scholarly journals The Sensitivity of Central Bank Interest Rate on Commercial Banks’ Stock Market Returns in Kenya

2021 ◽  
Vol 7 (5) ◽  
pp. p72
Author(s):  
Micah Odhiambo Nyamita ◽  
Martine Ogola Dima
Keyword(s):  
Interest Rate ◽  
Central Bank ◽  
Interest Rates ◽  
Stock Returns ◽  
Commercial Banks ◽  
Secondary Data ◽  
Market Returns ◽  
Cross Sectional ◽  
Stock Market Returns ◽  
Panel Data Regression

Commercial banks occupy a significant position in the transmission of monetary policy through the financial market. Furthermore, commercial banks have assets and liabilities which are interest rate sensitive, and their stock returns are believed to be particularly responsive to changes in the central bank base lending rates. Therefore, this study investigated the sensitivity of central bank interest rate changes on stock returns of listed commercial banks in Kenya for nine year period, from 2006 to 2014. The study used a hybrid of cross sectional and longitudinal quantitative surveys method, applying GMM panel data regression model on the secondary data from the 11 listed commercial banks in Kenya. The study found out that there is a significant strong positive sensitivity of average annual changes in central bank interest rates (CBR) on the stock returns of the listed commercial banks in Kenya, from 2006 to 2014, measured using CAPM. Hence, listed commercial banks’ managers in Kenya should monitor, keenly, the changes in the central bank interest rates and make investor related decisions accordingly.

scholarly journals Determinan Suku Bunga dan Likuiditas Bank Terhadap Pertumbuhan Kredit di Indonesia

Jurnal Ecogen ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 200
Author(s):  
Yeniwati Yeniwati
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Commercial Banks ◽  
Secondary Data ◽  
Least Square ◽  
Bank Credit ◽  
Credit Growth ◽  
Ordinary Least Square ◽  
Banking Community ◽  
The Interest Rate

This study aims to determine the effect of the interest rate (BI rate) on bank credit growth in Indonesia, liquidity on bank credit growth in Indonesia and determine the effect of interest rates and liquidity on bank credit growth in Indonesia. The method used in this study is Ordinary Least Square (OLS) using secondary data from 2009 Quarter I to 2018 Quarter IV. The results of the analysis showed that there was an influence between interest rates on bank credit growth in Indonesia, there was an influence between liquidity on bank credit growth in Indonesia. Together there is an influence between interest rates and bank liquidity on the growth of bank credit in Indonesia. The policy implication of this research is that Bank Indonesia must maintain the benchmark interest rate set in order to trigger an increase in bank credit growth. In addition, Bank Indonesia must monitor the liquidity of commercial banks in Indonesia so that the trust of the banking community is even greaterKeywords : interest rate, Liquidity, Credit

scholarly journals Impact of Macroeconomic Variables on Karachi Stock Market Returns

2018 ◽  
Vol 10 (2) ◽  
pp. 28 ◽  
Author(s):  
Javed Pervaiz ◽  
Junaid Masih ◽  
Teng Jian-Zhou
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Market ◽  
Secondary Data ◽  
Research Process ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Index Value ◽  
The Impact

The study investigated The study examines the impact of selected macroeconomic variables (inflation, exchange rate, interest rate) on Karachi stock market returns. Mainly secondary data used in the research process. The study consists of data for the period of 10 years and 5 months starting from January 2007 till May 2017. For this purpose, monthly data of KSE-100 index has been observed for the period January 2007 to May 2017. The market returns have been calculated through the opening and closing index value of each month. The inflation, interest rate, and exchange rate has been taken as independent variables. Hypotheses have been tested to find out whether there exists a significant relationship between the Stock market return and macroeconomic variables or not. To test this hypothesis, Regression analysis used and results are calculated through Stata software.

