International Banking Confidence and Geopolitical Awareness: Study Findings

Introduction and Study Purpose

The purpose of this study was to determine whether the international banking community feels confident that it can sustain another global economic crisis, and specifically whether geopolitical awareness impacts that confidence level. Confidence plays a significant role in how money is invested, where it is placed, and what markets will do. Therefore, assessing the confidence levels of bankers at four major international banks — JPMorgan Chase, Deutsche Bank, HSBC, and Bank of China — is essential for understanding whether the sector can safely handle another global economic crisis like the one seen from 2007 to 2009, and to what degree, if at all, geopolitical awareness impacts that confidence level.

This chapter comprises four sections: (a) validity and reliability of the data, (b) results, (c) evaluation of the findings, and (d) a summary of results. The validity and reliability section discusses the overall study, factors impacting the interpretation of data collection or analysis, an overview of the categorical demographic data collected, the validity and reliability of the Likert-type data collected, and the assumptions of the validity and reliability tests used to analyze that data.

Validity and Reliability of the Data

Dependability and confirmability were addressed through rich, thick descriptions of themes, member-checking of the findings and interpretations, a reflexive journal kept by the researcher, and an inquiry audit completed by a third party of the research processes used throughout the study. For this study, rich, thick descriptions were included, as was member checking. A reflexive journal was kept by the researcher and an inquiry audit was completed by a third party to confirm the research processes used throughout the study.

Triangulation of sources did not occur through a variety of data collection methods but rather through the surveying of a variety of employees at four different international banks. This allowed the research to obtain data from more than one source location in the international finance industry. Member checking was also used to answer questions that arose after the initial round of survey data was collected and analyzed. Participants were emailed or messaged through social media when the researcher wanted to confirm whether his interpretation of the findings aligned with their actual beliefs and feelings. Member checking and triangulation both helped to ensure the credibility of the findings. Validity concerns the accuracy of a measure, and reliability concerns the consistency of a measure. In presenting the findings, it is critical to discuss how accurately the collection and analysis of data reflects the reality of the information sought.

Parametric Inferential Statistics

This study did not include a mixed-methods approach but rather only multiple data sources, and thus it did not offer a triangulation of sources beyond the banking members who participated in the survey of the four central banks. This lack of triangulation places at least one constraint on the validity of the data, in the sense that the findings are not tested for consistency across different data collection instruments. There may be other factors and variables not tested in this study that influence or affect the outcome.

Transferability was assured by providing rich, thick descriptions of the way data was collected, the context in which it was obtained, demographics of the participants, and other content that would help to deepen understanding of the population represented by the findings.

The overall study showed that the data met the assumptions of the statistical test. Evidence of psychometric soundness — in terms of adequate validity and reliability — was obtained through Pearson's r, internal consistency, face validity, a test for normality, and discriminant validity. Internal consistency reliability was assessed using Cronbach's alpha, which indicates how closely items in a group are related. Internal consistency reliability was supported: Cronbach's alpha was .80, indicating that the items had a relatively high degree of internal consistency. Data analysis appropriate for the purpose and design included internal consistency, construct validity, and item homogeneity. The following were tested: reliability and item homogeneity using Cronbach's alpha, item-total correlations, and inter-item correlations; construct validity was assessed using factor analysis.

In the scientific community, a reliability coefficient greater than .70 is typically viewed as acceptable. Tests for normality were conducted on the dependent variable. Though the Shapiro-Wilk test indicated a significant deviation from normality (.99, p < 0.05), a visual inspection of the histogram showed a normal distribution. Kurtosis and skewness were also within the 1.96 limitation (.12 for kurtosis and .11 for skewness), providing further evidence that the departure from normality indicated by the Shapiro-Wilk test was not extreme. In statistical tests, parametric testing assumptions must be satisfied for accurate interpretation. The assumption of normality requires that the distribution be approximately symmetric and bell-shaped, with skewness within the range of ±2 and kurtosis values within the range of ±7. In this study, the Shapiro-Wilk test showed significance, but visual inspection of the bell curve indicated otherwise.

