Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 217217 Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata Faculty of Business and Economic, Universitas Ciputra Surabaya e-mail: jennifer01@student.ciputra.ac.id Abstract: Banks are intermediary firms that have an important function in society and countries. Banks’ existence drives the banking industry to increase its financial performance through market ratio growth. This research aims to analyze the influence of CASA and NPM on market ratio for banks listed in the IDX during the period of 2010–2020. The originality of this research is that it focuses on the influence of affordable funds and profitability on market ratio PBV in the banking sector. The research type used is quantitative method with multiple linear regression approach. Sampling techniques used is purposive sampling. The population is 43 banking firms listed in the IDX on December 2020. The sample used is 200 sample data from 21 banks in Buku II until Buku IV categories in Indonesia during 11 periods, from 2010–2020. Testing techniques used in this research are descriptive statistics, hypothesis test, and classic assumption test with robust standard error. The research variables consist of a dependent variable (PBV), independent variables (CASA, NPM), control variables (PER, DPR, ROE), and a dummy variable (SOE and private owned). The result of this research is that CASA and NPM have a positive and significant effect on PBV. Hope- fully, this research can add consideration for banking management, financial supervisory agencies, investors, and the public about investment making decisions. Keywords: PBV, CASA, NPM A. INTRODUCTION The presence of the banking industry in Indonesia has a great influence on the country’s economic growth and on people’s behavior. Banks are intermediary institutions that play a role in collecting and distributing funds to the public (Triyanti & Susila, 2021). Many people today are starting to save, invest, and conduct transactions using their funds through banks. Banks are also trusted by the public as a safe place to deposit money. Due to public interest and need for banks, banking industry is encour- aged to always measure its financial perfor- mance in each period. One of the mechanisms to measure finan- cial performance in banking is through assess- ment of market ratios. Market value is a strong indicator to assess a company’s financial per- formance, including companies in the banking sector (Alamsyah, 2019). Price to Book Value (PBV) is a market value that shows whether or not the stock price is fair by comparing the stock price with the stock book value (Sari & Muslihat, 2021). Good financial performance indicates that the market value of banking is high, so that if there is a decline in market value, it will certainly affect the decline in company performance. In 2020, the start of the coronavirus af- fected Indonesia’s economic conditions, which impacted the performance of several industries. The Covid-19 pandemic has resulted in positive growth of banking intermediation function (Otoritas Jasa Keuangan, 2021). This condition shows that the pandemic does not have a nega- tive effect on banking financial performance. Business and Finance Journal, Volume 7, No. 2, October 2022 218 Financial problems in banking industry actually occurred before the Covid-19 pandemic. Over the past six years, there have been cases of around 3,074 bank branch offices closing due to financial failure, thus, many operational ac- tivities at branch offices had to be terminated (CNN Indonesia, 2021). The main motive for financial failure tends to be Human Resources (HR) limited knowledge in analyzing market risk. Superior and competent Human Resources (HR) can result in good performance for the company and minimize the potential for finan- cial distress in the company (Siahaan, et al., 2021). Banks began to devise strategies by con- ducting financial planning and analyzing market conditions through fundamental analysis. The liquidity factor in financial ratios can show the effect of banking performance during a certain period (Ningsih & Sari, 2019). In order to maintain their financial performance, major banks began to develop strategies to aggres- sively increase the composition of low-cost funds. The acquisition of cheap funds is used by banks as an effort to realize efficiency in terms of the cost of Third Party Funds (DPK, Dana Pihak Ketiga) (Khairunnisa, et al., 2020). Increasing low-cost funds through Current Account Sav- ings Account (CASA) ratio is expected to be able to maintain stable financial performance during the pandemic and minimize the risk of financial failure. The banking statistical data by Indonesian Monetary Authority (Otoritas Jasa Keuangan (2020)) shows that the composition of the high- est low-cost funds at commercial banks in Indo- nesia in 2020 is at 57.92%. Figure 1 shows that banks are increasing the composition of low- cost funds from year to year. It is known that in 2021, the composition of BRI’s CASA increased by around 11.2%, from 59.66% to 63.08%. Optimization of CASA is a strong prospect for the banking sector in the future regarding fund- ing issues. The increase in CASA resulted in a decrease in the cost of funds from 3.22% to 2.05% (IDX, 2022). The same strategy is also used by other state owned banks, such as BNI. The increase in the CASA ratio at BNI was around 68.4% in 2020, which resulted in a decrease in the cost of funds from 3.2% to 2.6% (CNBC Indonesia, 2021). These events suggest that CASA strategy led to a reduction in cost of fund. Figure 1 Statistical Data on Composition of Cheap Funds for Indonesian Commercial Banks as of 31 December 2010–2020 Source: Indonesian Monetary Authority (Otoritas Jasa Keuangan), 2020 Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 219 a maximum of five trillion rupiah (Nainggolan, 2020). According to Indonesia Monetary Au- thority (Otoritas Jasa Keuangan (2016)) BUKU III is a category that includes banks with core capital of at least five trillion rupiahs to a maximum of thirty trillion rupiahs (Sihotang, et al., 2020). Buku IV consists of banks with core capital of more than thirty trillion rupiahs (Cakranegara, 2020). Naturally, the quality of activities, services, and