Bank Pricing Research Articles

A Study on Effectiveness of Customer Retention Strategies Factors in Banking Sector

Competition among banks is fierce, and non-banks and other financial firms are also majorrivals. The problem is that it's really simple to replicate a financial product, and in the end, they allessentially do the same thing. Customer retention is a wide and complicated notion, and it is possible thatmany factors contribute to it. This paper study Customer service quality, customer happiness, switchingcosts, customer relationships, trust, and bank pricing were among the few determinants of customerretention that were examined in this study. India has a highly competitive banking sector thanks to theexistence of public, private, and international institutions. banks, faced with an increasingly competitivemarket, are implementing strategies to keep as many of their current clients as possible. Keeping currentcustomers happy is crucial in today's cutthroat business climate. The bank has to go above and beyondits basic functions to provide its clients a satisfying banking experience.

The Mismatch Between Macroeconomic Stability and Declining Stock Performance of Digital Banks in Indonesia: An Empirical Study of 2022-2023

This study examines the mismatch between macroeconomic stability and the stock performance of digital banks in Indonesia over the period 2022-2023. The results of the analysis show that the USD/IDR exchange rate and Bank Indonesia interest rate have a significant negative effect on stock prices, while inflation shows no significant effect. These findings suggest that despite stable macroeconomic conditions, the share prices of digital banks experienced a significant decline, indicating market inefficiencies. This study makes a theoretical contribution by revealing the role of exchange rate and interest rate fluctuations in influencing the stock performance of digital banks in emerging markets. In conclusion, factors such as investor sentiment, market behavior, and the influence of digital financial technology need to be taken into account in developing strategies to support the stability and growth of the digital banking sector in Indonesia. The results of this study are important for policymakers, regulators, and market participants in dealing with the challenges faced by the digital banking sector in Indonesia. Keywords Digital banking, macroeconomic stability, stock performance, market inefficiency.

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.

Relevance Vector Machines for Index Direction Predictions: An Application on Borsa Istanbul

This study investigates index prediction performance of Relevance Vector Machines (RVM) and frequently applied Ridge Regression and Support Vector Machines (SVM). Daily prices of BIST Banks and BIST Financials indices of Borsa Istanbul are used to obtain one-day-ahead predictions of the algorithms. According to estimated performance measures, RVM yielded mostly the best metrics in both periods of BIST Banks. While SVM obtained the best performance metrics on BIST Financials index, metrics of RVM were not far from the best. Overall, the results indicate the applicability of RVM in predicting index directions and has a potential to be a good rival of SVM.

Moderating Effect of Inflation Rate on the Relationship Between Earnings Retention Ratio and Share Price of Banks

Moderating Effect of Inflation Rate on the Relationship Between Earnings Retention Ratio and Share Price of Banks

The Effect of Over-Confidence on Jiwasraya's 2017-2020 Payment Defaults

Overconfidence is a term that refers to the human tendency to estimate their abilities, knowledge, or results with more confidence than they should. PT. Jiwasraya Insurance (Persero), the oldest insurance company in Indonesia which is owned by BUMN, was declared to have failed to pay its customers' policies in 2020. This failure to pay was caused by errors in managing customer funds, namely by collecting funds for JS Products. Saving Plan and investing with customer funds in high risk stocks. The purpose of this research is to find out why Jiwasraya experienced payment failure. Therefore, the variable prices of high-risk shares purchased by companies from 2017 to 2020 is used as a secondary variable. Secondary data was obtained from the Indonesian Stock Exchange and the Financial Services Authority. This study uses. Vector Auto regressive (VAR) analysis technique with Stata/IC 15.0 software. The research results show that it is the Jiwasraya company's share price that influences Jiwasraya's shares in the short term. In the long term, it shows that the share price of Semen Baturaja does not have a significant effect on Jiwasraya's share price. Meanwhile, the share price of the West Java Development Bank has a significant negative effect on Jiwasraya's share price. Then, PP Properti's share price has a significant positive effect on Jiwasraya's share price. The results of this research can be used as consideration for companies and investors in making investment decisions so as not to take high-risk actions because of too high self-confidence.

