Journal of Economic Modeling Research

In this study, by applyig a combination of Autoregressive Conditional Heteroskedasticity  and stochastic differential equations Models with Markowitz model we estimate the optimal portfolio investment in the housing market are discussed. For this purpose, use of assets, stock prices, housing prices, the price of coins and bonds during the period 1999-2013 with the monthly data. Autoregressive Conditional Heteroskedasticity  Models and stochastic differential equations results as input variables used to estimate the optimal portfolio Markowitz. Mean-variance analysis shows that during the real estate boom, housing as the dominant assets in risky assets and the largest share of funds to be allocated. During recent periods of recession as the housing sector, the housing of the optimal portfolio investment abroad and instead of stocks and investment coins in the basket of assets is considered dominant. Generally, bonds as risk-free assets in all periods as a reliable asset in the portfolio is considered optimal investor.

Structural parameters are necessary and important in some economic studies, especially in general equilibrium models. One of these structural parameters is degree of price rigidity. In this article we try estimate degree of price rigidity in Iran economy in a General Equilibrium Dynamic Stochastic Model with Bayesian method. Our result with using seasonal data of real consumption, GDP, inflation and taxes for 1377-1387 reach us to number 46 percent for price rigidity which show 46 percent of Iran's firms could not optimize their price in each period.

This study examines the effect of Herding in different states (low, high and extreme volatility) in Tehran Stock Exchange during the years 2009-2013 using Chang et al (2000) and Balcilar et al (2013) models. In this survey herding are tested under 3 market regimes in selected industries: Cement, Chemical, Pharmaceutical and Investment.
The results don't show evidence of herding in 4 industries using static model (Chang et al, 2000). So dynamic model (Balcilar et al, 2013) was used  to analyze Herding under 3 regimes in which our results support the presence of  herding under 2 market regimes (high and extreme) . The results also demonstrate evidence of herding behavior under the high volatility regime for all of the selected industries. Herding under the extreme volatility regime is only found in investment and cement industries.

In capital markets, stock price forecasting is affected by variety of factors such as political and economic condition and behavior of investors. Determining all effective factors and level of their effectiveness on stock market is very challenging even with technical and knowledge-based analysis by experts. Hence, investors have encountered challenge, doubt and fault in order to invest with minimum risk. In order to reduce cost and raise the profit of investment, determining effective factors and suitable time for sailing and purchase is one of the important problems that every shareholder or investor in stock market should consider. To reach this goal, a variety of approaches have been introduced, which are often intelligent, statistical, and hybrid. These approaches are mostly used to predict the stock price time series. Our proposed algorithm is hybrid and involves two stages: preprocessing and predictor. The preprocessing stage involves three steps: missing value, normalization and feature selection. Since there are many features in used datasets, genetic algorithm (GA) is used as the feature selection algorithm. In order to intelligent capability of Fuzzy Neural Network (FNN), this network with two structures (Mamdani and Sugeno) is used as a stock price prediction in second stage. This network is capable of extracting fuzzy rules automatically. Back propagation algorithm (gradient decent) is used for adapting all the parameters. 
Our algorithm is evaluated on ten datasets with seven features obtained from ten different companies. By comparing the simulation results of the simple and hybrid FNN network, we found that the lack of suitable feature selection algorithm will lead to high computational cost, and in many instances the hybrid algorithm outperforms the simple FNN. This results demonstrate the superiority of the hybrid FNN to the simple one. In general, since the number of Sugeno tuning parameters are more than Mamdani, its performance is better than mamdani. Moreover, our algorithm is comparable to the maximum precision rates of other approaches.