The assumptions of the Pearson correlation test were assessed for linearity. The assumptions of the t-test included random sampling, normality of data distribution, adequacy of sample size, and equality of variance in standard deviation. A total of 1,000 emails were sent to a randomized sample of employees at JPMorgan Chase, Deutsche Bank, HSBC, and Bank of China, asking them to participate in a survey hosted on SurveyMonkey. A total of 641 participants took part in the survey.

The survey method is most often used in quantitative studies, and the most current form is the self-reported survey. Surveys can be elaborate or simple but are most frequently used to obtain data from a population regarding a research question that focuses on the correlation of variables or issues of cause and effect (Walliman, 2017). The survey is conducted by first developing the survey questions or statements.

The Likert scale is commonly used to make measuring responses easier. It is a numbered scale of responses indicating the degree to which a respondent agrees or disagrees with a statement in the survey. When developing a survey, the researcher must ensure that statements are written in a way that responses can be adequately measured using such a scale. Otherwise, the data can be misleading — for instance, if a high value is assigned to responses agreeing with positively framed statements in one item but a high value is also assigned to responses agreeing with negatively framed statements in another, the survey results will be worthless. Thus, the survey should be piloted first to confirm its validity.

The advantages of the survey method include its ease of collecting information from a large group of participants without having to meet or interview them all. A survey can be mass-distributed and completed quickly without inconveniencing participants. The disadvantages include the risk that self-reporting can lead to underreporting, which can negatively impact the validity and generalizability of the survey and the study overall.

Evidence of Psychometric Soundness

Internal consistency reliability was assessed using Cronbach's alpha. Internal consistency reliability was supported: Cronbach's alpha was .80. Data analysis appropriate for the purpose and design included internal consistency, construct validity, and item homogeneity. The following were tested: reliability and item homogeneity using Cronbach's alpha, item-total correlations, and inter-item correlations; construct validity using factor analysis. Cronbach's alpha of .80 indicates that the items had a relatively high degree of internal consistency. In the scientific community, a reliability coefficient greater than .70 is typically viewed as acceptable.

Results by Research Question

The research questions for this study were:

1) Is the international banking community confident in its ability to handle another global economic crisis like the one experienced from 2007–2008?

2) Does geopolitical awareness have an impact on the confidence of the members of the international banking community regarding the sector's ability to handle another global economic crisis like the one experienced from 2007–2008?

3) Do changes in central bank monetary policy (i.e., going from quantitative easing to quantitative tightening) and awareness of rising debt levels around the world affect the confidence levels of the members of the international banking community regarding the sector's ability to handle another global economic crisis like the one seen from 2007–2008?

The findings indicated that there was no lack of confidence in general among employees of the international banking industry. They likewise showed that geopolitical awareness does not have a statistically significant negative effect on international banking employees' confidence levels. Third, the findings showed that awareness of monetary policy and rising debt levels does not significantly and negatively impact the confidence of these same employees.

Discussion

This study builds on the idea that confidence plays a significant role in how money is invested. Everything from bond markets to equity markets to precious metals and blockchain is impacted by confidence (Haitsma et al., 2016). Banks should therefore have some sense of their employees' confidence levels in case another financial and economic crisis occurs. To assist in this understanding, this study provides a tool for assessing confidence levels and offering a reading on the confidence of associates at four major international banks.

The demographics of participants consisted of sales specialists (39%), loan processors (22%), financial advisors (16%), investment banking analysts (15%), application analysts (5%), executive directors (3%), and risk analysts (2%), as shown in Table 1. Descriptive statistics of the independent and dependent variables are shown in Table 2.

Table 1: Demographics of Respondents

Job Position / Percentage of Respondents
Application Analyst: 5%
Investment Banking Analyst: 15%
Executive Director: 3%
Risk Analyst: 2%
Loan Processor: 22%
Financial Advisor: 16%
Sales Specialist: 39%

Most of the participants in the survey were in sales, which is a lower-level position. Loan processors made up the next highest share of participants, followed by financial advisors. Risk analysts made up only 2% of the respondents and executive directors only 3%. This distribution could be a factor in skewing the results of the survey with respect to any association between risk aversion, geopolitical awareness, and confidence. Considering that the majority of those surveyed were involved in sales and loan processing, it was expected that the data would naturally reflect a more positive view of the strength of the international finance industry, given that these individuals' jobs and careers depended on industry-wide strength.

