Listing 1 - 6 of 6 |
Sort by
|
Choose an application
Using bank level measures of competition and co-dependence, the authors show a robust positive relationship between bank competition and systemic stability. Whereas much of the extant literature has focused on the relationship between competition and the absolute level of risk of individual banks, they examine the correlation in the risk taking behavior of banks, hence systemic risk. They find that greater competition encourages banks to take on more diversified risks, making the banking system less fragile to shocks. Examining the impact of the institutional and regulatory environment on systemic stability shows that banking systems are more fragile in countries with weak supervision and private monitoring, with generous deposit insurance and greater government ownership of banks, and public policies that restrict competition. Furthermore, lack of competition has a greater adverse effect on systemic stability in countries with low levels of foreign ownership, weak investor protections, generous safety nets, and where the authorities provide limited guidance for bank asset diversification.
Access to Finance --- Bank competition --- Bank concentration --- Banks & Banking Reform --- Credit risk --- Debt Markets --- Default risk --- Distance to default --- Emerging Markets --- Finance and Financial Sector Development --- Financial Intermediation --- Lerner index --- Merton model --- Private Sector Development --- Systemic risk
Choose an application
Using bank level measures of competition and co-dependence, the authors show a robust positive relationship between bank competition and systemic stability. Whereas much of the extant literature has focused on the relationship between competition and the absolute level of risk of individual banks, they examine the correlation in the risk taking behavior of banks, hence systemic risk. They find that greater competition encourages banks to take on more diversified risks, making the banking system less fragile to shocks. Examining the impact of the institutional and regulatory environment on systemic stability shows that banking systems are more fragile in countries with weak supervision and private monitoring, with generous deposit insurance and greater government ownership of banks, and public policies that restrict competition. Furthermore, lack of competition has a greater adverse effect on systemic stability in countries with low levels of foreign ownership, weak investor protections, generous safety nets, and where the authorities provide limited guidance for bank asset diversification.
Access to Finance --- Bank competition --- Bank concentration --- Banks & Banking Reform --- Credit risk --- Debt Markets --- Default risk --- Distance to default --- Emerging Markets --- Finance and Financial Sector Development --- Financial Intermediation --- Lerner index --- Merton model --- Private Sector Development --- Systemic risk
Choose an application
Recently, the world economy has witnessed some turbulence and instability, both of which have raised concerns and added threats to the global economy. For example, climate change, trade war, regional political tension, Brexit, and the very recent Coronavirus epidemic have hit several countries across all continents at an astonishing rate and are among some of the factors that have increased uncertainty. We have also noticed a surge in technological innovations and their implications in the banking and financial sectors. Today, we talk about blockchain, fintech, insurtech, regtech, and big tech, which have changed the business model of banks, financial institutions, and also the management model for firms and public administration. To get better insight into all these trends, economists have used the finance and macroeconomic theory to analyze the micro- and macroeconomic consequences of all these events and to study their impacts on economic and financial sector stability, as well as economic development and growth. In this Special Issue, Economies is inviting researchers and academicians to submit their work to a Special Issue dedicated to “The Theory Applications of Finance and Macroeconomics”. Some of the topics that contribute to the Issue might address issues of trade tension, climate change, blockchain and cryptocurrencies, financial liberalization, macroeconomic issues, principles of international finance, and open economy macroeconomics.
Economics, finance, business & management --- broad money --- share market --- bank credit --- private sector growth --- financial inclusion --- banking sector of Pakistan --- supply side --- ARDL --- banking --- competition --- Lerner Index --- economic relationship --- TFP --- system GMM --- China–Africa --- bounds cointegration test --- information criterion --- model selection techniques --- plausible model --- fiscal redistribution --- financial development --- fiscal expenditure --- property income --- economic growth --- trade balance --- panel estimates --- macroeconomics --- poverty --- microfinance --- Pakistan --- firm growth --- threshold estimation --- public debt --- threshold effects --- MENA region --- quantum mechanics --- wave function --- extreme value analysis --- Bayesian inference --- stock market --- Value at Risk (VaR) --- Expected Shortfall (ES) --- prediction
Choose an application
Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.
Coins, banknotes, medals, seals (numismatics) --- Index parameter --- estimation --- wrapped stable --- Hill estimator --- characteristic function-based estimator --- asymptotic --- efficiency --- GARCH model --- HARCH model --- PHARCH model --- Griddy-Gibs --- Euro-Dollar --- safe-haven assets --- gold price --- Swiss Franc exchange rate --- oil price --- generalized Birnbaum–Saunders distributions --- ACD models --- Box-Cox transformation --- high-frequency financial data --- goodness-of-fit --- banking competition --- credit risk --- NPLs --- Theil index --- convergence analysis --- interest rates --- yeld curve --- no-arbitrage --- bonds --- B-splines --- time series --- multifractal processes --- fractal scaling --- heavy tails --- long range dependence --- financial models --- Bitcoin --- capital asset pricing model --- estimation of systematic risk --- tests of mean-variance efficiency --- t-distribution --- generalized method of moments --- multifactor asset pricing model --- Lerner index --- stochastic frontiers --- shrinkage estimator --- seemingly unrelated regression model --- multicollinearity --- ridge regression --- financial incentives --- public service motivation --- job performance --- job satisfaction --- intention to leave
Choose an application
Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.
Index parameter --- estimation --- wrapped stable --- Hill estimator --- characteristic function-based estimator --- asymptotic --- efficiency --- GARCH model --- HARCH model --- PHARCH model --- Griddy-Gibs --- Euro-Dollar --- safe-haven assets --- gold price --- Swiss Franc exchange rate --- oil price --- generalized Birnbaum–Saunders distributions --- ACD models --- Box-Cox transformation --- high-frequency financial data --- goodness-of-fit --- banking competition --- credit risk --- NPLs --- Theil index --- convergence analysis --- interest rates --- yeld curve --- no-arbitrage --- bonds --- B-splines --- time series --- multifractal processes --- fractal scaling --- heavy tails --- long range dependence --- financial models --- Bitcoin --- capital asset pricing model --- estimation of systematic risk --- tests of mean-variance efficiency --- t-distribution --- generalized method of moments --- multifactor asset pricing model --- Lerner index --- stochastic frontiers --- shrinkage estimator --- seemingly unrelated regression model --- multicollinearity --- ridge regression --- financial incentives --- public service motivation --- job performance --- job satisfaction --- intention to leave
Choose an application
Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.
Coins, banknotes, medals, seals (numismatics) --- Index parameter --- estimation --- wrapped stable --- Hill estimator --- characteristic function-based estimator --- asymptotic --- efficiency --- GARCH model --- HARCH model --- PHARCH model --- Griddy-Gibs --- Euro-Dollar --- safe-haven assets --- gold price --- Swiss Franc exchange rate --- oil price --- generalized Birnbaum–Saunders distributions --- ACD models --- Box-Cox transformation --- high-frequency financial data --- goodness-of-fit --- banking competition --- credit risk --- NPLs --- Theil index --- convergence analysis --- interest rates --- yeld curve --- no-arbitrage --- bonds --- B-splines --- time series --- multifractal processes --- fractal scaling --- heavy tails --- long range dependence --- financial models --- Bitcoin --- capital asset pricing model --- estimation of systematic risk --- tests of mean-variance efficiency --- t-distribution --- generalized method of moments --- multifactor asset pricing model --- Lerner index --- stochastic frontiers --- shrinkage estimator --- seemingly unrelated regression model --- multicollinearity --- ridge regression --- financial incentives --- public service motivation --- job performance --- job satisfaction --- intention to leave
Listing 1 - 6 of 6 |
Sort by
|