Section 4 Bank Profitability

#### **Chapter 5**

## Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data

*Maria Elisabete Duarte Neves, Joana Monteiro and Carmem Leal*

#### **Abstract**

This article aims to study the determinants of banking performance in the countries of the Iberian Peninsula, Portugal and Spain. To achieve the proposed objective, the methodology of panel data was used, specifically the estimation method Generalized Method of Moments (GMM-system). An unbalanced panel of 267 banks was used, of which 122 belong to the Portuguese banking sector and 145 to the Spanish banking sector. Two variables were used as performance measures, the average return on total assets (ROAA) and the average return on equity (ROAE). The results show that bank profitability is generally influenced by internal variables, and not so much by sector-specific or macroeconomic variables. Therefore, the results suggest that management decisions are the ones that most influence performance. We conclude that bordering countries, despite having different economies, have very similar influences on bank profitability.

**Keywords:** determinants of Bank profitability, Portugal, Spain, Iberian Peninsula, GMM system

#### **1. Introduction**

Financial institutions and in particular banks capture savings from economic agents that have higher levels of liquidity to lend to those that lack liquidity [1]. When these transactions are efficient, the economy and the financial sector of the countries tend to become more solid and stable [2].

According to the financial literature ([2, 3] among others), banking performance is affected both by internal determinants and by factors external to the bank. Thus, it is consensual that the internal factors result from policies applied by their managers. Meanwhile, the external determinants that, as they are exogenous to the institution, are not within the reach of the bank's direction and management. However, they can be predicted. And if the external factors are anticipated by the banks, they will be able, on time, to face the less favorable situations.

External factors can also, according to the literature ([2, 3], among others), be divided into two categories, industry-specific factors, and macroeconomic factors. These variables are determined by characteristics inherent to the types of institutions, as well as the economic and legal environment of the country in question [4].

Thus, through the estimation technique used by Arellano and Bond [5], Arellano and Bover [6], and Blundell and Bond [7], the Generalized Method of Moments (GMM), models that will allow obtaining more efficient results will be estimated. to possible endogeneity problems.

Thus, this study aims to determine the profitability of banks operating in Portugal and Spain in the period between 2011 and 2016. The sample consists of 267 banks in the Iberian Peninsula, of which 122 are Portuguese and 145 are Spanish. Overall, the results show that internal factors are the ones that most affect bank profitability in the three samples. The variables capital, operational efficiency, and the annual growth of deposits are the factors that best explain the profitability of the banking sector, both when considering individual countries and in the joint sample. The rest of the work is organized as follows: The second section presents the most relevant studies on the subject and hypotheses accordingly. Next, the research design is presented, which includes the sample data, the variables, and the estimation method. In Section 4 the main results are discussed and finally, in Section 5 the conclusions, limitations, and lines of future research are presented.

#### **2. Literature review**

Several authors [4, 8–13] showed that the determinants of bank profitability can be internal and external, and it is also possible that external factors can be subdivided into specific industry factors and macroeconomic factors.

Internal factors are specific to banks and are normally controlled by management [8, 14]. While exogenous factors derive from the country's economic and legal environment, they do not depend on the manager [3, 4, 14]. According to these authors, internal determinants can include asset structure, asset quality, capital, operational efficiency, revenue diversification, annual deposit growth, and size.

Likewise, among the external factors we can highlight ownership, whether the banks are listed or not, the inflation, and economic growth. All these variables were used in the aforementioned studies.

#### **2.1 Bank specific determinants**

#### *2.1.1 Asset structure*

Banks tend to diversify their loan portfolio and increase liquidity to reduce risks, particularly in times of crisis [14]. Much of the literature [9, 10] agrees that this action, to other safer assets, should cause profitability to increase more quickly. These operations tend to increase operational maintenance costs, however, García-Herrero et al. [15] argue that profit should also increase.

It should be noted that the increase in the level of credit can cause a high liquidity risk, if the manager does not effectively reduce its liabilities or if it does not know how to properly finance the increase in assets [10, 11]. If these operations are carried out well, the increase in loans will increase the bank's revenues, therefore it will also increase profitability [16]. Therefore, Saona [12] and Trujillo-Ponce [10] found a positive relationship between the relative percentage of loans in a bank's assets and its profitability. Also, Tan et al. [16] confirmed that liquidity risk exerts a positive influence when considering

#### *Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*

ROAA as a measure of bank profitability in Chinese banks, however, there is a negative relationship when considering ROAE. On the other hand, Trabelsi and Trad [17] empirically showed that asset structure negatively influences ROAA and positively influences ROAE. Guru et al. [8] and Rumler and Waschiczek [9] emphasize that the asset structure negatively influences bank profitability.

Thus, it can be seen that there is no consensus regarding the sign and significance of this variable with profitability. On the one hand, more loan amounts mean higher turnover and, in principle, more results. However, more loans also translate into more processing costs, higher chances of credit losses, and the cost of maintaining required capital reserves.

Thus, according to the literature, we expose hypothesis one, with no pre-defined sign.

Hypothesis 1—There is a significant relationship between the composition of banks' assets and their profitability (with no defined sign).

#### *2.1.2 Asset quality*

According to Trabelsi and Trad [17], this variable indicates the economic and financial situation of banks, as it warns us of financial vulnerability, assessing their resilience to financial shocks.

In fact, in unfavorable times, there may be an increase in bad debt assets, causing banks to distribute a portion of their gross margin for provisions, to cover any loan losses [10]. These operations are associated with a credit risk that affects bank profitability [3]. Thus, with an increase in impairment losses on loans and accounts receivable, the quality of the assets of banking institutions may be negatively affected [10]. Mester [13] also showed that the increase in loan quality is associated with an increase in bank operating costs, which may have an opposite effect to that expected.

Empirical analyzes by Alshatti [18], Athanasoglou et al. [2], Trabelsi and Trad [17], and Trujillo-Ponce [10] found a negative association between the quality of bank assets and their profit. Similarly, Dietrich and Wanzenried [3] showed a negative influence of asset quality on bank profitability during the time of crisis (2007–2009). Garcia and Guerreiro [19], on the other hand, were faced with a negative relationship when this variable was associated with ROAA, but when they use ROAE, this relationship is positive.

In contrast, Saona [12] showed a positive relationship between asset quality and profitability of Latin American banks. The author argues that this sign is observed because Latin American banks charge their customers with paying higher prices for services provided to combat the costs associated with credit risk. He also claims that these transactions are possible because the interest of investors is not protected in those countries. Following this literature, we propose the following hypothesis:

Hypothesis2—There is a significant relationship between the quality of assets and their profitability (with no defined sign).

#### *2.1.3 Capital*

Capital refers to the amount of own funds available to support banking activity, exerting a safety net in case of hostile developments [14]. Banks with a high net worth on assets are seen as safer and less risky banks compared to institutions with lower capital, that is, well-capitalized banks are able to cope with times of crisis [3, 8]. In fact, according to Iannotta, Nocera, and Sironi [20], a better capitalization of banks

#### *Banking and Accounting Issues*

may reflect a higher quality of management. This association can help banks finance their assets with lower interest rates, as the risk of bankruptcy is reduced [3, 15], thus making increase your profitability.

