Bank Stock Prices Research Articles

The dynamic of bank stock price and its fundamentals: Evidence from Indonesia

The dynamic of bank stock price and its fundamentals: Evidence from Indonesia

ANALYSIS RELATES TO THE IMPACT OF FINANCIAL PERFORMANCE ON BANKING STOCK PRICES

This study aims to analyze the effect of return on assets, return on equity and earnings per share on stock prices. This research is an explanatory research using quantitative methods. The sample used in this study is a state-owned banking company that meets the criteria by using the purposive sampling method. This study uses secondary data in the form of financial statements obtained from the Indonesia Stock Exchange for state-owned banks. The data analysis technique in this study used descriptive statistical analysis and panel data regression analysis using Eviews 12. The results showed that return on assets and earnings per share had a significant positive effect on stock prices, return on equity had no effect on bank stock prices for state-owned banking company

COVID-19 and policy responses: Early evidence in banks and FinTech stocks

The Australian government and Reserve Bank of Australia responded to challenges posed by the COVID-19 pandemic with a number of rapid interventions within a short period of time in early to mid-2020. We examine the impact of news relating to COVID-19, monetary policy interventions, containment measures, and the unwinding of restrictions on Australian bank and FinTech stock prices. The global pandemic was caused by factors outside the banking sector and capital markets, therefore, the policy responses from this unique crisis provides us with new knowledge. Bank and FinTech stock prices were more sensitive to the government's macroeconomic announcements and the unwinding of containment measures than to monetary policy interventions in this unique environment. The response of banks and FinTechs to COVID-19 related macroeconomic decisions is consistent with the response of bank stock prices in previous financial crises. This finding suggests a stronger emphasis on macroeconomic announcements is required as a stabilizing policy tool when managing future crises from outside the banking and capital market sectors.

Effect of the simple moving average on the movement of bank stock prices applied research in a sample of Iraqi private commercial banks

This study aims to identify one of the indicators of technical analysis, which is the simple moving average (SMA), and its impact on the movement of stock prices in private Iraqi commercial banks, by standing on the methods used in technical analysis and its various Models in general, and ways to benefit from them in determining the direction of stock prices in order to make the appropriate investment decision to buy or sell, diagnose the obstacles and difficulties that the participants face in predicting stock prices, and propose solutions and recommendations to overcome and overcome them from a scientific and practical perspective. Where the research community consisted of (25) Iraqi private commercial banks, while the research sample consisted of (5) banks with a rate of (20%) of the research community. The study used the analytical approach to the financial statements during the period between (1/2/ 2022-30/4/2022, where the financial data (banks stock prices) were calculated through the mathematical equation of the Simple Moving Average Index (SMA)) .

PERBANDINGAN RETURN SAHAM BANK BUMN SEBELUM DAN SESUDAH PENGUMUMAN PANDEMI COVID-19 DI INDONESIA

This study aims to analyze the comparison of stock returns of state-owned banks listed on the Indonesia Stock Exchange before and after the announcement of the Covid-19 pandemic. The data used is the weekly closing stock price of state-owned banks for the period January-February (before) and March-April (after). This research is a type of quantitative research with quantitative descriptive analysis method. Data collection techniques using the census method. The results showed that the stock returns of state-owned banks listed on the Indonesia Stock Exchange fluctuated in the period before and after the announcement of the Covid-19 pandemic

Analysis of Determinants of the Price of Banking Stocks Listed on the Indonesia Stock Exchange

This study aims to analyze the factors that influence the stock prices of banks listed on the Indonesia Stock Exchange. These factors consist of Loan To Deposit Ratio (LDR), Capital Adequacy Ratio (CAR), Return On Equity (ROE) and Operating Cost of Operating Income (BOPO). This study uses a sample of 24 banks that have been adjusted to the research criteria. Based on panel data regression analysis, it can be explained that LDR has a negative effect on stock prices, CAR has a negative effect on stock prices, ROE has a positive effect on stock prices and BOPO has a negative effect on stock prices.

Analisis Dampak COVID-19 dan Faktor-Faktor yang Mempengaruhi Indeks Saham Bank Jatim Menggunakan Pendekatan Regresi Time Series

Stock is one of the instruments that can be used to invest. The factors suspected of influencing the fluctuations in the stock price index are the Jakarta Composite Index (JCI), the rupiah exchange rate, and the Covid-19. The purpose of this study is to analyze the effect of the JCI, the rupiah exchange rate, and the Covid-19 on the Jatim Bank stock price index. To analyze the effect of the JCI, the rupiah exchange rate, and the Covid-19 on the Jatim Bank stock price index, time series regression analysis was used. The results of the analysis show that the JCI, the rupiah exchange rate, and the Covid-19 have a significant effect on the Jatim Bank stock price index. The p-value of the three variables is less than 0.05. The value of the determination coefficient is 65.56%, so that the diversity of the dependent variable that can be explained by the model is 65.56%.