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI RETURN SAHAM PADA BANK UMUM YANG TERDAFTAR DI BURSA EFEK INDONESIA

2021 ◽  
Vol 5 (1) ◽  
pp. 42-55
Author(s):  
Mulia Andirfa ◽  
Eka Chyntia ◽  
Iva Septarina ◽  
Maryana
Keyword(s):  
Stock Returns ◽  
Commercial Banks ◽  
Stock Exchange ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Financial Reports ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Positive Effect

This study aims to analyze the effect of ROE, CAR, NPL, BOPO, and DER simultaneously on stock returns in  commercial banks listed on the Indonesia Stock Exchange. The data used in this study are secondary data in the form of financial reports at PT. Bank Rakyat Indonesi Tbk, PT. Bank Negara Indonesia Tbk, PT. Bank Mandiri Tbk, PT. Bank Central Asia Tbk, and PT. Bank Mega Tbk. from 2014-2019. The data analysis method used is panel data regression analysis, namely the Fixed Effect Model (FEM). The results showed that: ROE theoretically and statistically affect stock returns in commercial banks listed on the Indonesia Stock Exchange. CAR is theoretically and statistically insignificant to stock returns in Commercial Banks listed on the Indonesia Stock Exchange. BOPO has a theoretical effect but does not have a statistical and significant effect on stock returns in  commercial banks listed on the Indonesia Stock Exchange. NPL and DER have no effect on stock returns in Commercial Banks listed on the Indonesia Stock Exchange. ROE, CAR, NPL, BOPO and DER simultaneously have a positive effect on stock returns in) Commercial Banks listed on the Indonesia Stock Exchange. ROE, CAR, NPL, BOPO and DER have the ability to explain their effect on stock returns in Commercial Banks listed on the Indonesia Stock Exchange of 44.09%. The remaining 55.01% is influenced by other variables outside this research model.

Long memory in the volatility of Korean stock returns

2002 ◽  
Vol 10 (2) ◽  
pp. 95-114
Author(s):  
Ji Hyeon Lee ◽  
Dong Seog Kim ◽  
Hoe Gyeong Lee
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
Fractional Integration ◽  
Market Returns ◽  
Cross Sectional ◽  
Stock Market Returns ◽  
Aggregation Effect ◽  
Special Cases ◽  
Figarch Model ◽  
Integration Order

In this paper, we empirically examine the volatility process of Korean stock market returns using the KOSPI200. To investigate the property of the process, we use the FIGARCH (Fractionally Integrated GARCH) model that includes GARCH and 1GARCH processes as special cases. Since the FIGARCH model allows fractional integration order, it can detect hyperbolically decaying volatility processes with cannot be explained by existing models with integer integration order. The result shows that the KOSPI200 exhibits long-term dependencies. To investigate the robustness of the obtained result, we analyze the time and cross-sectional aggregation effect using weekly data and individual stock returns that the KOSPI200 is comprised of. The long memory property of the KOSPI200 does not seem to be spuriously induced by aggregation.

SHORT-TERM HERDING EFFECT ON MARKET INDEX RETURNS

2019 ◽  
Vol 14 (01) ◽  
pp. 1950004
Author(s):  
ANDREY KUDRYAVTSEV
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Price ◽  
Herd Behavior ◽  
Market Returns ◽  
Short Term ◽  
Cross Sectional ◽  
Stock Market Returns ◽  
Market Return ◽  
Market Index

The study analyzes the predictability of stock market returns based on the previous day’s cross-sectional market-wide herd behavior. Assuming that herding may lead to stock price overreaction and result in subsequent price reversals, I suggest that daily stock market returns may be higher (lower) following trading days characterized by negative (positive) market returns and high levels of herding. Analyzing the daily price data for S&P 500 Index and all its constituents and employing two alternative market-wide herding measures based on cross-sectional daily deviation of stock returns, I document that the days of both positive and negative market returns tend to be followed by price reversals (drifts), if the market-wide levels of herding are high (low). The herding effect on the next day’s stock market returns is found to be more pronounced following the days when the sign of the market return corresponds to the direction of the longer-term stock market tendency and the days characterized by relatively large stock market movements. The effect also remains significant after accounting for the specific numerical value of the market return.

scholarly journals Time Series Analysis of Interest Rates Volatility and Stock Returns in Ghana

2019 ◽  
Vol 5 (2) ◽  
pp. 89-102
Author(s):  
Johnson Worlanyo Ahiadorme ◽  
Emmanuel Sonyo ◽  
Godwin Ahiase
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Stock Market ◽  
Time Series Analysis ◽  
Interest Rates ◽  
Market Returns ◽  
Stock Market Returns ◽  
Series Analysis ◽  
Long Run ◽  
Short Run