However, Djalilov and Piesse [14] suggest that the increase in financing costs due to the high level of capital could negatively affect bank profitability. Thus, the authors found a positive relationship between capital and profitability in the countries that made the initial transaction, however, the countries of the former USSR did not show any relationship between capital and the profitability of their banks. Dietrich and Wanzenried [3] also showed that in the pre-crisis period, capital did not influence the profitability of the Swiss banking sector, but between 2007 and 2009 they had a significantly negative ROAA. On the other hand, Knezevic and Dobromirov [11] show that the profits of Serbian national banks are not influenced by capital, on the other hand, foreign banks are negatively influenced.

Trujillo-Ponce [10] showed that Spanish banks are positively influenced by capital when profitability is calculated using ROAA, however, when it is related to ROAE, they present a negative relationship. In contrast, the Portuguese banks analyzed by Garcia and Guerreiro [19] showed a negative association with ROAA, but insignificant with ROAE.

Other studies, such as Alshatti [18], Athanasoglou et al. [2], Rumler and Waschiczek [9], Saona [12] and Trabelsi and Trad [17] show a positive relationship between return and equity on assets. While the studies by Guru et al. [8] and Shehzad, De Haan and Scholtens [21] have a negative sign.

According to the exposed literature, the following hypothesis is proposed:

Hypothesis 3—There is a significant relationship between the capital ratio of banks and their profitability (with no defined sign).

#### *2.1.4 Operational efficiency*

Beccalli et al. [22] argue that efficiency represents the minimization of inputs (that is, consuming fewer inputs for the same level of results) or the maximization of outputs (producing more outputs for the same amount of inputs). To this, authors such as Beccalli et al. [22] and García-Herrero et al. [15], call it *X*-efficiency (best practice indicator). According to some studies [2, 4], operational efficiency is one of the indicators that most influence bank profitability. Thus, for profitability to be high, the degree of efficiency of the financial institution's management must also be high [2, 3], that is, the reduction of operating costs (administrative expenses, employees' salaries, property expenses, among others) and, simultaneously, the increase in income, lead to a high level of bank profitability [11].

Traditionally, the operational efficiency of the banking sector is calculated using the cost-to-income (CIR) ratio, that is, expenses to income, with a high value reflecting more inefficiency. Therefore, it is expected that expenses will be lower than revenues so that efficiency will positively influence banks' profitability.

Thus, some showed a negative association between bank efficiency and profit [3, 8, 10, 11, 19, 21].

For example, Ding et al. [4] concluded that the Chinese banking sector is more efficient than US banking institutions in times of crisis, however, after the crisis, the US overlaps China. Tan et al. [16] found that efficiency in Chinese banks negatively influences ROAA and positively ROAE.

According to the literature cited, the fourth hypothesis is presented:

Hypothesis 4—There is a positive relationship between operational efficiency and your bank profitability.

*Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*

#### *2.1.5 Revenue diversification*

Banking activities can be divided into traditional activities and non-traditional activities, both of which are important for bank profitability. According to Trujillo-Ponce [10], non-traditional activities arise for diversification, trying, in this way, to generate new sources of income complementing traditional activities. In this sense, Stiroh and Rumble [23] follow in stating that financial institutions have to make more profitable sources that are generated by non-traditional activities so that they increase profitability levels and manage to survive the competition.

However, DeYoung and Rice [24] argue that one cannot put all the emphasis on non-traditional activities, due to the consequent increase in profitability, since, if they are not associated with traditional activities, they become an unsound strategy, thus putting, concerned the possible profit.

Even so, studies have concluded that revenue diversification has a positive impact on profitability above the spread [25]. While Saona [12] presented a negative sign for this relationship. Tan et al. [16] showed a positive relationship between nontraditional activities and ROAA, but a negative one with ROAE. However, Elsas, Hackethal and Holzhäuser [26], Stiroh and Rumble [23], and Trujillo-Ponce [10] did not find significant differences to be able to state that diversity affects profitability.

As per the provisions, it appears that there is a relationship between the diversity of revenues and the profitability of the banking sector. Accordingly, the following hypothesis arises:

Hypothesis 5—There is a significant relationship between revenue diversity and bank profitability (with no defined sign).

#### *2.1.6 Deposit growth*

In general, deposits represent stable and cheaper resources than other types of financing, and, to this extent, they contribute to increasing bank profitability [15]. But the global financial crisis led banks to adopt aggressive policies, mortgaging their margins at the expense of paying higher rates, which contributed to the decrease in profitability [10].

Dietrich and Wanzenried [3] state that an increase in deposits also implies attending to numerous factors, such as operational efficiency, as banks must be able to convert deposit liabilities into revenue-generating assets, taking into account good credit quality. However, high deposit growth rates also attract additional competitors, affecting the profitability of banking institutions.

Thus, Trujillo-Ponce [10] did not find any relationship between the growth rate of bank deposits and Spanish bank profitability. However, Garcia and Guerreiro [19] found that the growth of deposits intervenes positively in ROAA, but that it has no statistical significance in ROAE. In contrast, Dietrich and Wanzenried [3] are faced with a negative influence on ROAA and a positive influence on ROAE.

In harmony with the exposed literature, the following hypothesis is put forward:

Hypothesis 6—There is a significant relationship between the growth rate of deposits and bank profitability (no defined sign).

#### *2.1.7 Bank size*

The size of banks is one of the characteristics that have traditionally been used to determine their levels of profitability because, in principle, the bigger the bank, the

greater the use of synergies and economies of scale, leading to a reduction in expenses and, consequently, an increase in results and profitability [14, 20]. Saona [12] claims that a large bank will incur in large operations, therefore, it will be associated with a higher risk, which, consequently, will cause the institution to charge higher margins, positively influencing profit.

However, a bank that is too large may incur diseconomies of scale as it will have an increase in variable costs, such as operating, bureaucratic and marketing expenses, negatively affecting bank profitability [2, 3]. According to García-Herrero et al. [15], the increase in size can make bank management difficult due to the occurrence of aggressive competitive strategies.

Therefore, empirical investigations [12, 16, 17] have found a positive and significant relationship between profitability and size.

Dietrich and Wanzenried [3] showed that in Switzerland the largest banks are the least profitable, following Berger and Mester [27] who had concluded the same.

In another sense, Ding et al. [4] showed that the large US banks after the crisis were the ones that were able to restructure the fastest and obtain higher levels of profitability. Once the authors had obtained a negative relationship during the crisis. Also, Elsas et al. [26] and Knezevic & Dobromirov [11] found a negative and significant relationship between size and profitability. Other empirical research does not find any significant relationship between profitability and bank size [2, 9, 10, 18, 28].

Following the exposed literature, we proposed hypothesis 7:

Hypothesis 7—There is a significant relationship between the bank's size and its profitability (with no defined sign).

#### **2.2 Industry-specific determinants**

#### *2.2.1 Ownership*

Banks can be private or public institutions, the private ones belong, essentially, to private entities (more than 50% of these institutions) and the public ones, mainly, to the State. Berger and Mester [27] argue that the more external investors there are, the greater the control, the greater the efficiency, consequently the greater the profitability.

However, there is much empirical evidence that this variable does not influence the institution's profit [2, 18, 28].

DeYoung and Rice [24] and Knezevic and Dobromirov [11] found a negative relationship between ROAE and ROAA, respectively. Dietrich and Wanzenried [3] also concluded that ROAA is negatively influenced by the type of property, however, this is not statistically significant when the performance index is the ROAE.

