Palladium is an element of PGM group that has significant physical properties. This leads to more attention to this metal. Due to vast applications of palladium in industry and its usage in jewelry, its price plays an important role in economic. Therefore, forecasting its price is crucial subject in economic and engineering design. This paper proposes the model GM(1,1) to predict the Palladium ...

Stock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become significant. Many people use the share price movement process when com-paring different stocks while investing, and also want to pred...

Stock market price index prediction is regarded as a challenging task of the financial time series prediction process. Support vector regression (SVR) has successfully solved prediction problems in many domains, including the stock market. This paper hybridizes SVR with the self-organizing feature map (SOFM) technique and a filter-based feature selection to reduce the cost of training time and ...

electricity price predictions have become a major discussion on competitive market under deregulated power system. but, the exclusive characteristics of electricity price such as non-linearity, non-stationary and time-varying volatility structure present several challenges for this task. in this paper, a new forecast strategy based on the iterative neural network is proposed for day-ahead price...

This paper describes the application of two different neural network types for stock price prediction. The prediction is carried out by Kohonen self-organizing maps and error backpropagation algorithm. Both experimental networks deal with price change intervals in contradiction to precise value prediction. The results are presented and its comparative analysis is performed in this paper, as wel...

Purchasing goods or services produced in United States would force Indonesian company or investor to purchase U.S. dollar, and vice versa. The drastically changes of the foreign exchange rate between Indonesian rupiah and U.S. dollar would significantly affect the good’s price. Those facts motivated many studies focused on the exchange rate prediction. Various algorithms have been developed in ...

The accurate forecasting of metal prices is great importance to industrial producers as the supply raw materials a very important part production. futures market subject many factors, and are highly volatile. In past, most relevant research has focused only on deterministic point forecasting, with less performed interval uncertainty forecasting. Therefore, this paper proposes novel model that c...

Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading ...