Bank Stock Prices Research Articles

Analisis pengaruh faktor fundamental terhadap harga saham perbankan

This research examines the influence of fundamental factors (ROE, NPM, and EPS) on stock prices. This research is a type of associative quantitative research category through purposive sampling in obtaining a sample of 39 companies. All banks listed on the Indonesian Stock Exchange (IDX) in the 2019-2022 period are the target population of the research. This study collected archival data from official IDX website. The data is analysed using multiple linear regression with the help of the SPSS 26.0 Data Processing Software Application. The results showed that ROE and NPM have no significant effect on stock prices partially. Meanwhile, EPS has a significant effect on banking stock prices. A higher increase in EPS will have a significant impact on the raising of firm value in the capital market. For investors, EPS can be a major consideration in determining investment decisions. For banking companies, it is important to pay attention and improve the company's performance, especially related to EPS which has a significant influence on the increase in stock prices.

Factors Affecting Banking Stock Price on the Indonesian Stock Exchange 2017 to 2021

Factors Affecting Banking Stock Price on the Indonesian Stock Exchange 2017 to 2021

Comparative Analysis of Linear Regression, Decision Tree and Gradient Boosting for Predicting Stock Price of Bank Rakyat Indonesia

An investment is the placement of a current amount of funds in the hope of generating a profit in the future. There are several types of investments, including stocks, which are attractive options as they can bring a huge return to investors. However, rapidly fluctuating stock prices are influenced by various factors, such as company performance, interest rates, economic conditions, and government policies. In Indonesia, PT Bank Rakyat Indonesia Tbk (BBRI) had the largest profit among the 10 largest banks by the end of March 2024, with a profit of IDR 13.8 trillion. The higher the bank's return, the greater the investor's interest in purchasing the stock, influencing the stock price. The goal of stock price prediction is to forecast the stock's future price in order to increase investors' potential profits. Various methods, such as Linear Regression, Decision Tree, and Gradient Boosting, have been developed for stock price prediction. Comparative analysis is needed to determine the most accurate method in predicting the stock price of People's Bank of Indonesia, using Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and R-squared metrics (R2). The analysis showed that Linear Regression achieved the highest accuracy with R2 of 0.96, MAE of 65.72 and RMSE of 86.74 compared to the Decision Tree and Gradient Boosting models.

Implementasi CNN-BiLSTM untuk Prediksi Harga Saham Bank Syariah di Indonesia

Stock price forecasting plays a crucial role in stock investment. Accuracy in predicting stock prices can provide significant financial benefits and help reduce investment risks. Stock price data are time series with high-frequency characteristics, non-linearity, and long memory, which makes stock price prediction a complex challenge. This research proposes a method for predicting the stock prices of Islamic banks in Indonesia using CNN-BiLSTM. This method aims to improve prediction accuracy by utilizing the feature extraction capabilities of CNN and the ability of BiLSTM to understand the temporal sequences of stock data. The data used in this research are the closing stock prices of Bank Syariah Indonesia (BSI), Bank Tabungan Pensiunan Negara Syariah (BTPN Syariah), and Bank Panin Dubai Syariah (PDSB) from January 2, 2020, to July 4, 2024. Testing these three stocks yielded MAPE values of 2.376%, 2.092%, and 0.629%, respectively. The study results show that the CNN-BiLSTM prediction model produced has very good accuracy in predicting stock prices.

Why Did Bank Stocks Crash during COVID-19?

Abstract A two-sided “credit-line channel”—relating to drawdowns and repayments—explains the severe drop and partial subsequent recovery in bank stock prices during the COVID-19 pandemic. Banks with greater exposure to undrawn credit lines saw larger stock price declines but performed better outside of crises periods. Despite deposit inflows, high drawdowns led to reduced bank lending, suggestive of capital encumbrance upon drawdowns. Repayments of credit lines unencumbered capital which explains the stock price recovery starting Q2 2020. Bank provision of credit lines resembles writing put options on aggregate risk, and we propose how to incorporate this feature into bank stress tests. (JEL G01, G21)

Shari’ah governance and transparency: evidence from stock price synchronicity of Islamic banks