products is determined based on the size of the bank regulated by OJK based on the minimum capital structure (Setiadi & Suhartoko, 2021). The banking strategy for banks in Buku II to Buku IV categories to increase the ratio of low-cost funds and profit- ability can be used as a reference for other banks to measure the effectiveness of imple- menting these strategies in increasing market value. Signaling theory states that the basis for making investment decisions can be done through analysis of financial performance, such as liquidity, profitability, and market value in banking. Based on previous research, the ratio of liquidity and profitability has an effect on earnings performance, while profit has an effect on market value. The signal theory approach is used because CASA as a liquidity ratio can provide a signal to earnings performance (Widiantari & Iswara, 2021). The NPM profit- ability ratio can also give a signal to the company’s profit performance (Martini & Siddi, 2021). The values of CASA and NPM ratios have an effect on decision making on financial performance. This study will examine CASA and NPM as signals in the form of information about the PBV market ratio. This theory helps banking management to assess the company value and in making decisions based on the information to increase CASA and NPM ratios. The importance of CASA for banks is as a mechanism to increase the growth of Third Party Funds (DPK) through savings and current ac- counts products that lead to higher interest in- come (CNBC Indonesia, 2021). Banks can earn higher income due to a decrease in cost of funds resulted by a decrease in expensive funds, such as time deposits. It is known that the growth of TPF has an effect on banking profit performance (Jamhuriah & Nurhayati, 2021). Another purpose of CASA is to maintain banking liquidity. The growth of these deposits can encourage an in- crease in banking liquidity (Dewi & Rianita, 2021). Therefore, an increase in the ratio of low- cost funds has the potential to maintain the sta- bility of banking financial performance. In measuring financial performance, banks need to pay attention to the level of profitability in a period. Net Profit Margin (NPM) is a profitability ratio used to measure net profit to total revenue in a company (Fitriani, 2021). Net Profit Margin (NPM) is an important indicator in measuring profit performance in banking. It is known that in 2021, the big four banks in Indonesia experienced significant profit growth. The increase in profit occurred in BCA by 19.52%, BRI by 75.53%, Bank Mandiri by 79.58%, and the fastest growth occurred in BNI at 288.36% (CNBC Indonesia, 2022). The higher the profit growth, the better the bank performance (Widiantari & Iswara, 2021). This shows that banks are also focused on profit growth during the Covid-19 pandemic. Many banks are currently developing strat- egies through increasing CASA and NPM to improve financial performance during the pan- demic, starting from banks in the commercial banks for business activities (Buku II) category to Buku IV. Buku II consists of banks with minimum core capital of one trillion rupiah to Business and Finance Journal, Volume 7, No. 2, October 2022 220 In line with signal theory, the implementation of appropriate financial strategies by banks re- quires relevant information. To the best of the researcher’s knowledge, there has been no research that discusses the effect of CASA on the market value of PBV. The novelty of this study is that it focuses on the effect of the low-cost fund ratio as the main independent variable on the value of PBV in the banking sector in the Buku II to Buku IV categories. Previous research only examined the effect of CASA on banking net income within a shorter period and with a smaller number of samples. Research related to the CASA ratio that has been carried out is to measure its significant effect on earnings performance, ROA, and market share (Widiantari & Iswara, 2021; Daryanto, et al., 2020; Setiadi & Suhartoko, 2021). NPM research on PBV has been con- ducted previously in the consumption sector (Wulandari, et al., 2021). However, this re- search will analyze a different industrial sector. This can result in differences in research re- sults, thus, further testing will be carried out with different periods. 1. Research Questions Based on the background of the problem, the research questions of this study is formulated as follows: • Does CASA have a positive effect on market ratios for banks listed on the IDX in 2010– 2020? • Does NPM have a positive effect on market ratios for banks listed on the IDX in 2010– 2020? 2. Research Aim This study was conducted with the aim of analyzing the effect of CASA and NPM on the PBV market ratio of Buku II to Buku IV banks during the 2010–2020 periods. Based on the financial ratio approach, the measurement of the CASA ratio reflects the financial perfor- mance of the banking sector at the level of liquidity and the NPM ratio at the level of profitability. This study will examine the rela- tionship between the two ratios that have a positive effect on the Price to Book Value (PBV) ratio. PBV market value shows the high and low stock prices in a period. The higher the PBV value, the higher the company’s stock price (Kurnia & Ariyani, 2021). 3. Research Contribution The analysis serves to assist investors’ in- vestment decision making, company manage- ment, and other interested parties. The benefit of this research is to provide consideration for banking management regarding effective strat- egy to increase the ratio of low-cost funds and profitability ratios to increase market value. This study will also measure how significant the relationship between the CASA and NPM ra- tios are with the PBV market ratio in the banking sector to strengthen the results of fi- nancial performance analysis by investors. Therefore, this research can be one of the important mechanisms in conducting fundamen- tal analysis. 