In contrast, Rumler and Waschiczek [9] show that banks with public capital positively influence ROAE. Under these points of view the following hypothesis is placed:

Hypothesis 8—There is a significant relationship between the nature of bank ownership and its profitability (with no defined sign).

#### *2.2.2 Stock exchange quotation*

According to Beccalli et al. [22], information on the earnings of institutions can be incorporated into stock prices, however, changes in stock prices do not properly reflect the extent of changes in earnings. Dietrich and Wanzenried [3] argue that the fact that listed banks negatively affect institutions' profits makes them subject to greater requirements, such as additional reporting and greater market scrutiny. This

*Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*

fact may affect the profitability of banks with the additional costs that they entail. However, financial institutions listed on the stock exchange that has a positive influence on performance will suffer greater pressure from the financial market (shareholders, financial analysts, etc. … ).

Iannotta et al. [20] showed that the stock market positively affects bank profitability.

On the other hand, Dietrich and Wanzenried [3] faced a negative influence when using ROAA. García-Herrero et al. [15] showed that banks present on the stock exchange are not more profitable than those that are not.

By the way, the hypothesis to be tested will be:

Hypothesis 9—Banks listed on the stock exchange have greater profitability than unlisted ones.

#### **2.3 Macroeconomic determinants**

#### *2.3.1 Inflation*

Inflation can influence profitability depending on how it interferes with operating income and costs. Thus, if management manages to forecast the inflation rate, it can regulate interest rates appropriately, to increase revenues faster than costs [11]. Otherwise, banking costs will be higher than revenues and will negatively affect the profitability of banking institutions.

Athanasoglou et al. [2], García-Herrero et al. [15], Guru et al. [8], Rumler and Waschiczek [9], Saona [12], and Tan et al. [16] confirmed that the relationship between inflation and bank profitability is positive. However, Djalilov and Piesse [14] and Shehzad et al. [21] did not find a significant relationship between profitability and this variable. Trabelsi and Trad [17] and Trujillo-Ponce [10], in turn, showed that ROAA is positively influenced by the inflation rate while ROAE is negatively affected.

Following the literature, we propose the following hypothesis:

Hypothesis 10—There is a direct relationship between inflation and bank profitability (with no defined sign).

#### *2.3.2 Economic growth*

Economic growth varies over the years as the economy goes through several economic cycles. On the one hand, if the country's economic conditions are unfavorable, this could mean an increase in banks' provisions due to the loss of credit and the poor quality of assets mortgaged to profitability. On the other hand, if the country's economic conditions are favorable, the demand for credit from households and companies will increase and, consequently, so will profitability [10, 14].

However, Saona [12] concluded that in periods of strong economic growth, banks may tend to adjust their margins, leading to lower results and profitability. That said, Athanasoglou et al. [2], Dietrich and Wanzenried [3], Lee and Kim [28], Rumler and Waschiczek [9], Trabelsi and Trad [17], and Trujillo-Ponce [10] show a positive relationship between economic growth and economic profitability. While other investigations [11, 14, 15] have not found any relationship between economic growth and bank profitability. However, Saona [12] and Shehzad et al. [21] showed a negative association between Gross Domestic Product (GDP) and bank profitability. Finally, Garcia and Guerreiro [19] concluded that GDP negatively affects the banking sector if it is analyzed with the ROAE profit indicator, however, if it is related to ROAA, the sign becomes insignificant.

In line with the provisions, we propose the following hypothesis to be tested: Hypothesis 11—The country's GDP influences bank profitability.

#### **3. Research design**

#### **3.1 Sample data**

The sample, for the period between 2011 and 2016, is composed of 267 Iberian banks, of which 122 are Portuguese and 145 are Spanish. All databases without complete data for at least four consecutive years were excluded, a necessary condition for second-order correlation estimation [5]. As the second-order correlation is a GMM assumption, and this will be the estimation method used, this correlation must be tested [29]. Data to calculate bank- and industry-specific variables are sourced from Orbis Bank Focus, Bureau van Dijk database. While the macroeconomic variables come from The World Bank<sup>1</sup> .

#### **3.2 Sample variables**

#### *3.2.1 Dependent*

ROAA and ROAE have traditionally been used as measures of banking performance and to that extent are also the variables that we will use as dependent variables.

The average return on total assets (ROAA) is the ratio between Ebit and total assets [2, 30]. Garcia and Guerreiro [19] state that ROAA portrays management efficiency and is, therefore, an imminently economic indicator. Return on average equity (ROAE) is the ratio of net income to equity [2]. Rumler and Waschiczek [9] suggest that ROAE is a more popular performance measure among financial analysts.

This indicator translates into shareholder returns and, as such, there may be pressure from shareholders to distribute results, threatening the capitalization of banks. we know that the asset may be valued at acquisition cost, which can lead to the undervaluation or overvaluation of the elements that comprise it, thus influencing the ROAA ratio.

#### *3.2.2 Independent variables*

**Table 1** presents the explanatory variables to be used in the regression models, highlighting their internal origin, intrinsic to management, or external, without direct influence from the manager.

#### **3.3 Methodology**

Considering ROAE and ROAA as the dependent variables and the independent variables as defined previously, we obtain the following models:

$$\begin{aligned} \text{ROAE}\_{\text{it}} &= \beta\_0 + \beta\_1 \text{AS}\_{\text{it}} + \beta\_2 \text{AQ}\_{\text{it}} + \beta\_3 \text{EQ}\_{\text{it}} + \beta\_4 \text{CIR}\_{\text{it}} + \beta\_5 \text{RD}\_{\text{it}} + \beta\_6 \text{ADG}\_{\text{it}} \\ &+ \beta\_7 \text{SIZE}\_{\text{it}} + \beta\_8 \text{Owner} + \beta\_9 \text{Quotedted} + \beta\_{10} \text{INF}\_{\text{it}} + \beta\_{11} \text{GDP}\_{\text{it}} + + \mu\_{\text{it}} \end{aligned} \tag{1}$$

<sup>1</sup> https://data.worldbank.org/.

*Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*


#### **Table 1.**

*Specific characteristics of banks, industry-specific characteristics, and macroeconomic factors.*

$$\begin{aligned} \text{ROAA}\_{\text{it}} &= \pounds\_{0} + \pounds\_{1} \text{AS}\_{\text{it}} + \pounds\_{2} \text{AQ}\_{\text{it}} + \pounds\_{3} \text{EQ}\_{\text{it}} + \pounds\_{4} \text{CIR}\_{\text{it}} + \pounds\_{5} \text{RD}\_{\text{it}} + \pounds\_{6} \text{ADG}\_{\text{it}} \\ &+ \pounds\_{7} \text{SIZE}\_{\text{it}} + \pounds\_{8} \text{Owner} + \pounds\_{9} \text{Quoteded} + \pounds\_{10} \text{INF}\_{\text{it}} + \pounds\_{11} \text{GDP}\_{\text{it}} + + \mu\_{\text{it}} \end{aligned} \tag{2}$$

To estimate these models, the GMM dynamic model was used, initially proposed by Arellano and Bond [5] and improved by Arrellano and Bover [6] and Blundell and Bond [7]. By using the GMM method, we solve two fundamental problems such as endogeneity and unobserved heterogeneity [14, 15, 29].

