Bank Stock Research Articles

Analyzing the Risk-Return Tradeoff in Commercial Banks' Common Stock: A Case Study of Nepalese Banks

This study investigates the risk-return tradeoff in the common stock of Nepalese commercial banks over a five-year period from 2018/19 to 2022/23. By analyzing financial data from four prominent banks listed on the Nepal Stock Exchange (NEPSE) i.e. Global IME Bank Limited (GBIME), Nepal Investment Mega Bank (NIMB), Nabil Bank Limited (NABIL), and Kumari Bank Limited (KBL). The study depends on the closing prices of these four commercial banks, which were generously provided through the NEPSE Index and annual general meeting (AGM) reports of each respective bank. The research aims to provide a comprehensive understanding of their risk profiles and expected returns using the Capital Asset Pricing Model (CAPM). The study employs descriptive statistics like mean, standard deviation, coefficient of variation, and maximum/minimum returns. The findings reveal significant variations in performance and risk levels: GBIME and KBL show positive average returns with high volatility, whereas NIMB and NABIL exhibit negative average returns, indicating losses. GBIME’s stock is slightly less volatile than the market, while NIMB’s low beta suggests it is suitable for conservative investors. NABIL’s and KBL’s higher betas indicate more volatility, appealing to high-risk tolerant investors. The study underscores the importance of portfolio diversification and continuous monitoring of market conditions for informed investment decisions. These insights are valuable for investors, financial regulators, and policymakers in developing effective risk management strategies and enhancing financial stability in Nepal's banking sector.

Herd behavior in U.S. bank stocks

This study investigates investor herd biases in U.S. banks' stock returns before, after, and during the COVID-19 pandemic by focusing on the differential impacts of monetary policy cycles and bank regulatory framework. Our results display fundamental herding for both large stress-tested banks and non-stress-tested regional banks during the pre-pandemic tightening monetary policy period in which bank fundamentals were improved through regulatory changes after the global financial crisis. However, we find evidence of nonfundamental herding during the post-pandemic tightening monetary policy period in which bank fundamentals were weakened. This situation might have contributed to the value irrelevance of bank fundamental information to stock prices. Our results have important implications for regulators, policymakers, and investors.

Decoding market reactions: The certification role of EU-wide stress tests

We study the market’s reaction to the disclosure of EU-wide stress test results across four periods (2014, 2016, 2018, and 2021). Our novel approach contributes to the literature by studying how stress test disclosures influence both the mean and variance (first and second moments) of bank stock performance, extending beyond previous studies focused mainly on the first moment of equity returns. Using one-factor market and structural Engle–Siriwardane type GARCH models, we find that the publication of stress tests provides new information to the markets: Banks with weaker performance in the tests experience, on average, a reduction in stock returns and an increase in volatility, while the reverse holds for banks performing well. Our findings confirm the important role of stress tests in enhancing transparency and market discipline, thereby supporting investors in assessing the resilience of the banking sector more effectively, particularly during periods of higher uncertainty.

PENGARUH PROFITABILITAS TERHADAP NILAI PERUSAHAAN PERBANKAN MELALUI KINERJA KEUANGAN SEBAGAI VARIABEL INTERVENING

This study aims to test and analyze the effect ROA, ROE and EPS on banking company value with company financial performance as an intervening variable. The unit of analysis in this study is a banking stocks listed on the LQ45 index in 2018-2022 as many as 5 companies. Samples were taken using purposive sampling. Data analysis was carried out using the SmartPLS version 3.0 program and data collection through secondary data. Based on the results of data analysis, it is known that ROA significantly has a positive effect on financial performance. ROA has a negative effect on firm value. ROE has a positive effect on financial performance. ROE significantly has a negative effect on firm value EPS has a negative effect on financial performance. EPS significantly has a negative effect on firm value. Financial performance significantly has a positive effect on firm value. Financial performance mediates the effect of ROA on firm value positively and significantly. Financial performance mediates the effect of ROE on firm value positively. Financial performance mediates the effect of EPS on firm value negatively.