4. Previous Studies This study shows novelty in terms of test- ing the independent variables that has never been studied before in similar topic, such as the effect of CASA on the PBV value with three control variables (PER, DPR, and ROE) (Wijanarko, 2022; Oktavia & Kalsum, 2021; Wulandari, et al., 2021; Sari & Jufrizen, 2019; Ningsih & Sari, 2019). To the best of the Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 221 researcher’s knowledge and searches, there is no indications of same research regarding the relationship between CASA and market ratios as the PBV value. The high levels of liquidity and profitability certainly affect the market value of the banking system. In recent years, the ratio of low-cost funds has become an interesting topic of discussion in the banking world. The development of business strategies through in- creasing CASA is able to reduce funding prob- lems and improve financial performance, which affects the market value of banking. NPM test- ing of PBV conducted in this study also used a different industry from previous studies. The main difference between this research and previous research lies in testing the ratio of low-cost funds that can affect market value. If it is influential, then the development of busi- ness strategies in the banking sector through increasing the ratio of low-cost funds is consid- ered effective and can be used as a reference by banks. The range of years used in this study is much longer; the research is carried out on Buku II to Buku IV banks in Indonesia during the 2010–2020 period. In addition, the sample used in this study is different from that of previous studies (Jamhuriah & Nurhayati, 2021; Widiantari & Iswara, 2021; Setiadi & Suharto- ko, 2021; Daryanto, et al., 2020; Diana & Huda, 2019). There are several previous studies that have discussed topics relevant to this research from different perspectives. First, research on BUKU IV Banks in 2016–2020 shows that CASA and NPL have an effect on net income, while LDR has no effect (Widiantari & Iswara, 2021). Second, research on Buku IV Banks during the 2016–2019 period shows that CASA, NPL, NIM, CAR have an effect on ROA, while LDR has no effect (Daryanto, et al., 2020). Third, research on BUKU IV Banks during the 2009– 2019 period shows LDR, ROA, NIM, BOPO, KPMM, CKPN, PDN have an effect on market share, while CASA and NPL have no effect (Setiadi & Suhartoko, 2021). Fourth, research on automotive companies listed on the IDX in 2012–2016 shows that ROA has an effect on PBV, while CR and DAR have no effect (Ningsih & Sari, 2019). Fifth, research on PT BNI Tbk. during the period of 2012–2016 shows TPF has an effect on net profit (Jamhuriah & Nurhayati, 2021). Sixth, research on Islamic Commercial Banks in Indonesia in 2012–2017 shows that TPF has an effect on profits (Diana & Huda, 2019). Seventh, research on agricultural com- panies listed on the IDX in 2013–2016 shows that ROA has an effect and PER has no effect on PBV (Sari & Jufrizen, 2019). Eighth, re- search on the consumer goods sector in 2017– 2019 shows that DPR has an effect on PBV, while DER, ROE, SG, NPM, CR have no effect (Wulandari, et al., 2021). Ninth, research on banks listed on the IDX in 2017–2019 shows that EPS, PER, and PBV have an effect on stock prices (Wijanarko, 2022). Tenth, companies in the property sector in 2011–2015 show that PER, DER, DPR, and ROE have an effect on PBV (Oktavia & Kalsum, 2021). 5. Relationship between Variables and Hypo- theses a. Effect of Current Account Saving Account (CASA) on Price to Book Value (PBV) Current Account Saving Account (CASA) is a liquidity ratio that measures the value of savings and current accounts or low-cost funds to the amount of Third Party Funds (TPF). According to Widiantari and Iswara (2021), the Business and Finance Journal, Volume 7, No. 2, October 2022 222 higher the level of low-cost banking funds, the lower the interest expense. Usually banks only offer bank interest of around 2% to 5% each year for savings and checking accounts (Indrajaya, et al., 2021). An increase in the ratio of low-cost funds results in a decrease in the cost of funds. Therefore, large banks are now increasingly focused on increasing low-cost funds in order to increase liquidity and maintain the company’s economic stability. A high CASA ratio indicates that the components of savings and current accounts owned by banks tend to be high. Third Party Funds (TPF) consisting of checking accounts, savings and time deposits have a positive influence on banking operating profit (Jamhuriah & Nurhayati, 2021). Due to the relationship between CASA and profit, this study will test the effect of CASA on the PBV value, which is considered a market ratio. PBV value tends to be used to indicate the high or low price of shares outstanding in the market. The higher the PBV value, the better the com- pany value (Ambarwati & Vitaningrum, 2021).This study will use CASA ratio as the main independent variable. Thus, this study will test whether or not the higher the CASA ratio, the higher the market value in banking. H 1 : CASA has a positive effect on PBV for banks listed in the IDX for the 2010–2020 periods. b. Effect of Net Profit Margin (NPM) on Price to Book Value (PBV) Net Profit Margin (NPM) is a profitability ratio used to measure the level of net profit obtained by banks. This ratio tends to be used to measure the level of bank net profit based on total revenue in a period. The higher the NPM percentage, the better the company’s financial performance, which affects stock prices and increases investor interest (Rahmani, 2020). According to Hadi, et al. (2021) NPM has a positive effect on stock prices. The test results are related to the PBV value in this study. It is known that PBV value is not only influenced by the book value per share, but is also influenced by the price per share (Bustani, et al., 2021). This study uses NPM ratio as an independent variable to test its effect on PBV value. Thus, this study will examine whether higher level of Net Profit Margin (NPM) leads to higher mar- ket value in the banking sector. H 2 : NPM has a positive effect on PBV for banks listed in the IDX for the 2010–2020 periods. c. Price to Earning Ratio (PER) Price to Earning Ratio (PER) is a market indicator that shows whether or not the company’s stock price is fair, so it is not only based on uncertain future conditions estimates (Sari & Muslihat, 2021). This variable will be used as a control variable in the study. Accord- ing to Hasanudin (2022), research results show that