PurposeThe purpose of this study is to investigate internal governance mechanisms factors, focusing on Shari’ah-based governance mechanisms that affect the price synchronicity of Islamic banks (IBs).Design/methodology/approachThis study analyzes and compares the effect of Shari’ah and regular governance mechanisms on stock price synchronicity over 2013–2022 using a sample of 51 listed IBs in 13 countries in the Middle East and South Asia region. Using generalized least square method, this paper tests nine hypotheses addressing Shari’ah and regular governance mechanisms.FindingsThe findings generally reveal that Shari’ah-based governance mechanisms have a significant impact on the stock price synchronicity of IBs. The main determinants of stock price synchronicity among IBs are SSB size, SSB diversity, SSB members’ qualifications in finance Islamic jurisprudence and SSB interlocks. Shari’ah governance plays a detrimental role in improving the association between bank stock price synchronicity and transparency.Research limitations/implicationsThis paper includes three main limitations that may affect the accuracy of the findings. First, this paper relied on publicly available financial statements of IBs online. Hence, the data in this study is from few IBs in each country, which limits the analysis given the reliance is on the best-performing IBs in the country. Second, the results are restricted to the Middle East and South Asia and may not be generalized to other regions. Third, the sample is dominated by Middle East countries (i.e. 37 IBs out of 51).Practical implicationsBoth Shari’ah governance and regular governance have an impact on the transparency of IBs. Policymakers or regulators could encourage IBs to embed SSBs into their internal governance structure for the positive impact the SSBs attributes have on stock price synchronicity and transparency.Originality/valueThis research studies IBs, unlike most other works that focus on firms.

Analysis of The Influence of Company Fundamentals on Stcock Prices During the Transition Period and After the Implementation of the Remote Tranding System on the Stock Excange Indonesia (Study in Banking)

This study aims to determine the effect of ROE (Return on Equity, (PER) Price Earnings Ratio, DER (Debt to Equity Ratio), NPL (Non - Performing Loans), and BOPO (operating costs of operating income) on banking stock prices during the transition period and after the implementation of remote trading system technology on the Indonesian stock exchange and also examines whether there is a difference in the effect of these independent variables on stock prices in the two periods. This research was conducted with quantitative methods and used secondary data. The number of samples in this study was 6 banking companies listed on the Indonesia Stock Exchange from 2006 - 2020, where the transition period was from 2006-2009 and the remote trading period was from 2010-2020. The data were analyzed separately in both periods using multiple linear regression models, a classical assumption test, and also the Chow Test as an additional test using the SPSS 25 tool. The results showed that during the transition period only DER had no significant effect and 4 (four) other independent variables; BOPO, NPL, PER, and ROE have a significant effect on stock prices, while during remote trading the DER and PER variables have no significant effect and 3 (three) other independent variables; BOPO, PER, and NPL have a significant effect. During the transition period, the independent variables simultaneously have the effect of 70.3% on the price, but during the remote trading period, the ability of the five independent variables is only 35.5% in explaining the rise/fall of stock prices. The results of the Chow test show that there are differences in the influence or structural changes in the influence of independent variables on stock prices and the regression coefficients. There are also differences where the independent variables during the transition period are all inelastic (e < 1) and vice versa during remote trading all coefficient values the regression is elastic (e > 1).

Analisis Peramalan Harga Saham Dengan Metode Arima Terhadap Keputusan Investasi Pada Perusahaan Perbankan Dalam Indeks LQ45

Every trader or investor in buying shares will always confused with the highly volatile stock price movements, this is causes traders or investors to be careful in choosing prices on when entering to buy shares. ARIMA price forecasting method is a forecasting method that traders and investors can use to help make decisions.This study is a descriptive study with a quantitative approach with the aim of analyzing, explaining, and concluding the analysis of price forecasting using the ARIMA (Autoregressive Integrated Moving Average) method on investment decisions in banking companies listed in the LQ45 index on the Indonesia Stock Exchange. The data collection technique in this study is documentation of the LQ45 Banking Index Stock Price on the Indonesian Stock Exchange.The results obtained in this study are that the model used in forecasting banking stock prices is the best model, the models include BBCA ARIMA (5.2.0), BBRI ARIMA (5.2.0), BMRI ARIMA (5.2, 0), BBNI ARIMA (2,2,0), and BBTN ARIMA (5,2,0). BBCA's share price decreased by -14.9%. BBRI's share price decreased by -5.8%. BMRI's share price decreased by -6.8%. BBNI's share price decreased by -58.5%. BBTN's share price decreased by -18.8%.106. Investors should not buy shares in banking stocks listed in the LQ45 index. This is because prices tend to fall and make investors suffer losses. However, if trading or investing in the near future, investors will buy shares of BBRI and BBTN companies, because within 1 month the shares will increase and investors or traders can get capital gains.

