Abstract. As the banking sector plays a major role in supporting and increasing a country's economic rate, banks are expected to perform its function well. However, the COVID-19 pandemic and government containment measures led to a sudden stop in real economic activity and placed the financial system under strain, culminating in severe liquidity stress in 2020. This shock has hit all sectors, including the stock market, with many having become hesitant to invest in stocks. This study aims to determine the impact of the Risk-Based Bank Rating (RBBR) method on stock return of the banks in the BUKU III category in Indonesia. The study's population comprises all banks listed in the Indonesia Stock Exchange, and the purposive sampling technique is used, for a sample size of nine banks. Via multiple regression analysis techniques, the study findings show that credit risk, liquidity risk, earnings, and capital simultaneously and significantly impact the stock return of the banks in BUKU III. Furthermore, the categories of credit risk, NPL and earnings, and ROA have a significant and positive impact on the stock return of the banks in BUKU III, unlike capital, whose impact is not found to be significant. Since those factors affect banks' stock return, the banks' management ought to give more consideration to the importance of risk management.
Keywords: BUKU III, bank's healthiness, Risk-Based Bank Rating, stock return, COVID-19
Abstrak. Dengan peran yang signifikan dalam mendukung dan meningkatkan laju perekonomian suatu negara, sektor perbankan diharapkan dapat menjalankan fungsinya dengan baik. Namun, akibat dari pandemi COVID-19 dan tindakan pembatasan yang dilakukan oleh pemerintah menyebabkan terhentinya aktivitas ekonomi riil secara mendadak dan berdampak terhadap sistem keuangan, yang pada akhirnya berakibat memberikan tekanan yang berat terhadap likuiditas negara pada tahun 2020. Guncangan ini telah melanda semua sektor, termasuk pasar modal, yang mengakibatkan keraguan masyarakat untuk berinvestasi di pasar modal. Penelitian ini bertujuan untuk mengetahui pengaruh rasio Risk Based Bank Rating (RBBR) terhadap tingkat pengembalian saham pada sektor perbankan dalam kategori BUKU III di Indonesia. Populasi penelitian ini adalah seluruh bank atau sembilan bank dalam kategori BUKU III yang terdaftar di Bursa Efek Indonesia, dengan menggunakan teknik pengumpulan data purposive sampling. Dengan menggunakan teknik analisis regresi berganda, hasil penelitian menunjukkan bahwa risiko kredit, risiko likuiditas, pendapatan, dan permodalan secara simultan dan signifikan berpengaruh terhadap tingkat pengembalian saham bank-bank di BUKU III. Selanjutnya kategori risiko kredit yaitu Non-Performing Loan (NPL) dan earning yaitu Return on Asset (ROA) berpengaruh signifikan dan positif terhadap tingkat pengembalian saham bank- bank di BUKU III, lain halnya tidak seperti permodalan yang pengaruhnya tidak signifikan. Berdasarkan faktor-faktor yang mempengaruhi tingkat pengembalian saham perbankan, maka manajemen bank harus memprioritaskan pentingnya manajemen risiko.
Kata kunci: BUKU III, kesehatan bank, rasio Risk Based Bank Rating, tingkat pengembalian saham, COVID-19
*Corresponding author. Email:wiwiek.daryanto@ipmi.ac.id
th th th
Received: December 28 , 2021; Revision: December 28 , 2021; Accepted: December 28 , 2021 Print ISSN: 1412-1700; Online ISSN: 2089-7928. DOI: http://dx.doi.org/10.12695/jmt.2022.21.2.7
Copyright@2022. Published by Unit Research and Knowledge, School of Business and Management - Institut Teknologi Bandung (SBM-ITB)
The Impacts of Risk-Based Bank Rating (RBBR) Ratios on Stock Return of BUKU III Banks Listed on
The Indonesia Stock Exchange, 2011-2020
Wiwiek Mardawiyah Daryanto Sekolah Tinggi Manajemen IPMI, Jakarta
Introduction
In early January 2020, the World Health Org anization (WHO) identified novel coronavirus cases in Wuhan, China. This new disease was later officially named COVID-19 and SARS-CoV-2. It spread rapidly in 2020, to over 178 countries, posing a threat to public health and leading to an unprecedented disruption of the overall global economy.
Global economic growth was expected to plummet by 3.8% in 2020 (BI, LPI 2020).
Although limited policy tools were available to stem the spread of the disease, various countries identified the restriction of human mobility through lockdowns and border closures as an effective measure.
The Indonesian economy became sluggish during the COVID-19 outbreak. Indonesia has entered the recession zone, with negative growth for two consecutive years. As depicted in Figure 1, its Gross Domestic Product (GDP) shrank by 2.97% (YoY) in the first quarter of 2020, and slumped by 5.32% (YoY) in the second quarter of 2020.
Any shock to the economy translates into worsening employment conditions and poverty rates. Indonesia's poverty rate increased to 9.41% in March 2020 (BPS, 2020d), compared to 9.22% in September 2019 (BPS, 2021a). According to the Ministry of Manpower, by the end of May 2020, three million workers had been terminated or furloughed (CNBC Indonesia, 2020b). This number shows that the impact of COVID-19 has been severe at the national level (BPS, 2021b).
Rising unemployment has contributed to decreasing people's incomes and weakening people's purchasing power, amid an inflation forecast of only 1.68—the lowest rate of all time (BPS, 2021c).
The COVID-19 pandemic in Indonesia affected the capital market and caused a change in trading time on the Indonesia Stock Exchange; this was a negative signal, or bad news, which made invFigurestors more interested in selling their shareholdings (Kusnandar & Bintari, 2020). As depicted in Figure 2, the JCI experienced a decline in January 2020, and a drastic reduction in 2020.
The JCI was also in line with the economic growth, which decreased in the first quarter of 2020. The disease outbreak had an impact on the stock performance of all sectors and industries. In March 2020, stocks significantly fell when COVID-19 struck globally. The banking or financial sector stock index also dipped sharply in June 2020, as shown in Figure 3.
Figure 1.
Indonesian Gross Domestic Product (GDP) Growth, 2018-2020, Based on (%, QoQ) and (%, YoY)
(Source: Central Bureau of Statistics, 2021)
Figure 2.
Composite Stock Price Index (IHSG/RHS) for the Period 2019-2020
(Source: IDX, 2020)
Figure 3
IDX Statistic Banking/Finance Industry
(Source: IDX Data, 2019-2020)
Introduction
In early January 2020, the World Health Org anization (WHO) identified novel coronavirus cases in Wuhan, China. This new disease was later officially named COVID-19 and SARS-CoV-2. It spread rapidly in 2020, to over 178 countries, posing a threat to public health and leading to an unprecedented disruption of the overall global economy.
Global economic growth was expected to plummet by 3.8% in 2020 (BI, LPI 2020).
Although limited policy tools were available to stem the spread of the disease, various countries identified the restriction of human mobility through lockdowns and border closures as an effective measure.
The Indonesian economy became sluggish during the COVID-19 outbreak. Indonesia has entered the recession zone, with negative growth for two consecutive years. As depicted in Figure 1, its Gross Domestic Product (GDP) shrank by 2.97% (YoY) in the first quarter of 2020, and slumped by 5.32% (YoY) in the second quarter of 2020.