PER value has a positive effect on firm value as measured by the PBV market ratio. PER value can be one of the benchmarks that can affect the value of the company because they are correlated in terms of assessing the whether the share value is high or low. Thus, every time there is an increase in PER, the PBV value in the banking sector will increase. d. Dividend Payout Ratio (DPR) Dividend Payout Ratio (DPR) is a ratio that shows the number of dividends distributed in cash to shareholders based on profit perfor- mance in a certain period (Deitiana, et al., Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 223 2020). This variable will be used as a control variable in the study. The DPR’s ratio can be a benchmark in making investment decisions and used as a basis to determine dividend policy. Based on the results of the study, it shows that DPR ratio can be an indicator that affects the value of the company (Wulandari, et al., 2021). Thus, every time there is an increase in the DPR, the PBV value in the banking sector will also increase. e. Return on Equity (ROE) Return on equity (ROE) is a ratio that measures the level of profitability based on net income after tax on common stock (Wijaya, 2019). This variable will be used as a control variable in the study. According to the results of research by Saputri and Giovani (2021), the higher the return on equity, the higher the firm value. This shows that ROE is used to measure the company’s ability to generate net income from equity value (Worotikan, et al., 2021). The higher the ROE, the larger the return from a company’s stock. Thus, every time there is an increase in ROE, the PBV value in the banking sector will increase. B. RESEARCH METHODOLOGY 1. Signal Theory Signal theory is a theory that examines the behavior of banking management in providing views related to investment decision making to external parties, such as investors. Decision mak- ing can be based on analyzing the financial per- formance of banks. Signal theory is intended as a basis for providing information to management regarding the implementation of investment plans and strategies in the future (Widiantari & Iswara, 2021). This theory refers to the implementation of strategies to improve banks financial perfor- mance. Investment decision making by banking management can be supported by conducting fun- Figure 2 The Influence of CASA and NPM on Market Ratios of Banks Listed on the IDX during the 2010–2020 period Source: Author’s Data, 2022 Business and Finance Journal, Volume 7, No. 2, October 2022 224 damental analysis. In response to this, the low- cost funds ratio (CASA) can be used to measure banking financial liquidity, which is one of the important benchmarks for financial performance. In this study, NPM will be used to measure bank profitability level. The higher the level of liquid- ity and profitability, the better the value of the company (Iman et al., 2021). This shows that CASA as a liquidity ratio and NPM as a profit- ability ratio are relevant with this theory in terms of helping investment decision making. 2. Conceptual Framework The analytical model in this study consists of two independent variables with three control variables to test the hypothesis of the PBV market ratio, which shows the firm value of a bank, as the dependent variable. Signal Theory suggests that the analysis of CASA and NPM ratios can affect the market value of companies engaged in the banking sector. The theory can provide a signal to banks and investors to mea- sure stock performance. Based on the theoreti- cal basis and a collection of variables used in the study, the rationale for this research is as follows. 3. Research Type This research was conducted using quanti- tative approach with multiple linear regression. Quantitative research is a technique used to analyze a problem based on data in the form of relevant numbers. Quantitative research is usu- ally used to measure the effect of the object under study, namely the independent variable (X) and the dependent variable (Y) (Hisbullah, 2021). Multiple linear regression is a test tool used to analyze the relationship and influence of the independent variables on the dependent variable. This regression is usually used to mea- sure more than one independent variable in a study (Meiryani, 2021). 4. Sample and Population The population used in this study are com- panies engaged in the banking sector listed on the IDX for the period 2010–2020. The total of population are 43 banks listed on the IDX as of December 31, 2020. The sampling method in this study is purposive sampling with a non- probability sampling technique. The sampling technique was determined based on the infor- mation obtained with certain criteria set by the researcher. The criteria for banks selected for this study are as follows. Table 1 Research Sample Selection Criteria No. Sample Selection Criteria Amount 1 Banks listed in the Indonesia Stock Exchange from 2010–2020 (go public). 43 2 Banks that publish clear, complete, and audited consolidated annual reports. (22) 3 Banks that fall into the Buku II to Buku IV categories in Indonesia as of December 31, 2020. Buku II banks have core capital of IDR 1–5 trillion. Buku III banks have core capital ranging from Rp 5–30 trillion, while BUKU IV banks have core capital > Rp 30 trillion 21 Number of Research Samples 21 Based on the criteria in Table 1, the number of samples used in the study are 21 (twenty one) banks including 5 (five) banks in the Buku II cat- egory, 9 (nine) banks in the Buku III category, and 7 (seven) banks in the Book IV category. These banks consist of 4 (four) state-owned banks and 17 (seventeen) national private category banks as of 31 December 2020. Therefore, the total sample used for data processing is 231 samples from 21 (twenty one) banks that have been de- Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 225 termined for 11 (eleven) periods starting from 2010 to 2020. Based on the results of data col- lection, the number of samples available and can be used in the study is 200 samples. The names of banks that fall into the Buku II to Buku IV categories are as follows. Table 2 Buku II Research Sample 5. Data Collection Method The data collection technique used is sec- ondary data with quantitative measurement. The data is obtained through the consolidated an- nual reports of banks that are included in the Buku II to Buku IV (go public) categories, have complete information, with available annual reports starting from 2010–2020, with data accessible through the official company website, and with financial statements audited by Public Accounting Firm (Kantor Akuntan Publik, KAP). 