scholarly journals The Impact of Exchange Rates and Interest Rates on Bank Stock Returns: Evidence from U.S. Banks

2016 ◽  
Vol 11 (1) ◽  
pp. 124-139 ◽  
Author(s):  
Verma Priti
Keyword(s):  
Exchange Rates ◽  
Interest Rates ◽  
Stock Returns ◽  
Short Term ◽  
Volatility Spillovers ◽  
Hedging Strategies ◽  
Bank Stock ◽  
The Impact ◽  
Bank Portfolios

AbstractThis paper examines the mean, volatility spillovers and response asymmetries between short-term and long-term interest rates, exchange rates and portfolios of money center, large and medium-sized banks in the U.S. I use the multivariate version of Nelson’s (1991) Exponential Generalized Autoregressive Conditionally Heteroscedastic (EGARCH) model. Results indicate mean and volatility spillovers from short-term interest rates and exchange rates and long-term interest rates and exchange rates to three bank portfolios. Results also show response asymmetries from short-term interest rates and exchange rates and long-term interest rates and exchange rates to all the three bank portfolios. These findings have important implications for bankers in terms of devising different hedging strategies against interest rates and exchange rate risks.

scholarly journals Impact of Monetary Policy and Foreign Direct Investment Against Indonesia's Economic Growth

2022 ◽  
Vol 4 (1) ◽  
Author(s):  
Faridsky Faridsky ◽  
Syarwani Canon ◽  
Boby Rantow Payu
Keyword(s):  
Economic Growth ◽  
Monetary Policy ◽  
Exchange Rates ◽  
Interest Rates ◽  
Secondary Data ◽  
Analysis Model ◽  
Short Term ◽  
Indicator Variables ◽  
The Impact

This study aims to determine the impact of monetary policy and FDI on economic growth and discuss it. The monetary indicator variables used are inflation, interest rates and exchange rates. The data used in this study are secondary data in 1990-2019 sourced from data from the Central Bureau of National Statistics and the World Bank. The analysis model in this study uses Multiple Linear Regression with the Error Correction Model (ECM) analysis model. The results of the analysis show that in the long term monetary variables (inflation, interest rates and exchange rates) have a significant effect on economic growth. And in the short term FDI has a significant effect on economic growth. It is concluded that monetary variables (inflation, interest rates and exchange rates) are the main variables that affect economic growth in the long and short term.

scholarly journals ANALISIS MAKRO EKONOMI TERHADAP CADANGAN DEVISA INDONESIA (MELALUI PENDEKATAN MONETER)

2015 ◽  
Vol 4 (2) ◽  
pp. 127
Author(s):  
Novri Candra ◽  
Idris Idris ◽  
Selli Nelonda
Keyword(s):  
Exchange Rates ◽  
Interest Rates ◽  
Error Correction ◽  
Foreign Exchange ◽  
National Income ◽  
Foreign Exchange Reserves ◽  
Short Term ◽  
Negative Effect ◽  
Positive Effect

This study aimed to analyze the change in foreign exchange reserves which are affected by the state of national income, exchange rates, interest rates and inflation. This study was conducted to see the effect of the independent variable on the dependent variable in the long term and short term. The method used is the Error Correction Model (ECM). This study shows that the long-term effects of the variables national income and the exchange rate has a significant positive effect on foreign exchange reserves, while in the short term have a negative effect but not significant. Variable interest rates on long-term have a positive effect but not significant and in the short term have a significant negative effect on foreign exchange reserves. Variable inflation in the long term and short term no significant effect on the foreign exchange reserves. Results Error Correction Term (ECT) in this study amounted to 1,065, which means that in the short-term foreign exchange reserves will undergo considerable change and requires quite a long time to come back into balance.Keyword : Reserves, National Income, Exchange Rates, Interest Rates and Inflation ECM, ECT

scholarly journals Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2484
Author(s):  
Vladimir Balash ◽  
Alexey Faizliev ◽  
Sergei Sidorov ◽  
Elena Chistopolskaya
Keyword(s):  
Stock Market ◽  
Spillover Effects ◽  
Political Crisis ◽  
Dynamic Factor ◽  
Short Term ◽  
Volatility Spillovers ◽  
Conditional Time ◽  
Russian Stock Market ◽  
The Impact

