Gold is always a precious metal for many hundred years. Semi flexible gold demand and supply chain determines international gold prices in the long term. USA is ranked the world’s largest gold producer. This study ma...Gold is always a precious metal for many hundred years. Semi flexible gold demand and supply chain determines international gold prices in the long term. USA is ranked the world’s largest gold producer. This study mainly aims to investigate the dynamic factors which affect the price of gold and determine the essential macro-economic variable that has the most important role during the process. This paper examines USA over 13 years applying a formal test for time series, which interrogate cointegration relationships, what is the affiliation between gold price and other factors, which are explained in detail below. The present study has used the monthly data from January, 2003 to June, 2016. Databases are provided by the Federal Reserve, the central bank of the United States, and United States Energy Information Administration. Data analysis was performed with software package EViews 8. Through the time series, an analysis has been carried out on Dow Jones Index, the US exchange rate, silver price, interest rate, oil price and inflation rate which are thought to influence the price of gold in the most significant way. The data analysis includes the determination of the conditional heteroscedastic model to estimate volatility. Therefore, the best fitting model to the data set, which is the exponential GARCH model, is preferred. In accordance with the results of the empirical analyses in the USA, the highest negative correlation is found between gold prices and US exchange rate. Secondly, a positive correlation is found among gold prices, silver prices, and oil prices. Another point which takes attention as a result of the study is that economic and political structural breaks weighed heavily, traders and hedgers from all over the world were able to drive prices up to incredible highs. The added valueof our study arises from the inclusion in the analysis of macro economic variables, which has proved to have crucial relevance for the price of gold in the context of the recent economic structure.展开更多
In the 21st century, while the scope of banking activities has been expanding every day, collecting deposits and providing credit remain as their main and most important functions. They transfer the collected funds th...In the 21st century, while the scope of banking activities has been expanding every day, collecting deposits and providing credit remain as their main and most important functions. They transfer the collected funds thanks to the market confidence they create back to the market in terms of the credits they give. For the organizations operating in the banking sector, crediting is the highest revenue earning source. However, uncollected loans may disrupt the activities of banks and may reduce their effectiveness. Therefore, the control of bank credits has a particular importance in the bank balance sheets. In this study, the relationship between bank balance sheets and non-performing loans （NPL） will be analyzed using Granger causality test and vector autoregressive （VAR） method. This study aims to discuss the impact of NPL on balance sheets and contribute to making correct credit decisions. It also intends to assist to reduce the NPL ratios of banks and minimize the level of negativity in their financial statements.展开更多
文摘Gold is always a precious metal for many hundred years. Semi flexible gold demand and supply chain determines international gold prices in the long term. USA is ranked the world’s largest gold producer. This study mainly aims to investigate the dynamic factors which affect the price of gold and determine the essential macro-economic variable that has the most important role during the process. This paper examines USA over 13 years applying a formal test for time series, which interrogate cointegration relationships, what is the affiliation between gold price and other factors, which are explained in detail below. The present study has used the monthly data from January, 2003 to June, 2016. Databases are provided by the Federal Reserve, the central bank of the United States, and United States Energy Information Administration. Data analysis was performed with software package EViews 8. Through the time series, an analysis has been carried out on Dow Jones Index, the US exchange rate, silver price, interest rate, oil price and inflation rate which are thought to influence the price of gold in the most significant way. The data analysis includes the determination of the conditional heteroscedastic model to estimate volatility. Therefore, the best fitting model to the data set, which is the exponential GARCH model, is preferred. In accordance with the results of the empirical analyses in the USA, the highest negative correlation is found between gold prices and US exchange rate. Secondly, a positive correlation is found among gold prices, silver prices, and oil prices. Another point which takes attention as a result of the study is that economic and political structural breaks weighed heavily, traders and hedgers from all over the world were able to drive prices up to incredible highs. The added valueof our study arises from the inclusion in the analysis of macro economic variables, which has proved to have crucial relevance for the price of gold in the context of the recent economic structure.
文摘In the 21st century, while the scope of banking activities has been expanding every day, collecting deposits and providing credit remain as their main and most important functions. They transfer the collected funds thanks to the market confidence they create back to the market in terms of the credits they give. For the organizations operating in the banking sector, crediting is the highest revenue earning source. However, uncollected loans may disrupt the activities of banks and may reduce their effectiveness. Therefore, the control of bank credits has a particular importance in the bank balance sheets. In this study, the relationship between bank balance sheets and non-performing loans （NPL） will be analyzed using Granger causality test and vector autoregressive （VAR） method. This study aims to discuss the impact of NPL on balance sheets and contribute to making correct credit decisions. It also intends to assist to reduce the NPL ratios of banks and minimize the level of negativity in their financial statements.
