Stock Price Direction Prediction Using Artificial Neural Network Approach: The Case of Turkey

Forecasting the Direction of Short-Term Crude Oil Price Changes with Genetic-Fuzzy Information Distribution

“…The optimization process converged at the 100th generation. The estimated ( , ℎ, ) is (5,10,27) with the best fitness value is 1.426.…”

“…For Brent crude oil price series, (5,13,26) is the final solution of ( , ℎ, ) by − inference. For WTI crude oil price series, (5,10,27) is the final solution of ( , ℎ, ) by − V inference. To present spatial structure of inference knowledge, three-dimensional stereograms of information distribution matrix at the final solutions are plotted in Figure 2.…”

“…Similar to stock market, options market and short-term load forecasting problem (see [21,22]), the world crude oil market is also an important 2 Mathematical Problems in Engineering commodity trading market with a large number of investors participating in trading. There is considerable amount of literature devoted to forecasting crude oil price, such as nonlinear models (see [23][24][25]), econometric models (see [9][10][11]), and directional forecasting models (see [26][27][28][29][30][31]).…”

Applicability of BPN and MLP neural networks for classification of noises present in different image formats

“…The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human [12] Further, Eriki and Udegbunam used an ANN for evaluating the prices of housing units in Nigeria. [13] In this paper, the performance analysis of Back Propagation Network (BPN) and Multi Layer Perceptron (MLP) is discussed.…”

Predicting Stock Prices Using Polynomial Classifiers: The Case of Dubai Financial Market

“…In a different but related application, the NN was used to capture the underlying rules of movements in currency exchange rates with reasonable results in [8]. The use of Artificial Neural Networks to predict stock market behavior in terms of its direction was reported in [9] for Istanbul Stock Exchange where the historical data was grouped in seven different prediction systems models to which eight different ANN and Logistics Regressions models were applied. Chena et al [10] used the probabilistic neural network (PNN) to forecast the direction of Taiwan Stock Marekt Index return using historical data.…”