6. Data Analysis Method The data analysis method used is quantita- tive method with the concept of multiple linear regressions. The concept of multiple linear re- gression is used to analyze the magnitude of the relationship between variables, and whether it is simultaneously or partial (Triyanti & Susila, 2021). Tests were carried out using descriptive statistical analysis, hypothesis testing, and classi- cal assumption theory. Descriptive analysis sta- tistic is used to provide a description of the data, such as the mean, standard deviation, minimum, and maximum values. Then, hypothesis test is used to perform the Anova-F test (significance) and the R2 test (determinant coefficient). According to Ghozali (2016) classical as- sumption test is used to perform normality test, multicollinearity test, heteroscedasticity test, and autocorrelation test (Apriliana & Hendarti, 2021). In this study, data processing with re- gression will be carried out using a robust standard error. According to Hoechle (2007) the use of robust standard error can overcome the problem of autocorrelation and heteros- cedasticity tests on classical assumptions (Kohar- dinata, et al., 2020). Testing the normality of the data in this study is through the skewness/ kurtosis test. Table 3 Buku III Research Sample Tabel 4 Buku IV Research Sample Source: OJK Regulation No. 37/POJK.03/2019 and 2020 Annual Report No. Company Name Category 1 PT Bank China Construction Bank Indonesia Tbk. Private 2 PT Bank Woori Saudara Indonesia 1906 Tbk. Private 3 PT Artha Graha Internasional Tbk. Private 4 PT QNB Indonesia Tbk. Private 5 PT Bank Bumi Arta Tbk. Private No. Company Name Category 1 PT Bank Tabungan Negara (Persero) Tbk. SOE 2 PT Bank Tabungan Pensiunan Nasional Tbk. Private 3 PT OCBC Nisp Tbk. Private 4 PT Bank Permata Tbk Private 5 PT Maybank Indonesia Tbk. Private 6 PT Bank Mega Tbk. Private 7 PT Bank Mayapada Internasional Tbk. Private 8 PT Bank Bukopin Tbk. Private 9 PT Bank Sinarmas Tbk. Private No. Company Name Category 1 PT Bank Mandiri (Persero) Tbk. SOE 2 PT Bank Rakyat Indonesia (Persero) Tbk. SOE 3 PT Bank Central Asia Tbk. Private 4 PT Bank Negara Indonesia (Persero) Tbk. SOE 5 PT Bank CIMB Niaga Tbk. Private 6 PT Bank Danamon Tbk. Private 7 PT Bank Pan Indonesia Tbk. Private Business and Finance Journal, Volume 7, No. 2, October 2022 226 7. Multiple Linear Regression Model The researcher will test the hypothesis that CASA and NPM variables have a positive effect on the PBV value of banks listed in IDX during the 2010–2020 periods. Then, the researcher will also test the PER variable that has a positive ef- fect, DPR that has a positive effect, and ROE that has a positive effect on the PBV value of banks listed in the IDX during the 2010–2020 period. Three variables will be used as control variables in this study, namely PER, DPR and ROE. Dummy variables are artificial variables that is used to change previously qualitative variables into quan- titative variables in the form of numbers. The dummy variable used in this study is denoted by “dbank”, which classifies banks into the catego- ries of state-owned enterprises and private com- panies. The following is a regression equation model used in this empirical study. PBV = α + β 1 CASA + β 2 NPM+ β 3 PER + β 4 DPR + β 5 ROE + dbank + e Notes: PBV = Price to Book Value α = Constant β = Regression Coefficient CASA = Current Account Saving Account NPM = Net Profit Margin PER = Price to Earning Ratio DPR = Dividend Payout Ratio ROE = Return on Equity dbank = bank category dummy variable (0 = State Owned Bank; 1 = Private Banks) e = Banking term error 8. Operational Variable Definition The following is a definition of each vari- able used in the study. Variable Name Equation Definition Dependent Variable Price to Book Value (PBV) Market ratio that measures the price per share to the book value of the stock (Ismayana, et al., 2021) Independent Variable Current Account Saving Account (CASA) Liquidity ratio that measures low- cost funds to the amount of third- party funds (Widiantari & Iswara, 2021). Net Profit Margin (NPM) Profitability ratio that measures net profit to total revenue (Rais, et al., 2021). Control Variable Price to Earning Ratio (PER) Market ratio that measures price per share to earnings per share (Handayani & Arif, 2021). Dividend Payout Ratio (DPR) Ratio that measures the total dividends distributed to net profit (Megamawarni & Pratiwi, 2021). Return on Equity (ROE) Profitability ratio that measures net income to common stock equity (Rais, et al., 2021). Table 5 Operational Definition of Research Variables Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 227 C. RESULT AND DISCUSSION 1. Descriptive Analysis Statistic Based on the results of the descriptive sta- tistics in Table 6, the PBV variable as the market ratio used to measure the company value has a minimum value of 0.12 with a maximum value of 4.6. The average PBV value is 1.5638 and the stan- dard deviation is 0.9996047. This shows that banks with PBV value above the average of 1.5638 and closer to the maximum value of 4.6 have good corporate values. The higher the PBV value, the better the value of the banks. CASA as the main independent variable in the study has a minimum value of 11.13 with a maximum value of 80.3. The average value of this variable is 41.9514 and the standard devia- tion is 17.85018. There is no negative value for CASA ratio in banks. The average value of CASA in banks in Indonesia as classified by Buku II to Buku IV is quite high. The high maximum value of CASA can be due to some banks having a higher composition of savings and current accounts than the number of time deposits in a period. This is also inversely proportional to other banks, which tend to have a low CASA ratio. An increase in expensive funds can reduce the composition of savings and current accounts