We examine the effectiveness of frequently used technical indicators for intra-day forecast by applying them on the tick data of various stock prices. We show that the optimal combination of a few indicators chosen for each stock by using evolutional computation provides us a good forecast on the level of the future price at several ticks ahead. r 2007 Elsevier B.V. All rights reserved.

The forecasting problem is one of the main environmental problems that need efficient software tools. More concrete, it can mean meteorological/weather forecasting, air/soil/water pollution forecasting, flood forecasting and so on. Several methods based on artificial intelligence were proposed by taken into account that they can offer more informed methods that use domain specific knowledge, an...

Data mining techniques are frequently used to extract the disease related factors from the huge datasets. Data mining is the task of discovering formerly unknown, appropriate patterns and relationships in huge datasets. Generally, each data mining task differs in the type of knowledge it extracts and the kind of data demonstration it uses to convey the discovered information. Forecasting is a p...

the main purpose of the present research is to determine the relationship between the management earnings forecast errors and conservatism level and then surveying about the effects of forecast difficulty, and external financing on this relationship. regarding this, the financial information related to 147 stock firms, available during the period of study (2003-2015) were collected and analyzed...

China is the largest producer and consumer of coal in world. Qinhuangdao Port not only export port world, but also an important transportation hub China. The study change price great significance to whole country. In this paper, order avoid large prediction error a single model, ARIMA-SVM parallel combination model constructed, appropriate weight ratio ARIMA SVM obtained by calculation, so as o...

Air quality forecasting using nearest neighbour technique provides an alternative to statistical and neural network models, which needs the information on predictor variables and understanding of underlying patterns in the data. k-nearest neighbour method of forecasting that does not assume any linear or nonlinear form of the data is used in this study to obtain the next step forecast of PM10 c...