#### **4. Results**

#### **4.1 Descriptive statistics**

This chapter describes descriptive statistics (mean, minimum, maximum, and standard deviation) for the variables used in the sample. From what can be seen in **Table 2**, the study shows a positive mean of the dependent variables for all the years under observation. It is also observed, in the three samples, that the means of the independent variables are mostly positive, except GDP in the samples from the Iberian Peninsula and Portugal. Regarding the standard deviation, it can be seen that the annual growth of deposits is the variable that presents the highest value for the samples from the Iberian Peninsula and Spain. While Portugal presents the asset quality variable with the greatest discrepancy to the average.

#### **4.2 Discussion results**

**Table 3** presents the results for the banks of Portugal and Spain as the Iberian Peninsula, and **Table 4** an individual analysis of the determinants that affect the profitability of these two border countries. Thus, economic growth exhibits a statistically significant and positive sign for the joint analysis (**Table 3**). Such evidence may be due to the increase in credit on the part of families and companies after the financial crisis. As well as, a decrease in bad debt assets, during some favorable economic growth of the countries. Since in favorable growth situations, borrowers can meet their debts. By the provisions, hypothesis 11 is corroborated, following the results found by Lee and Kim [28], Rumler and Waschiczek [9], and Trabelsi and Trad [17]. Regarding inflation, this influences positively and significantly both the Iberian banking sector and the Portuguese banking sector (**Table 4**). However, banking in Portugal is only influenced by the operating performance index, which is the ROAA. In this way, hypothesis 10 is supported by the studies by Rumler and Waschiczek [9], Tan et al. [16], and Trujillo-Ponce [10]. This reveals that the managers of the banks under analysis can predict the rate of inflation, properly regulating interest rates so that revenues increase faster than expenses. On the other hand, an increase in inflation can also translate into an increase in the purchasing power of the population in general, so this increase can mean more deposits, more credit compliance, safer, therefore more profitability. The asset structure presents a negative and statistically significant result concerning the ROAE of the sample of Iberian and Portuguese banks. In fact, the asset structure of Spanish banks (**Table 4**) also shows the same sign for both dependent variables. By the provisions, it is clear that it is possible to corroborate hypothesis 1. This evidence is supported by the results of Rumler and Waschiczek [9] and Tan et al. [16]. This means that the banking sector is not able to efficiently manage and increase the loan portfolio in the period under review. A period that is characterized by strong competition and banking competitiveness, as banks were under great pressure to attract customers. However, an increase in the loan portfolio implies increases in operating costs, so if interest rates are not well adjusted, they will become incapable of supporting operating expenses, harming banks' profitability. As well, the increase in the loan portfolio can also lead to a high risk of credit defaults. It appears that the sign of the variable capital is positive in both Tables. That said, hypothesis 3 is corroborated. This evidence shows that Portuguese and Spanish banks are well-capitalized.

Regarding **Table 3**, Banks that present better levels of capital denote a lower risk of bankruptcy, they are considered.

with lower financing costs, therefore they can obtain higher gross margins, which leads to higher levels of profitability. These results are in line with the investigations of Garcia and Guerreiro [19], Trujillo-Ponce [10], and Saona [12]. Consistent with hypothesis 2, the results in **Table 4** show that asset quality negatively and significantly affects the ROAA of Portuguese banks and both performance indicators relative to Spain. This is due to the increase in impairment losses on loans, which negatively


*Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*

> **Table 2.** *Descriptives*

 *statistics.*


#### *Banking and Accounting Issues*

**Table 3.** *Estimationresults*

 *of models 1 and 2 for the Iberian Peninsula.*

*asymptotically*

 *distributed as* N *(0,1) under the null hypothesis of no serial correlation.*

 *The AR(2) test indicates that there is no second-order*

 *serial correlation.*


**Table 4.** *Estimation*

 *results for Portugal and Spain.*

#### *Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*

affects the performance of banking institutions. Naturally, in dire economic cycles, which is the case in the sample period, households tend to default on credit. Therefore, the period from 2011 to 2016 is marked by losses of millions of euros in loans to customers, which was noted in the financial statements of institutions. And once banks have a significant increase in bad debt assets, they tend to distribute their gross margin to cover expected losses [10]. This result is in line with the results obtained by Alshatti [18], Athanasoglou et al. [2], Trabelsi and Trad [17] and Trujillo-Ponce [10].

Regarding the operational efficiency variable, it manifests itself with a negative and significant sign in both Tables. The negative and significant coefficient of the cost-to-income ratio shows that poor expenditure management is one of the main contributors to poor profitability performance. In other words, to obtain a higher performance it is necessary to have a decrease in expenses and/or an increase in income [11]. The result obtained is under the empirical analysis by Dietrich and Wanzenried [3] and Shehzad et al. [21], that is, the higher the CIR, the lower the efficiency and therefore the profitability.

The annual growth rate of deposits is showing a statistically significant and positive sign. Indeed, hypothesis 6 is corroborated, following the result obtained in the investigation by Dietrich and Wanzenried [3] and Garcia and Guerreiro [19]. The increased demand for deposits increases bank profitability both in the Iberian Peninsula and in Portugal and Spain. Banks may be benefiting from the increased purchasing power of depositors following the effects of the financial crisis. To that extent, there will be no need to incur aggressive policies (which can negatively affect performance through lower margins) to attract a greater number of depositors. Finally, as happened with the authors Saona [12] and Tan et al. [16], and corroborating hypothesis 5, the results of Portuguese banking show a negative and significant sign for the variable revenue diversification, for both profitability indicators. This result suggests that non-traditional activities, by themselves, do not boost Portuguese banking profitability.

Also, DeYoung and Rice [24], had already warned that if banks did not associate these activities with traditional activities, they could incur losses. Despite this, this result may be due to charges, for example, with securities. As a means of recapitalization, to comply with the rules established by the Basel III agreement, banks were subject to CoCos (Contingent Convertible Bonds) bonds, however, the financial charges with the high-interest rates of these bonds may have harmed the banks' performance. Portuguese.

It should be noted that the significant variables in the three samples always show the same sign, which somehow gives credibility to the results found. In the sample of Spanish banks, it is possible to verify that the explanatory variables are exactly the same using the ROAA or the ROAE as dependent variables, which similarly suggests that the explanatory variables were well selected. In general, when operating profitability is used as a performance measure, the variables that remain significant in all samples are bank capitalization, operating efficiency measured by the CIR and the growth of deposits.

Likewise, when using ROAE as a performance measure, the signs and significance of these variables remain unchanged and the composition of assets is added as a determinant of return on equity. These results suggest that the role of managers is fundamental in defining and monitoring capital and deposit growth ratios to improve performance. Furthermore, it is necessary to improve operational efficiency as well as maximize the asset structure, which in a highly competitive environment has not been able to increase bank profitability levels.

*Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*

#### **5. Conclusion**

The economic and financial stability of banking institutions is important for the economic stability of the country where the sector is located. Therefore, satisfactory levels of profitability can translate into the stable financial health of countries.

This study aimed to analyze the factors that influence the profitability of Portuguese and Spanish banks, during a period between 2011 and 2016.

The empirical study was carried out considering three sub-samples to observe the Iberian Peninsula as a whole, and each country individually in order to understand the differences in the determinants of profitability in these two border countries. However, our results show that the profitability of Portuguese and Spanish banks is mostly influenced by the same internal variables, which shows that, probably, the fact that they are neighboring countries can lead to similar behavior of managers. These management decisions are those that exert the greatest influence on bank profitability.