and vice versa. NPM as an independent variable has a minimum value of 0.45 with a maximum value of 49.87. The average value of this variable is 16.9646 and the standard deviation is 9.779678. In the banking sector there are several banks with net profit levels that are too high. This is indicated by the maximum value of the NPM variable, which is quite far from the banking industry average. High profit growth can also be a positive reflection of the prospects for bank financial performance in that period. In addition, there are also several banks with very low NPM values that almost touch negative numbers. This is resulted by several bank that incurred losses in certain periods. PER variable as a control variable is clas- sified as a market ratio similar to PBV having a minimum value of -1.7 with a maximum value of 91.4. The mean value is 14.92635 and the standard deviation is 10.54409. In contrast to PBV, the market ratio of PER in banking is negative caused by losses for the current year in a certain period. The DPR variable, which is also a control variable in the study, has a mini- mum value of 0 with a maximum value of 91.5. The average value is 18.67135 and the standard deviation is 19.13965. The minimum value of 0 is due to several banks not distributing divi- dends during a certain period. The excessive distribution of dividends occurred when the banking sector managed to record a profit for the year with dramatically increase compared to previous years. In general, the policy of not distributing dividends by banks is influenced by profit or loss in the current year. ROE variable as a control variable has a minimum value of 0.4 and a maximum value of 43.83. The average value is 13.8938 and the standard deviation is 8.397265. The high values of ROEs in several banks indicate a high rate of return on equity. The average value can be used as a benchmark for the level of ROE in similar industries. The dummy bank variable shows a minimum value of 0, which means it is classi- fied as a state-owned bank, and a maximum value of 1, which means it is classified as a private owned bank. The average value is 0.79 and the standard deviation is 0.4083303. This shows that the average value is closer to the maximum value of 1. Most of the samples used in this study are classified as private owned banks, which are categorized as buku. Business and Finance Journal, Volume 7, No. 2, October 2022 228 2. Hypothesis Testing a. Significance Test Based on the criteria of the significance test in the study, a data can be considered feasible if the test value F = 0 (Siregar & Dani, 2019). The results of the simultaneous signifi- cance test in Table 7 show that all the variables used in the study have met the prerequisites. The variables used in this study consist of PBV (dependent), CASA (independent), NPM (inde- pendent), PER (control), DPR (control), ROE (control), and dbank (dummy). The results of data processing show the value of Prob > F of 0, which means that it is less than 0.05 and the ANOVA-F test is fulfilled. Therefore, the model in this study is suitable for testing the PBV variable. Table 7 Significance Test Result (ANOVA-F Test) close to 1 (one). The closer the number is to 1 (one) indicates that the data has a strong rela- tionship, which means that the independent variable in the study is able to explain the dependent variable. The test results show that the variables CASA, NPM, PER, DPR, and ROE are able to explain 0.8604 or 86.04% of the PBV variable. The remaining value of 13.96% can be influenced by other factors not included in this study. Table 8 Determinant Coefficient Test Result (R2 Test) Variable Mean Std. Dev. Min Max PBV 1,5638 0,9996047 0,12 4,6 CASA 41,9514 17,85018 11,13 80,3 NPM 16,9646 9,779678 0,45 49,87 PER 14,92635 10,54409 -1,7 91,64 DPR 18,67135 19,13965 0 91,5 ROE 13,8938 8,397265 0,4 43,83 dbank 0,79 0,4083303 0 1 Table 6 Descriptive Statistics Source: Author’s Data, 2022 Source: Author’s Data, 2022 Number of obs 200 F (6, 193) 135,75 Prob > F 0,00 Root MSE 0,37928 b. Determinant Coefficient Test Based on the results of the determinant coefficient test in Table 8, the value of R2 is substantial because it is in the range that is Number of obs 200 R-Squared 0,8604 Source: Author’s Data, 2022 c. Normality Test Based on the requirements of normality test, a data can be said to be normally distrib- uted if it is > 5% or 0.05 (Fathihani, 2020). The results of the normality test of the data in Table 9 show that the variables used in the study are normally distributed. The value of Prob>chi2 = 0.0849 > 0.05 means that all the variables used meet the prerequisites. There- fore, based on the test results of the variables studied, the normality test of this research model is fulfilled. Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 229 Table 9 Data Normality Test Result Variable Obs Pr (Skewness) Pr (Kurtosis) Adj chi2(2) Prob>chi2 res 200 0.0967 0.1454 4.93 0.0849 Source: Author’s Data, 2022 d. Multicollinearity Test In this research model, all the variables studied can be said to be free from the multicollinearity problem if they have a VIF value < 10 (Fathihani, 2020). Based on the results of data processing in Table 10, the VIF values in all the variables studied show results of < 10. CASA variable has a VIF value = 2.08 < 10, NPM VIF value of 2.08 < 10, PERVIF value of 1.10 < 10, DPR VIF value of 1.18 < 10, ROE VIF value of1.65 < 10, dbank is 1.71 < 10, and the average VIF of all variables other than the dependent variable is 1.63. This shows that there is no correlation (non-collinearity) between the independent, control, and dummy variables in the study. Therefore, all the vari- ables studied did not show any symptoms of correlation between independent variables, thus, all variables passed the multicollinearity test. This shows that this research model is feasible for further testing. e. Robust Standard Error Analysis Result In testing the data, robust standard error is used to overcome the problems of autocorre- lation test and heteroscedasticity test in re- search (Kohardinata, et al., 2020). A variable can be said to be influential if the p-value is <0.05 and has a positive or negative value based on â. Based on the results of data pro- cessing using