Any shock to the economy translates into worsening employment conditions and poverty rates. Indonesia's poverty rate increased to 9.41% in March 2020 (BPS, 2020d), compared to 9.22% in September 2019 (BPS, 2021a). According to the Ministry of Manpower, by the end of May 2020, three million workers had been terminated or furloughed (CNBC Indonesia, 2020b). This number shows that the impact of COVID-19 has been severe at the national level (BPS, 2021b).
Rising unemployment has contributed to decreasing people's incomes and weakening people's purchasing power, amid an inflation forecast of only 1.68—the lowest rate of all time (BPS, 2021c).
The COVID-19 pandemic in Indonesia affected the capital market and caused a change in trading time on the Indonesia Stock Exchange; this was a negative signal, or bad news, which made invFigurestors more interested in selling their shareholdings (Kusnandar & Bintari, 2020). As depicted in Figure 2, the JCI experienced a decline in January 2020, and a drastic reduction in 2020.
The JCI was also in line with the economic growth, which decreased in the first quarter of 2020. The disease outbreak had an impact on the stock performance of all sectors and industries. In March 2020, stocks significantly fell when COVID-19 struck globally. The banking or financial sector stock index also dipped sharply in June 2020, as shown in Figure 3.
Figure 1.
Indonesian Gross Domestic Product (GDP) Growth, 2018-2020, Based on (%, QoQ) and (%, YoY)
(Source: Central Bureau of Statistics, 2021)
Figure 2.
Composite Stock Price Index (IHSG/RHS) for the Period 2019-2020
(Source: IDX, 2020)
Figure 3
IDX Statistic Banking/Finance Industry
(Source: IDX Data, 2019-2020)
It has been well-documented that the threat of waves of the pandemic leads to a fall in consumption and investment, and hence to further increases in precautionary savings. As seen in Figure 4, bank deposits grew by almost 11% in 2020, the fastest growth in at least the past five years. This increase in deposits has taken place despite a fall in interest rates of more than 130 basis points, responding to a cut in the Bank Indonesia reference rate of 150 basis points. In addition, a rise in undisbursed loans was reported in 2020, signaling a weak appetite for bank loans.
Undisbursed loans show the gap between withdrawn and approved loans, typically for working capital. Total undisbursed loans as a share of approved loans rose by 1.4 percentage points by the end of 2020, reversing the declining trend from the previous five years.
These trends suggest that confidence in the banking system remains high, but also that risk appetite and opportunities to invest and spend continue to be soft.
The present study seeks to investigate the internal factors influencing the stock return of BUKU III banks. The sample includes all nine publicly listed banks under the BUKU III category. The BUKU III category was chosen as its total assets amounted to IDR 2.684.467 billion in 2020 (OJK, 2020), or 31% of total bank assets in all categories. Furthermore, banks in BUKU III have the potential to climb i n t o t h e BU K U I V c a t e g o r y i f t h e y continuously improve their performance.
According to POJK No. 6/POJK.03/2016, banks are divided into four BUKU categories based on core capital, as follows:
1. B U K U I , w i t h c o r e c a p i t a l
≤Rp1,000,000,000,000.00 (one trillion rupiah).
2. B U K U I I , w i t h c o r e c a p i t a l Rp1,000,000,000,000.00 (one trillion rupiah) ≥ Rp5,000,000,000,000.00 (five trillion rupiah)
3. BU K U I I I , w i t h c o r e c a p i t a l R p.
5,000,000,000,000.00 (five trillion rupiah)
≥ Rp. 30,000,000,000.00 (thirty trillion rupiah)
4. BUKU IV, with core capital ≥Rp.
30,000,000,000.00 (thirty trillion rupiah).
Literature Review
The literature review in this study is conducted a r o u n d t wo c o n c e p t s, n a m e l y b a n k performance and stock price. Risk-Based Bank Rating (RBBR) analysis is employed to measure the banks' performance. The stock price used in this research is the common stock price for banks listed in the Indonesia Stock Exchange.
As a technique to evaluate banks' performance, the RBBR risk approach was issued by the Bank Indonesia and the Financial Services Authority (OJK) under regulation No.
13/1/PBI/2011, followed by the Circular Letter of the Financial Services Authority in SE OJK No. 14/SEOJK. 03/2017 (Suryani and Habibie, 2017).
The conceptual framework for this study is based on the researcher's understanding of how variables connect to each other, providing results for the research objective. This study will draw correlations in banking performance during the COVID-19 pandemic.
Banking performance will be proxied by CAR, NPL, LDR, NIM, ROA, and COVID-19 c o n d i t i o n s a s d u m my va r i a b l e s. T h e framework for this study can be seen in Figure 5.
Figure 4.
Key Indicators of Liquidity in the Banking Sector (%)
(Source: OJK, 2021)
Figure 5.
Conceptual Framework
(Source: Author, 2021)
Relationship of Capital Adequacy Ratio (CAR) to Stock Return
Capital pertains to the company's ownership rights to its assets (net assets). In being measured, the aspect of capital (capital) is proxied through the CAR ratio.
Hendrayana and Yasa (2015) demonstrate that CAR has a negative effect on stock return. This study explains that a high CAR allows for capital that is still idle or unproductive, so that the income from a bank will be small, and investors are less responsive to high CAR.
However, Ristanto (2021) finds the banking performance ratios among Indonesian banks registered in the Indonesian Stock Exchange, NPL, and OER/BOPO to have been significantly different before and after the pandemic, and CAR, LDR, ROA, and ROE to not have been affected significantly before and during the pandemic.
In Indonesian State-Owned Enterprise (SOE) banks, CAR growth during the COVID-19 pandemic experienced an uptrend in Q1-Q4 2020 (Maulidia, 2021). For the rural banks, the CAR performance level can be categorized as
“very healthy” compared to the period before the pandemic, which was “healthy” (Yasin & Fisabilillah, 2021).
This study is in line with findings by Tiono and D j a d d a n g ( 2 0 2 1 ) a n d S u l l i v a n a n d Widoatmodjo (2021), which indicate banks, on average, have experienced CAR increase during the pandemic. This implies that banks in BUKU III are ready to face pandemic risks. Hence, the developed hypothesis:
H1: There is a positive impact of CAR on stock return.
It has been well-documented that the threat of waves of the pandemic leads to a fall in consumption and investment, and hence to further increases in precautionary savings. As seen in Figure 4, bank deposits grew by almost 11% in 2020, the fastest growth in at least the past five years. This increase in deposits has taken place despite a fall in interest rates of more than 130 basis points, responding to a cut in the Bank Indonesia reference rate of 150 basis points. In addition, a rise in undisbursed loans was reported in 2020, signaling a weak appetite for bank loans.
Undisbursed loans show the gap between withdrawn and approved loans, typically for working capital. Total undisbursed loans as a share of approved loans rose by 1.4 percentage points by the end of 2020, reversing the declining trend from the previous five years.
These trends suggest that confidence in the banking system remains high, but also that risk appetite and opportunities to invest and spend continue to be soft.
The present study seeks to investigate the internal factors influencing the stock return of BUKU III banks. The sample includes all nine publicly listed banks under the BUKU III category. The BUKU III category was chosen as its total assets amounted to IDR 2.684.467 billion in 2020 (OJK, 2020), or 31% of total bank assets in all categories. Furthermore, banks in BUKU III have the potential to climb i n t o t h e BU K U I V c a t e g o r y i f t h e y continuously improve their performance.
