جستجوی مقالات مرتبط با کلیدواژه « GARCH » در نشریات گروه « اقتصاد »

Having an investment portfolio with minimum risk and maximum return is the Pareto optimum that all investors in the financial markets are looking for. Achieving this goal is not possible due to its idealistic nature, and people can only approach this optimal situation. However, the basic principle in the composition of the investment portfolio is to have financial assets with minimal correlation in the portfolio. This is followed to reduce the yield spillover effect among the portfolio assets. This is the reason for this study to investigate the yield spillover between assets such as gold, dollar, euro and major stock market indices such as automotive, banking and chemical group index for the daily period from 2018 August 26 to 2023 March 15, using the ARCH approach. Results of EGARCH(1,2), EGARCH(1,1), GARCH(1,2), GARCH(2,2) and AR(2) models for banking group index, chemical group index, gold, euro and dollar respectively which are based on the selected information criteria, showed that the spillover effect of the studied assets is different from each other.

Considering the position of oil in the economy of countries with oil resources, oil price uncertainty is one of the important sources of risk and uncertainty that affects the investment decisions of companies. In addition, another important issue that should be considered in this regard is whether the companies' investment response to the positive and negative uncertainty is symmetric or asymmetric.  Considering that the chemical products industry has an important role in the economic development of the country and is also affected by the developments of other markets such as the oil market, in this study the asymmetric effects of Brent oil price uncertainty on the investment of chemical products group companies in the Tehran stock exchange has been investigated from 2010 to 2021. The research modeling is based on dynamic panel models and the calculation of oil price uncertainty has been done by the GARCH method. Relationships between variables have also been estimated using the Generalized Method of Moment (GMM). The results show that during the period under review, oil price uncertainty had a negative effect on corporate investment. On the other hand, the findings indicate that the positive and negative oil price uncertainty has an asymmetric effect on corporate investment.

Oil prices and their uncertainties significantly impact the economies and financial markets of nations, influencing the cash reserves held by companies. Given the pivotal role of the chemical products industry has an important role in economic development and is also affected by other markets such as the oil market, this study aims to to investigate the effect of Brent oil price uncertainty on the cash holding of the chemical products group in the Tehran Stock Exchange during the period of 2010-2019. The research modeling is based on dynamic panel models and oil price uncertainty is computed through the GARCH method, while the relationships between variables are estimated using the Generalized method of moments (GMM) technique in two steps. The results of the study indicate that there is a positive and significant relationship between oil price uncertainty and cash holdings during the period under review. In addition, the effect of control variables such as financial leverage, cash flow, size, capital expenditures, liquidity, stock return, and return of assets is positive, and the effect of total debt, value added of industry, and interest rates on the cash is negative.

Investigating the effect of oil price uncertainty on the Tehran Stock Exchange index is of great importance because with increasing uncertainty in oil prices, the systematic risk of the stock market index increases. On the other hand, in oil exporting countries such as Iran, oil revenues are among the most important and influential factors in macroeconomic variables and, consequently, financial market indicators. The present study investigates the effect of oil price uncertainty on the Tehran Stock Exchange index using the wavelet-based quantile regression model (MODWT-MRA) during the period April 2011 to April 2021 in Iran.. The results of the model estimate showed that with the increase in oil price uncertainty, the Tehran Stock Exchange index will decrease. According to the results, the effect of oil price uncertainty on the Tehran Stock Exchange index in the first few quantiles has a smaller coefficient than the final quantiles, so the negative effect of oil price uncertainty on the Tehran Stock Exchange index in recent months is more than the first months. Also, the coefficient value on the component 5 scale is much higher than the component 1 scale; Therefore, the negative effect of oil price uncertainty on the Tehran Stock Exchange index in the short run is much greater than the value of this effect in the long run. This is because in the long run, the investor will adjust to the uncertainty.

This study seeks to investigate the effect of uncertainty caused by oil shocks on the stock market in the Tehran Stock Exchange. For this purpose, in this research, first using Box and Jenkiz approach and using the family of Garch models, for the daily period of 2008 to 2021 (4632 days in total), first the oil price uncertainty index and the Tehran Stock Exchange index are extracted. The effects of these two variables on each other were then investigated using VAR analysis. The results show that the global oil price has a significant effect on the stock market index and oil price fluctuation has a significant effect on the stock market index fluctuation. There is also a positive relationship between oil prices and stock return index using causality test; This means that the increase in oil prices leads to an increase in the stock return index in the Tehran securities market. Also, the results of the instantaneous reaction functions emphasize the positive relationship between oil price shocks and the stock return index.

