We study the complexity of the stock market by constructing ǫ-machines of Standard and Poor’s 500 index from February 1983 to April 2006 and by measuring the statistical complexities. It is found that both the statistical complexity and the number of causal states of constructed ǫ-machines have decreased for last twenty years and that the average memory length needed to predict the future optim...

Abstract. – Recently, we have developed a method based on discrete wavelets to characterize the correlation and scaling properties of non-stationary time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The natural built-in variable windows in wavelet transform makes this procedure well suited for the non-stationary data. W...

In this paper, we present a software package for the data mining of Twitter microblogs for the purpose of using them for the stock market analysis. The package is written in R langauge using apropriate R packages. The model of tweets has been considered. We have also compared stock market charts with frequent sets of keywords in Twitter microblogs messages.

According to the nature of their activities, banks are exposed to various types of risks. Hence, risk management is at the heart of financial institutions management. In this study, we intend to summarize the information content of bank financial statements on diverse risks faced by banks and then determine how stock markets react to bank's risk management behavior. The methodology used in this...

Modeling and forecasting volatility of capital markets has been important area of inquiry and research in financial economics with the recognition of time-varying volatility, volatility clusturing, and asymmetric response of volatility to market movements. Given the anticipated growth of the Nepalese stock market and increasing interest of investors towards investment in Nepalese stock market, ...

The paper briefly analysis the methods used in forecasting of the stock market quotations, from the classic methods, used by the fundamentalists and chartist annalists, to the newest methods. The practical situations, where the analyzed methods are suitable, are also indicated.

In this study, we built a network for the US stock market based on the correlation of different stock returns. Community detection techniques were then applied to the constructed correlation network. The resulting communities were consistent with the identified market sections using Standard Industrial Classification code, which demonstrates that performances of public stocks within the same se...

The discovery of evolutionary laws of financial market is always built on the basis of financial data. Any financial market must be controlled by some basic laws, including macroscopic level, submicroscopic level and microscopic level laws. How to discover its necessity-laws from financial data is the most important task of financial market analysis and prediction. Based on the evolutionary com...