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

Institutional Investors in the Tehran Stock Exchange (with a large amount of assets and a significant share of transactions) have a significant effect on the market. This issue, along with the low depth of the market, gave them a power to be influential in the market, and as a result, they can manipulate the prices and create fluctuations in the market. While the main duty of Institutional Investors is to stabilize, they can abuse their market power and increase market instability. Therefore, recognizing their behavioral types in different level of risk is important. This study answers the question of whether the behavior of Institutional Investors in the Tehran Stock Exchange, in controlling and managing market risk, changes with changing levels of risk. The study is done for years 2018 to 2020 that the Tehran Stock Exchange experienced a huge fluctuations and includes 20 market-making companies. The method used in the research is the panel quantile model, which gives the possibility of studying the behavior of Institutional Investors in different quantiles. The results show the Institutional investors have 3type of behavior. At the initial and lower levels of risk, Institutional actors increase market risk. But at higher levels of risk quantiles, Institutional actors have a negative effect on market risk and at the middle level of risk they are neutral. This implies that market Institutional actors tend to have a moderate level of risk. Therefore, in the studied years, the Institutional investors increased the risk in the market and only when the fluctuations have reached higher levels, they have prevented large fluctuations according to their interests.

Digital currency analysis, especially Bitcoin, as the most popular digital currency, has received a lot of attention in recent years. The reason for this can be related to its innovative features, simplicity, transparency and increasing popularity. Since its introduction, Bitcoin has created great challenges and opportunities for policymakers, economists, entrepreneurs and consumers. The main purpose of writing this article is to investigate and analyze the fluctuations and returns of Bitcoin using univariate conditional variance heterogeneous autoregression models in the period between March 2012 and March 2019. In this framework, GARCH, GJR-GARCH, TGARCH EGARCH and GARCH-M univariate GARCH models are used. The results show that the best model for risk assessment in univariate GARCH models is GARCH-M model, because the liquidity risk predicts the Bitcoin price index with less error than other univariate models. Also, the results obtained in the EGARCH model show that there are no leverage effects in Bitcoin rate changes and the estimated model is a symmetric model. Examining several other univariate GARCH models also showed that the price of Bitcoin has symmetry in positive and negative news, this means that positive and negative shocks have the same effect on the price of bitcoin.

Nowadays, the capital market is one of the key economic sectors closely linked to other sectors, especially the monetary and banking. On the other hand, maintaining the stability of the capital market is a major concern for any economy. The financial crisis of 2008 has challenged the role of central bank on financial stability. In this regard, present research examine the effect of central bank independence on stock market volatility as a measure of financial instability in Tehran Stock Exchange from 1991 to 2019.In this regard, the stock market volatility series are generated utilizing the GARCH model and then the Autoregressive Distributed Lag (ARDL) model is estimated. Next, ARDL bounds testing for co-integration is employed and finally long-run relationship is estimated. The research findings show that the Central Bank Independence has a positive and significant effect on the volatility in Tehran Stock Exchange.However, move towards the reduction of the central bank independence does not seem reasonable due to its inflationary consequences.In this context, by maintaining the central bank independence from one hand, and trying to increase the central bank transparency on the other hand, the two goals of price stability and financial stability can be achieved simultaneously.

Exchange rate is one of the most influential factors affecting Iranchr('39')s macroeconomic variables. Exchange rate fluctuations in Iran have always been one of the major challenges for policymakers. On the other hand, many central banks today consider transparency as one of the main and vital priorities in achieving the effectiveness of monetary policy and communicating effectively with the people and being accountable. This transparency can affect macroeconomic expectations and the exchange rate. In this study, the effect of central bank transparency on exchange rate fluctuations is investigated using the ARDL method over the period 1981-2018. This study is based on analytical, applied and correlational research methods, which uses time-series econometric regression model. The transparency of the central bank, as independent variable, is measured by Dincer & Eichengreen index, and exchange rate fluctuations, as dependent variable, are constructed by GARCH method. The results show that the transparency of the central bank reduces exchange rate fluctuations in both short run and long run, and there is a long-term synergistic relationship between research variables.