This study analyzes the spillover effects of volatility in the Russian stock market. The paper applies the Diebold–Yilmaz connectedness methodology to characterize volatility spillovers between Russian assets. The spectral representation of the forecast variance decomposition proposed by Baruník and Křehlik is used to describe the connectivity in short-term (up to 5 days), medium-term (6–20 days) and long-term (more than 20 days) time frequencies. Additionally, two new augmented models are developed and applied to evaluate conditional spillover effects in different sectors of the Russian economy for the period from January 2012 to June 2021. It is shown that spillover effects increase significantly during political and economic crises and decrease during periods of relative stability. The rising of the overall level of spillovers in the Russian stock market coincides in time with the political crisis of 2014, the intensification of anti-Russian sanctions in 2018 and the fall in oil prices and the start of the pandemic in 2020. With the consideration of the augmented models it can be argued that a significant part of the long-term spillover effects on the Russian stock market may be caused by the influence of external economic and political factors. However, volatility spillovers generated by internal Russian idiosyncratic shocks are short-term. Thus, the proposed approach provides new information on the impact of external factors on volatility spillovers in the Russian stock market.

scholarly journals THE EFFECT OF GOVERNMENT MACROECONOMIC POLICY ON INDONESIA'S FISHERIES EXPORT TO THE UNITED STATES IN 1989-2019

2021 ◽  
Vol 6 (2) ◽  
pp. 267
Author(s):  
Akhmad Jayadi ◽  
Tanto Firmansyah
Keyword(s):  
United States ◽  
Exchange Rate ◽  
Exchange Rates ◽  
Interest Rates ◽  
Government Spending ◽  
The United States ◽  
Short Term ◽  
Negative Effect ◽  
Positive Effect

Indonesia is a maritime country that has huge potential in fisheries sector. The average of indonesian fisheries production and export volumes always increase every year. This study aims to analyze the effect of exchange rates, government spending, inflation, interest rates, and sanitation policies to Indonesia fishery export to the United States in 1989-2019. Data were obtained from the Indonesian Ministry of Finance, the World Bank, UN COMTRADE, and the Indonesian Ministry of Maritime Affairs and Fisheries. This study uses the Error Coerrection Model (ECM) method to examine the effect of the independent variables on the dependent variable in the long term and short term. This study explains that in the long-term, government spending and exchange rate have positive effect, and interest rates have negative effect on export. In short-term, government spending and exchange rate have positive effect on export. Inflation and sanitation policy do not affect export in the long-term or short-term, while interest rates in the short-term do not affect Indonesian fishery exports. Keywords: Exports, Government Spending, Exchange Rates, Non-Tariff Barriers, Error Correction Model.JEL: F10, F13, C32

scholarly journals When Does Monetary Policy Sway House Prices? A Meta-Analysis

2021 ◽  
Author(s):  
Dominika Ehrenbergerova ◽  
Josef Bajzik ◽  
Tomas Havranek
Keyword(s):  
Interest Rates ◽  
Yield Curve ◽  
House Prices ◽  
Meta Analysis ◽  
Empirical Literature ◽  
Short Term ◽  
Mortgage Markets ◽  
The Mean ◽  
The Impact

Several central banks have leaned against the wind in the housing market by increasing the policy rate preemptively to prevent a bubble. Yet the empirical literature provides mixed results on the impact of short-term interest rates on house prices: the estimated semi-elasticities range from -12 to positive values. To assign a pattern to these differences, we collect 1,447 estimates from 31 individual studies that cover 45 countries and 69 years. We then relate the estimates to 39 characteristics of the financial system, business cycle, and estimation approach. Our main results are threefold. First, the mean reported estimate is exaggerated by publication bias, because insignificant results are underreported. Second, omission of important variables (liquidity and long-term rates) likewise exaggerates the effects of short-term rates on house prices. Third, the effects are stronger in countries with more developed mortgage markets and generally later in the cycle when the yield curve is flat and house prices enter an upward spiral.

scholarly journals Stock And Bond Price Dynamics-Evidence From An Emerging Economy