COVID-19 and bank performance in dual-banking countries: an empirical analysis

We explore how banks’ income and stock prices respond to the COVID-19 policy measures in countries with the dual-banking system, and whether Islamic banks over- or underperform compared to conventional banks. Applying two-way fixed-effect regressions, we document that the changes in Islamic banks’ finance income as well as net income decline as much during the COVID-19 pandemic as the changes in interest and net income of conventional banks. Event-study tests show that the stock prices of Islamic banks respond as negatively as the ones of conventional banks to workplace closures. We do, however, document that the two types of banks respond differently to income support schemes. The change in Islamic banks’ finance income and net income increase significantly more compared to that of their conventional peers when governments install income support initiatives. Also, Islamic banks’ stock prices respond more positively to the income support programs than the ones of conventional banks. Because we control for investment banking activities and services to large clients, our findings on the stronger response of Islamic banks to income support programs seem to result from Islamic banks’ focus on private customers who are supported during the pandemic. Overall, we conclude that the Shariah compliance does not limit the adverse impact of the COVID-19 crisis on Islamic banking, but that Islamic banks’ performance responds more positively to income support initiatives than the one of conventional banks.

China’s commercial bank stock price prediction using a novel K-means-LSTM hybrid approach

China’s commercial Bank shares have become the backbone of the capital market. The prediction of a bank's stock price has been a hot topic in the investment field. However, the stock price is always unstable and non-linear, challenging the traditional statistical models. Inspired by this problem, a novel hybrid deep learning approach is proposed to improve prediction performance. By modifying the distance measurement algorithm into DTW, an improved K-means clustering algorithm is proposed to cluster out banks with similar price trends. Then those clustered stocks are used to train a long and short-term memory (LSTM) neural network model for static and dynamic stock price prediction. Besides, by transforming the output of the LSTM network into multi-step output to predict multi-time intervals at one time, the performance of the long-term forecasts is improved. Through experiments, it is found that the hybrid model performs better than the single model in generalization ability and accuracy(i.e. R-SQUARE, MAE, MSE). Moreover, the multi-step output static prediction outperforms the dynamic rolling prediction for long-term prediction. In summary, this approach can predict stock prices more accurately and help investors and companies to make more profitable decisions.

Pengaruh ROA, ROE, dan EPS terhadap Harga Saham Perusahaan Perbankan yang Terdaftar di Bursa Efek Indonesia Tahun 2017-2020

The capital market in Indonesia can be an alternative for people to invest. One of them is investing in stocks. However, in investing in stocks, investors should have information related to the dynamics of stock prices before choosing and investing their funds in the company. There are two analyzes in determining the right stock, that is fundamental analysis and technical analysis. One of the fundamental analysis in making investment decisions using profitability ratios. The profitability ratios used in this study are Return on Assets (ROA), Return on Equity (ROE) and Earning Per Share (EPS). The purpose of this study was to determine the effect of Return on Assets, Return on Equity and Earning Per Share on stock prices in banking companies listed on the Indonesia Stock Exchange in 2017-2020. The author conducted research for the years 2017 – 2020. The population used was 45 banking companies and the sample set was 10 companies with certain criteria using purposive sampling as the sampling technique. The research method uses descriptive research with a quantitative approach. The data analysis technique used multiple linear regression. The results in this study explain that Return On Assets partially has a positive and insignificant effect on banking stock prices listed on the Indonesia Stock Exchange, Return On Equity partially has a negative and insignificant effect on banking stock prices. listed on the Indonesia Stock Exchange, Earning Per Share partially has a positive and significant influence on the price of banking shares listed on the Indonesia Stock Exchange, Return On Assets, Return On Equity and Earning Per Share simultaneously have a significant effect on the stock price of banking.

Forecasting Stock Prices of Select Indian Private Sector Banks – A Time Series Approach

<p>Forecasting stock markets and individual stocks has been a well-researched area in the world of finance. Fundamental and technical analysis is widely used by investors in analysing stock prices. Researchers have used various methods to predict stock prices such as Hidden Markov models, genetic algorithms and neural networks (Enke, Grauer, and Mehdiyev, 2011; Hassan, Nath, and Kirley 2007). Time series analysis is used in forecasting asset prices (Long et al, 2021; Eita, 2012). Indian private sector banks are among the best-performing stocks on the Indian stock exchanges over the last decade, as they have consistently captured market share from their public sector counterparts. ARIMA is a useful technique to forecast stock and stock index prices (Box and Jenkins, 1970). This study aimed to evaluate the effectiveness of the ARIMA model in forecasting private bank stock prices in India. Forecasted values differed from actual prices, suggesting markets may be efficient and other variables may also prove to be influential in forecasting Indian private bank stock prices.</p>