Were it the case that factors such as geopolitics and record-high debt levels could undermine the industry, it would present the possibility that the industry itself was fundamentally lacking in inherent strength. To assess these relationships, however, it is essential to consider the data in terms of the research questions posed at the outset of this study.

Research Question 1

Is the international banking community confident in its ability to handle another global economic crisis like the one experienced from 2007–2008?

Table 2 shows that within the international banking community, the most confidence was expressed by HSBC employees and Bank of China employees regarding the community's ability to handle a global economic crisis. Employees of JPMorgan Chase were overwhelmingly neutral-to-confident and were by far the least concerned group about difficulties that might be faced in another crisis. The recurring theme found in the survey responses was that employees felt their banks were better prepared to handle another crisis. The outlier was Deutsche Bank, where employees expressed very little confidence — three out of four participants demonstrated a substantial lack of confidence in the industry's ability to cope with another crisis. Employees at Deutsche Bank expressed minimal belief that their bank was prepared. Of the four banks, employees at the Bank of China were the most optimistic, with only 5% of participants expressing a lack of confidence.

Table 2: Confidence Levels of the Banking Community

Bank / Not Confident / Neutral / Confident
JPMorgan Chase: 10% / 50% / 40%
Deutsche: 75% / 5% / 20%
HSBC: 25% / 10% / 65%
Bank of China: 5% / 35% / 60%
Mean: 28.75% / 25% / 46.2%

There did not appear to be any statistically significant correlation between the two variables regarding confidence and crisis perception. The p-value was greater than 0.05, and thus the null hypothesis was rejected. To test the assumptions of linearity, Pearson's r and regression analysis were conducted using ANOVA. Pearson's r for the data obtained was +.95, indicating excellent reliability. The t-test p-value was above 0.05 for each of the three research questions, indicating that the null hypotheses for each should be rejected.

Model Summary (Research Question 1)
R: .164 | R Square: .027 | Adjusted R Square: −.017 | Std. Error of the Estimate: 6.8794
Predictors: (Constant), Crisis perception | Dependent Variable: Confidence

ANOVA (Research Question 1)
Regression — Sum of Squares: 57.875 | Mean Square: 28.937 | F: .611 | Sig.: .547
Residual — Sum of Squares: 2082.370 | Mean Square: 47.327
Total — Sum of Squares: 2140.245
Dependent Variable: Confidence | Predictors: (Constant), Crisis perception

Residuals Statistics (Research Question 1)
Predicted Value: Min 4.295, Max 9.089, Mean 7.511, Std. Deviation 1.1217, N 641
Residual: Min −7.9074, Max 31.5980, Mean .0000, Std. Deviation 6.7282, N 641
Std. Predicted Value: Min −2.867, Max 1.416, Mean .000, Std. Deviation 1.000, N 641
Std. Residual: Min −1.147, Max 4.791, Mean .000, Std. Deviation .968, N 641
Dependent Variable: Confidence

The findings showed that the model was not statistically significant, as p > 0.05. The R-squared is less than 3%, making it a poor predictor. The correlation between the variables was not especially meaningful.

Thus, aside from the outlier of Deutsche Bank employees, there was no significant indication of an industry-wide lack of confidence among employees in international finance, nor any correlation between perceptions of past crises and projections of future fears. Possible explanations for this lack of association include the belief that employees trusted their employers to have implemented appropriate controls and policies in the wake of the 2008 crisis and that those banks were now better prepared to handle risk and volatility. Though this survey was conducted before the market volatility of March 2020 related to the global spread of COVID-19, the rapid bounce-back of markets over subsequent weeks suggests that employees of these firms may have been justified in their confidence that their institutions could handle volatility with relative ease.