Understanding Barriers to Financial Access: Insights from Bank Pricing Data

Understanding Barriers to Financial Access: Insights from Bank Pricing Data

An Innovative Study on Stock Price Prediction for Investment Decision Through ARIMA and LSTM with Recurrent Neural Network

The securities market is extremely volatile and difficult to prognosticate. Stock prices are depending upon numerous factors. To reduce the risk of volatility, it is very important to apply an accurate mechanism to forecast stock prices. The importance of share price prediction forecasting in finance and economics has sparked researchers’ interest in creating more reliable forecasting models over time. In this research paper, the researchers try to explore two different applications based on linear and nonlinear (RNN) functions. The criteria for the stock price predictions are evolved using Auto Regressive Integrated Moving Average (ARIMA) which takes the linearity function from the past share prices. The ARIMA model assumes the future prices usually be similar to past. Sudden changes may not reflect in this model. The nonlinearity Recurrent Neural Network (RNN) is going to be applied for share price prediction so that it can be taken into account the quick changes that are occurring in the market environment. To test the RNN, the study used the Long Short Term Memory (LSTM) model which takes the support of Artificial Intelligence. Taking the sample of share prices of banks listed in the NIFTY index, the ARIMA and LSTM have been performed and analyzed. Stock price predictions for banks listed in the NIFTY bank index are found better with the ARIMA model than with the LSTM model.

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.

Portfolio Analysis of Financial Institutions in Nepal

In this paper we empirically investigated risk return dynamics of the financial institutions that were selected from the Nepal Stock Exchange for the period of 2016-2022. The objective of this study is to analyze the portfolio of different FIs based on the return and risk parameters using ex-post returns data. This study employed financial and statistical tools to draw the conclusion. The beta values show that commercial banks’ share prices are more volatile than the prices of development banks and finance companies. The alpha coefficients reveal that share prices of all commercial banks and development banks are found overvalued and couple of finance companies is undervalued. The results of correlation coefficient offer a scope of diversification in the Nepalese stock market.

The Analysis of Black-Scholes Model of Option Pricing with Time-Varying Parameters on Share Prices for Capital Market

This paper studied the perception of European option which is geared towards valuation of financial assets at a prescribed time in the future. In particular, the analytic formula of Black-Scholes model was considered for share prices of Fidelity and Access banks which gave closed form prices of call options. The explicit price on the variations of maturity days is found accordingly. The closed form prices of both banks were compared. The simulation results show that: the share price determines the value of call option prices. An increase on the maturity days dominantly increases the value of call option for both Fidelity Bank, Access Bank and their future merger Bank. Merging of the two banks improved the value of call option prices. Fidelity bank has a good maximum value of call option prices during the period of investments, Kolmogorov ?Smirnov (KS) test shows that the two call option prices (Fidelity and Access) do not come from a common distribution, the normality test of both banks are not significant. The results presents to the Banks management, a basis for taking vital decisions, depending on the levels of their investments.

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

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.

The Effect of Sustainability Financial Disclosure, Sustainability Governance and Financing In The Sustainable Business Activities Category On The Share Price of Banks Listed On The Indonesia Stock Exchange

This research aims to determine the influence of sustainable financial disclosure, sustainable governance and financing in the category of sustainable business activities on banking share prices listed on the Indonesia Stock Exchange. Based on data processing from 40 banks listed on the Indonesia Stock Exchange, the results showed that sustainable financial disclosure using the GRI FS indicator had a significant positive effect on the share prices of banks listed on the Indonesia Stock Exchange. Meanwhile, sustainability governance does not have a significant effect on the price of banking shares listed on the Indonesia Stock Exchange, and environmental costs do not have a significant effect on the price of banking shares listed on the Indonesia Stock Exchange

J&L Railroad: The Board Meeting

This short case could be handed out at the end of class discussion on “J&L Railroad” [UVA-F-1053] in preparation for the following class, or if students are more experienced with hedging and option pricing, the instructor may choose to cover both cases in a single class period. It is the companion case to “J&L Railroad” [UVA-F-1053], and presents more technical issues regarding the hedging problem by requiring students to understand option-pricing principles. The board likes the CFO's hedging recommendations, but it wants a more careful analysis of the bank's prices for its risk-management products: the caps and floors. Besides demanding an understanding of option pricing, this case puts particular emphasis on the calculation and use of implied volatility.

PENDEKATAN RGEC DALAM PENGUKURAN KESEHATAN PERBANKAN SELAMA PANDEMI COVID-19

In 2020, there was a decrease in the net profit of state-owned banks by an average of 40% for each bank, followed by an increase in the potential for credit risk and a decrease in the share price of state-owned banks. In maintaining the level of public trust, banks must continue to maintain their level of health. This level of health can be calculated through RGEC (Risk Profile, Good Corporate Governance, Earning and Capital) calculation analysis. The method used is descriptive comparative, namely by examining annual financial reports which are then compared with other reports so that differences in the soundness level of banks and state-owned banks are known during the Covid-19 pandemic. The results of this study show difference in the level of soundness every year during the COVID-19 pandemic from 2020 to 2022 at state-owned banks as indicated by changes in RGEC calculation ratios.

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.

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.