The banking network plays a prominent role in the financing of businesses. In recent years, due to increased government spending and disproportionate increases in government revenues, a budget deficit has been created, and due to the high dependence between the government and the banking network, in some cases increased current spending has been provided through borrowing from the banking network. Theoretical Framework: One of the most important factors that effect on the formation of the financial crisis is the instability in other financial markets, especially the exchange rate, which affects the GDP of the country and the current expenditures of the government, and affecting the performance of the banking sector subsequently. By affecting the government budget, the exchange rate can affect the motivation of the government and government-affiliated companies to obtain loans and facilities from the banking network. Also, the increase in the exchange rate by increasing the cost of goods and services leads to a decrease in disposable income and subsequently a decrease in people's consumption. According to dependence of industrial sector to imports of intermediary goods, changes in exchange rate causes a change in the supply sector (Boschi & D' Addona, 2019). On the other hand, exchange rate volatility due to the uncertainty and increases in the cost of production has been effective on government debt to the banking system and current expenditures (Adrian & Shin,2010).

In this study, using the wavelet transform model during the period of 1388-1397 monthly, the nominal exchange rate volatilities, government debt to the banking network, and current government expenditures are divided into three levels by using wavelet transform. In fact, wavelet transform explains the deviation from the main trend. To examine the relationship between the variables, the use of patterns such as Granjer causality is used, which provides a momentary criterion of causality test, therefore, it is unable to analyze the dynamics and reliability of variables relationship. In addition, in such methods, because the lag of variables can be used, it is possible to eliminate the immediate effects. Spectral analysis is used to solve this problem (Aguiar, et al.,2008).

In the short term, there is no significant correlation between nominal exchange rate fluctuations and current government spending fluctuations. Interestingly, there is a significant correlation between government debt to banking network fluctuations and exchange rate fluctuations. This indicates that about 17% of the fluctuations in the foreign exchange market and government debt to the banking network are consistent. Significantly, there is a relatively high correlation between government debt to banking network fluctuations  and current government spending fluctuations in the short term, and about 32.5 percent of changes and fluctuations in each have led to a change in the other one, and in fact It can show the lack of independence of the country's banking network and the dependence and attitude of the government to provide current expenses from this source. There is a positive and significant correlation between nominal exchange rate fluctuations and current government spending fluctuations in the medium term. Of course, only about 19% of the fluctuations in each are positively followed by other fluctuations. In the medium term, the movement between exchange rate fluctuations and government debt to banking network fluctuations increases compared to the short-term (0.26), and this can also indicate the delayed effects of the exchange rate. Interestingly, there is a high correlation between government debt to banking network fluctuations and current government spending fluctuations, and over a longer period the fluctuations between the two are more intense in terms of intensity and direction. The time factor plays a very important role in the correlation between government debt fluctuations and exchange rate fluctuations. The correlation between these two cases started from about 0.17 in the short term and reached 0.53 in the long run. In terms of time factor, it has shown more biger about fluctuations in current government expenditures and fluctuations in government debt to banks than the other cases. The correlation between the two fluctuations has risen from 32.5 percent in the short term to 76 percent in the long term. Conclusions and Suggestions: government and the banking network have a close relationship with each other, and this relationship is due to the fact that many of the country's banks are state-owned be greater in the long run. In fact, this is one of the main reasons for the non-performing loans in the country's banking network, and the government has used its bargaining power to cover its current expenditures, which have been very volatile in recent years and take loans and did not pay on time. In fact, based on the results, banking network has been a tool to cover current government expenditures, and due to exchange rate fluctuations in the country and increasing government current expenditures, government debt to the banking network can increase and reduce the credit ability of the banking network and can lead to inefficient allocation of resources.

This research aims to study the relationship between value-added of the construction sector and the Iranian economy using Iranian National Accounts data for period 1959-2014. The gross domestic product of Iran is broken down into three segments: construction, oil, and the rest, and the cyclical components of each of these variables are extracted. Applying different statistical techniques (correlation, least square regression, and vector autoregressive analysis) along with defining and extracting prolonged relative low-activity periods –times consistent of at least two consecutive periods of negative growth rates of the cyclical component– we have found that: 1) fluctuations of oil sector leads those of the construction and the rest (oil and construction excluded) sectors. 2) prolonged relative low-activity periods in the construction sector often begin concurrent or after the whole economy, and often ends one year later than the whole economy. 3) a shock to the rest sector has a significant impact on the construction sector. 4) the fluctuations in the construction sector do not have a significant effect on the rest sector. All in all, the results provide no evidence that the construction sector leads or drives the Iranian economy.

