the purpose of this study is to examine the dynamic effects of some macroeconomic variables: money stock, gross domestic product, consumer price index and exchange rates on determining housing price index behavior in iran using the error correction model. using seasonal data, the model is estimated by johansen-juselius cointegration approach during 1990-2007. the results reveal that all variabl...

In this analysis the interdependence between foreign exchange markets and stock markets for selected accession and cohesion countries is discussed. This includes basic theoretical approaches. Monthly data for the nominal stock market indices and nominal exchange rates are used, where Ireland, Portugal, Spain, Greece, Poland, Czech Republic, Slovenia, and Hungary are included in the analysis. Fr...

This goal of the paper is introduction and experimental evaluation of neuro-genetic system for short-term stock index prediction. The system works according to the following scheme: first, a pool of input variables are defined through technical data analysis. Then GA is applied to find an optimal set of input variables for a one day prediction. Due to the high volatility of mutual relations bet...

in this research, role of accruals in elaboration of quality of earning of the companies accepted in mumbai stock exchange has been studied and relationship between quality of earning through accruals and its constituents and abnormal stock return has been studied. the studied sample includes 35 companies in group a of mumbai stock exchange in 2009-2013.fordata analysisandhypothesistesting mult...

nowadays, liveliness and rapid maintenance of the development process of the companies are dependent on the accurate and complete understanding of the merits of the financial activities. since these merits are relative concepts that are based on comparisons, lists of ranking and comparison of industries with each other act as useful signposts for managers, politicians, and investors. the point ...

Stock market prediction is important and of great interest because successful prediction of stock prices may promise attractive benefits. These tasks are highly complicated and very difficult. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm i...

This study presents an integrated system where wavelet transforms and recurrent neural network (RNN) based on artificial bee colony (abc) algorithm (called ABC-RNN) are combined for stock price forecasting. The system comprises three stages. First, the wavelet transform using the Harr wavelet is applied to decompose the stock price time series and thus eliminate noise. Second, the RNN, which ha...