (in $1000s HKD) during the Non-FC period is 4341.818, and the mean value during the FC period is 4296.946. The T value shows 0.001, indicating that the difference “dif” in revenue is not statistically significant at a 10-percentage level. The “p-value” is 0.982, which is much greater than 0.10, suggesting that the difference between Revenue during FC and Non-FC periods is not statistically significant. Revenue levels remained consistent across both periods.

2.3.3. Justification

All OLS coefficients are reported with heteroskedasticity- and autocorrelation-consistent (HAC) robust standard errors. This correction mitigates potential bias from both unequal variances and first-order serial correlation, making additional diagnostic tests unrequired for coefficient inference. Therefore, the statistical significance of the coefficients presented in Table 3(a), Table 3(b), Table 4(a), and Table 4(b) can be interpreted with greater confidence.

Additionally, owing to the extremely small crisis-period subsamples (n = 3 - 4), Welch’s unequal-variance t-test would have very low degrees of freedom and likely display unstable critical values. Upon visual inspection, the sample variances show no material dispersion difference across periods; therefore, the equal-variance (“pooled”) t-statistics is retained as the more reliable choice in this setting. Given these considerations, the assumption of equal variances was adopted for simplicity and practicality.

3. Conclusion

The purpose of this study is to investigate the impacts of two major globally events, specifically the 2008-09 Global Financial Crisis and the COVID-19 pandemic, on firm level performance in Hong Kong SAR. The findings reveal that the COVID-19 pandemic had a greater statistical significance compared to the 2008 Global Financial Crisis in terms of firm financial performance. Specifically, COVID-19 pandemic was associated with sharp declines in ROE, EBITDA, EPS, and net profit margin, but provided surprising increases in dividends and current ratio. This suggested that the company may have attempted to signal financial strain and maintain investor confidence during the pandemic, despite facing declining profits. In contrast, the financial crisis exhibited a much lower statistical significance relevant to the variables measured; in fact, the only variable that demonstrated significance was net gearing.

For future study, a recommendation would be to take into account a broader set of companies; this can be within the same region if aiming to target one economy. However, to further investigate the impacts on a more global scale, future research can analyze a greater dataset, which means looking economies beyond Hong Kong SAR, such as the Southeast Asian, European, or American regions.

Appendix

Data definition table.

Indicator Name	Definition	Source of Data
Dividend (in $1000s HKD)	Interim + final + special (cash + share alternative)	Great Eagle Holdings Limited https://www.greateagle.com.hk/financial-reports-page
Net Gearing	Net gearing based on statutory accounting principles is arrived at by dividing net debts attributable to Shareholders of the Group by equity attributable to Shareholders of the Group based on appraised value of investment properties and depreciated cost of hotel properties
Current Ratio	Current Asset/Current Liability
Net profit (in $1000s HKD)	Total earnings after subtracting all expenses
Return On Equity (ROE)	Net Income/[(Equity + Last year’s equity)/2]
EBITDA	(EBITDA = Net Income before tax + depreciation)/revenue
Net Profit Margin	Net profit/revenue
Earnings Per Share	EPS (basic) dividing a company’s net income by the total number of outstanding shares
Revenue (in $1000s HKD)	Total amount of money after sales

Conflicts of Interest

The author declares no conflicts of interest regarding the publication of this paper.

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