Variables Explaining Bank Stock Prices

Moss, Jimmy D.; Moss, Gisele J.

doi:10.19030/jabr.v26i4.301

Cited by 6 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to Dehuan (2008), the shares traded on the Shanghai Stock Exchange were affected by the operating performance indicators of the companies. Moss & Moss (2010) demonstrated that bank stock prices are sensitive to changes in interest rates. Airout & Airout (2017) mentioned that the increase in profits and reserves of banks, their capital, andtheir investments leads to the rise in the price of banks' shares in the stock exchanges.…”

Section: Performance and Share Indexmentioning

confidence: 99%

“…According to Moss & Moss (2010), there is no correlation between stock prices, trade volume, liquidity, book value, and financial leverage, and they found a positive correlation between bank stock prices, dividends per share, and earnings per share. The study by Sharma (2020) concluded that earnings per share, dividend per share, and share book value also affect share market price; earnings per share and dividend per share determine the market share price.…”

Section: Price/earnings Ratiomentioning

confidence: 99%

See 1 more Smart Citation

The relationship between performance indicators and share prices of companies listed on sharia indices: a case study of S&P BSE 500 sharia index

Almonifi,

Bhosle

2023

IJIER

View full text Add to dashboard Cite

This study aims to empirically examine the relationship between performance indicators and share prices of companies listed on SP BSE 500 sharia index. Data were collected through the index’s closing price and financial reports of the ten top companies listed on SP BSE 500 Sharia index. This study identifies the most important indicators that affect share prices in stock exchanges: ROA, ROE, EPS, and P/ER using Panel method. The study findings indicate that EPS, ROA and ROE have non-significant impact SP, while P/ER has a significant positive on SP. This study highlights the development of companies’ performance indicators and the enhancing of investment strategies for stakeholders and investors. This study is contributing to the analysis of the relationship between the companies’ performance indicators listed on sharia indices and their shares prices.

show abstract

Section: Performance and Share Indexmentioning

confidence: 99%

Section: Price/earnings Ratiomentioning

confidence: 99%

The relationship between performance indicators and share prices of companies listed on sharia indices: a case study of S&P BSE 500 sharia index

Almonifi,

Bhosle

2023

IJIER

View full text Add to dashboard Cite

show abstract

“…Hence, cross-sectional heterogeneity exists across banks for their interest rate exposure. Literature provided substantial evidence for stock returns exhibiting statistically significant inverse relationship with interest rate changes (Alam & Salahuddin, 2009;Asprem, 1989;Ballester, Ferrer, & Gonzalez, 2011;Ballester et al, 2009;Benink & Wolff, 2000;Kasman, Vardar, & Gokce, 2011;Kwan, 1991; J. D. Moss & G. J. Moss, 2010;Park & Choi, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Interest Rate Sensitivity of Non-banking Financial Sector in India

Ghosh

Latha

Gupta

2018

Vikalpa: The Journal for Decision Makers

View full text Add to dashboard Cite

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.

show abstract

“…Interest rate and stock price effects have an influence on the variance of spread. Moss and Moss (2010) examined the relationship between bank common stock index price and the interest rate on Treasury securities. He also analyzed the correlation between interest rate term structure and bank stock prices.…”

Section: Commodity Indices Risk and Return Analysis Against Libor Benmentioning

confidence: 99%

Commodity Indices Risk and Return Analysis Against Libor Benchmark

Valluri

2018

APSTRACT

View full text Add to dashboard Cite

This study analyze the risk and return characteristics of commodity index investments against the LIBOR benchmark. Commodity-based asset allocation strategies can be optimized by benchmarking the risk and return characteristics of commodity indices with LIBOR index rate. In this study, we have considered agriculture, energy, and precious metals commodity indices and LIBOR index to determine the risk and return characteristics using estimation techniques in terms of expected return, standard deviation, and geometric mean. We analyzed the publicly available daily market data from 10/9/2001 to 12/30/2016 for benchmarking commodity indices against LIBOR. S&P GSCI Agriculture Index (SGK), S&P GSCI Energy Index (SGJ), and S&P GSCI Precious Metals Index (SGP) are taken to represent each category of widely traded commodities in the regression analysis. Our study uses time series data based on daily prices. Alternative forecasting methodologies for time series analysis are used to cross-check the results. The forecasting techniques used are Holt-Winters Exponential Smoothing and ARIMA. This methodology predicts forecasts using smoothening parameters. The empirical research has shown that the risk of each of the commodity index that represents agriculture, energy, and precious metals sector is smaller compared to its return, whereas LIBOR based interest rate benchmark shows higher risk compared to its return in recession, non-recession and overall periods. László Kozár -György Iván Neszmélyi

show abstract

Variables Explaining Bank Stock Prices

Cited by 6 publications

References 6 publications

The relationship between performance indicators and share prices of companies listed on sharia indices: a case study of S&P BSE 500 sharia index

The relationship between performance indicators and share prices of companies listed on sharia indices: a case study of S&P BSE 500 sharia index

Interest Rate Sensitivity of Non-banking Financial Sector in India

Commodity Indices Risk and Return Analysis Against Libor Benchmark

Contact Info

Product

Resources

About