Due to the fast delivery of news articles by news providers on the Internet and/or via news datafeeds, it becomes an important research issue of predicting the risk of stocks by utilizing such textual information available in addition to the time series information. In the literature, the issue of predicting stock price up/down trend based on news articles has been studied. In this paper, we st...

The power spectrum of the daily Dow Jones industrial average is calculated. It has been shown that the spectrum is P (f) 1=f, very close to that of the random walk series (1=f noise). In contrast to some previous belief, the Dow Jones index as well as other stock prices time series are not 1=f noise. The distribution of the daily change of the Dow Jones industrial average is also calculated. Se...

This is a known fact that news and stock prices are closely related and news usually has a great influence on stock market investment. There have been many researches aimed at identifying that relationship or predicting stock market movements using news analysis. Recently, massive news tests, called unstructured big-data, have been used to predict stock price. In this paper, we introduce a meth...

The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The mode...