Oil price shocks in recent decades have had a profound effect on the economies of the world, both exporters and importers of oil. Countries that depend on revenues from the sale of oil and gas resources during economic growth, as well as those that import Oil resources are particularly sensitive to changes and fluctuations in oil prices. Axes related to globalization and factors affecting the increase in the volume of international trade have raised many questions in the macroeconomy. Is a commercial instrument.In this study, we examine the effect of oil price shocks and trade openness turmoil on economic growth and inflation in two groups of oil exporting and importing countries.The results show that the research hypotheses that the response of economic growth and inflation to oil price shocks are asymmetric in both groups of oil exporting and importing countries. Also, the results of tests and estimation of patterns show openness. Trade has a positive effect on economic growth and inflation of oil exporting countries and a negative and positive effect on economic growth and inflation of oil importing countries.

Given that Iran's economy has always been accompanied by uncertainties and fluctuations due to the structural reasons such as dependence on oil revenues, high inflation, annual budget deficit and currency fluctuations, the main question is whether tax revenues have been able to neutralize or control the adverse effects of these uncertainties as a powerful financial instrument? So, we used the specified model and the Generalized Autoregressive Conditional Heteroskedastisity model (GARCH) based on quarterly data from 1990-2019 . The findings of the study confirm the uncertainty of the variables and show that tax revenues have been significantly affected by exchange rate fluctuations and inflation.

Deposits insurance, as an integral part of the set of strategies, plays a preventive role (through prudential supervision) as well as a forward-looking role (by guaranteeing public deposits) in the financial health of countries. The stability of the financial sector has been discussed.

The main purpose of the present study is to evaluate deposit insurance in the useless banking industry in Iran. Statistical population of Iran and the sample of selected banks include Parsian, Pasargard, Saman, Melli, Sepah and Housing in the period of 1385-1397.

The research method is descriptive-applied. Firstly, using the statistical data of the above mentioned banks, the credit risk of the banks is obtained and then using the GARCH model the estimation of the deposit insurance pricing is done.

The results show that the credit risk of different banks is different and therefore, the pricing of deposit insurance is different for private and public banks, it is suggested that the deposit insurance pricing system In Iran, it be calculated on a yearly basis according to the risk of each bank.

Regarding the role of the energy market, especially oil, on the economy of countries, it is important to identify the future evolution of the market. In this respect, predicting the changeable extreme evolution of the oil price is crucial for decision and policy makers. This study attempts to investigate the maximum changes of OPEC’s oil price by employing the concept of Value at Risk. To this end, GARCH family models based on the normal and extreme distribution were used, and it is expected that the focus on the latter in forecasting Value at Risk, especially in the face of extreme events, may end up in more realistic results. The results of the backtesting of models show that the ARMA-GARCH-EVT model predicts better than the other ones.

In many emerging and developing economies, sudden changes and volatilities in the exchange rate can be negatively affect economic growth by decline in investment, trade balance and profitability. Considering the fact that these economies are vulnerable to changes in capital inflows; remittances as one of the most important capital and financial inflows can lead to volatility and uncertainty in the exchange rate of developing countries and cause instability in the economy. Thus In this study, the mutual relationship between real exchange rate volatility and remittances volatility has been investigated and empirically analyzed by the use of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and three stage least square (3SLS) of simultaneous equations system approaches in the selected developing countries including Iran over the period 1980-2015. The results demonstrate that there is a relationship between the real exchange rate and remittances volatilities. In the meanwhile, the exchange rate volatility has a greater and significant effect on the volatility of remittances; while their reverse effect is small. In other words, the remittances volatility does not have a significant effect on the exchange rate volatility, which leads to economic stability. In addition, foreign direct investment, government spendings and trade openness cause volatilities in real exchange rates, and on the other side, inflation, financial development, household expenditure per capita and age dependency are the influential factors of remittances volatility in the studied countries.

The present study aims to provide a model for covering price risks in Iranian importers of agricultural commodities. In order to assess the efficiency of the model, daily spot and futures prices of soybeans and corn were collected from the Chicago Mercantile Exchange (CME) during the period 05/01/2010 to 06/08/2018. The data were analyzed for two situations as follows: 1- Futures contracts can be traded. 2- Futures contracts cannot be traded. One of such methods in the dynamic state is Markov switching GARCH model. The application of the Markov switching GARCH model produced a high volatility and a low volatility regime. In case the quasi futures contracts are used, the optimal risk coverage ratio for the soybean and corn products would respectively be equal with 0.849 and 0.9065; while the efficiency of the risk coverage would be respectively equal to 82 and 78 percent for these two products.

Iran has exported more than half a billion dollars’ worth of handmade carpet, which is about one quarter of the handmade carpet global market on average in the 1979- 2014 period. This research estimates the impacts of exchange rate volatility on the carpet exports using the General Auto-Regressive Conditional Heteroskedasticity (GARCH) model, J-J cointegration test and the vector error correction model (VECM). The results show that the real exchange rate, weighted average gross income of carpet importing countries, and inflation rate have positive impacts on the export of carpets. Results also show that exchange rate volatility effect is negative and significant in the short term. The J-J test results with effect test and maximum-eigenvalue test show that there is at least one long-run relationship. The VECM model also show that the exchange rate and exchange rate volatility are divergent and inflation rate and national income are convergent. Exchange rate volatility leads to income volatility of suppliers and price volatility for importers. Exchange rate volatility risk increases the risk of investment and production in the carpet industry and has a negative impact on the supply of carpets. On the demand side, as increasing market risk leads to the postponement or cancellation of the purchases, because the buyers are facing purchase price volatility. The stable monetary and foreign exchange rate policies will have positive impacts on the carpet exports and therefore are desirable.

