The Effect of Financial Derivative use on the Performance of Commercial Banks: Empirical Study in GCC Countries during 2000-2013

The commercial banks are working on innovative ways to achieve profits instead of traditional methods, and hedging of systemic risks by using financial derivatives because of the uncertainty and high volatility in the global and domestic financial markets especially in Golf Cooperation Council “GCC” countries. In this paper we investigated the effect of financial derivatives use on the performance of commercial banks in the “GCC” countries, where the study included nineteen banks distributed among the countries (Bahrain, Emirate, Qatar and Saudi) during the period 2000-2013, using the regression model with unbalanced panel data. We concluded the acceptance of dual fixed effects model shows that the relationship varies from one bank to another, due to the different characteristics of each bank and each country. That the use of derivatives is working on the reduction of no systemic risks, which improves the performance of commercial banks especially in the crisis period. Keywords: commercial banks, Banking Performance, GCC country, Panel data. JEL Classification: C3; G32; M41

Forecasting the threat of Covid-19 and Ukraine war on energy security: An empirical study using ‎GARCH-TGARCH

Recent developments in the oil and oil-related industries have made energy security a ‎top ‎priority. Concerns about immediate threats to economic growth as well as long-term ‎energy ‎security are sparked by high costs. To maintain the life quality for everyone in ‎the world, there ‎is a significant shared interest in ensuring that the globe can produce ‎and use energy in a ‎sustainable manner. The primary aim of the present paper is to measure ‎the impact of the dual ‎shock of the Covid-19 pandemic and Russia’s military action in ‎Ukraine on oil and oil-related ‎products sus as Brent Crude oil, WTI crude oil, Heating ‎oil, Natural Gas, UK natural gas and ‎Gasoline. To realize our investigation daily data ‎used for the period of 1st January 2020 to 7th ‎October 2022, the selected period ‎covered both of Covid-19 pandemic and Ukraine war ‎complications. The main findings ‎of the T-GARCH model state that there is a positive shock affect ‎on energy prices, particularly ‎oil prices that highly increased, followed by a notable augmentation in ‎the rest of ‎energy products during the Russia-Ukraine conflict. This situation can positively affect ‎the ‎hydrocarbon revenues for oil-exporting countries, in the counterpart the importing-‎countries ‎are most suffering from the high cost.

Forecasting the threat of Covid-19 and Ukraine war on energy security: An empirical study using ‎GARCH-TGARCH: Forecasting the threat of Covid-19 and Ukraine war on energy security: An empirical study using ‎GARCH-TGARCH

Recent developments in the oil and oil-related industries have made energy security a ‎top ‎priority. Concerns about immediate threats to economic growth as well as long-term ‎energy ‎security are sparked by high costs. To maintain the life quality for everyone in ‎the world, there ‎is a significant shared interest in ensuring that the globe can produce ‎and use energy in a ‎sustainable manner. The primary aim of the present paper is to measure ‎the impact of the dual ‎shock of the Covid-19 pandemic and Russia’s military action in ‎Ukraine on oil and oil-related ‎products sus as Brent Crude oil, WTI crude oil, Heating ‎oil, Natural Gas, UK natural gas and ‎Gasoline. To realize our investigation daily data ‎used for the period of 1st January 2020 to 7th ‎October 2022, the selected period ‎covered both of Covid-19 pandemic and Ukraine war ‎complications. The main findings ‎of the T-GARCH model state that there is a positive shock affect ‎on energy prices, particularly ‎oil prices that highly increased, followed by a notable augmentation in ‎the rest of ‎energy products during the Russia-Ukraine conflict. This situation can positively affect ‎the ‎hydrocarbon revenues for oil-exporting countries, in the counterpart the importing-‎countries ‎are most suffering from the high cost. ‎Recent developments in the oil and oil-related industries have made energy security a ‎top ‎priority. Concerns about immediate threats to economic growth as well as long-term ‎energy ‎security are sparked by high costs. To maintain the life quality for everyone in ‎the world, there ‎is a significant shared interest in ensuring that the globe can produce ‎and use energy in a ‎sustainable manner. The primary aim of the present paper is to measure ‎the impact of the dual ‎shock of the Covid-19 pandemic and Russia’s military action in ‎Ukraine on oil and oil-related ‎products sus as Brent Crude oil, WTI crude oil, Heating ‎oil, Natural Gas, UK natural gas and ‎Gasoline. To realize our investigation daily data ‎used for the period of 1st January 2020 to 7th ‎October 2022, the selected period ‎covered both of Covid-19 pandemic and Ukraine war ‎complications. The main findings ‎of the T-GARCH model state that there is a positive shock affect ‎on energy prices, particularly ‎oil prices that highly increased, followed by a notable augmentation in ‎the rest of ‎energy products during the Russia-Ukraine conflict. This situation can positively affect ‎the ‎hydrocarbon revenues for oil-exporting countries, in the counterpart the importing-‎countries ‎are most suffering from the high cost.

Forecasting the threat of Covid-19 and Ukraine war on energy security: An empirical study using ‎GARCH-TGARCH

Recent developments in the oil and oil-related industries have made energy security a ‎top ‎priority. Concerns about immediate threats to economic growth as well as long-term ‎energy ‎security are sparked by high costs. To maintain the life quality for everyone in ‎the world, there ‎is a significant shared interest in ensuring that the globe can produce ‎and use energy in a ‎sustainable manner. The primary aim of the present paper is to measure ‎the impact of the dual ‎shock of the Covid-19 pandemic and Russia’s military action in ‎Ukraine on oil and oil-related ‎products sus as Brent Crude oil, WTI crude oil, Heating ‎oil, Natural Gas, UK natural gas and ‎Gasoline. To realize our investigation daily data ‎used for the period of 1st January 2020 to 7th ‎October 2022, the selected period ‎covered both of Covid-19 pandemic and Ukraine war ‎complications. The main findings ‎of the T-GARCH model state that there is a positive shock affect ‎on energy prices, particularly ‎oil prices that highly increased, followed by a notable augmentation in ‎the rest of ‎energy products during the Russia-Ukraine conflict. This situation can positively affect ‎the ‎hydrocarbon revenues for oil-exporting countries, in the counterpart the importing-‎countries ‎are most suffering from the high cost.

Options Pricing by Monte Carlo Simulation, Binomial Tree and BMS Model: a comparative study of Nifty50 options index

Investment behaviour, techniques and choices have evolved in the options markets since the launch of options trading in 1973. Today, we are entering the field of Big Data and the explosion of information, which has become the main feature of science, impacts investors' decisions and their trading position, particularly in the financial markets. Our paper aims to testing the effectiveness of the most popular options pricing models , which are the Monte Carlo simulation method, the Binomial model, and the benchmark model; the Black-Scholes model, when we ignore/take on account the Moneyness categories and different time to maturities; five months, one year, and two years, in addition to comparing these models, we will then test the effect of each model on the prediction of the current options prices, using the regression analysis, and the Nifty50 option index during the period of 25/07/2014 to 30/06/2016. The result shows that all models are overpriced in all Moneyness categories with a high level of volatility in In-the money category, other finding concludes that the Monte Carlo Simulation method is outperforming when the volatility is lower, while the Black-Sholes model and the Binomial model are outperforming in the entire sample with ignoring the Moneyness