Daily changes in the logarithm of stock market index from 1997 to 2004 are analyzed for countries from three subgroups of economies classified by the International Monetary Fund (IMF): developing Asian countries, newly industrialized Asian economies and major advanced economies. For all markets, the daily changes are well fitted by a non-Gaussian stable probability density. The time evolution o...

We predict stock markets using information contained in articles published on the Web. Mostly textual articles appearing in the leading and the most influential financial newspapers are taken as input. From those articles the daily closing values of major stock market indices in Asia, Europe and America are predicted. Textual statements contain not only the effect (e.g., stocks down) but also t...

In this paper we present two non-parametric approaches used for time series analysis and modeling for a financial time series: the DJIA stock index open values. We used two recently developed algorithms and methods for time series prediction, Gene Expression Programming and Neural Networks because they are suitable for the series that present high variability, as in the present situation. After...

The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well-represented using ensemble of intelligent paradigms. To demonstrate the proposed technique, we considered Nasdaq-100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index. The intelligent paradigms consi...

The Indian stock market is one of the earliest in Asia being in operation since 1875, but remained largely outside the global integration process until the late 1980s. A number of developing countries in concert with the International Finance Corporation and the World Bank took steps in the 1980s to establish and revitalize their stock markets as an effective way of mobilizing and allocation of...

To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel–Ziv complexity (LZC) perform numerical research of the retu...

This paper deals with the analysis of long range dependence in the US stock market. We focus first on the log-values of the Dow Jones Industrial Average, Standard and Poors 500 and Nasdaq indices, daily from February, 1971 to February, 2007. The volatility processes are examined based on the squared and the absolute values of the returns series, and the stability of the parameters across time i...

This article studies the international integration of the national stock markets of sixteen European countries. The international financial market is represented by two indices: a European index and a World index. The methodology of co-integration, used in this article, is the proper econometrical solution for the treatment of non-stationary series as those used in the present research. Complem...

This paper investigates jumps and cojumps in European financial markets employing more than six years of tick by tick data on stock indices, currency and interest rate futures. Using a jump detection measure proposed by Lee and Mykland (2008), we find that while the U.S macroeconomic announcements cause significant jumps on all asset classes, European equity markets are found to be the more sen...

A roentgenographic scoring system was developed to help orthopaedic surgeons and bone banks estimate the quality of bone stock in proximal femoral allografts intended to use in revision arthroplasty. This system scores a standardized anteroposterior roentgenograph of the proximal femur using four indices representing morphological features of cancellous and cortical bone known to be clinically ...