In recent decades the development of capital markets in developing countries, economic growth is desirable to have. Developed countries owe much of its development direction of financial markets, especially the stock market knows. The stock market is precisely the collection of savings and private capital to finance investment projects and on the other hand, an official and is confident that the owners of dormant savings can be relatively affordable and safe place to seek investment and their funds to invest in companies operate. The role of the stock market to boost the economy of countries like Iran and wandered from one side to the large amounts of capita and on the other hand, face a shortage of investment, is striking. Therefore, understanding the factors influencing the behavior of the stock market can be considered useful for the capital's economy. In this context, this study examines the impact of fiscal and monetary policy shocks on stock market Iran. Regression model to estimate the structural model and the data for seasonal 1991: 1-2010: 4 was used. The results of the model indicate that the short-term shock to the money supply (monetary policy instrument) and long-term government spending shocks (monetary policy instrument) Fluctuations of stock price indices explain. In other words, the impact of monetary policy on stock prices faster than the impact of fiscal policy. Because government spending through the stock market affects ,First government spending on aggregate demand and thus income consumers and the general level of prices affects subsequent stock price changes, but by changing the money supply, the faster people can spend their surplus cash available to purchase the stock of assets that form part of it. The lag effect of monetary policy is much shorter than the lag effect of monetary policy

Modeling price fluctuations in financial markets is very important. We try to model price fluctuations in Tehran stock exchange using heterogeneous agents’ model.  We used agent-based computational approach. In this model, there are two kinds of agents, some agents have extrapolating expectations (chartists) and others have stabilizing or mean-reverting expectations (fundamentalists). The dynamics of shares of these two types of agents make price fluctuations. For determining the relative effectiveness of agents expectations, Diechi and Westerhoff (2012) method, is used.  For this purpose, weekly data of Tehran Stock Exchange price index (TEPIX) from 1997 to 2014 were used. Modeling results show that the relative sensitivity of buyers with different expectations, and their relative impact to aggregate demand, have significant and important role in the price dynamics of Tehran stock market. We also show that the relative impact of chartists to price fluctuations very important and over the past two decades, the share of them from aggregate demand have been more than 80 percent.

Value at risk (VaR) is one of the most important risk measures for computing risk which is entered in financial framework in past two decades. In general there are three approaches including parametric, nonparametric and semi-parametric is used for estimating of VaR. this paper present a new method that is named window simulation which is classified in nonparametric approach. Processing of VaR calculation in window simulation method based on reproduction of data such as Monte Carlo simulation. But, in this new method, data production is done in basis of distance and similarity measures. Considering generated distribution quantile, VaR is estimated. Next, VaR of Tehran Stock Exchange indices are computed by this method. Also the accuracy of estimated VaR is evaluated by backtesting statistics. Empirical results indicate that based on window method, the best outcome is associated to measures of Euclidean, DTW, Kolmogorov-Smirnov, square χ^2 , distance-similar and cosine respectively.

This paper investigates the relationship between monetary policy and stock market fluctuations for Iranian economy within a DSGE model. This study models the role of monetary policy in two monetary regimes including money growth and Taylor rule with traditional factors and optimal simple rule in the new Keynesian monetary framework with nominal wage and price rigidities in the Iranian economy. Bubbles in our model emerge through a positive feedback loop mechanism supported by self-fulfilling beliefs. Results show that: first, using an optimal simple rule and determining the optimal coefficients of the Taylor rule by policy makers decrease the loss function. Second, the sentiment shock which represents the size of current bubbles relative to newly born bubbles and transfers to the real economy through endogenous credit constraint, drives the movements of stock market fluctuations and variations in real economy, leading to explain the positive contemporaneous correlation between stock prices and the real economy Third, using an optimal simple rule and determining the optimal coefficients of the Taylor rule with stock price Fluctuations by policy makers decrease the loss function and it confirms that monetary policy should respond to stock market bubbles in the economy.