One caveat, however, is the role of central banks in injecting liquidity into markets through various maneuvers — such as the Federal Reserve's purchasing of high-yield junk bonds and the Bank of Japan's outright purchasing of equities. In response to the COVID-19 crisis, central banks injected more than $10 trillion USD into markets. Did employees of these firms anticipate that central banks would be there to support markets as they were following 2008? Was this the source of their trust?

Follow-up interviews and surveys with participants helped to answer that question, and member checking was utilized for that purpose. Emails were sent to participants to gauge whether they viewed the role of the central bank in supporting markets as a significant factor in their overall confidence in the industry. The overwhelming majority of replies were affirmative: 90% of respondents (240 total) stated that their impression that central banks would step in to bring stability to the marketplace — and thereby to the international finance industry — was the source of their confidence, since the central banks had set a precedent for precisely that type of activity in their response to the 2008 economic crisis.

Research Question 2

Does geopolitical awareness have an impact on the confidence of the members of the international banking community regarding the sector's ability to handle another global economic crisis like the one experienced from 2007–2008?

Throughout the international banking community, the employees of Deutsche Bank were most likely to be negatively impacted by awareness of geopolitical events, as shown in Table 3. Deutsche employees' awareness of geopolitical stressors — such as the threat of an Iranian crisis, oil embargoes, the rise of domestic and international terrorism, or a renewed Cold War with Russia — tended to linger in their minds more negatively than in the minds of employees at other banks. For employees at other banks, geopolitical tension was seen as "bullish" for markets, as it created a heightened understanding of macro factors that could help investors understand where to move money, what to invest in, what flows to follow, and what risks to consider. For at least half of employees at JPMorgan Chase, HSBC, and Bank of China, geopolitical awareness was positively correlated with confidence because these employees felt that by understanding geopolitical issues, their bank was better positioned to provide expert advice and guidance for clients. For three-fourths of Deutsche Bank employees, awareness of geopolitics did not inspire confidence but rather fear and dread. One explanation could be that these employees did not trust their firm to be able to navigate the fallout of geopolitical tension and conflict.

The question that arose, therefore, was whether employees' confidence in their own firm moderated their confidence in the industry overall. Since the majority of employees in the community demonstrated a positive impact on confidence as geopolitical awareness grew, it seemed necessary to engage in member checking once more and follow up the survey with an additional question framed in the context of COVID-19: Do you feel confident in your firm's ability to navigate the fallout from geopolitical conflict created by the conditions caused by the coronavirus pandemic? A total of 152 respondents answered, and 82% stated that they were confident in their firms.

Of the 18% who did not express confidence, 75% were employees of Deutsche Bank. This suggests that Deutsche Bank differs from its peers in the industry, at least in terms of how employees perceive the company and its internal strength.

The key insight from this finding is that a firm's reputation can impact employee perceptions of how to interpret geopolitical risk. If a firm's reputation is strong, employees are more likely to view geopolitical awareness in terms of how it can benefit clients and, by extension, themselves. If a firm's reputation is weak, employees are more likely to fear the fallout of geopolitical conflict and how it might negatively impact their firm and, in turn, their careers. This suggests that banks lacking internal strength — or plagued by an exodus of shareholders, as Deutsche Bank has been in recent years — are less likely to have employees who believe that geopolitical awareness is something that can be used to their advantage. Instead, they view any type of global tension or conflict as inherently risky and harmful for the industry because they fear the impact on already-weakened firms. Employees who view their firms as strong, on the other hand, will use geopolitical awareness with confidence, as they are not worried that their own company may be adversely impacted by global conflict, and for that reason they are more inclined to embrace geopolitical risk and help clients make the right investments or take out the right loans at the right time. Nearly half of all employees participating in the survey felt that geopolitical awareness gave them more confidence, not less, and almost three-fourths felt that at the very least it had no negative impact on their confidence levels regarding the industry as a whole, as Table 3 shows.

