The COVID-19 pandemic and induced economic and social constraints have significantly impacted the confidence of both consumers and businesses. Despite that, comprehensive studies of the impact of the COVID-19 pandemic on the consumer and business sentiment are still lacking. Thus, in our research we aim to identify consumer and business confidence indicators’ reaction to the spread of the COVID-19 pandemic in the Eurozone, the United States, and China. For this purpose, we used the method of correlation–regression analysis. We chose the consumer-confidence index, manufacturing purchasing manager’s index, and services purchasing manager’s index as dependent variables; and the number of confirmed cases of COVID-19, the number of deaths caused by COVID-19, and the mortality rate of COVID-19 infections as independent variables. The results showed a relatively rapid and robust effect of COVID-19 in the short period, but longer-term results depended on the region and were not so unambiguous: in the case of the Eurozone, the spread of COVID-19 pandemic did not affect the consumer-confidence index (CCI) or, in the cases of the United States and China, affected this index negatively; the purchasing managers’ index (PMI) in the services sector was significantly negatively affected by the mortality risk of COVID-19 infection; and the impact on the purchasing managers’ index (PMI) in the manufacturing industry appeared to be mixed.

All countries worldwide faced the COVID-19 pandemic and had to take actions to lower the economic shock. Financial authorities play an especially significant role in economics and can help to manage the negative consequences. This article focuses on the European central bank monetary policy and actions taken for COVID-19 risk management. This research aims to identify the significant factors influencing the long-term loans for enterprises’ credit conditions in a forward-looking approach and determine the impact of the spread of COVID-19 pandemic on banking sector credit risk, financial distress, lending growth, and financial soundness indicators. This research is focused on the credit transmission channel and the role of the Pandemic Emergency Purchase Program in different countries of the euro area. To reach the main goal, panel data regression models are used. Our findings showed that the banks’ risk tolerance is a principal factor influencing long-term loan credit standards. We also identified that the spread of the COVID-19 pandemic has a statistically significant negative effect on banking sector credit risk, financial distress, banking sector profitability, and solvency. Furthermore, after analyzing the euro area banking sector, we found that liquidity increased. Hence, it means that banks have enough funds to support sustainable economic growth, but on the other side, commercial banks do not want to take credit risk because of their risk tolerance. Our research findings show the mixed effect of the COVID-19 pandemic on financial stability: while the overall financial distress decreased and banking sector liquidity increased, the profitability and solvency decreased some extent.

This paper offers a detailed analysis of the evolution of financial decision-making theories, focusing on the shift from classical finance to behavioral finance. Classical finance theories, including the Efficient Market Hypothesis and Modern Portfolio Theory, assume that investors behave rationally and that the market is efficient. However, these theories have faced criticisms highlighting the importance of considering irrational behaviors in financial markets. Behavioral finance addresses this gap by integrating psychological insights into financial decision-making. This study systematically reviews the literature on behavioral biases that affect individual investors, identifying fundamental biases and their impact on investment decisions. The analysis emphasizes the role of cognitive limitations and psychological tendencies in shaping market dynamics, influencing asset pricing, investment strategies, and market returns. The research also notes a shift in focus from market-level outcomes to the behavior of individual investors, with an increase in publications. The paper concludes that understanding investors’ biases is crucial for developing effective risk management strategies and investment recommendations, ultimately leading to improved market performance. The findings underscore the growing importance of behavioral finance in explaining investor behavior and market anomalies, highlighting areas for future research in this evolving field.

