This paper provides detailed information on Team Poland’s approach in the electricity price forecasting track of GEFCom2014. A new hybrid model is proposed, consisting of four major blocks: point forecasting, pre-filtering, quantile regression modeling and post-processing. This universal model structure enables independent development of a single block, without affecting performance of the rema...

Nowadays, stock market is the one of the major sources of raising resources for India and is act as a key driver for economic growth of a country. The stock market forecasting is a very difficult and highly complicated task because it is affected by many factors such as economic conditions, political events and investor’s sentiment etc. The stock market series are generally dynamic, nonparametr...

For common people, stock investing is one popular way to manage their property. As Information Technology (IT) has risen in recent years, every security company has analyzed computer systems for their customers by developing their own investing. Taiwan is an island nation, and the economy relies on international trade deeply. The fluctuations of international stock markets will impact Taiwan st...

according to stock price excessive volatility in tehran stock exchange, the price limit mechanism is utilized in order to making the price fluctuation narrow and based on the specific periods, the price limit has encountered some variations which price limit has been determined by try and error within these periods and in a short stage of time many modifications existed through the applications...

Authors present the stock price prediction algorithm by using Bayesian network. The present algorithm uses the network twice. First, the network is determined from the daily stock price and then, it is applied for predicting the daily stock price which was already observed. The prediction error is evaluated from the daily stock price and its prediction. Second, the network is determined again f...

An accurate safety stock forecasting model has both academic and practical significance to inventory management. Reliable safety stock forecasting can not only help in making right decision but also in decreasing the cost and thereby increasing the profit significantly. Therefore in this paper, Artificial Neural Network (ANN) along with Clustering techniques, have been applied to predict the sa...

This chapter focuses on comparing the forecasting ability of the backpropagation neural network (BPNN) and the nonlinear autoregressive moving average with exogenous inputs (NARX) network trained with different algorithms; namely the quasi-Newton (Broyden-Fletcher-Goldfarb-Shanno, BFGS), conjugate gradient (Fletcher-Reeves update, Polak-Ribiére update, Powell-Beale restart), and Levenberg-Marqu...

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 ...