Table 3: The Impact of Geopolitical Awareness on Confidence Levels

Bank / Negative Impact / No Impact / Positive Impact
JPMorgan Chase: 5% / 45% / 50%
Deutsche: 75% / 5% / 20%
HSBC: 25% / 10% / 65%
Bank of China: 5% / 35% / 60%
Mean: 27.5% / 23.75% / 48.75%

Still, there did not appear to be any statistically significant correlation between the two variables regarding confidence and geopolitical awareness. The p-value was greater than 0.05, and thus the null hypothesis was rejected. To test the assumptions of linearity, Pearson's r and regression analysis were conducted using ANOVA.

Model Summary (Research Question 2)
R: .159 | R Square: .022 | Adjusted R Square: −.019 | Std. Error of the Estimate: 6.4793
Predictors: (Constant), Geopolitical awareness | Dependent Variable: Confidence

ANOVA (Research Question 2)
Regression — Sum of Squares: 56.692 | Mean Square: 28.937 | F: .611 | Sig.: .547
Residual — Sum of Squares: 2082.370 | Mean Square: 47.327
Total — Sum of Squares: 2140.245
Dependent Variable: Confidence | Predictors: (Constant), Geopolitical awareness

Residuals Statistics (Research Question 2)
Predicted Value: Min 4.262, Max 9.098, Mean 7.511, Std. Deviation 1.4566, N 641
Residual: Min −7.946, Max 32.696, Mean .0000, Std. Deviation 6.6512, N 641
Std. Predicted Value: Min −2.867, Max 1.415, Mean .0000, Std. Deviation 1.0000, N 641
Std. Residual: Min −1.146, Max 4.582, Mean .0000, Std. Deviation .9690, N 641
Dependent Variable: Confidence

The findings showed that the model as a whole was not statistically significant, as p > 0.05. The R-squared is less than 3%, making it a poor predictor of where confidence will be. The correlation between the variables was not especially meaningful, in spite of the fact that the majority of respondents associated geopolitical awareness with confidence rather than with a weakening of confidence.

Research Question 3

Do changes in central bank monetary policy (i.e., going from quantitative easing to quantitative tightening) and awareness of rising debt levels around the world affect the confidence levels of the members of the international banking community regarding the sector's ability to handle another global economic crisis like the one seen from 2007–2008?

The data indicate that awareness of central bank policy and rising debt levels has no significant impact on bank employees' confidence levels. Table 4 shows the effect of awareness of central bank monetary policy and increasing debt levels on confidence levels of bankers. Again, Deutsche Bank employees represent the least confident group, and JPMorgan Chase employees demonstrated the most neutrality. HSBC and Bank of China employees demonstrated a positive correlation between awareness of the variables and confidence, though neither was statistically significant.

One possible explanation for the positive correlation is that bankers at these firms again viewed awareness itself in positive rather than negative terms. The idea that awareness can enhance relationships between bankers and clients was a theme that recurred throughout the survey responses. Instead of seeing rising debt and central bank interventions as foreboding events heralding a major economic crisis, these bank employees saw awareness as something they could use to help clients make the right decisions. By being aware of these events, catalysts, and signals, sales specialists, financial advisors, loan processors, investment banking analysts, and risk analysts could feel more confident in their own ability to perform their banking duties. They responded that they could help clients feel informed, knowledgeable, and confident in their own decisions about how to invest, whether to take out a loan at a specific interest rate, or what types of financial products to buy.

However, this type of confidence was not shared by all bank employees. Three-fourths of employees at JPMorgan Chase felt that awareness of central bank monetary policy and rising debt levels played no part in how their confidence was formed. One reason for the lack of impact among JPMorgan Chase employees might be found in the firm's own organizational culture and risk-aversion strategies being implemented under the guidance of Jamie Dimon, who has himself been critical of both the scale of rising debt and the role of the central bank in credit tightening via monetary policy.

Deutsche Bank employees were by far the most negatively impacted by this awareness, with nearly one in two feeling that their confidence in the international banking industry was shaken by rising global debt and the monetary policy of central banks around the world. The question that remained was whether Deutsche Bank employees felt shaken in their confidence because they believed their bank lacked internal strength, or whether some other reason was at play. A post-survey question was put to these employees through member checking; the 74 respondents answered that they saw little long-term reason to be confident in the system, particularly now that free markets — especially in light of the response to the COVID-19 crisis — were fast beginning to resemble a command economy. Of those who reported a loss of confidence, the most cited concern was the erosion of free markets, followed by concern about a collapse of the USD and a default on sovereign debt that could totally upend the system and lead to open conflict among nations. This was one extreme of feeling among a minority of bank employees. The more common feeling among the majority of employees was that monetary policy and rising debt had either no effect or else a positive effect on their confidence levels.

