Predicting future movements of a stock could be usually better performed within multiple models analysis. However, different methods prediction will show completely varied results even in case same stock. Due to logics and progression process, each model return results. These have implied certain aspects or properties that the owns, they would reflect keys acknowledge analyzers decision makers ...

Predicting stock price is a trend yet very challenging task. It because the prices depend upon several internal and external factors. Stock prediction can be useful for financial sectors government help in informed decision-making. This paper analyzes market of K-Electric Karachi. found that K-electric on refinery sector. The data two sectors. Also, compares based moving average, auto-regressiv...

the difficulty of determining intrinsic value of stock prices have led many people to use technical analysis in order to forecast stock prices in the future. to predict the stock price we need to determine the generating process of stock prices. in recent years many time - series methods have been used for forecasting purposes. one of these methods is the rescaled range analysis (ris). in the a...

This paper re-evaluates key past results of unit root tests, emphasizing that the use of a conventional level of significance is not in general optimal due to the test having low power. The decision-based significance levels for popular unit root tests, chosen using the line of enlightened judgement under a symmetric loss function, are found to be much higher than conventional ones. We also pro...

During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis, different types of these models have been used in forecasting. Now, there is a question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison betw...

Railways as a dimension of transportation infrastructure has been widely welcomed in developed and developing industrial countries because of the ability to carry heavy loads over long distances, more safety, less depreciation, less cost, less pollution, etc. Therefore, knowledge of the dynamic behavior of the railway is essential for designers and builders. It is very important to study the vi...

Significant prediction of asset prices is of a great importance in financial economics. When studying economic and financial phenomena, it is essential to correctly specify the model. If the true dynamics are nonlinear, using linear methods will probably be irrelevant in doing empirical analysis. Existence of nonlinearity in financial markets has been argued by numerous studies. The main object...

Biomass conversion factors (BCFs, defined as the ratios of tree components (i.e. stem, branch, foliage and root), as well as aboveground and whole biomass of trees to growing stock volume, Mg m-3) are considered as important parameters in large-scale forest biomass carbon estimation. To date, knowledge of possible sources of the variation in BCFs is still limited at large scales. Using our comp...

Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descripti...