International financial integration is a process of reducing financial frictions that lead to formation of free capital flows. Joining the international financial flow influences the volatility of economic variables from different channels and hence, it is important to examine the conditions that key variables are less responsive to shocks despite the capital account transfers. One of the issues that is being considered in this regard is the choice of the currency regime. Hence, in this paper, in assistance with a general dynamic stochastic equilibrium model with price rigidity, at first, a channel was designed to simulate the financial integration scenario in line with the characteristics of the Iranian economy and then the model performance in two modes of floating and managed float exchange rate regime in response to government spending and oil shocks has been investigated. The results show that, in response to government spending shocks, the floating exchange rate will lead to less fluctuations in key variables such as production, consumption, inflation and real exchange rate and in response to the oil shocks, managed float exchange rate will lead to less fluctuations in production, consumption, inflation and real exchange rate.

The purpose of this paper is to examine the fluctuations of entrepreneurial wealth in an open participatory economy and compare it with an interest-based economy. In this hypothetical participatory economy, the investor can freely choose between two types of domestic cooperative financing and external interest-based financing (in international financial markets). To this end, a dynamic model is designed and solved based on the dynamics of entrepreneurial wealth. The results show that when the two cooperative economies are exposed to the same conditions, which means that the opportunity cost of investing is equal to both, entrepreneurial wealth and therefore national investment and production in the cooperative economy are less volatile than the conventional economy. But when the opportunity cost of investing in the two economies is different, only under conditions of entrepreneurial wealth and production in a participatory economy can they be less volatile than the conventional economy. It is considered that these conditions depend on the values of the interest rate parameters, the participation rate and the minimum safe return of the domestic economy.

The special features of the cryptocurrency have raised them as the future money of the global economy, while the monetary nature of these cryptocurrency has been questioned. In the economic literature, three main functions of money are considered as: (1) a medium of exchange, (2) a unit of account, and (3) a store of value. In this research, it will first attempt to address the history, nature and types of digital, virtual, and crypto money in the monetary system of the countries, and then, by modeling the exchange rate fluctuation of the selected cryptocurrencies, the Euro-Dollar and Gold with the GARCH family models, their monetary functions will be investigated. At the current time, it appears that the fluctuations of these types of cryptocurrency and the widespread inadequate use of them in micropayments, their monetary functions are seriously skeptical and therefore the use of money does not seem to be correct for them right now. With the advancement of technology and more people's familiarity with the advancement of technology, the depth of the cryptocurrency market could be increased, reducing their fluctuations and increasing the use of micro payments, and as a result, their money functions are expected to become more prominent over time.