According to POJK No. 6/POJK.03/2016, banks are divided into four BUKU categories based on core capital, as follows:
1. B U K U I , w i t h c o r e c a p i t a l
≤Rp1,000,000,000,000.00 (one trillion rupiah).
2. B U K U I I , w i t h c o r e c a p i t a l Rp1,000,000,000,000.00 (one trillion rupiah) ≥ Rp5,000,000,000,000.00 (five trillion rupiah)
3. BU K U I I I , w i t h c o r e c a p i t a l R p.
5,000,000,000,000.00 (five trillion rupiah)
≥ Rp. 30,000,000,000.00 (thirty trillion rupiah)
4. BUKU IV, with core capital ≥Rp.
30,000,000,000.00 (thirty trillion rupiah).
Literature Review
The literature review in this study is conducted a r o u n d t wo c o n c e p t s, n a m e l y b a n k performance and stock price. Risk-Based Bank Rating (RBBR) analysis is employed to measure the banks' performance. The stock price used in this research is the common stock price for banks listed in the Indonesia Stock Exchange.
As a technique to evaluate banks' performance, the RBBR risk approach was issued by the Bank Indonesia and the Financial Services Authority (OJK) under regulation No.
13/1/PBI/2011, followed by the Circular Letter of the Financial Services Authority in SE OJK No. 14/SEOJK. 03/2017 (Suryani and Habibie, 2017).
The conceptual framework for this study is based on the researcher's understanding of how variables connect to each other, providing results for the research objective. This study will draw correlations in banking performance during the COVID-19 pandemic.
Banking performance will be proxied by CAR, NPL, LDR, NIM, ROA, and COVID-19 c o n d i t i o n s a s d u m my va r i a b l e s. T h e framework for this study can be seen in Figure 5.
Figure 4.
Key Indicators of Liquidity in the Banking Sector (%)
(Source: OJK, 2021)
Figure 5.
Conceptual Framework
(Source: Author, 2021)
Relationship of Capital Adequacy Ratio (CAR) to Stock Return
Capital pertains to the company's ownership rights to its assets (net assets). In being measured, the aspect of capital (capital) is proxied through the CAR ratio.
Hendrayana and Yasa (2015) demonstrate that CAR has a negative effect on stock return. This study explains that a high CAR allows for capital that is still idle or unproductive, so that the income from a bank will be small, and investors are less responsive to high CAR.
However, Ristanto (2021) finds the banking performance ratios among Indonesian banks registered in the Indonesian Stock Exchange, NPL, and OER/BOPO to have been significantly different before and after the pandemic, and CAR, LDR, ROA, and ROE to not have been affected significantly before and during the pandemic.
In Indonesian State-Owned Enterprise (SOE) banks, CAR growth during the COVID-19 pandemic experienced an uptrend in Q1-Q4 2020 (Maulidia, 2021). For the rural banks, the CAR performance level can be categorized as
“very healthy” compared to the period before the pandemic, which was “healthy” (Yasin &
Fisabilillah, 2021).
This study is in line with findings by Tiono and D j a d d a n g ( 2 0 2 1 ) a n d S u l l i v a n a n d Widoatmodjo (2021), which indicate banks, on average, have experienced CAR increase during the pandemic. This implies that banks in BUKU III are ready to face pandemic risks.
Hence, the developed hypothesis:
H1: There is a positive impact of CAR on stock return.
Relationship of Net Interest Margin (NIM) to Stock Return
Net Interest Margin (NIM) represents the interest income on credit minus the cost of interest on deposits to the outstanding credit ratio, demonstrating a bank's ability to earn operating income. The higher the margin ratio is, the more effective the bank is in placing the company's assets in the form of credit. The effect of NIM on ROA is regarded as showing a positive influence, which means that profit will increase amid a higher interest income obtained from loans disbursed by banks.
Research on NIM in relation to stock returns indicates opposing results. Fathoni (2010) and Marviana (2009) posit that NIM has an effect on stock returns, unlike Martoyo (2007) and Risky (2009), who maintain that NIM has no effect on stock returns. Rintistya (2012) also shows that NIM has an effect on stock returns.
Hence, the developed hypothesis:
H2: There is a positive impact of NIM on stock return.
Relationship of Return on Asset (ROA) to Stock Return
Profitability ratio is often referred to as business profitability, and used to measure the level of business efficiency and profitability (Kasmir, 2006). Based on a study positing that ROA positively correlates with stock price ( S a r j o n o & S u p r a p t o, 2 0 2 0 ) , b a n k performance, proxied by ROA, experienced a decrease; yet, there was no significant difference of ROA in banks listed in IDX before and after the pandemic (Ristanto, 2021;
Tiono & Djaddang, 2021), while the rural banks experienced a significant decrease in ROA (Yasin & Fisabilillah, 2021). Hence, the developed hypothesis:
H3: There is a positive impact of ROA on stock return.
Relationship of Loan to Deposit Ratio (LDR) to Stock Return
According to Lukman (2009), LDR is the ratio between the total amount of credit extended and the funds a bank receives, measuring the bank's ability to repay the withdrawal of funds
by depositors by relying on the credit provided as a source of liquidity. Although the COVID- 19 pandemic has caused banks to experience a decrease in LDR—as confirmed by Maulidia (2021), Sullivan and Widoatmodjo (2021), Tiono and Djaddang (2021), and dan Yasin and Fisabilillah (2021)—the difference before and during the pandemic is not significant (Ristanto, 2021). Decreased LDR can lead to the whole market gaining negative profit.
Hence, the developed hypothesis:
H4: There is a positive impact of LDR on stock return.
Relationship of Non-Performing Loan Ratio (NPL) to Stock Return
The Non-Performing Loan (NPL) ratio is an indicator proxied in measuring the effect of the risk profile in the assessment a bank will face on its stock return. Mabruroh in Utami (2005) states that the NPL ratio has a positive effect on banking stock return. During the pandemic, for most banks, NPL indicators increased quite significantly (Maulidia, 2021;
Ristanto, 2021; Sullivan & Widoatmodjo, 2021;
Tiono & Djaddang, 2021). The higher ratio indicates that NPL will cause more problems in earning assets than in other bank outputs (Partovi & Matousek, 2019). Hence, the developed hypothesis:
H5: There is a positive impact of NPL on stock return.
Relationship of the COVID-19 pandemic to Stock Return
Bank stock was significantly influenced by the macroeconomic and financial markets simultaneously (Prastuti & Setianingrum, 2018). During the pandemic, the increase in GDP growth, as well as in the lending rate and risk-free rate, significantly impacted decreasing bank stock prices (Huy et al., 2020). The financial sector was most affected during the pandemic when an abnormal return value was accumulated (Herwany et al., 2021).
H6: There is a positive impact of COVID-19 on stock return.
Research Methodology
Population and Samples
This study employs a quantitative approach with a purposive sampling technique, and two considerations. The first is the observation period, which is 2011-2020 (YoY). The second is the criterion of banks under the BUKU III category and actively traded in the Indonesia Stock Exchange. A total of nine publicly listed banks are included in the sample, or 100% of the population: 1) PT. Pan Indonesia Bank, Tbk (PANIN); 2.) PT. Bank OCBC NISP, Tbk (OCBC NISP); 3.) PT. Bank Maybank Indonesia, Tbk (MAYBANK); 4.) PT. Bank Danamon Indonesia, Tbk (DANAMON); 5.) PT. Bank Permata, Tbk (PERMATA); 6.) PT.