The study utilized time series analysis models and employed the Johansen’s cointegration procedure and the vector error correction model to examine the short-run and long-run dynamics of the relationship between interest rates and stock market returns. The results of this study show that contrary to popular evidence from extant research, interest rate changes positively and significantly affect stock market returns in the long run and the deviation from the long-run equilibrium is corrected each period following a shock to the stock market in the short run. The positive linkages between interest rate changes and stock market outturns may be explained by the relative strength of banking stocks on the Ghana Stock Exchange. The analysis shows that as the long-run equilibrium is approached, the deviations in the short term decrease significantly.

scholarly journals DETERMINANTS OF INTEREST RATE SPREAD AMONG COMMERCIAL BANKS IN KENYA

2017 ◽  
Vol 2 (5) ◽  
pp. 75
Author(s):  
Leah Njoroge ◽  
Dr.Chogii Dr.Chogii
Keyword(s):  
Interest Rate ◽  
Central Bank ◽  
Credit Risk ◽  
Significant Relationship ◽  
Commercial Banks ◽  
Regression Coefficient ◽  
Secondary Data ◽  
P Value ◽  
Unique Contribution ◽  
Interest Rate Spread

Purpose: This study sought to find the determinant of interest rate spread among commercial banks in Kenya.Methodology: The study used a descriptive research design. The target population of this study included all the commercial banks in Kenya since the small number of population called for a census survey of all the banks. The study used secondary data which includes the governments’ publications, journals, banking survey reports, annual reports of the Commercial banks in Kenya and periodicals. Quantitative data was collected. Secondary data used to calculate interest rate spread was collected from the annual statements of the sampled commercial banks. The study used both descriptive and inferential statistics. The descriptive statistics included trend analysis, mean and standard deviation. The study used a pooled OLS regression model to analyze the relationship between the independent and dependent variables.Results: The regression results indicate that there is a positive and significant relationship between market structure and interest spread. This finding was supported by a regression coefficient of 0.200 (p value = 0.000). The reported p value was less than the critical p value of 0.05. The results also indicated that there is a positive and significant relationship between credit risk and interest spread. This finding was supported by a regression coefficient of 0.096 (p value = 0.008). The reported p value was less than the critical p value of 0.05. This implies that an increase in credit risk by one unit would result to an increase in the interest spread by 0.096 units. Further, the results indicate that there is a positive but insignificant relationship between access to information and interest spread. The regression results also indicated that there is a negative and significant relationship between regulation and interest spread. This finding was supported by a regression coefficient of -1.309 (p value = 0.000). The reported p value was less than the critical p value of 0.05.Unique contribution to theory, practice and policy: The study recommended that commercial banks should be encouraged to use the information from the credit reference bureaus so as to maintain a lower interest spread among Commercial banks in Kenya. The study also recommended that the central  bank should licence more CRBs which would assist the commercial banks in lowering the credit risk. the study recommended that the central bank should review the monetary policy and lower the T- bill (91 days). This would help to lower the interest spread among Commercial banks in Kenya.

scholarly journals SHORT TERM INTEREST RATES IMPACT ON GHANA STOCK MARKET

2013 ◽  
Vol 8 (3) ◽  
Author(s):  
Augustine Addo ◽  
Fidelis Sunzuoye
Keyword(s):  
Interest Rate ◽  
Stock Market ◽  
Interest Rates ◽  
Stock Exchange ◽  
Negative Relationship ◽  
Market Returns ◽  
Treasury Bill ◽  
Stock Market Returns ◽  
Long Run ◽  
Ghana Stock Exchange

The study examines the joint impact of interest rate and Treasury bill rate on stock market returns on Ghana Stock Exchange over the period between January 1995 and December 2011. Using Johansen’s Multivariate Cointegration Model and Vector Error Correction Model the study establish that there is cointegration between Interest rate, Treasury bill rate and stock market returns indicating long run relationship. On the basis of the Multiple Regression Analysis (OLS) carried out by Eviews 7 program, the results shows that Treasury bill rate and interest rate both have a negative relationship with stock market returns but are not significant.  These results show that interest rate and Treasury bill rate have both negative relationship but weak predictive power on stock market returns independently. The study conclude that interest rate and Treasury bill rate jointly impact on stock market returns in the long run.