In particular, it can be seen that the performance of banks, both in the Iberian Peninsula as a whole and in Portugal or Spain, is positively influenced by demand from depositors. Likewise, it is possible to verify that the more capital the financial institutions of both countries hold, the better their capacity to face adverse situations.

Finally, it is concluded that if Iberian banks do not efficiently manage their expenses and costs, they incur a poorly applied operational policy, negatively influencing the profitability of these institutions.

Therefore, despite different economic systems, Portugal and Spain have similar internal banking policies. This may be due to the strong presence of Spain in the Portuguese financial sector, establishing management methods that are very similar to each other.

Since in this work, only Iberian banks were used and to that extent, the sample is small, which may constitute a limitation in the extrapolation of these results, we propose to analyze in future work a broader set of countries with different legal and institutional environments, using an example to an additional efficiency model such as the DEA.

#### **Acknowledgements**

This work is supported by national funds, through the FCT—Portuguese Foundation for Science and Technology under the project UIDB/04011/2020. *Banking and Accounting Issues*

#### **Author details**

Maria Elisabete Duarte Neves1,2\*, Joana Monteiro2 and Carmem Leal2

1 Polytechnic of Coimbra, Coimbra Business School Research Centre|ISCAC, Quinta Agrícola-Bencanta, Coimbra, Portugal

2 Centre for Transdisciplinary Development Studies, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal

\*Address all correspondence to: mduarteneves@gmail.com

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Determinants of Banking Profitability in Portugal and Spain: Evidence with Panel Data DOI: http://dx.doi.org/10.5772/intechopen.103142*

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Section 5

## Financial Assets and Pandemics

**Chapter 6**

## Pandemics and Financial Assets

*Pattarake Sarajoti, Pattanaporn Chatjuthamard and Suwongrat Papangkorn*

#### **Abstract**

There have been several pandemics in the history of mankind. One of the major pandemics was the Spanish flu that took place in 1918, in which millions of lives were lost globally. Despite significant advances in science and medicine since then, the COVID-19 pandemic has still caused major impacts around the world. As evidenced, pandemics not only cause social and public health implications, but also cause effects on the economy as well. This chapter addresses the ill effects of pandemics on the economy and presents how the financial markets and financial institutions were influenced and how they responded to the pandemics. More specifically, this chapter identifies the effects of the pandemics on various assets (e.g., crude oil, gold, currencies, equity, bonds, and cryptocurrencies) around the world. In addition, the chapter also presents evidence of corporates' characteristics relative to their responses to the ill effects of the pandemics.

**Keywords:** pandemics, COVID19, capital markets, financial markets, financial assets, corporate governance

#### **1. Introduction**

It is now almost evident that our world seems to have entered into an infinite loop of new outbreaks of variants of the coronavirus that led to the COVID 19 pandemic. Beginning in early 2020, the coronavirus spread throughout the world and caused concern, as reflected in the world stock indexes. Even in the third year of this ongoing pandemic, it is clear that, despite vaccination and awareness, the new variant Omicron is causing investors to panic [1, 2]. Due to the extreme impacts of these epidemics, it is critical to investigate pandemics and their pessimistically veiled aspects to develop effective strategies. In this chapter, we will explore how this health outbreak impacted the economy and financial markets and how market participants responded to the pandemic.

The rest of the chapter is organized as follows. In the following sections, we review the literature on how the pandemic impacts the equity market and provide a brief discussion on how COVID-19 differs from other crises. Section 3 presents a discussion of how the pandemics impact other financial assets, including communities, foreign exchange, and cryptocurrencies. The fourth section analyzes corporate characteristics relative to their responses to the ill effects of the pandemic. Lastly, we end with the concluding remarks.

#### **2. Pandemic and financial market**

#### **2.1 Prior pandemic**

Throughout human history, there have been numerous health outbreaks, such as foot and mouth disease, severe acute respiratory syndrome (SARS), bird flu (H5N1), and swine flu (H1N1). During the SARS outbreak in 2003, a total of 8098 people worldwide became sick, and 774 people died. Even though SARS is contagious and spread by close person-to-person contact, it is short-lived, with only 8 months separating the first reported case and the end of the crisis. While Ebola was first seen in West Africa, unlike other outbreaks, Ebola killed 86 people on the first day of the disease. It has shown fatality rates ranging from 25–90% in past outbreaks. These outbreaks have significant social and economic impacts, such as increasing social tension and people's health as well as the economy.

Barro et al. [3] calculated that the death rate of the 1918–1920 Spanish influenza pandemic would imply a 6- to 8-percentage-point drop in GDP and consumption in a typical country. Other researchers, on the other hand, have shown that a health outbreak can have a significant impact on the stock market and real economic activity. During the SARS outbreak, for example, the growth rate of household income fell by more than 3% [4], while the average price of Hong Kong real estate fell by 1.6% [5]. In the same way, Ichev & Marinč [6] found that the 2014–2016 Ebola outbreak events were followed by bad financial market returns.

The epidemic had the most serious impact on the tourism industry: hotels, restaurants, theme parks, and airlines. Chen et al. [7] found that within a month of the SARS outbreak, Taiwanese hotel stocks experienced steep declines in earnings and stock prices (approximately 29%), while the manufacturing, retail trade, and banking industries were less affected. Meanwhile, some industries benefited from concerns about health outbreaks. During the SARS outbreak, the biotechnology sector emerged stronger [7]. Similarly, the study by Donadelli et al. [8] documented that diseaserelated news has a positive impact on pharmaceutical stocks. As a result, investors shifted their assets from the financial market to the relatively low-risk real sector [9].

The impact of the health outbreak does not only affect the economy and investors' behavior; it also influences corporations' operations and strategies. Health outbreaks have led to great uncertainty about future cash flow, and investors may reduce investment due to uncertain demand and limited budgets. Besides the uncertainty of the epidemic, which increases default rates on credit cards and mortgages [10], the cost of bank loans, restrains the volume of bank lending [11]. While the approval of vaccines significantly mitigates the adverse impact of the outbreak [11].

Media coverage of major disasters, such as the Ebola outbreak, can heighten anxiety, depression, and terror, leading to risk aversion and pessimism among investors. Del Giudice and Paltrinieri [12] investigated observed monthly flows of geographically specialized equity mutual funds in African countries during the Ebola outbreak. They discovered that the disease outbreak had a statistically significant negative impact on monthly net flows. The effect was especially strong when linked to the event's media coverage. In a similar vein, Ichev and Marinč [6] proposed that outbreak events are more relevant for companies that are geographically closer to both the outbreak's birthplace and the financial markets.

In short, the external and unexpected shocks from health outbreaks can affect economic trends and suddenly change investors' sentiment. The magnitude of the adverse impact also depends on the industry, media coverage, and geographic area.

#### **2.2 Why is the COVID-19 crisis different from other crises?**

In 2008, the global financial crisis triggered a massive liquidity crisis as authorities hurried to implement emergency assistance packages to save financial institutions and enterprises. It saw the demise of well-known financial institutions such as Lehman Brothers, Freddie Mac, and Fannie Mae, as well as Northern Rock. It's important to recognize that the pandemic issue is very different from the global financial crisis of 2008. The COVID-19 pandemic is a health-related disaster that has far-reaching consequences not just for global economies but also for our everyday lives.

