Bank Returns Research Articles

Can Ensemble Machine Learning Methods Predict Stock Returns for Indian Banks Using Technical Indicators?

This paper develops ensemble machine learning models (XGBoost, Gradient Boosting, and AdaBoost in addition to Random Forest) for predicting stock returns of Indian banks using technical indicators. These indicators are based on three broad categories of technical analysis: Price, Volume, and Turnover. Various error metrics like Mean Absolute Error (MAE), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), Root-Mean-Squared-Error (RMSE) have been used to check the performance of the models. Results show that the XGBoost algorithm performs best among the four ensemble models. The mean of absolute error and the root-mean-square -error vary around 3–5%. The feature importance plots generated by the models depict the importance of the variables in predicting the output. The proposed machine learning models help traders, investors, as well as portfolio managers, better predict the stock market trends and, in turn, the returns, particularly in banking stocks minimizing their sole dependency on macroeconomic factors. The techniques further assist the market participants in pre-empting any price-volume action across stocks irrespective of their size, liquidity, or past turnover. Finally, the techniques are incredibly robust and display a strong capability in predicting trend forecasts, particularly with any large deviations.

ANALISIS PORTOFOLIO KREDIT, RISIKO, DAN RETURN BANK UMUM KONVENSIONAL

This study aims to determine the credit portfolio strategy (focus or diversification strategy) based on the economic sector in conventional commercial banks grouped by business activity (BUKU) in the period January 2016 - December 2018 and analyze the effect of credit portfolio concentration and credit risk on rates of return. This study uses secondary data obtained from Indonesian Banking Statistics at the Financial Services Authority (OJK). This study used 4 samples, namely BUKU I, BUKU II, BUKU III, BUKU IV. Bank return as dependent variable was measured by Return on Assets (ROA) whereas Concentration of Credit Portfolio as independent variable was measured by the Herfindahl-Hirschman Index (HHI). The mediating variable (Credit Risk) was measured by Non-Performing Loans (NPL). This study used panel data regression with fixed effect model to test direct effects and Sobel Test to test indirect effect. The results showed that the concentration of the credit portfolio had a positive effect on credit risk, while credit risk had a negative effect on return. In addition, the mediating role of the credit risk variable is not proven to affect the effect of the credit portfolio and credit risk. In conclusion, the credit portfolio concentration strategy in certain sector can increase credit risk so that it tends to reduce the rate of return. Thus, this research suggests that banks need to diversify their credit portfolios to minimize credit risk.an risiko kredit.

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

How does financial performance affect financial inclusion for developing countries?

ABSTRACT This study aims to detect the relationship between financial inclusion and financial performance in the banking sector. Within this scope, firstly, we develop an index for financial inclusion which consists of various dimensions for 85 developing countries in the 2005–2017 time period. Then, we apply static and dynamic panel data analyses. Static panel data analysis findings indicate that financial performance indicators such as bank return on assets, bank return on equity, and bank net interest margin positively affect and bank lending-deposit spread negatively affects financial inclusion, but bank non-interest income to total income has a statistically insignificant coefficient. Also, as a robustness analysis, dynamic panel data analysis provides evidence that financial performance is important for financial inclusion. According to our findings, we can say that the increase in the profitability of the banking sector is one of the triggers of financial inclusion for developing countries.

Investor Perception, Market Reaction, and Post-Issue Performance in Bank Seasoned Equity Offerings