the robust standard error in Table 11, all the variables studied met the prerequi- sites and are significant. CASA variable has a positive effect on PBV because p-value = 0 <0.05. The NPM variable has a positive effect on PBV because p-value = 0.021 <0.05. In addition to the independent variables, all control variables also have a positive effect on the dependent variable (PBV). PER variable has a positive effect on PBV because its p-value = 0 <0.05. DPR variable has a positive effect on PBV because its p-value = 0.002 <0.05. ROE variable has a positive effect on PBV because its p-value = 0 <0.05. Then, the dummy bank variable (dbank) has a positive effect on PBV β Robust Std. Err. t p-value [95% Conf. Interval] CASA 0,0092698 0,0021979 4,22 0,000 0,0049348 0,0136048 NPM 0,0091055 0,0039055 2,33 0,021 0,0014025 0,0168085 PER 0,0607538 0,0047858 12,69 0,000 0,0513146 0,0701929 DPR 0,0044352 0,0014422 3,08 0,002 0,0015908 0,0072797 ROE 0,0906514 0,0044421 20,41 0,000 0,0818902 0,0994127 dbank 0,4689855 0,0839401 5,59 0,000 0,3034278 0,6345431 _cons -1,599189 0,1536472 -10,41 0,000 -1,902232 -1,296146 Variable VIF 1/VIF CASA 2,08 0,481014 NPM 2,08 0,479903 PER 1,10 0,911996 DPR 1,18 0,847512 ROE 1,65 0,607307 dbank 1,71 0,583887 Mean VIF 1,63 Table 10 Multicollinearity Test Result Source: Author’s Data, 2022 Table 11 Robust Standard Error Analysis Result Source: Author’s Data, 2022 Business and Finance Journal, Volume 7, No. 2, October 2022 230 PBV because its p-value = 0 < 0.05. Based on this regression model, all variables are feasible and meet the prerequisites for conducting re- search, so there are no variables that need to be eliminated. Thus, both hypotheses H 1 and H 2 can be accepted. The R2 value of 86.04% in the regression results shows that the relationship between variables has a strong influence. There- fore, all the variables studied have passed the test and there are no variables that need to be eliminated. Based on the regression model in Table 11, the regression results can be written with the following equation. f. Hypotheses Discussion H 1 : CASA has a positive effect on PBV for banks listed in the IDX for the 2010–2020 period The results of data processing show that CASA has a positive effect on PBV. CASA has a p-value of less than 0.05 (significance level). The first hypothesis (H 1 ) on the effect of the CASA variable on the PBV variable is accepted. This study proves that every time there is an increase in CASA of 0.0092698, the market value of PBV will increase. This shows that the increase in the ratio of low-cost funds such as savings and current accounts carried out by banks in the BUKU II to BUKU IV categories is proven to be effective, if the improvement strat- egy is carried out consistently. This is in line with the results of research showing that CASA has an effect on net profit (Widiantari & Iswara, 2021). Based on the results of the study, it is known that net profit also has an effect on banking stock prices (Fitriano & Herfianti, 2021). Factors that af- fect firm value (PBV) include stock prices and book value of equity. Indirectly, the increase in low-cost funds by banks reduces interest ex- pense, thereby increasing net profit for the year. The net profit will affect the stock prices in the capital market. Thus, according to the results of the study, if the value of the stock price is higher, the value of PBV will also increase (Firdaus & Rohdiyarti, 2021). Based on the signaling theory in the re- search, the relationship between CASA and PBV has been shown to have a positive effect. Measuring through CASA ratio is considered effective in assessing the high or low value of companies in the banking sector. This concept is in accordance with the understanding of signaling theory related to investment decision making. Signal theory provides information to the public that can be used to signal uncertainty about the company’s future performance (Yasar, et al., 2020). The correlation between these theories is shown with the purpose of giving a signal to banking management in making deci- sions regarding the implementation of a strat- egy to increase low-cost funds to increase firm value. CASA ratio can be an indicator that is able to provide a signal to shareholders in line with signal theory to invest in banks with a good CASA level. H 2 : NPM has a positive effect on PBV for banks listed in the IDX for the 2010–2020 periods The results of data processing show that NPM has a positive effect on PBV. Based on the results of research using robust standard error, NPM has a p-value of less than 0.05. The second hypothesis (H 2 ) in testing the effect of the NPM variable on the PBV variable is ac- cepted. This study proves that every time there is an increase in NPM by 0.0091055, there will Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 231 be an increase in the market value of PBV. This shows that the increase in the percentage of net profit in the BUKU II to BUKU IV categories of banks is proven to increase the PBV market value. The market value is a benchmark in assessing the high or low value of the company in the capital market. The results of this study are relevant to previous studies that have been conducted to test the positive effect of NPM on stock prices (Hadi, et al., 2021). The relationship with mar- ket value is that stock prices have a positive effect on the PBV ratio (Firdaus & Rohdiyarti, 2021). This shows that the higher the stock price, the higher the PBV. Therefore, an in- crease in NPM in banking can trigger an in- crease in firm value as measured by PBV. Different research results occurred in other study that showed that NPM has no effect on PBV (Wulandari, et al., 2021). This can be due to the differences in the type of industry being studied. In the research, according to Wulandari et al (2021), the object of research are compa- nies engaged in food and beverage processing (consumption). This study focuses on the effect of NPM on the PBV of the banking sector. Differences in industrial sectors can affect the pattern of relationships and correlations be- tween the variables studied. The relationship between NPM and PBV has been shown to be positive. Based on the theory studied, this shows that profit growth in the current