Mansour Zarra Nejad; Ali Raoofi
Abstract
Forecasting economic and financial variables is of high significance to economic policymakers and investors; however, it is a difficult and complicated task due to the volatile and complex nature of such data.
Numerous studies have been conducted concerning different methods of forecasting macroeconomic ...
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Forecasting economic and financial variables is of high significance to economic policymakers and investors; however, it is a difficult and complicated task due to the volatile and complex nature of such data.
Numerous studies have been conducted concerning different methods of forecasting macroeconomic and financial variables so far. Although frequent and sophisticated methods have been applied to forecast such variables, the nature of data under consideration has not sufficiently been taken into consideration. In terms of complexity, type and nature of data might impact the accuracy of forecasting models. In other words, linear or non-linear behaviors of data can be effective in the selection of the forecasting model. Recent research indicates that a better understanding of the generating process of variable data (linear/ non-linear) leads to easier and more accurate forecasts. If, for instance, the variable follows a linear behavior, linear models, such as ARMA , will produce more acceptable accuracy. On the contrary, using more complex modeling methods such as ANN and ANFIS is more justifiable when the variable behavior is non-linear and chaotic. Using complex models for a variable with linear behavior might lead to excessive model dependency on unnecessary volatility and, in turn, reduced forecast accuracy. This paper focuses on the study of linearity, non-linearity, and/or chaotic nature of TEPIX from March 25th, 2009 to October 15th, 2011 (625 observations) using BDS test . This test was administered in three stages to determine linearity, non-linearity, or “chaotic-ness” of TEPIX: First, the test was administered on daily stock market index return; second, the test was applied to ARMA model residuals; and finally, the test was carried out for ANFIS, GARCH , and ANN residuals. The results suggest that TEPIX return variable follows a non-linear behavior. Therefore, it is expected that non-linear models are better capable of forecasting this variable.
Then, different prediction techniques in ARMA linear model were compared with those of non-linear models including ANN, ANFIS, and GARCH. According to the evaluation criteria at hand (RMSE , MAE , U-Thiel, and MAPE), the accuracy of forecasts was compared . The results show that non-linear models enjoy better performance than ARMA model regarding all the criteria above. In addition, among non-linear models, ANFIS model displays the best performance in forecasting daily stock market index return. Taking the non-linear nature of data used into account, such results were predicable.
Keywords: Adaptive Neuro-Fuzzy Inference System (ANFIS), Neural Network, GARCH model, Non-linear Models, Chaos Theory, Stock Returns
JEL: G10, C52, C45, C22
Mansour Zarra Nezhad; Hassan Farazmand; Ali Fegheh Majidi
Abstract
The economies of Islamic countries have always under been the influence of trade and its effective factors. But so far, there has not been any comprehensive study concerning the effects of common currency on Islamic countries trade.
This paper attempts to investigate the effects of common currency ...
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The economies of Islamic countries have always under been the influence of trade and its effective factors. But so far, there has not been any comprehensive study concerning the effects of common currency on Islamic countries trade.
This paper attempts to investigate the effects of common currency on the 49 members of the Organization of Islamic Cooperation (OIC) based on Gravity Model during 1990-2010.
The results showed that the common money based on Gravity Model is justifiable due to the fact that a set of pull and push factors such as common border GDP exchange rate volatility, trade agreement, countries’ distance and common currencies in the OIC countries would determine the flow of trade among the Islamic countries. Generally, factors such as GDP, common border, the existence of trade unions and common money are recognized to have significant positive effects on the flow of trade among the Islamic countries, while other factors such as exchange rate volatility and countries distance have significant negative effects on the flow of trade amongthe Islamic countries.
Mansor Zarra Nezhad; Ebrahim Anvari
Abstract
In recent decades adopting unreasonable monetary and fiscal policies and
uncertainty in model-making and analysis of data, has become unsatisfactory in
macro goals. In a new Keynesian dynamic stochastic general equilibrium (DSGE)
model to study Iran economy, uncertainty is modeled as uncertainty about ...
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In recent decades adopting unreasonable monetary and fiscal policies and
uncertainty in model-making and analysis of data, has become unsatisfactory in
macro goals. In a new Keynesian dynamic stochastic general equilibrium (DSGE)
model to study Iran economy, uncertainty is modeled as uncertainty about the true
structural parameters that characterize the economy. In particular, the policymaker
does not know the true numerical values nor the statistical distribution of the fiscal
and monetary policy. The model considers the dependence of Iran economy to oil
export. Oil sector and oil export revenues have been modeled as a separate sector
and one of the government budget resources, respectively. Like in other New
Keynesian DSGE model, firms face nominal rigidities and the intermediate-good
sector is monopolistically competitive. Impulse response function of shocks show
that non-oil output increases in response to productivity, oil revenues, money growth
rate and government expenditure shocks. The finding shown that a policymaker that
follows a control approach under uncertainty sets interest rates less aggressively to
react against fluctuations in inflation or the output gap than in the case of absence of
uncertainty. Model uncertainty has the potential to change importantly how
monetary and fiscal policy should be conducted, making it an issue that can not be
ignore. In main result, policy performance can be improved if the discretionary
policymaker implements an optimum policy in the model. In effect, a fear of modeluncertainty can act similarly to a commitment mechanism. When there is uncertainty
about the persistence of inflation, it is optimal for policy makers to respond more
aggressively to shocks than if the parameter were known with certainty, since the
avoid bad outcomes in the future.
Mansour Zarra Nezhad; Yaser Taimori Asl
Abstract
Study of the changes in the stock price in Tehran stock exchange is of great
importance. This is because of its application in forecasting the stock price in the
stock exchange.
The aim of this article is to investigate the forces and mechanisms that cause the
dramatic changes in stock price and ...
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Study of the changes in the stock price in Tehran stock exchange is of great
importance. This is because of its application in forecasting the stock price in the
stock exchange.
The aim of this article is to investigate the forces and mechanisms that cause the
dramatic changes in stock price and the formation of chaotic trend. To test whether
the chaotic trend in the Tehran stock exchange exists, the daily stock price of
Bakhtar Cable Company (as a sample) for the period of 05/25/2008-08/20/2008 has
been tested using the Brock, Dechert and Scheinkman (BDS) test.
The results showed that there exists chaotic behavior in the stock price time series,
and the stock price moves in trend. The findings of the research confirmed that
chaotic method can be applied to detect and forecast the stock price trend in Tehran
stock exchange.