ECB communication sentiments: How do they relate to the economic environment and financial markets?

In this paper we examine multiple dimensions of ECB monetary policy communication by identifying its sentiment and relation with the economic environment and financial markets. We quantify communication sentiment using transcripts from official ECB communication events – press conferences, accounts and Executive Board speeches – as well as media reactions that highlight the key messages of those events. Importantly, we create distinctive lexicons for both of those communication types. We find that the overall trends in the sentiment indices for the analysed communication events closely resemble the movements of monetary policy stance as well as inflation dynamics in the euro area, both before and after the COVID-19 shock period. The communication tone generally shifts in advance of actual monetary policy actions. Using regression analysis, we find some expected, statistically significant effects of press conference sentiment on bank stock prices (information-type shock) and identify the impact of Executive Board speeches on euro area risk-free rates. Fragmentation issues among euro area member states do not seem to be negatively affected by the sentiments of the ECB’s communication. Still, policy makers should be aware that the tone of their communication events is likely to affect particular financial markets. These results are confirmed by various robustness checks.

Determinants of Price of Stock of Nepalese Commercial Banks

Determinants of stock price of Nepalese commercial banks are examined. Primary goal of the study is to analyze, and evaluate the share price fluctuations of Nepalese commercial banks. A descriptive and causal comparative research design was utilized to achieve the objectives of this research. Secondary data will be gathered from the annual reports of sample seven commercial banks, the NEPSE, and other related companies. The MPS has a positive relationship with EPS, P/E ratio, and BVPS but a negative relationship with DPS. It is found that there is a strong positive association between all independent variables (EPS, DPS, BVPS, and P/E Ratio) and the dependent variable (MPS) Examined are the factors that affect Nepalese commercial banks' stock prices. The analysis and evaluation of Nepalese commercial banks' share price fluctuations is the study's main objective. The MPS has a negative relationship with DPS but a positive relationship with EPS, P/E ratio, and BVPS. The study reveals that during the study period of the Nepalese commercial banks, MPS appears to move the greatest, while price earnings ratio fluctuates the least. The study period's findings also shown a significant positive correlation between commercial banks' stock prices and their EPS, DPS, P/E ratios, and BVPS. The EPS, DPS, P/E ratio, and BVPS have a considerable positive correlation with the share price of commercial banks.

Optimizing Banking Stock Price Prediction: Deep Learning Based Approach

Recently, the stock market has experienced significant instability, especially during the global pandemic which resulted in unprecedented economic impact. The main focus of this research is to develop an optimal prediction model using deep learning techniques for the projection of closing prices of bank stocks during the pandemic period. This study evaluates the performance of banking stocks, specifically ARTO, BRIS, BBNI, and BMRI in the Jakarta Composite Index (JCI). Data was extracted from Yahoo Finance and processed through LSTM and GRU algorithms, including data cleaning, normalisation, and descriptive statistical analysis. Scoring metrics such as MSE, RMSE, and MAPE are used to measure the effectiveness of the predictive models. The results show that the LSTM and GRU models can predict stock prices well. These findings provide a basis for trading strategies and improved decision-making in the stock market. Recent research confirms the importance of integrating deep learning methods such as LSTM and GRU in stock price prediction, helping to understand complex financial market fluctuations and improve prediction accuracy.

Are Financial Ratios Able to Predict Bank Stock Prices During the COVID-19 Pandemic?