Using a large sample of bank seasoned equity offerings (SEO) from 2002 to 2017, we first documented detailed descriptive statistics, and showed that nonperforming assets ratio, our primary measure of bank asset quality, reached the highest value immediately after the 2008 economic crisis, which also corresponds to a higher number of SEOs around these years because banks needed to recapitalize. The capital ratio, which is required to be at least at a minimum level (relative to risk-weighted assets) for banks by regulation, also increased after the economic crisis, which may be due to a higher requirement for banks as well as banks’ desire to hold more capital. The SEO announcement period abnormal stock-returns reached the lowest number around the economic crisis, as did the longer-run 6-month, post-SEO cumulative abnormal returns and buy-and-hold abnormal returns. Examining the differences between banks, we found, in both univariate and multivariate regression results controlling for other variables, that the bank capital ratio as at the time of the SEO announcement is significantly and positively associated with announcement period abnormal returns, while nonperforming assets ratio of the bank as at the time of SEO announcements is not. However, the nonperforming assets ratio as at the time of the SEO announcements had a significantly negative association with post-SEO, 6-month longer-run abnormal stock returns, while the capital ratio did not have any significant association. The nonperforming assets ratio as at the time of SEO announcement was also significantly and negatively related to bank return on assets 6 months and 12 months after SEO, while the capital ratio was not. Thus, investors appear to perceive a well-ingrained, well-publicized regulatory norm—the capital ratio—as indicative of value creation as at the time of bank SEO announcements, while loan asset quality, which may be relatively more opaque, may determine post-SEO performance.

Impact of Electronic Banking on Operational Performance of Commercial Banks in Sri Lanka

The banking industry has experienced a dramatic change resulting from the adoption of Information Communication Technology. The data was gathered from 2014-2019 concerning internet banking, branch network and Automated Teller Machine, based on the annual reports of selected ten banks. Regression analysis was done for the period to determine the effects of e-banking on commercial banks’ operations. Data is stationary at the level and normally distributed. Under the fixed-effect model, this study found a positive significant relationship among Internet Banking return on Assets, negative significant with Return on Assets and Branch Network, Automated Teller Machine. Also, an insignificant relationship between Return on Equity and Internet Banking so, internet banking is familiar with a recent year in Sri Lanka. Cost to Income and Internet Banking have a negative significance and other all variables are a significant relationship with Cost to Income. overall models statistically significant. Results suggest that E-banking has significantly improved the bank operational performance in Sri Lank from 2014 to 2019.

On bank return and volatility spillovers: Identifying transmitters and receivers during crisis periods

This study investigates dynamic bank-return correlation and spillovers among G7 advanced markets, employing an asymmetric multivariate GARCH approach and the forecast-error variance decomposition framework of a generalized VAR model and using a time-varying parameter autoregressive model. We utilize weekly bank stock indices over a long period (2000–2020) covering the recent Global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). Dynamic spillover analysis reveals evidence of contagion effects during recent episodes. It is also shown that the impact of the GFC is notably higher than that of the ESDC. Major spillover transmitters are the markets of France, Germany and the UK, with the US market being vulnerable to shocks from European markets. Useful implications arise for policy makers and investors.

The Effect of Covid-19 on Bank Profitability Determinants of Developed and Developing Economies

We have learned from the Covid 19 crisis that pandemics are inevitable, and the financial systems need to be ready to withstand such global shocks. This study aims to uncover determinants that are vital in maintaining bank profitability during such a crisis by providing evidence on how Covid-19 impacted bank profitability. Additionally, we test whether the crisis moderated the relationship between typical determinants and bank profitability across developed and developing economies. The study uses generalized least squared dummy variable model estimation. Six-year quarterly bank specific data of the top 10 countries from South Asia and Europe based on the highest GDPs is used. The study finds evidence of a significant impact of the pandemic on bank return on assets and equity. Additionally, the evidence suggests that covid-19 impacted bank profitability differently across the developed and developing countries. Covid-19 caused profitability to fall in the homogeneous European banks, whereas profitability increased for South Asian banks during the Covid crisis. We find that the pandemic moderated the relationship between bank profitability and its determinants. Credit quality and bank efficiency became less important in determining bank profitability during the Covid period. In contrast, bank size and maintaining liquidity became more important determinants. Additionally, the magnitude of capital ratio as a determinant of return on assets decreased during Covid. The moderating role of covid-19 on bank profitability determinants would be of value to both academicians and practitioners.