Prediksi Harga Saham Bank Bri Menggunakan Algoritma Linear Regresion Sebagai Strategi Jual Beli Saham

Shares are securities as proof of ownership of investors in a company. Stocks have a volatile nature, this makes stocks difficult to predict. Stock prediction is an effort to estimate the stock price, especially in the Bank Rakyat Indonesia company that will appear in the future, and to increase investors' profit opportunities in making investment decisions. During the COVID-19 pandemic, Bank BRI's shares experienced significant ups and downs in four months, which illustrates the sensitivity of the stock to an event. Therefore, it is important to predict stock prices to reduce the risk accepted by investors. The prediction itself requires time series data. Time series is data that is collected sequentially from time to time. The method used for time series data is Linear Regression because this method can handle time-series data. Based on these problems, stock prediction research will be conducted at the Bank Rakyat Indonesia company using the Linear Regression method. Bank Rakyat Indonesia share price data were obtained from the investing.com website from the period starting on January 1, 2008, to June 1, 2020. The data is processed starting from preprocessing to determine attributes, remove unnecessary attributes, and change the contents of the data type, then process split data to divide the dataset into training and test data. The attributes used in this study are Date and Price and the distribution of the data used is 60:40, 65:35, 70:30, 75:25, and 80:20. The best ratio is at 80:20 which produces train and test accuracy of 0.89 and 0.91, Then each training data and testing data are entered into the linear regression model for prediction. The error results from the predictions were calculated using MAPE and yielded a percentage of 13.751% for training data, 13.773% for test data, and 13.755% for overall data. The MAPE results indicate that the linear regression method can be used to predict the stock price of BRI Bank.

Mengukur Pengaruh CAR, ROA, NIM, LDR, dan Rasio NPL terhadap Harga Saham Bank pada Era Pre-Pandemic dan Era During Pandemic Covid-19

The research goal is to analyze the effect of Capital Adequacy Ratio (CAR), Return on Assets (ROA), Net Interest Margin (NIM), Loan to Deposit Ratio (LDR), and Non-Performing Loan Ratio (NPL) on Banking Stock Prices included to LQ45 Index along pre-pandemic era (2016-2019) and during pandemic Covid-19 era (2020-Q3/2021). This research is a kind of descriptive quantitative research using a sample of 5 go public banks (Plc) listed on the LQ45 Index, namely BNI, Bank Mandiri, BRI, BTN, and BCA. The research data compiled by quarterly method. Data analysis of this research using the Statistical Product and Service Solutions (SPSS) version 25. The results of this research indicated that in the pre-pandemic era, the independent variables that had a significant effect on the dependent variable (banking stock prices) were CAR, ROA, LDR, and ratio NPL. Meanwhile, during the pandemic era, the independent variables that have a significant effect on the dependent variable (banking stock prices) are CAR, NIM, LDR, and NPL Ratio

Mengukur Pengaruh CAR, ROA, NIM, LDR, dan Rasio NPL terhadap Harga Saham Bank pada Era Pre-Pandemic dan Era During Pandemic Covid-19

The research goal is to analyze the effect of Capital Adequacy Ratio (CAR), Return on Assets (ROA), Net Interest Margin (NIM), Loan to Deposit Ratio (LDR), and Non-Performing Loan Ratio (NPL) on Banking Stock Prices included to LQ45 Index along pre-pandemic era (2016-2019) and during pandemic Covid-19 era (2020-Q3/2021). This research is a kind of descriptive quantitative research using a sample of 5 go public banks (Plc) listed on the LQ45 Index, namely BNI, Bank Mandiri, BRI, BTN, and BCA. The research data compiled by quarterly method. Data analysis of this research using the Statistical Product and Service Solutions (SPSS) version 25. The results of this research indicated that in the pre-pandemic era, the independent variables that had a significant effect on the dependent variable (banking stock prices) were CAR, ROA, LDR, and ratio NPL. Meanwhile, during the pandemic era, the independent variables that have a significant effect on the dependent variable (banking stock prices) are CAR, NIM, LDR, and NPL Ratio

Analisis Harga Saham Perbankan Sebelum dan Setelah Pengumuman Covid-19 di Indonesia

This study aims to analyze banking stock prices before and after the announcement of Covid-19 in Indonesia. The stock price in this study uses the daily closing stock price. The sample was selected using purposive sampling technique. This study collected 5 national private foreign exchange banking companies listed in the ranking with the largest number of assets, namely Bank Central Asia Tbk, Bank Cimb Niaga Tbk, Bank Pan Indonesia Tbk, Bank OCBC NISP Tbk, and Bank Danamon Indonesia Tbk. Data were analyzed using the Wilcoxon Signed Rank Test. The analysis results show that there are significant differences in the stock prices of banking companies before and after the announcement of Covid-19 in Indonesia.