Distribution of lobster larvae, Homarus americanus, and zooplankton prey in the gulf of maine and georges bank stock area

The American lobster, Homarus americanus H. Milne-Edwards, 1837 supports a valuable fishery subject to rapid warming of the Gulf of Maine (GOM) and Georges Bank (GBK). Comprehensive information related to large-scale larval distribution is lacking due to the logistical challenge of sampling their hyper-dispersed larvae. In 2021, we established seasonal abundance patterns of larvae and their prey in the GOM on an unprecedented spatial scale with a season-long survey at transects spanning approximately 300 km of coastline. We compared the current distribution of larvae with historical surveys with respect to differences between inshore and offshore (5 versus 40 km), and between eastern and western hydrographic regions. We also examined spatial and temporal patterns in the abundance of zooplankton prey. The distribution of recently hatched stage I larvae extended offshore at the transect off Rye, NH and was consistent with the reported movement of ovigerous lobsters offshore to hatch their eggs. By contrast, stage I larvae were most abundant nearshore and rare offshore at other transects along the coast. Our results confirmed historical patterns of high abundance of competent stage IV larvae in the western Gulf of Maine and low abundance in the east. We also identified the potential for a temporal mismatch between the abundance of larvae and the biovolume of copepods at transects in Milbridge, ME and Rye, NH with peak copepod abundance occurring either well before or after the peak abundance of lobster larvae. The data collected fill a gap in our understanding of larval distributions and seasonal progression in the Gulf of Maine, establish a baseline for future studies, and provide an opportunity to validate established biophysical models of larval transport. Yet a longer time series of broad-scale surveys is needed to better understand intricacies of factors influencing larval abundance and distribution. The project was an industry-led collaboration with government and academic scientists providing proof of concept for future collaborative research.

Credit market conditions, expected return proxies, and bank stock returns

We evaluate the performance of expected return proxies during extreme credit market conditions and extreme phases of business cycles when realized returns on banks stocks are large in absolute value. We construct three sets of expected return proxies for individual bank stocks: (i) characteristic-based proxies; (ii) standard risk-factor-based proxies; and (iii) risk-factor-based proxies in which betas depend on firm characteristics. Based on the newly developed minimum error variance (MEV) criterion (Lee et al., 2020), the best performing expected return proxy is the risk-factor-based model that allows betas to vary with firm characteristics. We also examine whether these three expected return proxies can capture actual returns during either extreme credit market or extreme business-cycle conditions. We find that both risk-factor-based proxies explain returns better than characteristic-based proxies during these periods.

Homogeneity Pursuit in the Functional-Coefficient Quantile Regression Model for Panel Data with Censored Data

Abstract Homogeneity identification of panel data models has been popular in the literature in recent years. Most of the existing works only focus on the complete data case. This paper considers a functional-coefficient quantile regression model for panel data with homogeneity when its response variables are subject to censoring. In particular, we consider a more general censoring framework, i.e. different types of censoring are allowed to occur in the model simultaneously. For this, a “three-stage” method is proposed, which includes the preliminary estimation of subject-specific function coefficients based on data augmentation, the identification of group structure over subjects by clustering, and post-grouping estimation of function coefficients. Simulation studies considering the left-, right-, and double-censored data, are carried out to verify the finite-sample properties of the proposed method. Simulation results show that our method gives comparable performance to the complete data case. The application to the bank stock data further illustrates the practical advantages of this method.

