Financial Economics
Year:2016 | Volume:9 | Issue:33|Papers Count:8

Livestock and poultry industry has depended much on soybean meal. This dependence has led to fluctuations in the price of this product and therefore, forces market participants to follow the sensitivity and accuracy. These fluctuations created serious concerns about the supply and price of soybean meal. So, this study, using monthly and weekly data of Soybean prices in the exchange market, tried to forecast soybean price. So Soybean Meal price has predicted with neural network GMDH algorithm and ARIMA. The results based on the root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MPAE) showed that the GMDH algorithm, has a better ability to predict the price accurately.

In this study, the effect of financial development has examined on energy consumption by using the Generalized Method of Moment (GMM) in two groups of developing countries during 1993-2011 period. The first group includes 14 oil-producing developing countries and the second group includes 19 non-oil-producing developing countries. For each group of countries, two separate models were estimated, the first model by using banking sector variable, and the second model estimated by using capital market variable. The results showed that, GDP per capita in the non-oil-producing countries compared with oil-producing countries has a greater positive effect on per capita consumption of energy. The oil-producing price variable compared with the Non-Oil- Producing developing countries has a greater negative effect on per capita consumption of energy. The ratio of domestic credit variable to private sector (% of GDP) in non-oil producing developing countries 0.02% and in oil-producing developing countries is 0.009 percent .Comparison of the effects of domestic bank credit variable to the private sector (as a percentage of GDP) on per capita consumption of energy in the two groups of countries reflects the higher efficiency of the banking sector in the non-oil-producing countries .On the other hand, variable rate of turnover of shares traded in the non-oil producing developing countries is -0.003 percent and in oil-producing developing countries is -0.009 percent .Statistical analysis of the variable of capital market of shares traded in both developing oil-producing and non-oil-producing developing countries also shows that the effect of capital market development in energy consumption in oilproducing developing countries is more negative and smaller than the non-oil-producing developing countries.

Complicated time series such as stock prices and their changes are commonly hypothesized as random and subsequently unanticipated parameters, while probably, these time series could the resultant of a chaos or a regular non–linear active process and consequently they will be anticipatable. This article examines whether TEDPIX of Tehran Stock Exchange (TSE) are following the random walk process or evaluated by a chaotic process in the period of 1380-1392. For analysis of the hypothesis, unit root, BDS, autocorrelation and auto-regression were used. The results of the study indicate that TEDPIX is a chaotic and non– randomized parameter. These results are related to the inefficiency of the TSE market and subsequently showed that the TSE market has the potential of short– time predictability and there is a non–clearance information progress.

The stock price indices are indispensable variables in economic systems, these usually complicated time series are almost stochastic, and hence their variation is assumed unpredictable. For this purpose, nonlinear and predictable examinations are used to test the existence of determined chaotic trend and nonlinear process in daily time series of Tehran’s stock index from 1387/4/8 to 1392/7/10.The results reflect that sign test proves the non-stochastic nature of price index. The BDS’ results and those of sign test show that stock price index follows a nonlinear process. The independence tests like BDS test, White test, Chow test, test the correlation between observations in which the results are affirmative. Moreover, the cointegration-adjusted tests are used for testing the chaotic process of the price index and the results of both are affirmative. For predicting the stock price index in ongoing periods, we have used ARFIMA, FIGARCH, LSTAR, and ESTAR. Among those models, which examine the existence of long run memory in stock price index, FIGARCH, which tests the long run memory and variance, has the most capacity of accurate prediction. Among the nonlinear models, ESTAR has the most capacity. At the last, prediction is reported for ten periods with the one head process.

Since the development of institutions, agencies and financial markets of each country can have significant effects on income distribution of that country. The aim of this study is to examine the relation between the financial development and inequality in developed and developing countries by using generalized least square method(GLS) and generalized method of moments(GMM) and related theories, studied by entering variables like unemployment rate, the average years of schooling indices of human development, government size and per capita during the period 2000 to 2013. Thus, according to the ranking report of the United Nations Human Development(UNDP) in 2014, 35 countries with very high human development index and 32 countries with high and medium human development index have been selected as developed and developing countries, respectively, which these regions have had full data. The estimation results have been obtained using Stata14 and Eviews9. Empirical results obtained for developed countries, showed that the square of financial development is part of the descending inverted U curve. For developing countries, the estimation result of GLS approved the inverted U curve for the variables financial development and per capita income, while the GMM results income with income inequality, respectively. Finally, according to the above discussion, it can be concluded that for the developed and developing countries, the increase of financial institutions will reduce the income inequality.

This paper investigates monetary policies effects on property pricing for the case of Iran over the period 1369-1392. For this objective, we apply Cointegration technique and vector error correction model (VECM). We obtain Data set from Iran’s central bank time series database. The results of this study showed that there is a short-run and long run relationship from bank credit and a long-run relationship from liquidity and inflation to physical property prices. In addition, there is a short-run and long run relationship from inflation and a longrun relationship from liquidity and banks short-run profit rate to financial property prices. These results suggest that monetary effects on especially financial property prices appear with time lag.

Capital market as a bridge between "individual and institutional savers" and "investors need funds" by doing the two important duty: "to finance long-term" and "risk management" play an important role in increasing the reliability and volume investment, especially in long-term economic activities. Petrochemical companies known as chemical industry, which is the largest market participants on the Tehran Stock Exchange, As the daily average trading value has been allocated 21% of the total value of daily trading in stock market at August 92. The petrochemical industry has created the added value with the sale of crude oil and gas, in addition to has created huge resources, by collecting small savings society have been a considerable share of the stock market trading.Petrochemical gas feed price increase is the subjects that experts and economic decision-making will be discussed along time ago in the media, that in the 93 budget approved by the Assembly were approved in 1392. The present study aimed to investigate the impact of feedstock price increases on Tehran stock market indices. In this study, time series data on a daily basis from the date of 01/07/91 to 30/07/93 have been analyzed the ARCH family models and Virtual variables. The results suggest that increasing the price of feedstock’s approval before Tehran had a significant effect on stock market indices and the yield is influenced by a positive trend.

Productivity, especially energy productivity, and its improvement is an inevitable requirement in each country. In this study, the effects of changes in energy prices, net investment and the share of value added on the growth rate of energy productivity is discussed. As well as, by using Solow-Swan growth model, the energy productivity convergence in the period 2000-2011 in a selection of OPEC countries is examined. For the data analysis, panel data is used. Based on results, factors affecting the growth rate of energy productivity used in the research have significant effect on the growth rate of energy productivity. In addition, we found that those countries with a lower induced consumption, they have higher growth rate in the long-term consumption.