Table 4: The Effect of Central Bank Monetary Policy and Awareness of Increasing Debt Levels on Confidence Levels

Bank / Negative Effect / No Impact / Positive Impact
JPMorgan Chase: 15% / 75% / 10%
Deutsche: 45% / 25% / 30%
HSBC: 25% / 10% / 65%
Bank of China: 5% / 35% / 60%
Mean: 22.5% / 36.25% / 41.25%

There did not appear to be any statistically significant correlation between the two variables regarding confidence and awareness of rising debt levels or central bank monetary policy. The p-value was greater than 0.05, and thus the null hypothesis was rejected. To test the assumptions of linearity, Pearson's r and regression analysis were conducted using ANOVA.

Model Summary (Research Question 3)
R: .141 | R Square: .023 | Adjusted R Square: −.016 | Std. Error of the Estimate: 6.6831
Predictors: (Constant), Awareness of central banking monetary policy and increasing debt levels around the world | Dependent Variable: Confidence

ANOVA (Research Question 3)
Regression — Sum of Squares: 53.875 | Mean Square: 28.535 | F: .642 | Sig.: .539
Residual — Sum of Squares: 2062.862 | Mean Square: 46.345
Total — Sum of Squares: 2162.182
Dependent Variable: Confidence | Predictors: (Constant), Awareness of central banking monetary policy and increasing debt levels around the world

Residuals Statistics (Research Question 3)
Predicted Value: Min 4.295, Max 9.099, Mean 7.511, Std. Deviation 1.121, N 641
Residual: Min −7.907, Max 31.598, Mean .000, Std. Deviation 6.728, N 641
Std. Predicted Value: Min −2.867, Max 1.416, Mean .000, Std. Deviation 1.000, N 641
Std. Residual: Min −1.149, Max 4.593, Mean .000, Std. Deviation .978, N 641
Dependent Variable: Confidence

The findings showed that the model was not statistically significant, as p > 0.05. The R-squared is less than 3%, making it a poor predictor. The correlation between the variables was not especially meaningful. Thus, in spite of the associations that could be drawn, statistical significance was not found. Interpretations of the data could not therefore be corroborated or supported by quantitative statistical analysis. In the end, the data suggest that more inquiry is required — either to explore additional variables that might affect confidence or to better understand the viewpoints of employees at these banks and what they perceive to be directly influencing their confidence.

References

Adrian, T., & Shin, H. S. (2010). Liquidity and leverage. Journal of Financial Intermediation, 19(3), 418–437.

ADRP 6-0. (2012). Mission command. Headquarters, Department of the Army.

Ainger, J. (2019). The unstoppable surge in negative yields reaches $17 trillion. Bloomberg.

Alonso-Trabanco, J. (2019). Geopolitics and the Asian Infrastructure Investment Bank — Analysis. Eurasia Review.

Anand, P. (1995). Foundations of rational choice under risk. Oxford University Press.

Ashton, P. (2009). An appetite for yield: The anatomy of the subprime mortgage crisis. Environment and Planning A, 41(6), 1420–1441.

Armas, A., Castillo, P., & Vega, M. (2014). Inflation targeting and quantitative tightening: Effects of reserve requirements in Peru. Economia, 15(1), 133–175.

Bauman, K. E., Fisher, L. A., Bryan, E. S., & Chenoweth, R. L. (1984). Antecedents, subjective expected utility, and behavior: A panel study of adolescent cigarette smoking. Addictive Behaviors, 9(2), 121–136.

BBC. (2019). US economy under Trump: Is it the greatest in history?

Bennett, W. L., & Segerberg, A. (2011). Digital media and the personalization of collective action. Information, Communication & Society, 14(6), 770–799.