The Effects Of Risk Based Bank Rating On Stock Return During Covid-19 Of BUKU IV Banks In Indonesia

On December 31, 2019, the Wuhan City Health Commission, China, announced a cluster of cases of pneumonia, which causes the disease Covid-19. Indonesia's Gross Domestic Product (GDP) began to weaken at the end of the first quarter of 2020 from 4.9% to 2.9% (Q-o-Q), and then declined sharply in the second quarter of around -5.32%. The next quarter still saw negative growth but with less severity. Due to the Covid-19 crisis, investors began to hesitate to invest and withdraw their funds from the stock market, causing the Indonesian stock exchange (IDX) in Q1-2020 to fall 29.83% (YoY). In addition, it also led to a decline in banking stock prices, where the INFOBANK15 index fell from Rp.1,033.43 in Q4-2019 to Rp.732.54 in Q1-2020, or decreased by 29.12%. This study aims to determine the level of soundness based on the Risk Based Rating (RBBR) and the effect of the health level of the bank on bank stock returns. This research uses purposive sampling technique. RBBR analysis is used to determine the soundness of each RBBR ratio and is obtained from secondary data on the quarterly financial statements of seven publicly audited banks in Q4-2018 to Q1-2021. Banks under BUKU IV are in a healthy and very healthy condition based on the RBBR method, and research shows that NPL, LDR, ROA have a significant and positive effect on stock returns. Meanwhile, NIM and CAR have no effect on stock returns.

Transnational spillover effects of European sovereign rating signals on bank stock returns

We conduct an event study to investigate how sovereign credit rating events in European countries affect other countries’ bank stock returns. Based on a comprehensive set of 297 exchange-traded European banks, we examine whether cross-country sovereign-to-bank spillover effects exist within the European Union, and whether the impact of sovereign rating signals on foreign bank stock prices has changed after the European sovereign debt crisis. Our results confirm the existence of cross-country spillover effects from sovereign ratings to foreign bank equity returns within the European Union. Moreover, we document a shift in the relationship between foreign sovereign rating changes and abnormal returns after the outbreak of the sovereign debt crisis. Finally, we find that if banks’ exposures to foreign sovereign debt from the GIIPS countries are high, spillover effects associated with rating signals from these countries are significantly stronger.

Comparative Analysis of Support Vector Machine and EGARCH Modelling of Zenith Bank Plc. Stock Price on Economic Growth in Nigeria

In this 21st century, stock exchange has become a crucial and determining factor for the global economy, any variability in this market affects personal, corporate financial activities and the economic growth a country. A lot of analysis using different models were explored by several authors. However, this study set out to investigates the statistical behaviour of Zenith Bank PLC stock price using Support Vector Machine (SVM) and EGARCH Model on economic growth in Nigeria by adopting quantitative techniques using the causal-comparative research method. The findings from this research shows a coefficient of the Zenith bank Low stock price at (0.546945) and high stock price at (0.453562) which indicates that low stock price is insignificant because is less than α = 0.05, while high stock price of greater than α = 0.05 is significant to predict the Zenith bank stock price. Findings from the study has further revealed that SVM mode approach is more appropriate than EGARCH model and recommends that stockholders, financial analyst and researchers who are investing in stock market should adapt the SVM model approach to determine the volatility rate or level of stochastic in the financial time series data.
 Keywords: Stock Price, Support Vector Machine (SVM), EGARCH Model, Stock Exchange, Economic Growth

Reinventing a brand’s identity: effect of name and logo announcements on the stock price of Indian banks

Reinventing a brand’s identity: effect of name and logo announcements on the stock price of Indian banks

A Data Organization Method for LSTM and Transformer When Predicting Chinese Banking Stock Prices

The accurate prediction of stock prices is not an easy task. The long short-term memory (LSTM) neural network and the transformer are good machine learning models for times series forecasting. In this paper, we use LSTM and transformer to predict prices of banking stocks in China’s A-share market. It is shown that organizing the input data can help get accurate outcomes of the models. In this paper, we first introduce some basic knowledge about LSTM and present prediction results using a standard LSTM model. Then, we show how to organize the input data during the training period and give the comparison results for not only LSTM but also the transformer model. The numerical results show that the prediction results of LSTM and transformer can be improved after the input data are organized when training.