Bank Tabungan Pensiunan Nasional, Tbk (BTPN); 7.) PT. Bank Bukopin, Tbk (BUKOPIN); 8.) PT. Bank Mayapada Internasional, Tbk (MAYAPADA); and 9.) PT.
Bank Mega, Tbk (MEGA). A multiple regression model is used to test the relationship between variables, processed with the SPSS software.
The data in this study is processed through several stages, as depicted in Figure 6. The RBBR analysis is conducted first, followed by a series of descriptive analyses with an indicator of mean, standard deviation, and the correlation coefficient for the data at the second stage. The third stage is meant to determine the independent and dependent variables. At the fourth stage, a classical assumption test of the nor mality and heteroscedasticity problem in the data is performed; and the existence of a correlation between independent variable and dependent variable is gauged. The fifth stage entails the determination of a partial test, simultaneous test, and adjusted R2 to obtain the results of the regression model. Lastly, the results of all tests are interpreted.
Figure 6.
Data Analysis Flow (Source: Author, 2021)
Relationship of Net Interest Margin (NIM) to Stock Return
Net Interest Margin (NIM) represents the interest income on credit minus the cost of interest on deposits to the outstanding credit ratio, demonstrating a bank's ability to earn operating income. The higher the margin ratio is, the more effective the bank is in placing the company's assets in the form of credit. The effect of NIM on ROA is regarded as showing a positive influence, which means that profit will increase amid a higher interest income obtained from loans disbursed by banks.
Research on NIM in relation to stock returns indicates opposing results. Fathoni (2010) and Marviana (2009) posit that NIM has an effect on stock returns, unlike Martoyo (2007) and Risky (2009), who maintain that NIM has no effect on stock returns. Rintistya (2012) also shows that NIM has an effect on stock returns.
Hence, the developed hypothesis:
H2: There is a positive impact of NIM on stock return.
Relationship of Return on Asset (ROA) to Stock Return
Profitability ratio is often referred to as business profitability, and used to measure the level of business efficiency and profitability (Kasmir, 2006). Based on a study positing that ROA positively correlates with stock price ( S a r j o n o & S u p r a p t o, 2 0 2 0 ) , b a n k performance, proxied by ROA, experienced a decrease; yet, there was no significant difference of ROA in banks listed in IDX before and after the pandemic (Ristanto, 2021;
Tiono & Djaddang, 2021), while the rural banks experienced a significant decrease in ROA (Yasin & Fisabilillah, 2021). Hence, the developed hypothesis:
H3: There is a positive impact of ROA on stock return.
Relationship of Loan to Deposit Ratio (LDR) to Stock Return
According to Lukman (2009), LDR is the ratio between the total amount of credit extended and the funds a bank receives, measuring the bank's ability to repay the withdrawal of funds
by depositors by relying on the credit provided as a source of liquidity. Although the COVID- 19 pandemic has caused banks to experience a decrease in LDR—as confirmed by Maulidia (2021), Sullivan and Widoatmodjo (2021), Tiono and Djaddang (2021), and dan Yasin and Fisabilillah (2021)—the difference before and during the pandemic is not significant (Ristanto, 2021). Decreased LDR can lead to the whole market gaining negative profit.
Hence, the developed hypothesis:
H4: There is a positive impact of LDR on stock return.
Relationship of Non-Performing Loan Ratio (NPL) to Stock Return
The Non-Performing Loan (NPL) ratio is an indicator proxied in measuring the effect of the risk profile in the assessment a bank will face on its stock return. Mabruroh in Utami (2005) states that the NPL ratio has a positive effect on banking stock return. During the pandemic, for most banks, NPL indicators increased quite significantly (Maulidia, 2021;
Ristanto, 2021; Sullivan & Widoatmodjo, 2021;
Tiono & Djaddang, 2021). The higher ratio indicates that NPL will cause more problems in earning assets than in other bank outputs (Partovi & Matousek, 2019). Hence, the developed hypothesis:
H5: There is a positive impact of NPL on stock return.
Relationship of the COVID-19 pandemic to Stock Return
Bank stock was significantly influenced by the macroeconomic and financial markets simultaneously (Prastuti & Setianingrum, 2018). During the pandemic, the increase in GDP growth, as well as in the lending rate and risk-free rate, significantly impacted decreasing bank stock prices (Huy et al., 2020). The financial sector was most affected during the pandemic when an abnormal return value was accumulated (Herwany et al., 2021).
H6: There is a positive impact of COVID-19 on stock return.
Research Methodology
Population and Samples
This study employs a quantitative approach with a purposive sampling technique, and two considerations. The first is the observation period, which is 2011-2020 (YoY). The second is the criterion of banks under the BUKU III category and actively traded in the Indonesia Stock Exchange. A total of nine publicly listed banks are included in the sample, or 100% of the population: 1) PT. Pan Indonesia Bank, Tbk (PANIN); 2.) PT. Bank OCBC NISP, Tbk (OCBC NISP); 3.) PT. Bank Maybank Indonesia, Tbk (MAYBANK); 4.) PT. Bank Danamon Indonesia, Tbk (DANAMON); 5.) PT. Bank Permata, Tbk (PERMATA); 6.) PT.
Bank Tabungan Pensiunan Nasional, Tbk (BTPN); 7.) PT. Bank Bukopin, Tbk (BUKOPIN); 8.) PT. Bank Mayapada Internasional, Tbk (MAYAPADA); and 9.) PT.
Bank Mega, Tbk (MEGA). A multiple regression model is used to test the relationship between variables, processed with the SPSS software.
The data in this study is processed through several stages, as depicted in Figure 6. The RBBR analysis is conducted first, followed by a series of descriptive analyses with an indicator of mean, standard deviation, and the correlation coefficient for the data at the second stage. The third stage is meant to determine the independent and dependent variables. At the fourth stage, a classical assumption test of the nor mality and heteroscedasticity problem in the data is performed; and the existence of a correlation between independent variable and dependent variable is gauged. The fifth stage entails the determination of a partial test, simultaneous test, and adjusted R2 to obtain the results of the regression model. Lastly, the results of all tests are interpreted.
Figure 6.
Data Analysis Flow (Source: Author, 2021)
Measurement of Variables Independent Variable
Risk-Based Bank Rating (RBBR)
The Risk-Based Bank Rating (RBBR) is a method used to measure the health of a bank, in line with applicable law Peraturan Bank I n d o n e s i a ( P B I ) R e g u l a t i o n No.13/1/PBI/2011. According to the law, the banks' performance must be assessed using a risk approach, or RBBR, and the results are reflected in four categories, namely a) risk profile, b) good corporate governance, c) earnings, and d) capital.
a. Risk Profile
Eight types of risk are assessed: 1) credit risk, 2) market risk, 3) liquidity risk, 4) operational risk, 5) legal risk, 6) reputation risk, 7) strategic risk, and 8) compliance risk. In this research, the Non-Performing Loan (NPL) ratio is selected for credit risk and Loan to Deposit Ratio (LDR) for liquidity risk, which can be categorized as the significant risk profile used to measure risk profile, as Table 1 illustrates.