Although empirical studies show that different types of loans have different risks (moreover, consumer credit risk is higher compared to other types of loans), it is common to study the credit risk of the banking sector as a whole, or of an individual bank’s whole loan portfolio, and the macro-economic factors affecting it (without grouping them by type of loan). Thus, an analysis of the credit risk of the whole loan portfolio (measured by all non-performing loans) is insufficient. Therefore, the aim of this research is to identify the macroeconomic determinants of the consumer loan credit risk and quantitatively assess their impact in Central and Eastern European countries. After the analysis of scientific literature in the field of credit risk determinants, a detailed classification of factors influencing banking credit risk is proposed. The distinguishing feature of the classification is that the factors influencing credit risk are classified at five different levels; twelve groups of general macroeconomic conditions variables were selected as the potential factors of NPLs. This classification can be useful to better understand and investigate the factors influencing banking credit risk for the whole loan portfolio (in the same way as the factors that affect the credit risk of different types of loans, e.g., consumer loans). Using the methods of constant, fixed and random-effects panel analysis, simple OLS, least squares with breakpoints regression analysis and Markov regime-switching models, the impact of the macroeconomic variables from twelve separate groups is evaluated. The data from 11 CEE countries are used, and the period from 2008 to 2020 is covered. The results of this assessment reveal that in the group of CEE countries, such variables as GDP and labour market variables appeared to have contributed to the increase in the share of non-performing consumer loans, while inflation and real estate market variables were related to the decrease in consumer NPLs; at the same time, the impact of variables form other groups appeared to be mixed-nature or insignificant. The results of this research are useful in that they allow the identification of the most important determinants of consumer loan credit risk and thus allow making assumptions about NPL changes due to the changing macroeconomic situation. In the case of Lithuania, this kind of study (assessment of macroeconomic determinants of consumer loan credit risk) was conducted for the first time. Consumer loan credit risk assessment is especially relevant in an increasing interest rate environment, and deeper analysis can help banks and other financial institutions to manage credit risk. On the other hand, a better understanding of the main influencing factors of the macroeconomic environment can help central banks and other official institutions take appropriate monetary and fiscal policy decisions to ensure a good credit transmission channel for sustainable economic growth.

In the scientific literature, there is a lack of a systematic approach to credit risk factors. In addition, insufficient attention is still paid to analysing the macroeconomic factors of consumer loan credit risk. Thus, this research aims to evaluate the macroeconomic factors of consumer loan credit risk in Central and Eastern European countries’ banking systems. The findings of the study can be formulated as follows. After analysing scientific literature on credit risk factors, an improved and detailed (at five different levels) classification of factors influencing banking credit risk is proposed. This classification can be beneficial for more enhanced analysis of the factors influencing banking credit risk for the whole loan portfolio as well as for different types of loans, e.g., consumer loans. For quantitative evaluation of the impact of macroeconomic factors on consumer loan credit risk, the methods of panel data analysis and bivariate and multiple regressions are employed. Eleven CEE countries in the period from 2008 to 2020 are analysed. The results revealed that the aggregate of general macroeconomic condition factors is negatively related to consumer loan NPLs. Moreover, the economic growth, stock market, foreign exchange market, and institutional environment factors proved to be risk-decreasing, while credit market and bond market factors had a risk-increasing impact. The results of this research might help financial institutions manage credit risk more efficiently and also might be relevant to governments and central banks when selecting and applying fiscal and monetary policy measures. This study also makes policy recommendations.

The COVID-19 pandemic and pandemic-induced lockdowns and quarantine establishments have inevitably affected individuals, businesses, and governments. At the same time, the spread of the COVID-19 pandemic had a dramatic impact on financial markets all over the world and caused an increased level of uncertainty; the stock markets were no exception either. Most of the studies on the impact of the COVID-19 pandemic on stock markets are based either on the analysis of a relatively short period (the beginning of pandemic) or a longer period, which, in turn, is very heterogeneous in terms of both the information available on the COVID-19 virus and the measures taken to contain the virus and address the consequences of the pandemic. However, it is very important to assess the impact not only at the beginning of the pandemic but also in the subsequent periods and to compare the nature of this impact; the studies of this type are still fragmentary. Therefore, this research aims to investigate the impact of the COVID-19 pandemic on stock markets of two of the most severely affected European countries—Italy and Spain. To reach the aim of the research OLS regression models, heteroscedasticity-corrected models, GARCH (1,1) models, and VAR-based impulse response functions are employed. The results reveal that the stock market reaction to the spread of the COVID-19 pandemic differs depending on the country and period analyzed: OLS regression and heteroscedasticity-corrected models have not revealed the statistically significant impact of the spread of the COVID-19 pandemic, while impulse response functions demonstrated the non-zero primary response of analyzed markets to the COVID-19 shock, and GARCH models (in the case of Spain) confirmed that the COVID-19 pandemic increased the volatility of stock market return. This research contributes to the literature by providing a comprehensive impact assessment both during the whole pre-vaccination period of the pandemic and during different stages of this period.