While no two epidemics are comparable, the current pandemic is fundamentally different from previous outbreaks. COVID-19 is much more dangerous than previous outbreaks [13–15]. Compared to other health outbreaks, the number of deaths COVID-19 has caused (more than 5.64 million people as of January 28, 2021) is actually more comparable with previous flu pandemics. More stringent public health measures that disrupt economic activity were implemented in response to the pandemic. As a result, the COVID-19 pandemic disaster has paralyzed the world more than any other crisis. Empirical evidence also suggests that the impact of European and US markets during the era of COVID-19 is high as compared to the GFC time [16]. Additionally, the implied volatility index (VIX), also known as the "fear gauge," has moved and has risen to its highest level since the GFC, while the US 10-year treasury yield index has fallen to a new low [17]. In addition, unlike other disease outbreaks, only WHO's public health risk announcements related to COVID-19 had a significant negative effect on stock markets, at least for 30 days [18].

Overall, no pandemic is likely to have had such a devastating economic impact as COVID-19, which caused a near-total shutdown of social and economic activity.

#### **2.3 Equity market and COVID-19**

In December 2019, the COVID-19 outbreak was triggered in the city of Wuhan, which is in the Hubei province of China. More than 2 years have passed, and the virus is still spreading over the planet. Although China was initially the epicenter of the outbreak, instances are now being reported in a variety of other nations. The impact of the outbreak was not only the slowing down of the Chinese economy with interruptions to production, the functioning of global supply chains has also been disrupted. The outbreak triggered fears and uncertainty in the financial markets, resulting in lower market returns and increased stock market volatility [18–22]. As a result, investors suffered significant losses in a short period of time due to a very high level of risks [23]. This, in turn, has led to more financial market turmoil and made the economic shock even worse. Compared to previous pandemics, there was more borrowing and more debt among businesses and households during this time. This makes the short-term shocks more powerful than in the past.

During periods of high economic policy uncertainty, especially during COVID-19, economic policy uncertainty has a significant impact on the financial stock market and affects investment returns. Various studies have examined the impact of investor sentiment on the stock market during the pandemic. Some researchers use the VIX as a proxy for investors' general attitude or tone toward future cash flows and investment risk of a particular security or financial market (e.g., [15, 24, 25]). An increase in VIX indicates a greater need for risk protection and higher market volatility. In particular, the VIX is used to quantify investors' fear. One of the early studies by Baker et al. [14] examined the US stock market volatility based on the daily news headlines

and found that the pandemic had an unprecedented effect on VIX, especially after February 24, 2020. In addition, they argued that no prior infectious disease outbreak has resulted in daily stock market swings as dramatic as the response to COVID-19 developments in 2020. One of the possible explanations for this result would be the government's limits on commercial activity and deliberate social separation, which have powerful consequences in a service-oriented economy.

Other researchers focused on the implied volatility derived from stochastic volatility models (e.g., [26–28]). For instance, Mirza et al. [28] evaluated the price reaction, performance, and volatility timing of European investment funds during the outbreak. They found that social entrepreneurship funds outperformed their counterparts during the epidemic. These results reflect the reality that as the world becomes increasingly uncertain, investors are putting more emphasis on social aspects. Stock volatility, however, is not directly observed in practice, but rather inherently latent. Thus, some researchers recommend using so-called realized volatilities, which are calculated by adding the squared intraday interval return, as a proxy for volatility. Chatjuthamard et al. [29] separated the realized volatility into continuous and discontinuous jump components to investigate the impact of COVID-19 on the global stock market. They found that an increasing the growth rate of COVID-19 confirmed cases would lead to increased volatility and jumps while reducing the return. Besides, they also found that the risk from COVID-19 overshadows economic, financial, and political risks. Overall, these studies highlight the fact that COVID-19 caused pronounced market movements, extreme volatility, and unprecedented disruption to the economy.

Though the pandemic has been found to disrupt the financial market, some industries have been more affected than others. In the wake of the pandemic, some industries (such as transportation, hotels, and restaurants) have ceased operations, while others continue to operate to provide basic requirements (e.g., communication, healthcare, and pharmaceuticals). As a result, investment and consumption patterns have shifted dramatically. Some of the losses are attributable to investors' realistic estimate that profits may drop as a result of the pandemic's effects. For instance, Mazur et al. [30] found that during March 2020, natural gas, food, healthcare, and software sectors performed abnormally well, generating high returns, whereas petroleum, real estate, entertainment, and hospitality stocks plummeted considerably, losing more than 70% of their market capitalizations.

In light of the growing disruptions caused by the COVID-19 pandemic, the information flow related to the pandemic is critical. The higher media coverage in the pandemic period led to negative sentiments which caused markets to decline and volatility to rise. This view is supported by Haroon and Rizvi [31], who found panic by news outlets has been linked to increased stock volatility and the association is stronger for industries severely affected by the pandemic's occurrences. Researchers show the number of confirmed COVID-19 cases and deaths could be predictive factors of financial assets, such as stock volatility [19, 32], oil prices [33], and cryptocurrencies [34]. Similarly, Baker et al. [14] documented that news related to COVID-19, both positive and negative, is the dominant driver of large daily U.S. stock market moves. With technological advancement, a growing body of literature seems to agree that investors' attention and trends measured by internet activities, such as Google Trends, Twitter tweets, and other social media trends, could possess predictive power for trading volume and volatility of financial assets. This view is supported by Chatterjee and French [35], who documented that equity market volatility and liquidity are more sensitive to the uncertainty contained in tweets, as measured by the Twitter market uncertainty index (TMU), during the outbreak. Interestingly,

#### *Pandemics and Financial Assets DOI: http://dx.doi.org/10.5772/intechopen.103972*

previous research has established that fake news and media coverage during the outbreak has had an adverse effect on some countries' stock market returns [36].

The timeframe could be considered another determinant of the impact of the coronavirus on the global market. The global market's uncertainty increased when the coronavirus moved from epidemic to pandemic stage (11th March 2020 onwards) [37]. The equity market dramatically fell during the pandemic stage, evident from the higher negative return.

Another factor that could impact the relationship between the COVID-19 situation and the stock market is government interventions. The government has played a critical role in addressing the crisis caused by this disease outbreak. During the recent pandemic, governments implemented a variety of policies to mitigate the pandemic's impact. Globally, travel bans (i.e., closing international borders), lockdowns (i.e., restricting people's movement), and fiscal stimulus and relief packages (e.g., monetary policy, interest rates, quantitative easing, and corporate bond liquidity stabilization fund) were implemented. Stock markets responded positively to these policies because they could slow the spread of the disease and potentially calm panic. This view is supported by Narayan et al. [38], who investigated the effects of the G7 countries' government responses to the pandemic. They discovered that stock markets reacted favorably to government policies, particularly lockdowns. Baker et al. [14] agreed, finding that lockdowns and voluntary social distancing were the primary reasons why the US stock market reacted much more negatively to COVID-19 than to previous pandemics.