Earnings
Based on the Circular Letter of Bank Indonesia No. 13/24/DPNP 2011, the assessment of profitability factors includes evaluating earnings performance, sources of profitability, the sustainability of profitability, and the management of earnings. Two steps are used in analyzing banks' earnings: Return on Assets (ROA) and Net Interest Margin (NIM).
Return on Assets (ROA)
The earning performance of banking pertains to a bank's ability to obtain a refund of assets and capital for the expansion benefits of all banking business activities (Sahut & Mili, 2011). The earning quality can be proxied by the return on assets (ROA) as an essential parameter to examine how much profit a bank earns from its total assets.
The ROA formula is as follows:
Risk Based Bank Rating Ratio
Risk Profile
Non-Performing Loan (NPL) Loan Deposit Ratio (LDR) Table 1.
Risk Profile Calculation
Non-Performing Loan (NPL)
Non-perfor ming loans are considered substandard, doubtful, and loss-inducing. The NPL ratio is calculated by dividing non- performing loans by total loans. The smaller the credit risk endured by the bank is, the smaller the NPL ratio is.
The higher the NPL ratio is, the greater the potential number of uncollected loans is, and can result in declining bank profitability (Gerald, 2003).
The NPL formula is as follows:
(Source: BI Circular Letter No. 13/24/DPNP/2011)
Loan-to-Deposit-Ratio (LDR)
A bank's ability to provide sufficient funds to meet all obligations and commitments issued to its customers at any time is referred to as liquidity, or the ability to pay short-term obligations (Sahut & Mili, 2011).
The Loan-to-Deposit Ratio (LDR) is used to measure bank liquidity.
The LDR formula is as follows:
Net Interest Margin (NIM)
Net Interest Margin (NIM) refers to a bank's ability to generate net interest income by placing productive assets owned by companies (Sari and Dahar, 2016).
The NIM parameter criteria is displayed in Table 1.
The NIM formula is as follows:
Capital
Capital is part of the bank's funding sources, and can be used to raise other funds and as a protection to absorb shocks from loss of business (Greuning and Iqbal, 2011). Capital assessment is based on the Capital Adequacy Ratio (CAR) determined by Bank Indonesia.
CARs are useful to accommodate the risk of loss a bank may face. The higher the CAR is, the more it reflects the bank's ability to better deal with the risk of loss.
The Capital Adequacy Ratio formula is as follows:
2. Dependent Variable a. Stock Return
This study uses as dependent variables the stock returns of all publicly listed banks categorized in BUKU III in the period 2011- 2020. Stock return is the percentage of increase in stock value, and represents the current value of stocks in addition to any dividends paid compared to the original value (Dhand, 2021).
In the evaluation of stock performances, the stock return needs to be compared to other stock in the same industry. The calculation for stock return is as follows:
Where:
SR = PER of company i at period of ti,t
Stock Price = Stock price of company i at i,t
period of t
Stock Price = Earnings per share of company i,t-1
i at period of t-1
Measurement of Variables Independent Variable
Risk-Based Bank Rating (RBBR)
The Risk-Based Bank Rating (RBBR) is a method used to measure the health of a bank, in line with applicable law Peraturan Bank I n d o n e s i a ( P B I ) R e g u l a t i o n No.13/1/PBI/2011. According to the law, the banks' performance must be assessed using a risk approach, or RBBR, and the results are reflected in four categories, namely a) risk profile, b) good corporate governance, c) earnings, and d) capital.
a. Risk Profile
Eight types of risk are assessed: 1) credit risk, 2) market risk, 3) liquidity risk, 4) operational risk, 5) legal risk, 6) reputation risk, 7) strategic risk, and 8) compliance risk. In this research, the Non-Performing Loan (NPL) ratio is selected for credit risk and Loan to Deposit Ratio (LDR) for liquidity risk, which can be categorized as the significant risk profile used to measure risk profile, as Table 1 illustrates.
Earnings
Based on the Circular Letter of Bank Indonesia No. 13/24/DPNP 2011, the assessment of profitability factors includes evaluating earnings performance, sources of profitability, the sustainability of profitability, and the management of earnings. Two steps are used in analyzing banks' earnings: Return on Assets (ROA) and Net Interest Margin (NIM).
Return on Assets (ROA)
The earning performance of banking pertains to a bank's ability to obtain a refund of assets and capital for the expansion benefits of all banking business activities (Sahut & Mili, 2011). The earning quality can be proxied by the return on assets (ROA) as an essential parameter to examine how much profit a bank earns from its total assets.
The ROA formula is as follows:
Risk Based Bank Rating Ratio
Risk Profile
Non-Performing Loan (NPL) Loan Deposit Ratio (LDR) Table 1.
Risk Profile Calculation
Non-Performing Loan (NPL)
Non-perfor ming loans are considered substandard, doubtful, and loss-inducing. The NPL ratio is calculated by dividing non- performing loans by total loans. The smaller the credit risk endured by the bank is, the smaller the NPL ratio is.
The higher the NPL ratio is, the greater the potential number of uncollected loans is, and can result in declining bank profitability (Gerald, 2003).
The NPL formula is as follows:
(Source: BI Circular Letter No. 13/24/DPNP/2011)
Loan-to-Deposit-Ratio (LDR)
A bank's ability to provide sufficient funds to meet all obligations and commitments issued to its customers at any time is referred to as liquidity, or the ability to pay short-term obligations (Sahut & Mili, 2011).
The Loan-to-Deposit Ratio (LDR) is used to measure bank liquidity.
The LDR formula is as follows:
Net Interest Margin (NIM)
Net Interest Margin (NIM) refers to a bank's ability to generate net interest income by placing productive assets owned by companies (Sari and Dahar, 2016).
The NIM parameter criteria is displayed in Table 1.
The NIM formula is as follows:
Capital
Capital is part of the bank's funding sources, and can be used to raise other funds and as a protection to absorb shocks from loss of business (Greuning and Iqbal, 2011). Capital assessment is based on the Capital Adequacy Ratio (CAR) determined by Bank Indonesia.
CARs are useful to accommodate the risk of loss a bank may face. The higher the CAR is, the more it reflects the bank's ability to better deal with the risk of loss.
The Capital Adequacy Ratio formula is as follows:
Dependent Variable Stock Return
This study uses as dependent variables the stock returns of all publicly listed banks categorized in BUKU III in the period 2011- 2020. Stock return is the percentage of increase in stock value, and represents the current value of stocks in addition to any dividends paid compared to the original value (Dhand, 2021).
In the evaluation of stock performances, the stock return needs to be compared to other stock in the same industry. The calculation for stock return is as follows:
Where:
SR = PER of company i at period of ti,t
Stock Price = Stock price of company i at i,t
period of t
Stock Price = Earnings per share of company i,t-1
i at period of t-1
Data Analysis Technique
Multiple regression is the analysis technique used to determine the effect of NPL, LDR, ROA, NIM, and CAR on stock return in 8 (eight) actively traded banks in the Indonesia Stock Exchange. The equation for multiple regression is as follows:
R =α+β NPL +β ROA +β CAR + ε it-1 1 t 3 t-1 4 it it
R =α+β NPL +β ROE +β CAR + ε it-1 1 t 3 t-1 4 it it
R =α+β LDR +β ROA +β CAR + ε it-1 1 t 3 t-1 4 it it
R =α+β LDR+β ROE +β CAR + ε it-1 1 3 t-1 4 it it
Where:
R = Stock return of company i on t-1 period it-1
of time
α = Regression model intercept β = Regression coefficient
NPL = Non-performing loan on period tt
LDR = Loan deposit ratio on period tt
ROA = Return to asset on period tt-1
ROE = Return to equity on period tt-1
CAR = Capital adequacy ratio on period tit
Multicollinearity Test Table 3.