“Is there any Causality between the Islamic Banks’ Deposit Returns and the Conventional Banks’ Interest Rates? Evidence from Malaysian Commercial Banking”

This paper examined and compared the Islamic banks’ time series rates of return to depositors, 1-month, 3-month, 6-month, 9-month, and 12-month as well as the rate of return on Islamic Bank's Mudharabah saving and with the conventional banks’ similar time series deposit interest rates during 2001-2015. Non-cointegration of monthly and quarterly series of deposit interest rates, established by Johansen Cointegration test, led to the VAR Granger causality test which showed unidirectional causality running from the conventional banks’ deposit interest rates to the Islamic banks’ rate of returns. The establishment of cointegration for the conventional bank and the Islamic bank series of 6-month, 9-month, and 12-month as well as saving deposit rates series by Johansen Cointegration test led to the VEC model which establishes the short term dynamics and the stability of long run equilibrium between the rates of return of Islamic banks and interest rates of the conventional banks. The Vector Error correction results showed the speed of convergence varied from 18 percent to 24 percent. The results of the VEC Granger causality /Wald test (F-test) found unidirectional causality i.e. the direction causality running from conventional banks’ interest rate to the Islamic bank’s rate of return in all series, 6-month, 9-month, 12-month, and the saving deposit.

Are Islamic banks more resilient to the crises vis-à-vis conventional banks? Evidence from the COVID-19 shock using stock market data

The debate regarding the performance of Islamic banks vis-à-vis conventional counterparts has attracted growing attention recently. Exploiting the Covid-19 health and economic crisis as an exogenous shock, we extend this debate by examining the resilience of Islamic banks vis-à-vis conventional banks during this shock. Using data from the Gulf Cooperation Council member states, we find stock market investors have not assessed the Islamic banks to be superior to conventional ones during the Covid-19 market meltdown. Specifically, our findings show Covid-19 confirmed cases, government social distancing policies and feverish period (i.e., 24 February to 17 March 2020) have had negative impact on stock returns of both Islamic and conventional banks alike. Interestingly, the adverse impact of social distancing policies is stronger on Islamic banks due to their inherent higher cost structure. Additionally, we find the marginal adverse impact of Covid-19 shock is weaker on banks with higher liquid assets holdings on the onset of the Covid-19 shock. Moreover, larger banks were hit harder during the first quarter of 2020, however, they also recovered more quickly during the second quarter. Results are robust with alternative estimation methods, matched sample of Islamic and conventional banks, cross-sectional analysis with fever period and extended sample period.

Exploring the asymmetric effects of loan portfolio diversification on bank profitability

The paper analyzes how the effects of loan portfolio diversification on bank profitability differ according to bank size and state ownership. Through data on Vietnamese banks during 2008–2019 and the dynamic panel model, we strongly confirm the average adverse impacts of sectoral loan portfolio diversification on bank profitability. Further analysis indicates that the drawback of loan portfolio diversification is mitigated for larger banks rather than smaller counterparts. Regarding the asymmetric effects induced by bank ownership, bank profits increase with loan portfolio diversification at state-owned banks, as opposed to the cost implication found for private banks. Additionally, the paper documents the nonlinear inverted U-shaped relationship between loan portfolio diversification and bank returns as a bank risk function. Concretely, increased bank risk could diminish the harmful effects of loan portfolio diversification on bank returns; when the level of risk is exceptionally high, these harmful effects may rise again.

The Impact of Corporate Governance and Political Connectedness on the Financial Performance of Lebanese Banks during the Financial Crisis of 2019–2021

The Lebanese banking sector has become risky due to political and economic crises. At such times, corporate governance mechanisms ensure objectivity of assessment and rationality in decision making. We examine the impact of internal corporate governance mechanisms on the performance of Lebanese banks, with political involvement in the administration and ownership of the banks. We used linear regression on a sample of 194 bank-year observations from 2016 to 2021. The presence of independent members on boards of directors, and ownership concentration due to family ownership, had positive effects on bank return on assets, return on equity, liquidity levels, and loans issued. Efficient control, along with the presence of audit, and compliance committees reduced risk by increasing capital adequacy and reducing non-performing loans. Both administrative political connections and ownership political connections increased return on assets, increased return on equity, increased liquidity levels, and increased loans to deposits, while increasing non-performing loans. Agency conflicts suggest that granting loans due to political pressure increased non-performing loans.