Government interventions signal changes in future economic conditions, which may affect company cash-flow expectations and, as a result, stock prices. As a result, investors may revise their portfolios, resulting in increased volatility within and across asset classes. In line with this notion, Zaremba et al. [39] investigate the relationship between COVID-19 pandemic policy responses and stock market volatility in 67 countries. Surprisingly, their findings suggested that stringent policy responses increase return volatility and that the effect is unrelated to the increase in confirmed COVID-19 cases and deaths. One implication of these findings is that, while government interventions may slow the spread of the pandemic, they may also increase volatility in financial markets, resulting in widespread sales of risky assets.

Though in previous health crises, the geographical location of the outbreak determined the relationship between the event and the financial market, globalization has brought economies closer together and strengthened the interdependence of financial markets around the world. The number of COVID-19 deaths in one country influences not only the performance of the local stock market but also the stock markets of other countries and commodities. Akhtaruzzaman et al. [40], for instance, found that listed firms across China and G7 countries experience a significant increase in conditional correlations between their stock returns as the pandemic's trajectory develops. China and Japan appeared to be net spillover transmitters, implying that financial contagion follows a pattern similar to virus infection. He et al. [41] suggested that the impact of COVID-19 on the European and US stock markets has a spillover effect on the Asian stock markets, particularly China. In addition, they also reported no evidence to suggest that the outbreak has had a negative impact on these countries' stock markets greater than the global average, as measured by the S&P Global 1200 index.

Conversely, some authors claim that the pandemic has accelerated the trend of de-globalization and de-dollarization [42]. Okorie and Lin [43] observe that the fractal contagion effect occurs only in the short run and that it disappears in the middle

and long run for both stock market return and volatility. Similarly, Ali et al. [37] split the timeframe into three phases, beginning with casualties in China (which shows China as the epicenter of the epidemic), moving to the start of casualties in Europe (which shows Europe as the epicenter of the epidemic), and finally, when casualties began in the United States (the new epicenter). Unlike in previous pandemics, the levels of volatility in the Chinese market did not change significantly during all three phrases, indicating a lower level of global integration and early efforts by the authorities to stop the virus's spread.

When faced with the unknown upheaval of the coronavirus crisis, investors fear and avoid taking any risks, leading them to engage in irrational behavior. After the GFC, investors are more sensitive to asset losses. As a result, they are more likely to imitate the behavior and actions of other investors based on private information or public knowledge about their behavior. This irrational behavior can lead to significant mispricing and might create additional risks in financial markets. In finance, this kind of action is also known as herding behavior. Prior literature suggested that, under extreme market conditions induced by COVID-19, herding behavior is more pronounced for upside market movement, lower market trading volume, and lower market volatility [44]. Similar results are also found in the cryptocurrency market [45] and crude oil market [46].

Everyone has an incomplete view of the world. But we form a complete narrative and fill in the gaps. Our past experiences shape who we are today, as well as our decision-making process. Likewise, it has been suggested that prior exposure to similar events can influence risk aversion and investment decisions [47]. This notion is also true during the recent pandemic. Researchers found supporting evidence for the imprint theory in the behavioral bias of investors. Investors who have previously experienced such crises are more likely to react promptly than those without such experience or imprints. In addition, the timely attention and proactive responses to coronavirus situations of both individuals and governments are more prominent in nations with previous health outbreak experiences [48]. It was found that during the COVID-19, countries that had SARS 2003 saw less return and volatility spillover between stock markets [49]. This could imply that companies with past pandemic experience were found to make better decisions in the coronavirus outbreak. However, researchers also found that the experience of the current pandemic also impacted investors' decisions. Brands with names resembling aspects of the "coronavirus" began to experience abnormal losses and sustained periods of trading volatility [50]. Likewise, Yue et al. [51]'s findings showed that households that know someone infected with COVID-19 lose confidence in the economy and are more likely to change their risk behavior and become risk-averse.

In view of all that has been mentioned so far, it seems that the recent pandemic COVID-19 has exacerbated financial market volatility and the economic shock. Nevertheless, the impacts of COVID-19 are heterogenous across industries, time frames, governments, and the flow of information.

#### **3. Alternative investment and COVID-19**

As investors worry about the pandemic's economic consequences, the volatility has spiked, in some cases to levels last seen during the global financial crisis. Market liquidity has deteriorated significantly and investors embraced alternative investments in their portfolio for higher returns and shifting away from low-yield debt

#### *Pandemics and Financial Assets DOI: http://dx.doi.org/10.5772/intechopen.103972*

securities. As part of this trend, precious metals [52–55], bitcoin [52, 53], commodities [56, 57], and foreign exchange currencies [54, 58, 59] are all considered safehaven assets in periods of financial crisis.

Precious metals, such as gold, silver, platinum, and palladium, are considered effective diversifiers against stock market returns in several developed and emerging economies. They can help investors build a portfolio that mitigates the downside market risk. Ji et al. [56] evaluated the safe-haven role of assets from December 2019 to March 2020. By observing the downside risk (i.e., the left-tail of the return distribution), they argued that gold has an irreplaceable role in preserving the value of investment during the recent crisis. Besides, many countries have adopted unconventional macroeconomic measures in response to the COVID-19's impact on the exchange rate and to prevent disruption in the long-term downward trend in exchange rate volatility. And gold serves as a safe-haven asset to protect against the risk of exchange rate depreciation [60].

Yet, with the unique characteristics of COVID-19, gold could not always act as a safe haven. This view is supported by Akhtaruzzaman et al. [52], who found that gold served as a safe-haven asset for stock markets only from December 31, 2019 to March 2020. However, from March 17 to April 24, 2020, gold failed to protect investor wealth and became a hedge instead. This interesting result confirms the findings reported by Cepoi [36], who observed the gold return has a nonlinear positive correlation with the stock markets, which intensifies during extreme bearish and bullish periods, indicating that gold does not behave as a safe-haven asset. Likewise, Cheema et al. [54] suggested that during the pandemic, investors might have lost trust in gold and preferred liquid and stable assets rather than gold. Taken together, it is unclear whether gold acts as a safe haven during the COVID-19 turmoil.

Some claim that cryptocurrency or digital currency is distinct from financial assets and that it might be viewed as a new form of virtual gold. It is frequently portrayed as a panacea capable of replacing financial institutions and protecting the global financial system from sovereign risk and vulnerability [61]. Furthermore, the cryptocurrency appears to be unrelated to stock market returns [61, 62] and exchange rate [63]. Therefore, they are an ideal asset to reduce financial risks during periods of crisis. During the COVID-19, some researchers suggested that cryptocurrencies, such as Bitcoin, could play an important role as a safe haven (for example see [64–66]). Goodell and Goutte [65] applied wavelet methods to daily data of COVID-19 deaths and Bitcoin prices from December 31, 2019 to April 29, 2020, demonstrating that the intensity of the COVID-19 crisis caused a rise in Bitcoin prices. Similarly, Caferra and Vidal-Tomás [66] suggested that, unlike traditional stock markets, cryptocurrencies only experienced a brief moment of financial panic during COVID-19 because of the lack of a link between digital currency and the actual economy. Bouri et al. [53] also found that bitcoin is the least reliant and has a competitive advantage over gold and other commodities.