Fundamental analysis, such as financial ratios, is important to ensure capital markets move efficiently. This analysis represents 69% of the variation in stock prices in the capital market. However, fundamental analysis has not been widely carried out because expertise is needed to analyze qualitative and quantitative data from company characteristics that underlie the movement of a stock. In 2020 – 2022, bank performance experienced fluctuations due to the Covid-19 pandemic which caused bank share prices to also fluctuate. On the other hand, banks have an important role as intermediary institutions or intermediaries to support the funding needs of the real sector or the business world. However, previous research on fundamental analysis largely excluded companies in the financial sector. Therefore, this article aims to find out whether financial ratios are able to predict bank share prices during the Covid-19 pandemic. There are five financial ratios used in this research, namely loan loss provision ratio, total capital ratio, profit margin ratio, current ratio, and solvency ratio. The population in this study are financial companies listed on the Indonesia Stock Exchange for the period 2020 - 2022. The sample was selected using a purposive sampling method and obtained 38 companies and 114 observations. The results of multiple regression analysis show that the loan loss provision ratio has a significant negative effect and the total capital ratio has a significant positive effect on bank share prices. Meanwhile, the net profit margin ratio, current ratio and solvency ratio do not have a significant effect on bank share prices. This research has implications for encouraging banks to improve disclosure policies and encouraging investors to hone fundamental analysis skills to reduce mispricing and make markets more efficient.

CEO overconfidence and the informativeness of bank stock prices

This study examines the effect of the overconfidence of chief executive officers (CEOs) on the informativeness of banks' stock prices. Using an option-based overconfidence measure, we demonstrate that banks with overconfident CEOs have less informative stock prices. This finding is robust to alternative measures of overconfident CEOs and to addressing endogeneity with propensity score matching, an instrumental variable approach, and difference-in-differences analysis. Furthermore, banking and financial market crises strengthen the negative effect of overconfident CEOs on stock price informativeness, especially in larger banks. Finally, better corporate governance or higher capital mitigates the negative impact of overconfident CEOs on banks' stock price informativeness. Policymakers should consider implementing supervisory strategies that require banks to provide accurate information and encourage private-sector monitoring of banks.

Effects of Inflation, Ten-Year Bond Yield Rate, and VIX Index on the Stock Prices of Banks Across All Three Market Capitalizations in India

This study investigates the impact of critical economic factors—namely, inflation, the 10-year bond yield rate, and the VIX index—on the stock prices of banks operating across different market capitalization segments in India. Through a comprehensive regression analysis framework, this research quantifies the relationships between these economic factors and bank stock prices while accounting for potential variances across large-cap, mid-cap, and small-cap banks. Utilizing data from the past five years, this analysis not only provides a nuanced understanding of how these macroeconomic indicators influence bank stock prices but also explores the specific effects on banks of varying market capitalizations. The findings reveal that small-cap companies are predominantly influenced by internal management decisions and capital allocation, whereas the consumer price index significantly predicts and reflects stock price behavior. Conversely, the bond yield rate and VIX index show minimal impact on stock prices. This study offers valuable insights for investors, policymakers, and financial institutions, aiding in the development of informed investment strategies and risk management practices.

The Influence of Intellectual Capital and Financial Performance on the Stock Prices of Commercial Banks in Indonesia with Company Size as a Moderation Variable

The Influence of Intellectual Capital and Financial Performance on the Stock Prices of Commercial Banks in Indonesia with Company Size as a Moderation Variable

Examining Volatility in Bank Stock Prices: A Comparative Exploration of Dividend Policies, Macroeconomic Influences, and Company-Specific Factors

This study aims to ascertain and compare factors influencing stock price volatility in terms of dividend policy, macroeconomic and company specific aspects for selected subset of listed banks in Bangladesh. Eleven years of secondary data (from 2011 to 2021) for fifteen commercial banks (representing 61.5% market capitalization of the banking sector) was acquired from diverse sources. The dependent variable chosen is stock price volatility, whereas the dividend policy is initially represented by dividend payout ratio (PRt & PRt-1), dividend yield (DYt & DYt-1). Several firm and country-specific macroeconomic indicators are used as control variables. A methodical approach followed by panel data analysis has been employed to identify a suitable model that can yield more accurate estimators. Consequently, some diagnostic tests are also performed to account for diagnosed problems: contemporaneous cross-sectional correlation, group-wise heteroskedasticity and autocorrelation; Driscoll-Kraay standard error regression model is finally applied. The study not only found significant negative impact of dividend payout ratio but also spotted a significant influence of inflation, EPS, and firm size on stock price volatility. Price volatility influenced by “No dividend policy” can be reinvestigated from the aspect of behavioral finance in the future. Furthermore, this study also sheds light on to what extent firm-specific and macroeconomic influence impact stock price volatility in Bangladesh's banking sector.