year can be an effective strategy for banks in increasing firm value (PBV). In line with signal theory, which is often used in the business literature, NPM is able to provide signals regarding the effectiveness of banking management strategies in improving financial performance (Kharouf, et al., 2020). This is because NPM ratio is included as a profitability ratio, which is usually used by banking manage- ment and investors in conducting fundamental analysis. NPM gives a signal to investors that high profit growth can increase the value of the company, so that investors can increase the number of shares in banks with financial per- formance that continues to grow positively. g. Control Variable Testing the ratio of PER, DPR, and ROE as control variables shows positive effect on PBV. PER has a p-value of less than 0.05. The higher the PER, the higher the PBV. The results of this study are in line with research by Hasanudin (2022). PER and PBV are ratios of the same group, namely the market ratio. The two vari- ables influence each other because they have similarities to the measurement of market value based on stock price indicators. DPR has a p-value of less than 0.05. The higher the DPR, the higher the PBV. The results of this study are in line with research according to Wulandari et al (2021). DPR variable can affect the PBV market value because DPR ratio shows the dividend distribution policy during a certain period. For the most part, banks will distribute dividends when they manage to score high net profits during a certain period and tend not to distribute dividends to public inves- tors when they experience losses in a given year or when there are signals of financial health problems. Thus, banks that are able to distrib- ute high dividends and consistently show good financial performance will result in increase in market value. ROE has a p-value of less than 0.05. The higher the ROE, the higher the PBV. The results of this study are in line with research by Saputri and Giovanni (2021). The ROE value shows the rate of return from net income to the value of Business and Finance Journal, Volume 7, No. 2, October 2022 232 equity, while the value of equity is one of the indicators in the calculation of the PBV ratio. Thus, the relationship between ROE and PBV is influenced by the total equity factor in banking. The dbank variable has a p-value of less than 0.05. This shows that the dummy variable used in the study passed the multiple linear regres- sion test because the variable has a positive effect on PBV. h. Managerial Implication The impact of the strategy to increase low- cost funds by banks is able to increase the book value of the company due to a decrease in the cost of funds. Banks can increase CASA ratio through increasing savings and current accounts by reducing the composition of time deposits in Third Party Funds (DPK). The increase in CASA has proven to be effective in increasing the value of the company. From the investor’s point of view, the increase in CASA in banking is a good opportunity for investors to increase their share ownership through purchasing bank shares in the capital market. Investors tend to do fundamental analysis before making investment decisions in companies with good financial per- formance. Thus, CASA can be an indicator for investors in assessing the financial health of banks. The impact of the strategy to increase profits can result in an increase in the book value of the company. This is because earnings performance has an effect on bank stock prices, while stock prices influence PBV values. In addition, a high level of NPM indicates that banks have good profit growth over a period. Based on the investor’s point of view, banks with good profit growth tend to have stable financial performance and are able to manage the level of profitability of their companies. Therefore, an increase in NPM can encourage investors to increase the amount of investment in a bank because NPM affects the book value of a bank. Therefore, both CASA and NPM can be used by banks to measure financial perfor- mance and can be used as benchmarks for investors in making investment-related decisions. i. Research Limitation It is a given that this research is still lacking in certain parts due to the limitations of the study. Classification of banking data based on core capital can lead to quite extreme scale comparisons. In addition, the phenomenon of the Covid-19 pandemic in 2020 is another fac- tor that might result in the volatility of data for the variables. This is shown in the range of minimum and maximum values of the descrip- tive analysis, which has a considerable distance from the average of similar industries. There- fore, a small part of these limitations can affect the results of data processing and interpretation carried out by researchers. D. CONCLUSION The results of data processing show that the independent variable CASA has a positive effect on PBV, meaning that H 1 is accepted. This shows that the higher the CASA, the higher the PBV market value of banks in the Buku II to Buku IV categories for the 2010–2020 periods. In order to increase market value, the strategy of increas- ing low-cost funds can be applied by other banks and has proven to be quite effective, as shown through empirical evidence from this study. In- creasing CASA can be done by increasing savings and current accounts, thereby reducing the com- position of time deposits, which has an impact on lowering funding costs. Jennifer, Wirawan Endro Dwi Radianto, Cliff Kohardinata, Determinant Effect of CASA and NPM on Market Ratio of Banks Listed in IDX 233 The independent variable NPM has a posi- tive effect on PBV, meaning that H 2 is accepted. This shows that the higher the NPM, the higher the PBV market value of banks in the BUKU II to BUKU IV categories for the 2010–2020 periods. The strategy of increasing the percent- age of net profit can be applied by other banks and has proven to be quite effective in increas- ing market value. The increase in net profit is also able to encourage an increase in market value. The measurement of market value using PBV ratio indirectly represents bank value. E. REFERENCES Alamsyah, M. F. (2019). 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