Nonetheless, some researchers argue that cryptocurrencies, such as bitcoin and ethereum, only exhibit short-term safe-haven properties as well as high volatility [67]. Cryptocurrencies appeared as speculative assets and presented more systematic risk than investments in the stock markets during COVID-19 [50, 54]. Conlon and McGee's [68] finding suggested that, rather than acting as a safe haven, Bitcoin may instead increase portfolio downside risk relative to holding the S&P 500 alone. Yet, not all cryptocurrencies behave in the same manner. Goodell and Goutte [69] examine the role of COVID-19 in the paired co-movements of four cryptocurrencies and seven equity indices. They found that the co-movements between cryptocurrencies

and equity indices gradually increased as the pandemic escalated. However, they also found that tether behaved differently from other cryptocurrencies. It moved negatively with equity markets both before and during the COVID-19 outbreak. One explanation for this result would be that the stablecoin tether has particular utility as a vehicle for liquidity, and one tether is supposed to be backed by one dollar. Hence, the properties of the tether are similar to those of fiat currency rather than digital currency. This finding is also consistent with Hasan et al. [70], who found Tether has emerged as a strong new safe haven during the pandemic.

In addition to gold and cryptocurrency, currencies and commodities can also potentially offer a safe-haven role in financial markets. Alali [58], or example, says that the Swiss franc is a good investment during a time when there is a lot of diseases. Similarly, Cheema et al. [54] also found the Swiss franc served as a strong safe haven during both the Global Financial Crisis of 2008 and the COVID-19 pandemic. Nevertheless, some studies suggest that cross-currency hedge strategies are likely to fail during this period. Umar and Gubareva [59] detected a positive relationship between the panic level, as measured by the Pavenpack Coronavirus Panic Index, and the dynamics of leading fiat currencies, such as the Euro, British pound, and Renminbi currencies.

The coronavirus has been labeled a pandemic; thus, its effects are expected to be seen throughout multiple countries, regions, and continents. To put it another way, it is likely to have an impact on worldwide demand and supply of products and services, particularly commodity prices. Ji et al. [56] show that soybean commodity futures remain robust as safe-haven assets during the current pandemic. There is also evidence of a positive relationship between commodity price returns and the global fear index (GFI), confirming that commodity returns increase as COVID-19 related fear rises [57]. In addition, Salisu et al. [57] also suggested that the commodity market offers better safe-haven properties than the stock market. Just like other financial assets, the properties of commodities are heterogeneous. Oil prices seem to have dropped a lot since the pandemic started, but food commodity futures like soybeans made money on average during the COVID-19 pandemic [56].

Considering all of this evidence, it seems that which asset is considered as a safehaven asset during the COVID-19 turmoil. These inconsistent results are common findings in financial literature, suggesting that the relationship between financial assets is dynamic. Safe-haven assets can change over time [52, 70]. For example, gold may have been perceived as a safe haven during the early stages of the COVID-19, but as the pandemic progressed, gold has become a hedging asset instead.

#### **4. Corporate in the midst of the pandemic**

While some researchers have focused on how the financial markets react to the pandemic situation, other researchers have focused on firm actions and characteristics during the outbreak. As mentioned earlier, the pandemic would impact the corporate operation. Governments are shutting down huge sectors of their economies, ostensibly to stop the spread of infectious diseases but potentially putting the vast majority of businesses in danger of running out of cash. While the effect is temporary for some firms, many firms will experience it in the long term, leading to financial distress. Under these circumstances, corporate funding is becoming increasingly important to prevent liquidity issues from becoming solvency issues (e.g., [71–73]). There is evidence suggesting that during the early phase of the pandemic,

#### *Pandemics and Financial Assets DOI: http://dx.doi.org/10.5772/intechopen.103972*

firms were able to raise substantial amounts of external financing by drawing down lines of credit from banks and by accessing the public market [74]. Besides, the rating risk induced by the COVID-19 shock could impact the firms' decisions on the source of funding. Firms on the cusp of being downgraded to non-investment status (i.e., firms with a BBB rating) are likely to behave most aggressively to increase their cashholding through their credit lines with banks, while AAA- to A-rated firms manage to maintain access to liquidity through the public capital market, that is, by issuing bonds and equity. In contrast to existing evidence on bond maturities in previous crises, firms chose to issue bonds with maturities that exceeded those of bonds issued before by the same firms, as well as the average maturities during normal times [75]. Considering all of this evidence, it seems that during the early part of the crisis, firms were able to raise funds quickly when the lockdowns began and cash flow shortfalls emerged. This suggests that lessons from previous crises have helped inform the policy response to the current pandemic.

A large number of published studies suggest that corporate governance could mitigate the negative effects of the health crisis (e.g., [76, 77]). Corporate governance practices are being tested and questioned in the aftermath of the COVID-19 outbreak. When it comes to meeting stakeholder expectations, businesses must make difficult decisions. In this situation, stakeholders would expect management to be quick to adapt and change the firm's policies and processes. The pandemic, with its heavy toll on both social and financial aspects, has highlighted the importance of societal responsibility. According to Albuquerque et al. [76], firms with high environmental and social (ES) scores experienced lower stock price declines than other firms. This finding highlights how ES policies can help build resilience in the face of the COVID-19 pandemic. Similarly, Broadstock et al. [77] discovered that firms with high ESG (environmental, social, and governance) performance have lower downside risk and are more resilient during turbulent times, particularly during the COVID-19-caused financial crisis. According to the evidence reviewed here, corporate governance may strengthen corporate immunity to the COVID-19 pandemic.

Despite the fact that the COVID-19 shock was global, not all firms were impacted in the same way, and they did not respond in the same way. Firms with a high level of financial flexibility can more easily fund a cash flow shortfall caused by the COVID-19 shock. Furthermore, the uncertainty caused by the COVID-19 pandemic increases stakeholders' demand for societal responsibility.

#### **5. Conclusion**

Pandemics are large-scale infectious disease outbreaks that can significantly increase morbidity and mortality over a wide geographic area. Furthermore, the recent COVID-19 virus outbreak demonstrates how infectious diseases spread quickly in open economies and can jeopardize a country's economic stability. The impact of the COVID-19 pandemic will be devastating to the global economy, as it has been in previous crises. In comparison to previous crises, COVID-19 differs from other economic shocks in many ways, including the causes and the public policy response. As the pandemic spread, governments around the world halted economic activity, and panic caused by the economic consequences and uncertainty resulted in a stock market crash. Because of technological advancements, news travels faster than ever before, causing more panic and fear of more bad news. The volatility caused by the crisis influenced many investors' perceptions and behaviors. For higher returns and

#### *Banking and Accounting Issues*

portfolio diversification, investors turned to alternative investments such as commodities, cryptocurrencies, and foreign exchange. Nonetheless, as the pandemic spread, those alternative investments did not always result in lower downside risk and higher yield.

The pandemic has had an impact on businesses all over the world, but the damage has not been distributed evenly. Certain industries have suffered more than others, and many face an uncertain future. Firms would need to increase liquidity in their businesses as well as maintain good corporate governance in response to the crisis in order to create resilience during the pandemic outbreak.

### **Author details**

Pattarake Sarajoti1 , Pattanaporn Chatjuthamard2 and Suwongrat Papangkorn3 \*

1 Research Unit in Finance and Sustainability in Disruption Era, SASIN School of Management, Chulalongkorn University, Bangkok, Thailand

2 Center of Excellence in Management Research for Corporate Governance and Behavioral Finance, SASIN School of Management, Chulalongkorn University, Bangkok, Thailand

3 SASIN School of Management, Chulalongkorn University, Bangkok, Thailand

\*Address all correspondence to: suwongrat.papangkorn@sasin.edu

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section 6