2011 ◽  
Vol 10 (9) ◽  
pp. 93
Author(s):  
M. Venkateshwarlu ◽  
T. Ramesh Babu
Keyword(s):  
Interest Rates ◽  
Stock Returns ◽  
Term Structure ◽  
Stock Prices ◽  
Empirical Studies ◽  
Bond Markets ◽  
Bond Price ◽  
Short Term ◽  
Bond Prices

The motivation for this study is that real stock prices are observed to overreact to changes in interest rates. The real stock prices drop when long-term interest rates rise. It has been observed that bonds and stock prices are typically studied in isolation. The present paper attempts to analyze the dynamic linkages between stock and bond prices in India. One of the important contributions of this study is that in India, very little/almost no work has been done to understand the dynamics of the stock and bond prices after the recent recession. The present study examined the bivariate causal relationship between stock prices and bond prices. In the long term; i.e., periods from 2004 to 2007 and 2008 to 2009, there is no causality from stock market to bond market and vice versa. However, it is found that the bond and stock prices had a bivariate causality in the year 2009 and univariate causality in 2010. The results are interesting and support the view that excess volatility causes granger between the stock and bond markets. This can be inferred as a result of recession investors moving to bond markets and after the signs of recovery the investors might be returning to the stock markets. It is also evident that short-term interest rates have power to forecast short-term stock returns and risk premiums on observation of co-movement between stock and bond prices. This is reiterated by many empirical studies that have shown that the term structure of nominal interest rates contains information potentially useful for the conduct of monetary policy.

scholarly journals The volatility of bank stock prices and macroeconomic fundamentals in the Pakistani context: an application of GARCH and EGARCH models

2020 ◽  
Vol 11 (4) ◽  
pp. 609-636
Author(s):  
Muhammad Mohsin ◽  
Li Naiwen ◽  
Muhammad Zia-UR-Rehman ◽  
Sobia Naseem ◽  
Sajjad Ahmad Baig
Keyword(s):  
Exchange Rates ◽  
Interest Rates ◽  
Stock Returns ◽  
Covariance Matrix ◽  
Stock Prices ◽  
Market Returns ◽  
Macroeconomic Fundamentals ◽  
Bank Stock Returns ◽  
Bank Stock ◽  
The Garch Model

Research Background: The banking sector plays a crucial role in the world?s economic development. This research paper evaluates the volatility spillover, symmetric, and asymmetric effects between the macroeconomic fundamentals, i.e., market risks, interest rates, exchange rates, and bank stock returns, for the listed banks of Pakistan. Purpose of the article: The main purpose of this study is to examine the volatility of Pakistani banking stock returns due to the influence of market risk, interest rates, and exchange rates. Pakistan is selected for the study because the volatility of its banking stock returns is strongly influential in achieving sustainable economic development. Methods: By applying the OLS with the Heteroskedasticity and Autocorrelation Consistent (HAC) covariance matrix, the GARCH (1, 2), and the EGARCH (1, 1), analysis is conducted for the period from January 1, 2009 to December 31, 2019 using samples of 13 listed banks. Findings & Value added: The ARCH parameter is significant in the OLS with the HAC covariance matrix estimation, which is a clear indication of the existence of heteroskedasticity in the squared residuals and the inaccuracy of the OLS with the HAC covariance matrix. The results of the OLS with the HAC covariance matrix suggest using the GARCH model family to accurately measure the volatility of bank stock prices. The results of the mean equation in the GARCH (1, 2) and EGARCH (1, 1) indicate the positive significance of market risk and the low significance of interest and exchange rates, confirming that market returns strongly affect the sensitivity of bank stock returns compared to interest and exchange rates. It should be noted that the ARCH (?) and GARCH (?) parameters of the variance equation fulfill the non-negative conditions of the GARCH model. Furthermore, the leverage parameter (?) is found to be positively significant for all banks, and volatility is found to be influenced by positive shocks compared to negative shocks. Conclusively, it can be stated that market returns determine the dynamics of the conditional returns of bank stocks. Nevertheless, the interest and exchange rate volatilities determine the conditional bank stock returns? volatility.

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