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...

Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize ma...

In this paper, we characterize the equilibrium price of a prediction market in which risk averse traders have heterogeneous beliefs in probabilities. We show that the prediction market is accurate, in the sense that the equilibrium price equals the mean beliefs of traders, if and only if the utility function of traders is logarithmic. We also provide a necessary and sufficient condition for the...

This paper formulates app store analysis as an instance of software repository mining. We use data mining to extract feature information, together with more readily available price and popularity information, to support analysis that combines technical, business and customer facing app store properties. We applied our approach to 32,108 non-zero priced apps available from the Blackberry app sto...

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...

Price forecast is a task challenging and very important in competitive electricity market context. Both market players and regulators concern very much about the price evolution, on one hand, the prediction of the market price is a crucial information for the production arrangement and bidding strategies. On the other hand, the regulators need to analyze the market behavior and monitor the mark...

It is very necessary to research the fluctuation of agricultural products prices as well as the data character. In this paper, the wholesale price of agricultural product is considered. The monofractal analysis and multifractal analysis methods are introduced to study wholesale price. We select the appropriate algorithm to calculate the fractal characteristics of the celery wholesale price. Res...

The current gold market shows a high degree of nonlinearity and uncertainty. In order to predict the gold price, Empirical Mode Decomposition (EMD) was introduced into Support vector machine (SVM). Firstly, we used the EMD method to decompose the original gold price series into a finite number of independent intrinsic mode functions (IMFs), and then grouped the IMFs according to different frequ...