فصلنامه مدلسازی اقتصادی
سال چهاردهم شماره 1 (پیاپی 49، بهار 1399)

This study intended to examine the correlation between the stock market return and the oil price return within a multivariate GARCH model. To this end, the correlation of these two variables with the spillover rate, conditional mean, oil price fluctuations, and the stock market indexes of 10 OPEC members, i.e. Algeria, Iran, Iraq, Kuwait, Nigeria, Qatar, Venezuela, Saudi Arabia, the UAE, and Ecuador, were examined in the form of monthly times series for the 2014–2019 time span. The results showed that there is a positive correlation between the oil price volatility and the stock market return in OPEC member countries. In addition, there is a greater correlation between the oil price fluctuations and the stock return in countries where oil revenues make a bigger contribution to GDP. It was also concluded that the oil price volatility spreads to that of the stock returns.

This paper investigates the adaptability of (TDP) models for pricing patterns in Iranian economy. For this purpose, price sub-indexes monthly time-series in the period of 2014(4) to 2017(11) are used. Moreover, appropriate wavelet transformation method is applied to extract pricing patterns from the time-series. Based on our findings, firstly heterogeneity is observed between pricing patterns of distinct groups of goods and services significantly which is inconsistent with (TDP) models assumption about the random distribution of price changing signals. Secondly, the pricing patterns changes over time which does not match with the assumption of uniform distribution of random signal during the time. As a result, the (TDP) models are not able to explain the pricing behavior patterns of the Iranian economy and the alternative approaches such as state-dependent pricing or rationally inattentive methods can be applied.

The aim of this article is to measure the dynamics connectedness of Tehran stock market with stock exchanges of selected countries from the Middle East and China, oil and gold markets, the dollar index and the euro-dollar and yuan-dollar. To this end, a variance decomposition approach has been used to measure connectedness of markets between January 2008 and the end of July 2019. The findings show that the variance of forecast errors in most of markets are due to the shocks of those markets themselves. The Qatari Stock Exchange has a significant impact on Saudi and UAE stock exchanges. As the time horizon increases, Brent's oil market will be more influential than other markets, and this market will be more affected by the stock exchanges of the Arab countries and the Shanghai Composite. According to the results, investing in the Tehran Stock Exchange and the yuan-dollar exchange rate due to insignificant dynamics connectedness with other markets is recommended to hedge risk.

The economy of Iran, since 1385s In addition to significiant decrease in output has experienced the high and two-digit inflation rates. For this reason, review of determinantes of inflation rate and output has a remarkable necessity. The factors like population growth, Eccessive technological advancement, private investment and initial level of per capita income and money growth are the variables affecting on the growth. Also, the idea of “inflationary money” has the relative consensus among economists, but identifying of the factors that determine the intensity of the effectiveness of the monetary policy on inflation rate and output makes it possible for monetary policymakers to planning for controlling inflation and increasing the output. Trade Openness is one of the factors that has a determinative role in review of difference the effectiveness of money growth on inflation rate and output in different countries. The aim of the present study is the test of Trade balance effect symmetry and the Incidence of the effects of monetary policy on economic growth and inflation. For this purpose, years 2000-2014, related to 34 selected countries with high middle-income and Generalized Method of Moments (GMM) have been used. The research showed that more trade openness leads to increase the impact of monetary policy on output and decease the impact of monetary policy on inflation.the more trade liberalization through omitting or decreasing of tarrifs and import quotas are the main suggestions of this study

The purpose of this paper is to investigate the long-term and short-term relationships between the behavior of gas and oil prices in regional markets and their impact on each other using the VECM correction method during the period 2000-2019. For this purpose, due to the wide range of variables in each region, proxy technique has been used to analyze the markets of gas and oil regions. The findings show that among the regional prices of the gas and oil market in Asia and Europe (unlike the US market), due to the relationship of aggregation, the influence of oil market fluctuations is very high. Due to the importance of the role of financial markets in facilitating oil and gas transactions, it is suggested that the major supply of oil and gas through the energy exchange be considered.

The purpose of this essay is to scrutinize the effects of the announcements of OPEC (including increasing, decreasing and not changing the supplies) on the fluctuations of oil price in crude oil markets. For this purpose, this research has applied the conditional variance inconsistency and affected the variance control to consider the effects of these announcements on the fluctuations of crude oil from 1987 to 2019 based on the outcomes obtained from the analysis of events. applied the conditional variance inconsistency and affected the variance control to consider the effects of these announcements on the fluctuations of Brent and WTI crude oil from 1987 to 2019 based on the outcomes obtained from the analysis of events. The findings reveal that these announcements differently affect the WTI Brent and the fluctuations of oil market. These types of announcements differently influence the fluctuations of the crude oil market. Indeed, this effectivity is reduced by time dragging. According to the results, it is suggested that members cooperated together in planning and executing decisions in an organized pattern in order to highly affect the crude oil market.

The main purpose of this paper is to identify the factors influencing the creation and increase of non-current debts to make a more appropriate decision in granting facilities. For this purpose, to select effective variables, from the analysis algorithms of correlation and Lasso components; And to classify the samples, neural networks and support machine were used. In this study, a sample of 660 legal customers of Sepah Bank for the years 2006-2017 was selected and focused on the characteristic variables extracted from the facility contracts of these customers along with financial, non-financial, auditing and economic variables. The results showed that the Lasso algorithm focused on financial, economic and auditing variables, performed better than the neighboring component analysis algorithm, and based on this algorithm, 10 key variables affecting non-current debts were identified. Due to the better performance of support vector machines with radial cores, its use in modeling non-current debts is recommended.