Undoubtedly, the financing structure in each country's economy is considered to be the main element of the economic system of that country, because the life of an economy depends on its production and growth in its various fields, and its production and growth will not be realized without the required financial resources. The task entrusted to the economic system of the country is within the framework of its financing structure.
According to some economic experts, in Iran, the state budget, private sector savings and external resources are three determinants of financing sources. This means that active enterprises in various fields of production can pay for these resources to cover their needs. The government budget as one of the sources of financing firms due to dependence on oil revenues, can not be a powerful stimulus to sustain economic growth in the country. With regard to foreign sources, because of the sanctions, there can be no special account on them to finance various production sectors. Thus, it can be concluded that in the current economic conditions, the only possible option for financing firms is private sector savings; which can be equipped with the capital market and the money market (i.e., banks). Therefore, given that turbulence or fluctuations in inflation is one of the challenges in the banking system, what is highlighted in this paper is the uncertainty associated with inflation, and with the amount of bank loan facilities, and the facilities that most small and medium-sized enterprises have need to survive in the current state of the economy. Specifically, cheap bank facilities are referred to as facilities that are used by low-cost bank's resources for applicants.
Considering the importance of the banking system in the financing structure of firms and also need of small and medium firms for cheap banking facilities, and the bank's actions in the face of fluctuations of economic variables such as inflation, in order to maintain bank's financial strength, it seems that the study of the effect of macroeconomic variables on the performance of the banking system of the country has great importance.
Since developing countries, including Iran, have a high degree of uncertainty in macroeconomic variables. And this uncertainty also affects the decisions of bank officials, this paper examines the relationship between the uncertainty of inflation and Gharz-al-hassane facilities paid by commercial banks, in the form of a two-variable GARCH model using monthly data for the period of 2005-2014.
There are several methods to assess uncertainty and volatility in variables, but the most commonly used method in most econometric studies is the use of GARCH patterns. This method, proposed by Bollerslev (1986) is a modeling based on variance of variables over time.
GARCH patterns are categorized in a general classification based on the number of variables in the pattern, into univariate patterns and multivariate patterns. Single-GARCH patterns have limitations that make them difficult to use; one assumes that the conditional variance of each series is independent of all other series. In addition, in this type of models, covariance between series is not considered as an important factor of volatility of variables. These limitations make these patterns in many cases unrecognizable. The multivariate GARCH patterns can potentially overcome the deficiencies and defects of single-variable patterns. Multivariate patterns are very similar to single-variable models, and hence their estimates are similar to simple GARCH-single-variable patterns. However, in addition to the previous equations, there are certain equations for expressing how covariance moves over time (Heidari & Bashiri, 2011).
The first type of GARCH multivariate patterns is the Vech (q, p) pattern introduced by Bollerslev, Engle and Woldrige (1988). In 1991, another class of Vech (q, p) was introduced by Baba, Engle, Kraft and Kroner (1991) which became known as BEKK. This pattern has an interesting feature that, by applying several constraints, the variance-covariance matrix is a positive and definite condition. The problem with previous GARCH multi-variable protocols, including DCCs, is that they are not compatible; therefore, in order to avoid inappropriate results for estimating the conditional mean, variance, and variance of variables of inflation and facilities of the borrower, we use the cDCC model of MGARCH (1,1).
The results from the cDCC model estimation show that the uncertainty of inflation on the amount of Gharz-al-hassane facilities had a positive effect; which was not statistically significant at 5% level. On this basis, it can be concluded that with the increase of inflation, which is a depreciation of the money value and consequently a decline in the purchaser's purchasing power, the amount of Gharz-al-hassane loans has also increased. This is while expected in inflationary conditions, people withdraw these deposits or convert into long-term deposits. In the case of banks, it is also expected that by increasing inflation and rising money prices, and applying incentive policies to attract more long-term deposits instead of Gharz-al-hassane deposits, as a result, the amount of Gharz-al-hassane funds will be reduced and the amount of bank facilities will be lowered from these sources. However, the results indicate inverse of this issue in the selected time frame. It is a result that can prevent the adoption of false policies by the banking authorities. Thus, the banks are aware of the positive correlation between the inflationary fluctuations, that are increasing in inflation in the Iranian economy, and the commercial loans granted by commercial banks, withdrew its previous policies and put new policies in place to keep their capital under inflationary conditions.
As a suggested strategy, banks can use this in the context of the inflationary period in which some firms and households suffer from a drop in supply and demand due to rising prices, in order to adjust the business cycles; Thus, during this period, the resources of its Gharz-al-hassane deposits, which have not been reduced due to inflationary fluctuations, will be provided to this sector of enterprises and households. In this way, firms can continue to produce, and households are also buying power, both of which are a step towards more production and prosperity. On the other hand, the banks themselves have received a fee from the facility, and have also made a contribution to the investments made and can partly offset the depreciation of their finances during the inflationary period.

Housing is one of the economic major sectors of the macro economy of country and micro economy of the household. Changes in home prices, including consideration of issues in recent years. In this regard, several studies for examining the determinant variables of Housing supply and demand and prices have been. This article attempts with using of model dissimilar variance Household ARCH, paying to provide a model for the volatility of housing prices over the period 1391 - 1350.The results indicate that the EGARCH model gives the best results. And illustrate occur shocking in housing prices during the years of 1390 to 1392 to happen. And the growth rate of housing prices will remain constant after the year 1395.

This study investigates the effect of volatility structural changes on the shock transmission and volatility Spillover between gold and stock markets in Iran during 2007-2013. For this purpose, firstly, we will detect the time periods of structural breaks in volatility of gold and stock returns endogenously using the standard and modified iterated cumulated sums of squares (ICSS) algorithm. Then, this information incorporates to model the volatility process. The application of bi-variate GARCH model in off-diagonal BEKK parameterization suggest that shock transmission and volatility spillover between gold and stock markets is bidirectional in Iran. Also, based on the present research findings, ignoring or incorrect detection of structural breaks mislead the researcher about the direction of volatility transmission between gold and stock markets.