The main objective of this research is to investigate the impact of financial structure on the Iranian economic growth volatility by applying GARCH & ARDL methods using quarterly data over the 1991-2015 period. The results indicate that financial development and financial structure have negative and positive effects on the economic growth volatility in Iran, respectively. The results reveal that financial structure in Iran is facing with several challenges, so that regardless of negative impact of financial development on economic growth volatility, the financial structure leads to economic growth volatility. In addition, oil revenues, government final consumption expenditure and capital formation have significant and negative relationships with economic growth volatility in the period under study.

As one of the most important economic variables, exchange rate imposes many risks on another sectors of the economy. One of the important functions of the central banks is to proper manage these fluctuations in the foreign exchange market and to reduce the risks it poses to economic activists in the short, medium and long-term periods. This study introduces and estimates new indicators of exchange rate fluctuations in different time scales to manage the exchange rate fluctuations more appropriately according to the central bank's approach. This method utilizes the combination of the wavelet and GARCH models, and data is collected from Iran’s foreign exchange market for the period of Sep-2008 to 2015.

The main objective of this study is to investigate the effect of exchange rate and exchange rate uncertainty on domestic consumption in Iran during 1988q2-2015q1.Therefore,GARCH method is used to estimate the exchange rate uncertainty and the Bonds test approach to ARDL models is used to analyze the existence of long-run relationship, and the Vector Error-Correction model is used to analyze the short-run deviations of variables from their long-run equilibrium values. The results indicate that the exchange rate has direct significant long run and short run effect on the consumption, but exchange rate uncertainty has indirect significant effect on the consumption in Iran. Positive relationship between exchange rate and consumption confirms the exchange rate path theory in Iran. Negative relationship between exchange rate uncertainty and consumption confirms absorption theory in Iran. The results suggest monetary authorities in Iran to adopt appropriate exchange policy for decreasing exchange rate uncertainties. Due to insignificant short run and significant long run effect of government expenditure on consumption, it is suggested to adopt managed government expenditure growth rate in mid-term program.

Many researchers have used different methods to forecast the volatility of goods and capital markets. However, only few have taken into account the importance of data frequency on their predictions. However, none of them have considered the possibility of long run memory in predicting the volatility of oil market. In order to fill this gap in the literature, we have estimated a class of ARFIMA and GARCH models (long- and short-run memory models) with different data frequency to predict oil market volatility. Based on Root Mean Square Error (RMSE) criterion, irrespective of model's type, all models with high frequency data outperform the low frequency data models. The result also shows that at each frequency level, the prediction powers of both ARFIMA and GARCH models are the same. To sum up, we suggest the use of short-run memory model with high frequency data to forecast volatility of oil market. Hence, it seems a proper GARCH model can do the job and there is no need to use ARFIMA model for this purpose.

The stateof bankrupcy and losses incurred by many banks in recent global financial crisis has doubled the importance of paying attention to the liquidity of banks as an indicator of health and stability of banking systems. In addition, due to dependence of banking system's performance on economic variables at the macro level, with a consideration on intermediatory function of banks and role of macroeconomic instability in creating financial system instability, which influences bank's performance and activity, studying the stability and health of the banking system has become more important. Therefore the purpose of this study is to evaluate the impact of macroeconomic fluctuations on liquidity risk of bank. Using GARCH and EGARCH models, panel data, the effects of macroeconomic fluctuations on liquidity risk of banks in Iran is studied by using quarterly data of 14 largest banks of the country during 2006:2-2014:1. The results show that fluctuations in GDP, inflation, exchange rate and stock price index as most important macroeconomic variables have significant effects on liquidity risk of banks. Therefore, higher fluctuations in Iranian economy can result in shortages of liquidity in banks and changing composition of bank deposits and eventually exposing banks to higher liquidity risks.

For any country, the stock market reflects the country's economic structure, but also is an important source of capital circulation in that country. Therefore identification of effective factors on stock market volatility is important for economic policy makers. In this regard, the present study tried investigating the impact of macroeconomic variables, including money supply growth, inflation rate, industrial production growth and market exchange rate changes on the Tehran stock exchange volatility. To achieve this purpose, seasonal data during 2003-2015 period and GARCH-X and VAR model was used. The results of model estimation show that the money supply growth and exchange rate changes have a positive and significant impact on stock returns and inflation rate has positive but insignificant impact on stock returns. Also industrial production growth has negative and significant impact on stock returns. Therefore, it is recommended that the country's planners and policy makers to prevent the lack of uncertainty in the capital markets, should avoid unmanaged economic policies and programs.