Multicollinearity Test Results
Results and Discussion
Table 2.
Descriptive Statistic Results
As Table 2 shows, stock return has a mean of - 46.8%, signifying that throughout the 10 years from 2011 to 2020, the investors got an average return of -46.8% from their investment in the nine banks. Other than the mean, there is a stock return maximum of 54%, which represents the highest stock return among the banks in BUKU III. In addition, it can be seen that the standard deviation results of six independent variables, that is NPL (X1), LDR (X2), ROA (X3), NIM (X4), CAR (X5), and COV-19 (X6) also the dependent variable which is Stock Return (Y).
Classical Assumption Test Normality Test
Figure 7 displays the data represented by the dots spreading close to and following the direction of the diagonal line. This proves that the regression model for the impacts of NPL (X1), LDR (X2), ROA (X3), NIM (X4), CAR (X5), and COV-19 (X6) on stock return (Y) fulfills the conditions and passes the normality test.
Figure 7.
Normality Test Results (Source: SPSS Output, 2021)
Table 3 displays the result of the tolerance value and Variance Inflation Factor (VIF) of X1, X2, X3, X4, X5, and X6. Since all the
tolerance values are more than 0.2 and the VIF value is less than 10 (ten), the model is concluded to be free from multicollinearity.
Figure 8.
Heteroscedasticity Test Results (Source: SPSS Output, 2021)
Data Analysis Technique
Multiple regression is the analysis technique used to determine the effect of NPL, LDR, ROA, NIM, and CAR on stock return in 8 (eight) actively traded banks in the Indonesia Stock Exchange. The equation for multiple regression is as follows:
R =α+β NPL +β ROA +β CAR + ε it-1 1 t 3 t-1 4 it it
R =α+β NPL +β ROE +β CAR + ε it-1 1 t 3 t-1 4 it it
R =α+β LDR +β ROA +β CAR + ε it-1 1 t 3 t-1 4 it it
R =α+β LDR+β ROE +β CAR + ε it-1 1 3 t-1 4 it it
Where:
R = Stock return of company i on t-1 period it-1
of time
α = Regression model intercept β = Regression coefficient
NPL = Non-performing loan on period tt
LDR = Loan deposit ratio on period tt
ROA = Return to asset on period tt-1
ROE = Return to equity on period tt-1
CAR = Capital adequacy ratio on period tit
Multicollinearity Test Table 3.
Multicollinearity Test Results
Results and Discussion
Table 2.
Descriptive Statistic Results
As Table 2 shows, stock return has a mean of - 46.8%, signifying that throughout the 10 years from 2011 to 2020, the investors got an average return of -46.8% from their investment in the nine banks. Other than the mean, there is a stock return maximum of 54%, which represents the highest stock return among the banks in BUKU III. In addition, it can be seen that the standard deviation results of six independent variables, that is NPL (X1), LDR (X2), ROA (X3), NIM (X4), CAR (X5), and COV-19 (X6) also the dependent variable which is Stock Return (Y).
Classical Assumption Test Normality Test
Figure 7 displays the data represented by the dots spreading close to and following the direction of the diagonal line. This proves that the regression model for the impacts of NPL (X1), LDR (X2), ROA (X3), NIM (X4), CAR (X5), and COV-19 (X6) on stock return (Y) fulfills the conditions and passes the normality test.
Figure 7.
Normality Test Results (Source: SPSS Output, 2021)
Table 3 displays the result of the tolerance value and Variance Inflation Factor (VIF) of X1, X2, X3, X4, X5, and X6. Since all the
tolerance values are more than 0.2 and the VIF value is less than 10 (ten), the model is concluded to be free from multicollinearity.
Figure 8.
Heteroscedasticity Test Results
(Source: SPSS Output, 2021)
Figure 8 shows that the dots are spreading and do not have a clear pattern, and that the dots are spreading above and below 0 (zero) in the Y.
This proves that the model is free from heteroscedasticity issues.
Coefficient of Correlation (R) and Coefficient of Determination (R2) Results
Table 4.
Coefficient of Correlation (R) and Coefficient of Determination (R2) Results
Using the level of significance 0.05 and Degree of Freedom (dF) of 47, which is 1.677, the explanation for Table 6 (t-test results) is as follows:
1. t-Count for credit risk measured by NPL (X1) is -3.582 < t-Table = 1.677 and the level of significance is less than 0.05, which is <0.000. This means that NPL (X1) has a positive impact on stock return (Y) partially.
2. t-Count for liquidity risk measured by LDR (X2) is -1.556 < t-Table = 1.677 and the level of significance is greater than 0.05, which is 0.123. The result can be used to declare that LDR (X2) has no partial impact on stock return (Y) partially.
3. t-Count for earnings measured by ROA (X3) is -0.457 < t-Table = 2.018 and the level of significance is less than 0.05, which is <0.000. The result can be used to declare that ROA (X3) has a positive impact on profitability on stock return (Y) partially.
4. t-Count for earnings measured by NIM (X4) is 0.007 < t-Table = 1.677 and the level of significance is greater than 0.05, which is 0.961. The result can be used to declare that NIM (X4) has no partial impact on stock return (Y) partially.
5. t-Count for capital measured by CAR (X5) is 0.132 < t-Table = 1.677 and the level of significance is greater than 0.05, which is 0.225. The result can be used to declare that CAR (X5) has no partial impact on stock return (Y) partially.
6. t-Count for COVID-19 (X6) is -0.463 < t- Table = 1.677 and the level of significance is greater than 0.05, which is 0.645. The result can be used to declare that COVID- 19 (X6) has no partial impact on stock return (Y) partially.
Based on the analysis conducted, the researcher suggests that future studies expand the population to be studied further. This can help generate a broader view and real perspective of the banking industr y's performance in Indonesia during the COVID- 19 pandemic.
Recommendations
Four practical recommendations stem from the overall findings in this research:
1. Bank management ought to consider the importance of the impact of credit risk, liquidity risk, earnings, and capital. Based on the results of this study, the four factors affect banks' stock return.
2. Bank management should pay more attention to the impact of credit risk, i.e., Non-Performing Loan (NPL) and earnings, specifically Return on Asset (ROA), on banks' stock return. Banks need to create more efficient risk management, to lead to higher profits for privately-owned banks. 3. Investors are expected to pay more attention
to a bank's risk profile factors, since they significantly influence the stock return of the bank.
The interpretation of coefficient correlation (R) displayed in Table 4 as 0.499 means that the five independent variables and the dependent variable have a positive relationship. The value from the result of analysis determination (R2) is 0.249, which indicates that the contribution of the impacts of NPL (X1), LDR (X2), ROA (X3), NIM (X4), CAR (X5), and COV-19 (X6)
on stock return (Y) is 24.9%, while the remaining 75.1% is affected by other variables not examined in this study.