In this study we compare a set of Markov Regime-Switching GARCH models in terms of their ability to forecast the Tehran stock market volatility at different time intervals. SW-GARCH models have been used to avoid the excessive persistence that usually found in GARCH models. In SW-GARCH models all parameters are allowed to switch between a low or high volatility regimes. Both Gaussian and fat-tailed conditional distributions are assumed for the residuals, and the degrees of freedom can also be state-dependent to capture possible time-varying kurtosis. Using stationary bootstrap and re-sampling, the forecasting performances of the competing models are evaluated by statistical loss functions. The empirical analysis demonstrates that SW-GARCH models outperform all standard GARCH models in forecasting volatility. Also, the SW-GARCH model with the t distribution for errors has the best performance in fitting a model and estimation.

Importance of risk and uncertainty in financial markets became more apparent after financial crisis in 2007. Volatility is the most important measure of risk in financial markets. Thus, modeling volatility of financial markets is one of the important issues in finance and economics. In this paper first we tried to specify key features of volatility of daily returns of Tehran stock exchange price index (TEPIX) and then using these features, we modeled volatility of this index. We found that this index is fat-tailed distributed and mean- reverting. Furthermore, we showed that there is no leverage effect, so using of TARCH and EGARCH models are not convenient. Finally, we found that AR(2)-GARCH(1,1) Model can capture features of data in the best way.

This paper has examined the long memory of oil market volatility. For this purpose, the paper has employed different types of long run ARCH models including FIGARCH-BBM, FIGARCH-chung, FIEGARCH, FIAPARCH-BBM and FIAPARCH-chung and short run ones including GARCH, EGARCH, GJR AND APARCH with three different assumptions of normal, t-student and generalized error distributions. Results obtained from all long run models indicate the volatility persistence, i.e. the long memory of oil market volatility. Furthermore, with regard to Akaike’s information criterion, FIAPARCH-chung with assumption of t-student distribution has the best performance. Also, according to Schwarz Criterion, FIGARCH-chung model with assumption t-student distribution is the best model in modeling volatility of oil market. Based on the results, long run models considering long memory property of volatility indicate a better performance than the short run ones. Finally, based on obtained results, asymmetric distributions including t-student and GED are found to be more suitable than normal distribution.

This paper examines the dynamic relationship of stock markets, stability, predictability, volatility, and persistence of shocks volatility of stock markets in Iran, Saudi Arabia, United Arabic Emirates, Qatar, Bahrain and Oman. In this paper, Generalized Autoregressive Conditional Heteroskedasticity model (GARCH) and Autoregressive Moving Average model (ARMA) are implemented by using monthly data during 1990-2010. The results indicate that stock market doesn’t have notable predictability in Iran and there is Cluster volatility for return of stock in most markets and almost, in none of these markets except Oman, explosive volatilities are observed. It is also indicated that the return for markets of Bahrain and Oman doesn’t have stability in significant level of 5 percent and for Iran it doesn’t have stability and durability in significant level of 1 percent. In addition, although the markets of these countries have high capacities for return of investment, but, in particular, the findings show a low correlation between these markets. Also, the results for the period in question explain that none of these markets has the ability of leadership among others.

Fluctuation of exchange rate and its deviation from equilibrium path are one of the most important macroeconomic variables that is affected by different side of economical sectors. Whereas, the Exchange rate fluctuation and its deviation from equilibrium path haven’t the same and similar effects on all of the economical sectors, and considering eminent important of industrial development on the development of the country; This paper examines and evaluates the exchange rate fluctuation and its deviation from equilibrium path on value added of industrial sectors. So first we calculate deviation of real exchange rate from long run equilibrium path by use of Cottani’s model Then, in order to calculate short run exchange rate with error correction method framework. In order to avoid non stationery of some of the variables used in these models, and other problems, we have used a new econometric method; integration and auto regressive distribution lag (ARDL); and then considered the effects of exchange rate fluctuations and its deviation from equilibrium path on value added of industrial sectors This paper shows that fundamental hypothesis; posterior reverse relationship between real exchange rate deviation of equilibrium path and value added of industrial sectors; is accepted.