Impact of Macro-Microeconomic Factors on Stock Price of Islamic Bank Listed on IDX

Investors, however, also need to take into account the local economic trends. This has become a requirement for all Muslims worldwide and is done in order for the invested assets to become more productive and deliver the most benefit. This study intends to determine how macroeconomic and microeconomic variables (ROA, ROE, inflation, and GDP) affect the stock prices of Islamic bank listed on the IDX over a time period spanning 2016 to 2020 using the VAR/VECM method. The result show that there is no short-run correlation between any of the micro and macro variables, according to the results of the Vector Error Correction Model (VECM) test. On the other hand, there is a long-run correlation between the stock prices of Islamic Banks listed on the IDX and micro factors (ROA and ROE). In contrast to the ROA variable, Return on Equity (ROE) actually has a long-term negative impact on stock prices. Return on Assets (ROA) has a positive long-term impact on company prices. The ROE variable, regardless of the influence, whether it be positive or negative, makes the biggest percentage contribution to stock prices, followed by ROA, IPI, and then CPI.

PENGARUH FAKTOR INTERNAL DAN EKSTERNAL PERUSAHAAN TERHADAP HARGA SAHAM PADA BANK HIMBARA

The capital market is a place for investors to channel funds in the form of shares with the aim of investing. There are various internal and external factors that can influence Himbara Bank's stock price. The aim of this research is to determine the influence of GCG, firm size and inflation on firm performance and stock prices. This research uses quantitative analysis. In this research, the data analysis technique used is panel data path analysis. The data used is secondary data, using a time series from 2013-2022. The research results found that GCG partially influences firm performance. Firm size influences firm performance. Inflation affects firm performance. Firm size influences stock prices. Inflation has no effect on stock prices. Firm performance influences stock prices. Firm performance mediates firm size on stock prices. Firm performance does not mediate inflation on stock prices.

The Impact of Covid -19 Pandemic in Development Banks’ Stock Performance Evidence from Nepal

Propose: This study explores the relationship between COVID-19 and the stock market in Nepal from February 15th, 2020, to February 15th, 2023, with a focus on the impact on development banks. Adopting a descriptive research design, the study analyzes the risk and fluctuation in stock prices of development banks during the pandemic. The first half of 2020 witnessed a significant stock market crash due to the global spread of COVID-19 and subsequent economic disruptions caused by lockdowns. Methods: The study examines how different sectors within the stock market reacted to COVID-19, with sectors like natural gas and healthcare showing positive returns, while others like petroleum and entertainment experienced declines. It emphasizes the tradeoff between risk and return in inancial management, highlighting investors' demand for compensation for bearing risk. Findings: The findings suggest that development banks in Nepal faced increased risk and fluctuation in stock prices during the pandemic. However, the study also reveals opportunities for investors, as economic crises can create investment prospects. Contrary to some literature, the study indicates that the market index in Nepal showed positive correlations with the number of COVID-19 cases, deaths, recoveries, and active cases, suggesting no significant impact of COVID-19 on the stock market index. Values: This study contributes to understanding the dynamics of the stock market during crises like COVID-19 and provides insights for investors and financial analysts. Keywords: COVID-19, Development banks, Stock market, Stock market capitalization, Impact.

An Empirical Assessment of Factors Impacting Stock Prices of Nepalese Commercial Banks

This study examines the impact of various financial variables on the pricing of commercial banks in Nepal. Key financial metrics analyzed include earnings per share, dividend yield, price-toearnings (P/E) ratio, earnings yield, book value per share, money supply, market-to-book value ratio, and stock return. The research highlights the importance of market financial ratios in the investment decisions of Nepalese investors. Using data from 10 out of 20 commercial banks listed on the Nepal Stock Exchange, spanning 110 yearly observations from fiscal years 2012/13 to 2022/23, multiple regression models were employed to determine the relationships between these factors. The findings reveal that earnings per share, dividend yield, P/E ratio, book value per share, money supply, market-to-book value ratio, and stock return are significantly positively correlated with the prices of commercial banks. Conversely, earnings yield shows a negative correlation. Despite the strong preference for price and profitability metrics, the study's limited sample size and focus on commercial banks may affect the generalizability of the results. This research provides critical insights, particularly emphasizing the importance of earnings per share, dividend yield, P/E ratio, and book value per share in guiding investors' financial decisions in Nepal. The findings are anticipated to benefit investors, scholars, policymakers, and other stakeholders by enhancing their understanding of the factors influencing stock prices in the Nepalese banking sector.