Hypothesis Testing
Simultaneous Test (F-Test) Result
(Source: SPSS Output, 2021)
Table 5.
F-Test Result
(Source: SPSS Output, 2021)
The significant value is less than 0.05. This means that the confidence of this prediction is above 95% and probability of prediction error is below 5%, which is 0.000. The value of the F-Table in this model is 2.21, signifying that the F-Count value is more than the F-Table value (4.577 > 2.21).
Hence, the independent variables significantly affect the dependent variable simultaneously.
(Source: SPSS Output, 2021)
Partial Test (t-Test) Result Table 6
T-Test Result
Figure 8 shows that the dots are spreading and do not have a clear pattern, and that the dots are spreading above and below 0 (zero) in the Y.
This proves that the model is free from heteroscedasticity issues.
Coefficient of Correlation (R) and Coefficient of Determination (R2) Results
Table 4.
Coefficient of Correlation (R) and Coefficient of Determination (R2) Results
Using the level of significance 0.05 and Degree of Freedom (dF) of 47, which is 1.677, the explanation for Table 6 (t-test results) is as follows:
1. t-Count for credit risk measured by NPL (X1) is -3.582 < t-Table = 1.677 and the level of significance is less than 0.05, which is <0.000. This means that NPL (X1) has a positive impact on stock return (Y) partially.
2. t-Count for liquidity risk measured by LDR (X2) is -1.556 < t-Table = 1.677 and the level of significance is greater than 0.05, which is 0.123. The result can be used to declare that LDR (X2) has no partial impact on stock return (Y) partially.
3. t-Count for earnings measured by ROA (X3) is -0.457 < t-Table = 2.018 and the level of significance is less than 0.05, which is <0.000. The result can be used to declare that ROA (X3) has a positive impact on profitability on stock return (Y) partially.
4. t-Count for earnings measured by NIM (X4) is 0.007 < t-Table = 1.677 and the level of significance is greater than 0.05, which is 0.961. The result can be used to declare that NIM (X4) has no partial impact on stock return (Y) partially.
5. t-Count for capital measured by CAR (X5) is 0.132 < t-Table = 1.677 and the level of significance is greater than 0.05, which is 0.225. The result can be used to declare that CAR (X5) has no partial impact on stock return (Y) partially.
6. t-Count for COVID-19 (X6) is -0.463 < t- Table = 1.677 and the level of significance is greater than 0.05, which is 0.645. The result can be used to declare that COVID- 19 (X6) has no partial impact on stock return (Y) partially.
Based on the analysis conducted, the researcher suggests that future studies expand the population to be studied further. This can help generate a broader view and real perspective of the banking industr y's performance in Indonesia during the COVID- 19 pandemic.
Recommendations
Four practical recommendations stem from the overall findings in this research:
1. Bank management ought to consider the importance of the impact of credit risk, liquidity risk, earnings, and capital. Based on the results of this study, the four factors affect banks' stock return.
2. Bank management should pay more attention to the impact of credit risk, i.e., Non-Performing Loan (NPL) and earnings, specifically Return on Asset (ROA), on banks' stock return. Banks need to create more efficient risk management, to lead to higher profits for privately-owned banks.
3. Investors are expected to pay more attention to a bank's risk profile factors, since they significantly influence the stock return of the bank.
The interpretation of coefficient correlation (R) displayed in Table 4 as 0.499 means that the five independent variables and the dependent variable have a positive relationship. The value from the result of analysis determination (R2) is 0.249, which indicates that the contribution of the impacts of NPL (X1), LDR (X2), ROA (X3), NIM (X4), CAR (X5), and COV-19 (X6)
on stock return (Y) is 24.9%, while the remaining 75.1% is affected by other variables not examined in this study.
Hypothesis Testing
Simultaneous Test (F-Test) Result
(Source: SPSS Output, 2021)
Table 5.
F-Test Result
(Source: SPSS Output, 2021)
The significant value is less than 0.05. This means that the confidence of this prediction is above 95% and probability of prediction error is below 5%, which is 0.000. The value of the F- Table in this model is 2.21, signifying that the F-Count value is more than the F-Table value (4.577 > 2.21).
Hence, the independent variables significantly affect the dependent variable simultaneously.
Partial Test (t-Test) Result
(Source: SPSS Output, 2021)
Table 6 T-Test Result
4. Future researchers on the topic are expected to complete the variables with all components of the Risk-Based Bank Rating (RBBR) method, namely operational risk, law risk, strategic risk, compliance risk, reputation risk, and Good Corporate Governance (GCG).
Conclusion
Based on the overall results in this study, it can be obser ved that qsimultaneously and significantly impact the stock return (Y) of the nine publicly listed banks categorized under BUKU III. NPL (X1) and ROA (X3) have a positive impact on the stock return (Y) of the nine publicly listed banks categorized under BUKU III. Whereas, other variables (LDR (X2), NIM (X4), CAR (X5), and COV-19 (X6) have no impact on the stock return (Y) of the nine publicly listed banks categorized under BUKU III.
References
BI. (2020). Kinerja perekonomian dan sinergi kebijakan nasional di periode covid-19 (p. 26).
OJK. (n.d.). OJK, Ikhtisar Perbankan.
Retrieved 12 August 2021, from https://www.ojk.go.id/id/kanal/perbankan /ikhtisar- perbankan/Pages/Lembaga- Perbankan.aspx
Ristanto, S. (2021). Pengaruh pandemi covid-19 terhadap kinerja bank di indonesia: studi pada bank yang terdaftar di bursa efek Indonesia.
Universitas Islam Indonesia.
Maulidia, N. (2021). Analisis kinerja keuangan bank di masa pandemi covid-19 pada bank bumn yang terdaftar di bursa efek Indonesia. Jurnal Ilmiah Mahasiswa FEB, 9 ( 2 ) , A r t i c l e 2 . https://jimfeb.ub.ac.id/index.php/jimfeb/art icle/view/7469
Yasin, A., & Fisabilillah, L. W. P. (2021).
Analisis Komparasi Kinerja Keuangan Bank Perkreditan Rak yat (BPR) Sebelum dan Pada Pandemi Covid-19.
EQUILIBRIUM : Jurnal Ilmiah Ekonomi Dan Pembelajarannya, 9(2), 142– 152. doi:
10.25273/equilibrium.v9i2.10011 Tiono, I., & Djaddang, S. (2021). Analisis
komparasi kinerja keuangan pada perbankan konvensional buku iv di indonesia sebelum dan sesudah pandemi covid-19. Balance: Jurnal Akuntansi, Auditing Dan Keuangan, 18(1), 72–90. doi:
10.25170/balance.v18i1.2336
Sarjono, H., & Suprapto, A. T. (2020). Camel ratio analysis of banking sector share price in indonesia stock exchange.
PalArch’s Journal of Archaeology of Egypt / Egyptology, 17(7), 2213–2222.
Ristanto, S. (2021). Pengaruh pandemi covid-19 terhadap kinerja bank di indonesia: studi pada bank yang terdaftar di bursa efek Indonesia.
Universitas Islam Indonesia.