One of the opportunities that enable better utilization of funds to finance the country's policy makers, CEOs and financial institutions gives profit, use of barter transactions rather than cash transactions and money payment.  Although It deals with history as long as the formation of the first human set (before the invention of money and Intermediate goods), but the use of these methods to solve the problems of working capital has recently profit institutions literature and commercial transactions and has brought many benefits to users. In this article we have tried to introduce different methods of barter exchanges, clearing the way its numerous advantages explained and network productivity for economic development without growth, liquidity is provided. As a result, users could utalize the barter exchanges to development products or services and growth in competitive business environment, without affecting the growth of liquidity that causes fluctuation.

In recent years “Financial Conditions Index" (herein FCI) has been used as a key indicator of the monetary policy condition. Considering the importance of this index, the purpose of the present research is to reach a comprehensive index that includes all the monetary transmission mechanisms based on the Iranian economy. To this aim, a weighted average of the banking interest, real exchange rates , credits and price of other assets (namely the stock price index, and housing price index ), need to be calculated. The weighted average of the variables are obtained by estimating the, backward-looking aggregate supply and demand equations for Iran. In the next stage, in order to test the validity of the obtained index, and because of the importance of price stability for the central bank, the predictive power of the index from inflation in Iran was examined using Non-Nested Tests and Root Mean Square Error (RMSE). Seasonal data series are collected for the period of 1991-2012.The findings of this study show that the weight of housing price variable is higher than the other variables, whilst, the stock price index coefficient was not significant in any lag. Moreover, the results of second stage tests, indicate a good predicative power of the FCI index from the inflation in Iran.

In this paper we analyzed the strategic interaction between government and central bank in Iranian economy. Using dynamic differential games and Nash equilibrium within cooperative and non-cooperative setting, we try to find the optimal values of debt, deficit and monetary base. The results of simulation show that in cooperative case the level of equilibrium debt is lower than the non-cooperative case and converge speed is higher in cooperative setting than non-cooperation setting. Also in cooperative case than non-cooperative case, less creation of money and less government deficit are needed for debt stabilization in long run. The results also show that in both cooperative and non-cooperative cases under uncertainty, more active policies are used to track debt to its equilibrium level. These active policies lead debt goes to smaller level.

In this study by using Markov Regime Switching Heteroscedasticity Models (MRSH) in the form of state-space model the behavior of stock returns is examined. This approach endogenously permits the volatility to switch as the date and regime change and allows us to decompose the permanent and transitory component of stock returns. The period of the study is the fourth month of 2000 to the seventh month of 2013. The durations of the high-variance regimes for permanent components short-lived and revert to normal levels quickly and low variance regime for this components is more lasting, but durations of high-variance regime for transitory component is reverse. Also, in during periods of study low variance regime is dominant by a permanent component of stock returns but for the transitory component the high variance state is true captured.

One of the capital asset pricing models is CCAPM model that first time were presented by Breeden (1979). In the standard and the basic CCAPM establishes a linear relationship between consumption’s beta and excess return on assets but unfortunately, linear CCAPM made The Equity Premium Puzzle. After presenting puzzles like equity premium puzzle, adjustments were made in the CCAPM. For this purpose in this paper, adjustments have been made in the preferences as explores the implications of a novel class of preferences for the behavior of asset prices. This class of preferences was suggested first time by Marshall (1920), that according to it, people derive utility not only from consumption, but also from the very act of saving.
In this paper, we derive the Euler equations after modeling preferences based on the savings and consumption estimate them with GMM. In order to estimate the models, is examined quarterly data of 1977 to 2010. The models are significant in the other words it can be concluded that consumption and saving are successful in explaining stocks returns. Based on the estimated parameters in the models we can conclude that β is greater than 0.8 and savings is significant in preferences function but don’t have high value. In addition, these results indicate that economic agents are risk averse.