Bernstein, J. (2019). A tight job market is a potent force against inequality and wage stagnation. The Washington Post.

Bouvatier, V., & Delatte, A. L. (2015). Waves of international banking integration: A tale of regional differences. European Economic Review, 80, 354–373.

Bruno, V., & Shin, H. S. (2015). Capital flows and the risk-taking channel of monetary policy. Journal of Monetary Economics, 71, 119–132.

Boxwell, R. (2018). How China's rampant intellectual property theft, long overlooked by US, sparked trade war. South China Morning Post.

Brown, B. (2019). Inflation and the boom-bust cycle in corporate leverage. Atlantic Economic Journal, 47(1), 25–34.

Buskins, V. (2015). Rational choice theory in sociology. International Encyclopedia of the Social & Behavioral Sciences (2nd ed.), 901–906.

Buyl, T., Boone, C., & Wade, J. B. (2019). CEO narcissism, risk-taking, and resilience: An empirical analysis in US commercial banks. Journal of Management, 45(4), 1372–1400.

Cai, K. G. (2018). The One Belt One Road and the Asian Infrastructure Investment Bank: Beijing's new strategy of geoeconomics and geopolitics. Journal of Contemporary China, 27(114), 831–847.

Chang, C., Duke, J., & Hsieh, S. (2011). A loophole in financial accounting: A detailed analysis of repo 105. Journal of Applied Business Research, 27(5), 30–45.

Clarke, H. D., Rapkin, J., & Stewart, M. C. (1994). A president out of work: A note on the political economy of presidential approval in the Bush years. British Journal of Political Science, 24(4), 535–548.

Colander, D., Goldberg, M., Haas, A., Juselius, K., Kirman, A., Lux, T., & Sloth, B. (2009). The financial crisis and the systemic failure of the economics profession. Critical Review, 21(2–3), 249–267.

Cornish, D., & Clarke, R. (1987). Understanding crime displacement: An application of rational choice theory. Criminology, 25(4), 933–947.

Cosentino, B. W. (2020). Loving yourself: How to raise your self-esteem.

Council on Foreign Relations. (2018). Geostrategic and military drivers and implications of the Belt and Road Initiative.

Cox, J. (2019). Private payroll growth tops estimates as job market shows signs of tightening. CNBC.

Dimon, J. (2017). Letter to shareholders. JPMorgan Chase.

Dijink, G. (2002). National identity and geopolitical visions: Maps of pride and pain. Routledge.

Domm, P. (2019). Falling interest rates are sending a warning signal to the stock market. CNBC.

Durden, T. (2019). Bill Dudley shocker: Ex-NY Fed president urges Fed's Powell to prevent Trump re-election. Zero Hedge.

Giles, C. (2017). Central bankers face a crisis of confidence as models fail. Financial Times.

Glasser, K. (2019). War games: Trump, Bolton, and the alleged march to fight Iran. The New Yorker.

Greenfield, H. (2010). The decline of the best: An insider's lessons from Lehman Brothers. Leader to Leader, 55, 30–36.

Haitsma, R., Unalmis, D., & de Haan, J. (2016). The impact of the ECB's conventional and unconventional monetary policies on stock markets. Journal of Macroeconomics, 48, 101–116.

Hanson, T. (2013). Failure of command at Pea Ridge, 1862. In D. Wright (Ed.), 16 cases of mission command. Combat Studies Institute Press.

Harris, R. (2013). Warning signs prior to the financial crisis of 2008: A comparative analysis. Journal of Management & Engineering, 6(1), 88–97.

Harris, M., & Raviv, A. (1990). Capital structure and the informational role of debt. The Journal of Finance, 45(2), 321–349.

Harwood, J. (2019). 5 reasons why income inequality has become a major political issue. CNBC.

Heller, R. (2017). Monetary mischief and the debt trap. Cato Journal, 37(2), 247–261.

Ho, J., & Cheng, W. (2016). Metaphors in financial analysis reports: How are emotions expressed? English for Specific Purposes, 43, 37–48.