scholarly journals FASILITAS DISKONTO (DISCOUNT WINDOWS) SEBAGAI INSTRUMEN MONETER DITINJAU DALAM PERSPEKTIF EKONOMI ISLAM

2019 ◽  
Vol 4 (1) ◽  
pp. 71
Author(s):  
RINA EL MAZA ◽  
EGI PUTRA SETIAWAN
Keyword(s):  
Interest Rate ◽  
Central Bank ◽  
Interest Rates ◽  
Commercial Banks ◽  
Profit Sharing ◽  
The Public ◽  
The Government ◽  
Islamic Economic ◽  
The Interest Rate

The government has an important role in the welfare of the people's economy. One of them is through the role of the central bank by carrying out monetary policy. This policy was adopted by the central bank or Bank Indonesia (BI) through several instruments, including through regulating discount rates for commercial banks. In this case, BI sets the inflation target as a reference for determining interest rates. When the inflation rate exceeds the targeted, BI will raise interest rates which in turn will reduce the credit issued by commercial banks to the public, because commercial banks must pay higher interest rates to the central bank. And the results of the analysis that the interest rate charged in the credit (Lending Facility) discount facility is classified as an act of usury. Meanwhile, the profits obtained from the deposit of funds in the Facility Deposit transaction are not permitted in the Islamic economy, because in the Islamic economy there is no interest rate but profit sharing, given the fixed and concrete interest rates. In addition, the discount facility is also incompatible with some Islamic economic principles, including; the principle of Illahiyah, Justice, and the government.

scholarly journals Interest Rate Sensitivity of Non-banking Financial Sector in India

2018 ◽  
Vol 43 (3) ◽  
pp. 152-170
Author(s):  
Renu Ghosh ◽  
K. Latha ◽  
Sunita Gupta
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Stock Returns ◽  
Financial Institutions ◽  
Rate Sensitivity ◽  
Interest Rate Risk ◽  
Cross Sectional ◽  
Rate Risk ◽  
The Interest Rate ◽  
The Impact

Executive Summary Before financial liberalization, interest rates were administered and exhibited near-zero volatility. The easing of financial repression in the 1990s generated experiences with interest rate volatility in India. Administrative restrictions on interest rates in India have been steadily eased since 1993. This has led to increased interest rate risk for financial firms. Most research studies have almost exclusively focused on the developed countries especially the banking sector of the United States. The present study attempts to examine the interest rate risk of non-banking financial institutions in India by using the methodology of panel regression and generalized autoregressive conditional heteroscedasticity (GARCH) (1, 1) model for the period from 1 April 1996 to 30 August 2014. The sample used in the study consists of all non-banking financial companies (NBFCs) listed in the S&P CNX 500 index which has continuous availability of share prices over the study period. The study also examines the impact of unanticipated changes in interest rate on stock returns of NBFCs. The Box–Jenkins methodology is applied to calculate unanticipated changes in interest rate variable, autoregressive integrated moving average (ARIMA) (24, 1, 0) model. The time series used in the present study is found to be stationary at the first logarithmic difference. Stock returns exhibit significant exposure with both market returns and interest rate changes. The interest rate sensitivity of large, medium, and small financial institutions is also found to be different. Estimation results for the variance equation in GARCH (1, 1) model suggest that the volatility for individual firm stock returns is time-variant. The ARCH and GARCH coefficients are found to be significant, providing evidence against using traditional model (ordinary least square (OLS)) that assumes time-invariant volatility. This implies that the market has a memory longer than one period and volatility is more sensitive to its own lagged values than it is to new surprises in the market. This study also investigates the possible determinants that account for cross-sectional variation in the interest rate sensitivity of NBFCs. It is found that the size of the firm is the preferred determinant that accounts for cross-sectional variation in the interest rate sensitivity of finance companies. When unanticipated changes in interest rate are used in lieu of actual interest rate changes, not much difference is observed in the significance coefficients. The only significant difference observed is in the magnitude. The impact of actual interest rate changes is more than the impact of unanticipated interest rate changes in absolute terms. This difference in the magnitude of impact arises because actual data incorporate movement in both anticipated and unanticipated components of interest rate. Hence, NBFCs managers and regulators should adopt policies and strategies to avoid the transmission of interest rate risk in their stock returns.

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