A wide range of banking activities And its close relationship with the economy is an important reason for the importance of the reliability of banking system and its influencing factors. Accordingly to play the optimal role, banks face several challenges. Optimal management of assets, liabilities And Evaluateing the risks associated with them Such as credit risk and liquidity risk is considered as one these challenges this article attempts to define goals and optimally manage assets and liabilities with a focus on determining the optimal amount of cash and liquidity risks. According to multilateral objectives, Constraints in the banking system And the experiences of the past years, the model used in this article is Fuzzy goal programming with fuzzy constraints. The proposed model has the ability to provide optimal amounts of each of the items of the balance sheet for the coming years in accordance with previous years. To reach the final answer nine Goals and more than thirty fuzzy limits used in the model. Goals presented in the paper Are: Maximizing profits, Observing the limits of the deposit facility, Improving the share of bank deposits of the banking system, Increasing the amount of balance sheet items, Increasing the amount of some items assets to total assets, Observing the Capital adequacy limits, Reducing the volume of investment in tangible fixed assets, more Receivables than debts from central, more Receivables than debts from institutions Also in order to achieve the importance of each of these goals an Analytic Hierarchy Process is used. Finally, the results in crisp and fuzzy model are compared and improvement of results in fuzzy model is observed.

Exchange rate is one of the key indicators affecting macroeconomic performance, and inflation is one of the most important indicators which represents the macroeconomic performance. The aim of this paper is to identify the relation between these two important economic variables. By using the model of structural time series and Kalman Filter algorithm the effect of exchange rate gap (the difference between official exchange rate and parallel market exchange rate) on inflation in Iran has been investigated during 1961- 2012. The results of this paper indicate that exchange rate gap has a significant positive impact on inflation in Iran, so that 1 percent increase in exchange rate gap lead to 3 percent increase in inflation in Iran.  These results have approved the single currency policy to control inflation in the country.

The main purpose of this study, is to evaluate the effect of diversion earnings forecast and earnings realized on returns stocks in Tehran Stock Exchange. In fact, this research aims to examine the diversion of earnings resulting from the diversion of corporates managers forecasts earnings, what impact these diversion of earnings have on the returns of stock price. To achieve this, 194 companies listed in the Tehran Stock Exchange selected in the period of 2005-2013.
In this study, two groups of companies experienced the highest returns and lowest returns over the period studied, have been selected. Multi-factor model of Fama and French (1993) was used as the theoretical basis. The results indicate that forecasts of companies have experienced highest returns in comparison with lowest returns are more cautious and accurate than prediction of their future earnings. Changes in earnings realized and Tehran Stock Exchange index returns have positive and considerable relationship with stock returns as well, but these relationships for companies with highest returns are stronger than companies with lowest returns.

The present article studies the interactive relationships between oil price volatility and industries stocks of basic metals, petroleum and chemical products by using Vector Auto Regressive (VAR) and Multivariate Generalized Autoregressive Conditional Heteroskedastisity (GARCH) models from March 2004 to March 2015 empirically . In this research, the VAR-GARCH model is proposed, which is developed by Ling and McAleer (2003). The model survives the return and volatility problems among the considered series and this is the VAR-GARCH advantage. The results show that there are Average effects between oil market and stocks market of basic metals and petroleum products, But this effects are not true for chemical industry market.  The volatility effects between world oil price and chemical and basic metals industry markets  is not existed, but between oil market volatility and petroleum products stock volatility, Significant negative relationship is existed. There for, the investors should reduce their portfolios basket dependences on oil price as much as possible.

Efficient portfolio management, has been attractive for financial researchers and was wished for investors from past to now. In this research, a multiperiod portfolio optimization problem for asset liability management of an investor who intends to control the probability of bankrupt is investigated. The proposed portfolio is consisting of number of risky assets, risk free asset and a type of debt. A mean variance model, with constraint of bankrupt controlling in different time horizons is proposed. Lagrangian Multiplier Method with dynamic programming is used for solving proposed model and regarding to its complexity degree, Genetic algorithm was the best selection for reaching numerical results. The proposed model is ran with real data consisting of 10 accepted company in Tehran stock exchange, bonds and bank loan as an investor debt.