Ho, P. H., Huang, C. W., Lin, C. Y., & Yen, J. F. (2016). CEO overconfidence and financial crisis: Evidence from bank lending and leverage. Journal of Financial Economics, 120(1), 194–209.

Huang, K., & Shang, C. (2019). Leverage, debt maturity, and social capital. Journal of Corporate Finance, 54, 26–46.

Huston, J. H., & Spencer, R. W. (2018). Quantitative easing and asset bubbles. Applied Economics Letters, 25(6), 369–374.

Japan Times. (2018). China to allow victims of IP theft to sue for damages.

Kanagaretnam, K., Lobo, G. J., Wang, C., & Whalen, D. J. (2015). Religiosity and risk-taking in international banking. Journal of Behavioral and Experimental Finance, 7, 42–59.

Lee, J. P., Lin, E. M., Lin, J. J., & Zhao, Y. (2019). Bank systemic risk and CEO overconfidence. The North American Journal of Economics and Finance.

Lewis, E. F., Hardy, M., & Snaith, B. (2013). Estimating the effect of nonresponse bias in a survey of hospital organizations. Evaluation & the Health Professions, 36(3), 330–351.

Lima, L., et al. (2016). The quantitative easing effect on the stock market of the USA, the UK and Japan: An ARDL approach for the crisis period. Journal of Economic Studies, 43(6), 1006–1021.

Loomes, G., & Sugden, R. (1982). Regret theory: An alternative theory of rational choice under uncertainty. The Economic Journal, 92(368), 805–824.

Lupton, J. (2018). 10 years after the financial crisis. JPMorgan.

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370.

Mauldin, J. (2018). The next recession might be worse than the Great Depression. Forbes.

McDonald, R., & Paulson, A. (2015). AIG in hindsight. Journal of Economic Perspectives, 29(2), 81–106.

McLaughlin, J. (2019). As concerns grow about faltering US support for UAE, China steps in to fill the void. Yahoo News.

McLean, B., & Nocera, J. (2011). All the devils are here: The hidden history of the financial crisis. Penguin.

Miquel, G. P. I., Qian, N., Xu, Y., & Yao, Y. (2015). Making democracy work: Culture, social capital and elections in China. NBER Working Paper No. w21058.

Nilakantan, N. (2010). Marketing of derivatives in the aftermath of Lehman Crisis. Synergy, 8(2), 43–53.

Ordonez, G. (2018). Confidence banking and strategic default. Journal of Monetary Economics, 100, 101–113.

Pikulina, E., Renneboog, L., & Tobler, P. N. (2017). Overconfidence and investment: An experimental approach. Journal of Corporate Finance, 43, 175–192.

Rajan, R., & Winton, A. (1995). Covenants and collateral as incentives to monitor. The Journal of Finance, 50(4), 1113–1146.

Reuters. (2018). Regulated banks soften stance on leveraged lending guidance.

Roach, S. S. (2009, February). A wake-up call for the US and China: Stress testing a symbiotic relationship. Testimony before the US-China Economic and Security Review Commission of the US Congress.

Rooney, K. (2019). Share buybacks soar to record $806 billion — bigger than a Facebook or Exxon Mobil. CNBC.

Salhin, A., Sherif, M., & Jones, E. (2016). Managerial sentiment, consumer confidence and sector returns. International Review of Financial Analysis, 47, 24–38.

SEC. (2010). Litigation Release No. 21489 / April 16, 2010. U.S. Securities and Exchange Commission.

Sen, A. K. (1977). Rational fools: A critique of the behavioral foundations of economic theory. Philosophy & Public Affairs, 317–344.

Shambaugh, D. L. (2013). China goes global: The partial power (Vol. 111). Oxford University Press.

Simon, H. A. (1972). Theories of bounded rationality. Decision and Organization, 1(1), 161–176.

Smith, K. (2019). How this trade war will remake the world. Bloomberg Opinion.

Van Lerven, F. (2016). Quantitative easing in the Eurozone: A one-year assessment. Intereconomics, 51(4), 237–242.

Walliman, N. (2017). Research methods: The basics. Routledge.