The Role of Economic Policy Uncertainty in Predicting Stock Return Volatility in the Banking Industry: A Big Data Analysis

The research aims to study the effects of economic policy uncertainty on the return volatility of stocks with data from the largest banking institutions in Greece. Volatility is constructed using intraday data, whereas the research period extends over a period of about thirteen years, more specifically from January 5, 2001, to June 30, 2014. This period includes various phases of the market, such as stock market crashes along with stock market booms (e.g. the financial crisis of 2007 and 2008 in the United States and the European sovereign debt crisis). The estimated regressions were used to indicate the direct effects of economic policy uncertainty on the return volatility of the stocks of the four large Greek banks. The volatility index is constructed based on intraday data, whereas four different estimators of volatility were used. There is a statistically significant "direct" effect of economic policy uncertainty on the volatility of stock returns of the largest Greek banks, which are (a) Alpha Bank, (b) Eurobank, (c) National Bank of Greece, and (d) Piraeus Bank. Such findings are highly important for specific groups of people, such as investors, policymakers, and regulators. This study is the first research that seeks to identify the effect of economic policy uncertainty on the stock return volatility of the Greek banking system, constructed from intraday data. Doi: 10.28991/ESJ-2022-06-03-011 Full Text: PDF

THE IMPACT OF BUY – SELL RECOMMENDATIONS ON BANKS’ STOCK RETURNS

The aim of this research was to investigate the impact of stock buy-sell recommendations of brokerage houses on the stock returns of banks operating in Borsa Istanbul (BIST). Accordingly, it has been attempted to assess if investors can receive abnormal returns in accordance with the recommendations of brokerage houses using the case study technique. The validity of the semi-strong effective form of investors who made a buying-selling decision based on brokerage house recommendations was investigated. The returns of the banks' stocks were obtained from the data-stream database. The study evaluated buy-sell recommendations for four large brokerage houses and analyzed data from January 2018 through December 2020. The event study method was used, and t-test was performed in order to determine the difference of abnormal returns from zero in the research. As a result of the research, a negative abnormal return was determined on the day of the event and the day after the sell recommendation was given. Besides, a positive abnormal return was determined on the day before the announcement and on the day of the event in the bank stocks on which buy recommendation has been given. In this respect, the average abnormal and cumulative abnormal returns indicated that BIST was not an efficient market in a semi-strong form for the banking sector. When the sell recommendations and their effects are examined within the scope of the research, it is seen that the day before [-1] p=0.016 value was obtained, on the day, [0] p=0.018 value was obtained, the next day and two days later [+1, +2] p=0.077 and 0.046 values were obtained. On the other hand, when the buy recommendations and their effects are examined, it is seen that the day before [-1] p=0.000 and on the day [0] p=0.098 values were obtained. T-test results and p values show that brokerage house recommendations are effective on stock returns in the BIST banking sector, and therefore BIST banking sector is effective in a weak form. The obtained results of the study were crucial for investors who invested in short-term stocks.

Bank stock performance during the COVID-19 crisis: does efficiency explain why Islamic banks fared relatively better?

This paper evaluates the stock performance of Islamic banks relative to their conventional counterparts during the initial phase of the COVID-19 crisis (from December 31, 2019, to March 31, 2020). Using 426 banks from 48 countries, we find that stock returns of Islamic banks were about 10–13% higher than those of conventional banks after controlling for a host of the bank- and country-level variables. This study explains the Islamic banks’ superior crisis stock performance by exploring the potential role of pre-crisis bank efficiency. In a univariate analysis, we document higher non-parametric Data Envelopment Analysis (DEA) efficiency levels for Islamic banks than conventional banks in the year preceding the COVID-19 crisis. Our multivariate regressions show that the risk-adjusted DEA efficiency scores can explain crisis stock returns for Islamic banks but not conventional banks. The evidence is robust to alternative measures of stock returns, efficiency models, and other empirical strategies. Finally, we present insight on the importance of key bank characteristics in determining the stock returns of conventional banks during the crisis period.