Ownership and investor responses to news on fraud and pecuniary actions: a comparative analysis of Indian banks

Purpose This study aims to understand investors’ reactions to news on fraud and pecuniary and regulatory action in privately owned and government-owned banks. Design/methodology/approach To examine the role of ownership holdings, this study deploys event study methodology and cross-sectional regression to analyze the abnormal returns and the intergroup dynamics. Event study methodology studies the abnormal return on stock prices on days when fraud, pecuniary actions and regulatory news were reported for 36 banks that are listed on the NSE. Data on news has been collected from Reuters for 110 months. Cross-sectional regression analyses are done to examine whether selected variables on bank characteristics influence the abnormal returns. Exploring the intergroup dynamics between government and privately owned banks helps to accentuate how stakeholders influence investor responses. Findings Private and government-owned banks display an anomalous return pattern during the events, though to varying degrees and for a longer duration. The sharp downturn observed in private banks in response to pecuniary and regulatory actions related to news can be attributed to the associated risk of these banks. Intergroup dynamics further demonstrate that the effect of such news regarding government-owned bank stocks is more pronounced on privately owned banks compared to the effect of news related to privately owned banks on public banks. Originality/value The study shows how ownership structure variedly impacts investors’ response to news related to fraud, and pecuniary and regulatory actions on Indian banks, which may eventually ask for customized investment approaches for government-owned and privately owned banks.

MARKET REACTION TO THE IMPLEMENTATION OF BASEL CAPITAL IN SOUTH AFRICAN BANKS: EVENT STUDY APPROACH

This study investigated the stock market reaction and the effect of the implementation of Basel II and Basel III on the stock returns of South African banks. In achieving this aim, this study focused on daily and annual data of six commercial banks from 3rd January 2004 to 31st December 2022. The event study methodology was employed to identify abnormal returns around the specified event dates. The effect of the changes in Basel capital requirements on stock returns was not uniform across the four events. The market reacted favourably to the implementation of the Basel II requirements in the country. There was a significantly negative market reaction to the subsequent full implementation of Basel III official. Finally, higher Basel capital requirements (CAR) was associated with lower bank stock returns. The findings implied that bank regulators increase capital to strengthen the banking system but constrain the maximisation of shareholders’ values.

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.

Determinants of Bank Profitability and Implications for Company Value with Moderating Dividend Policy

The research is quantitative and the objective is to determine the internal (Loan Quality, Third Party Fund, Managerial Efficiency) and external (BI Rate, Inflation) variables that determine Bank profitability, and the impact of this profitability on company value by moderating the Bank's stock dividend policy. The method used is panel data regression and moderated regression analysis using Eviews 10. The data used is secondary data with a sample of 10 Book 4 banks listed on the Indonesian Stock Exchange for the 2011-2020 period. The results obtained are first Loan Quality, Third Party Funds, Managerial Efficiency, Bank Indonesia Interest Rates and Inflation Rates simultaneously have a significant and positive effect on Banking Profitability, second Banking Profitability partially has a significant and positive effect on Company Value and third Banking Profitability which is moderated by Dividend Policy partially has a significant and positive effect on Company Value

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.

The Implication of the New CBN Cashless Economy Policy on Nigerian Banking Stocks: GARCH Models Approach

The importance of the banking sector to any nation's economy cannot be overemphasized. An efficient banking system enhances effective resource allocation and therefore promotes economic growth. Since this sector is important to any economy, the central bank in every nation plays a leading role in formulating policies aimed at regulating and stabilizing the banking system with the ultimate aim of achieving macroeconomic stability. The Cashless policy was first introduced in Nigeria in January 2012 to ease the difficulty inherent in cash-related transactions. However, at the time the policy was introduced, deposit banks were not prepared to ensure a smooth working cashless economy system. The policy was thus suspended in August 2015 and consequently re-introduced in January 2023. This study investigated the effect of this cashless policy on Nigerian banking stocks using GARCH and tGARCH models. The study reveals that banks’ stocks return was affected at the time under review by the cashless economy policy. The study further shows that it will take about a month and nine days for the conditional variance in the series to revert halfway. The convergence of the parameters based on Monte Carlo simulations indicates that both the models can capture the volatility in the stock returns, except that tGARCH seems to be skewed to the right as is expected.