Partovi, E., & Matousek, R. (2019). Bank efficiency and non-performing loans:
Evidence from Turkey. Research in International Business and Finance, 48, 2 8 7 – 3 0 9 . d o i : 10.1016/j.ribaf.2018.12.011
Prastuti, D., & Setianingrum, P. H. (2018). The Effect of Foreign Exchange Rate, Inflation Rate and Market Return on Return of Bank Perseros’ Stock.
Indonesian Journal of Business, Accounting and Management, 1(1), Article 1. doi:
10.36406/ijbam.v1i1.221
Huy, D. T. N., Loan, B. T. T., & Anh, P. T.
(2020). Impact of selected factors on s t o c k p r i c e : A c a s e s t u d y o f V i e t c o m b a n k i n V i e t n a m . Entrepreneurship and Sustainability Issues, 7 ( 4 ) , 2 7 1 5 – 2 7 3 0 . d o i : 10.9770/jesi.2020.7.4(10)
Herwany, A., Febrian, E., Anwar, M., &
Gunardi, A. (2021). The Influence of the COVID-19 Pandemic on Stock Market Returns in Indonesia Stock Exchange. The Journal of Asian Finance, Economics and Business, 8(3), 39–47. doi:
10.13106/jafeb.2021.vol8.no3.0039
Sahut, J.-M., & Mili, M. (2011). Banking distress in MENA countries and the role of mergers as a strategic policy to resolve distress. Economic Modelling , 28(1),
1 3 8 – 1 4 6 . d o i :
10.1016/j.econmod.2010.09.017
Dhand, A. (2021, January 18). Stock Return.
Scripbox. https://scripbox.com/pf/stock- return/
Hendrayana, Putu W. dan Yasa, Gerianta W.
(2015), Pengaruh Komponen RGEC p a d a P e r u b a h a n H a r g a S a h a m Perusahaan Perbankan di Bursa Efek Indonesia, E-Jurnal Akuntansi Universitas Udayana, 10(2), 554-569.
Kasmir (2004), Manajemen Perbankan, Jakarta, PT Raja Grafindo Perkasa.
Utami, Setyaningsih Sri (2004), Pengaruh Rasio Keuangan Terhadap Harga Saham (Studi pada perusahaan Perbankan di Bursa Efek Jakarta). Jurnal Ekonomi dan Kewirausahaan, 5( 2), 110-122.
Biro Pusat Statistik/ BPS (2019-2020), PDB Indonesia Triwulanan 2016-2020.
Bank Indonesia (2011). Bank Indonesia Regulation No. 13/1/PBI/2011 on the Assessment of The Commercial Banks.
Jakarta.
Otoritas Jasa Keuangan (2017). Laporan Publikasi Bank Umum Konvensional.
R e t r i e v e d f r o m
https://www.ojk.go.id/id/kanal/perbankan /data-dan-statistik/laporan-keuangan- perbankan/default.aspx. Accessed on March 3rd, 2017.
4. Future researchers on the topic are expected to complete the variables with all components of the Risk-Based Bank Rating (RBBR) method, namely operational risk, law risk, strategic risk, compliance risk, reputation risk, and Good Corporate Governance (GCG).
Conclusion
Based on the overall results in this study, it can be obser ved that qsimultaneously and significantly impact the stock return (Y) of the nine publicly listed banks categorized under BUKU III. NPL (X1) and ROA (X3) have a positive impact on the stock return (Y) of the nine publicly listed banks categorized under BUKU III. Whereas, other variables (LDR (X2), NIM (X4), CAR (X5), and COV-19 (X6) have no impact on the stock return (Y) of the nine publicly listed banks categorized under BUKU III.
References
BI. (2020). Kinerja perekonomian dan sinergi kebijakan nasional di periode covid-19 (p. 26).
OJK. (n.d.). OJK, Ikhtisar Perbankan.
Retrieved 12 August 2021, from https://www.ojk.go.id/id/kanal/perbankan /ikhtisar- perbankan/Pages/Lembaga- Perbankan.aspx
Ristanto, S. (2021). Pengaruh pandemi covid-19 terhadap kinerja bank di indonesia: studi pada bank yang terdaftar di bursa efek Indonesia.
Universitas Islam Indonesia.
Maulidia, N. (2021). Analisis kinerja keuangan bank di masa pandemi covid-19 pada bank bumn yang terdaftar di bursa efek Indonesia. Jurnal Ilmiah Mahasiswa FEB, 9 ( 2 ) , A r t i c l e 2 . https://jimfeb.ub.ac.id/index.php/jimfeb/art icle/view/7469
Yasin, A., & Fisabilillah, L. W. P. (2021).
Analisis Komparasi Kinerja Keuangan Bank Perkreditan Rak yat (BPR) Sebelum dan Pada Pandemi Covid-19.
EQUILIBRIUM : Jurnal Ilmiah Ekonomi Dan Pembelajarannya, 9(2), 142– 152. doi:
10.25273/equilibrium.v9i2.10011 Tiono, I., & Djaddang, S. (2021). Analisis
komparasi kinerja keuangan pada perbankan konvensional buku iv di indonesia sebelum dan sesudah pandemi covid-19. Balance: Jurnal Akuntansi, Auditing Dan Keuangan, 18(1), 72–90. doi:
10.25170/balance.v18i1.2336
Sarjono, H., & Suprapto, A. T. (2020). Camel ratio analysis of banking sector share price in indonesia stock exchange.
PalArch’s Journal of Archaeology of Egypt / Egyptology, 17(7), 2213–2222.
Ristanto, S. (2021). Pengaruh pandemi covid-19 terhadap kinerja bank di indonesia: studi pada bank yang terdaftar di bursa efek Indonesia.
Universitas Islam Indonesia.
Partovi, E., & Matousek, R. (2019). Bank efficiency and non-performing loans:
Evidence from Turkey. Research in International Business and Finance, 48, 2 8 7 – 3 0 9 . d o i : 10.1016/j.ribaf.2018.12.011
Prastuti, D., & Setianingrum, P. H. (2018). The Effect of Foreign Exchange Rate, Inflation Rate and Market Return on Return of Bank Perseros’ Stock.
Indonesian Journal of Business, Accounting and Management, 1(1), Article 1. doi:
10.36406/ijbam.v1i1.221
Huy, D. T. N., Loan, B. T. T., & Anh, P. T.
(2020). Impact of selected factors on s t o c k p r i c e : A c a s e s t u d y o f V i e t c o m b a n k i n V i e t n a m . Entrepreneurship and Sustainability Issues, 7 ( 4 ) , 2 7 1 5 – 2 7 3 0 . d o i : 10.9770/jesi.2020.7.4(10)
Herwany, A., Febrian, E., Anwar, M., &
Gunardi, A. (2021). The Influence of the COVID-19 Pandemic on Stock Market Returns in Indonesia Stock Exchange. The Journal of Asian Finance, Economics and Business, 8(3), 39–47. doi:
10.13106/jafeb.2021.vol8.no3.0039
Sahut, J.-M., & Mili, M. (2011). Banking distress in MENA countries and the role of mergers as a strategic policy to resolve distress. Economic Modelling , 28(1),
1 3 8 – 1 4 6 . d o i :
10.1016/j.econmod.2010.09.017
Dhand, A. (2021, January 18). Stock Return.
Scripbox. https://scripbox.com/pf/stock- return/
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