in this study, 3 models of time-varying parameters (tvp), dynamic model selection (dms) and dynamic model averaging (dma) and a comparison with the ordinary least squares (ols) method in matlab in the time period 2003-2013 (with data on a monthly basis) are discussed. in the present study, the variables of unofficial exchange rate changes, interest rate changes and inflation in oil price foreca...

Since the 1970s, services marketing has grown into a major sub discipline of marketing. It is constantly claimed – but is refuted in the article – that services are now the dominant economic activity in developed countries and keeps growing while the two traditional goods sectors, manufacturing and agriculture, are declining. In today's competitive world, having expertise, knowledge and marketi...

Artificial Neural Network (ANN) has preeminent learning ability, but often exhibit inconsistent and unpredictable performance for noisy data. In addition, it may not be possible to train ANN or the training task cannot be effectively carried out without data reduction when the amount of data is so large. In this paper, we have used a Neuro-genetic model to predict the index value for Stock Pric...

the goal of this research is to predict total stock market index of tehran stock exchange, using the compound method of arima and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. first, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It sho...