Volatility impacts on the European banking sector: GFC and COVID-19

This paper analyses the volatility transmission between European Global Systemically Important Banks (GSIBs) and implied stock market volatility. A Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity model is applied to determine the dynamic correlation between returns of Europe’s GSIBs and the world’s most prominent measure of market “fear”, the CBOE Volatility Index (VIX). The results identify a higher negative co-relationship between the VIX and GSIB returns during the COVID-19 period compared with the Global Financial Crisis (GFC), with one-day lagged changes in the VIX negatively Granger-causing bank returns. The asymmetric impact of changes in implied volatility is examined by quantile regressions, with the findings showing that in the lower quartile–where extreme negative bank returns are present–jumps in the VIX are highly significant. This effect is more pronounced during COVID-19 than during the GFC. Additional robustness analysis shows that these findings are consistent during the periods of the Swine Flu and Zika virus epidemics.

How do the global equity and bond markets affect Islamic and conventional banks? A comparative cross-country analysis using multivariate regression quantiles

Using the multivariate quantile autoregression technique, we examine how equity returns of Islamic and conventional banks are affected by shocks to major financial indices such as the DJUSI index, the MSCI World Index, the VIX index and the United States 10-years Treasury bond interest rate. We compare the stability of the two banking systems to financial risk spillovers at the global and regional levels based on data from 16 countries for the period after the 2008 crisis. The empirical findings suggest that Islamic banks’ equities have weaker codependency with major equity markets than conventional banks at the global level while Islamic banks’ codependency with the 10-years US Treasury bond rate tends to be stronger than conventional banks indicating the sensitivity of Islamic banks to global interest rates. The empirical results also reveal that there does not seem to be any significant difference between stock price reactions of Islamic and conventional banks both at the regional and global levels in response to shocks to major financial indices. Regarding regional comparison of Islamic banks only, we find that Islamic bank performance does not vary much across heterogeneous geographic regions.

Bank’s Digitalization and Financial Performance during Pandemic in Indonesia

The pandemic-led recession has made a downturn in the banking industry’s performance. Digitalization is seen as a good strategy to support banks' business operations during the pandemic-led recession. This paper focus on how the banking and financial industry maintained their performance during the covid-19 led recessions through digitalization. I use descriptive statistics approach and regression analysis to analyze how digital transformation help to maintain business performance during a pandemic. In addition, I use regression analysis to estimate the effect of a pandemic on banks’ financial performance and how digital transactions may help to maintain banks’ performance. The regression estimation result shows that pandemic conditions associated with -0.177 points decrease in ROA while digital infrastructure may not have relations with banks’ ROA. Further, the volume of digital transactions is associated with the increase of bank's return on asset (ROA) as much as 10%. These results imply that even though pandemics have negative impacts on banks’ performance, empirical evidence shows that digital transactions have helped the banking industry to maintain its profit during the pandemic.

The effects of intellectual capital on risk and return of banks: nonlinear modelling approach

The effects of intellectual capital on risk and return of banks: nonlinear modelling approach

Uncertainty and bank funding liquidity risk in Vietnam

This paper examines the impact of uncertainty on bank funding liquidity risk. Based on a sample of Vietnamese commercial banks from 2007 to 2019, we show evidence that micro uncertainty in the banking sector leads to higher funding liquidity risk, as proxied by lower deposit ratios. Additional analyses reveal that this nexus widely depends on bank heterogeneity. More precisely, various bank-specific forces that improve banks? financial strength (i.e., an increase in bank return, loan quality, capitalization, liquid assets, and bank size) tend to mitigate the adverse impact of uncertainty on bank funding liquidity risk. Our findings are robust to changes in multiple combinations of regressors, different key bank-level variables to calculate the dispersion of shocks as banking uncertainty measures, and alternative econometric approaches.