Social media-based implosion of Silicon Valley Bank and its domino effect on bank stock indices: evidence from advanced machine and deep learning algorithms

Social media-driven speculations play a crucial role in triggering the collapse of the banking system and stock markets. In this paper, we investigate the effect of Twitter-based investor sentiment on the collapse of Silicon Valley Bank (SVB), the 16th largest bank in the US. Additionally, we examine the spillover effect of the social media-based investor sentiment and SVB collapse on the bank stock indices from twelve countries where Global Systemically Important Banks (G-SIBs) operate. Advanced machine and deep learning models are employed to model the social media-based investors’ sentiment regarding SVB implosion and its spillover effect on the G-SIBs’ bank stock indices. Our results reveal that social media-based negative investors’ sentiment played an important role in SVB implosion. Our results further show that the negative investors’ sentiment persisted, and its systemic shock was transmitted to the G-SIBs bank stock indices. Importantly, our results provide a lead and lag relationship between investors’ sentiment and returns of G-SIBs bank stock indices. The findings of this study offer crucial insights for policymakers to consider the external shocks associated with social media-based investors’ sentiment when devising policies related to bank runs, thus helping to prevent future financial crises and cross-border contagion.

Genetic Characterization of Endangered Sterlet (Acipenser ruthenus, Linnaeus 1758) Gene Bank Broodstock, Natural and Cultured Populations in Hungary

The sterlet (Acipenser ruthenus) is the smallest-bodied endangered species among the six native sturgeon species of the Danube River, and self-sustaining populations still inhabit the Hungarian section of the Danube River and its largest tributary, the Tisza River. Their populations are drastically decreasing; however, they still have natural reproduction in these habitats. For the genetic conservation of the species, an ex situ gene bank is maintained in Hungary. The present study aimed to analyze the genetic resources of a gene bank with a near 40-year history and to compare it with natural populations and farmed stocks. Twelve microsatellites were used for population genetics analyses and individual genotyping of 268 specimens from two natural habitats (Danube and Tisza Rivers) and three captive stocks (a gene bank broodstock and two farms). Microsatellites revealed similar patterns among wild populations and gene bank stocks and did not show genetic differentiation (FST: 0.016–0.017) among them. These results confirmed that the gene bank broodstock properly represents the genetic background of the Danube and Tisza populations and is suitable as a source of breeding materials for the restocking programs. Negative trends were detected in the farmed stocks, reflected in reduced polymorphism at a few loci. The results of the principal component analyses indicate the farm stocks’ separation from the wild and gene bank stocks. The present genetic characterization study reveals a valuable captive stock of the endangered sterlet populations and provides unique information about the genetic similarities and differences among farms and wild stocks in Hungary. Our results provide information that contributes to preserving the genetic structure and variability in sterlet populations and supports the management of gene bank broodstock—avoiding inbreeding and preserving the unique genetic background of the Carpathian basin.

Stock Price Analysis and Forecasting of Bank of China Based on ARIMA Model

The stock market is of great importance to the development of the national economy. The price changes of bank stocks have an important impact on the whole stock market. Therefore, it is of practical value to model the changes in bank stock prices and forecast the future trends. Currently, there is a limited number of studies examining the utilization of the ARIMA model in forecasting stock prices. It is crucial to investigate its level of accuracy. This study employs the ARIMA model to conduct an empirical analysis on the time series data of Bank of China's opening price from January 1st, 2024, to January 31st, 2024. The objective is to predict the stock price for the subsequent 28 days and compare it with actual values. The findings reveal that short-term stock price predictions based on the ARIMA model exhibit a high degree of precision. In conclusion, the ARIMA model can offer valuable insights and serve as a theoretical foundation for investors and decision-makers to some extent. This paper will provide reference for the subsequent research on stock price forecasting and ARIMA model, and fill the existing research gaps.

Macro-financial nexus: a systematic review on the impact of macroeconomic factors on bank stock returns

Macro-financial nexus: a systematic review on the impact of macroeconomic factors on bank stock returns