This paper investigates international stock market dynamics and their linkages. It uses factor models to extract stock market indicators from common cyclical stock components of industrialized countries, emerging markets, the BRICT, and global stock markets. We find that the stock market indicators for these groups are correlated with each other and with the global market factor. The BRICT disp...

Article history: Received 7 August 2009 Received in revised form 10 September 2009 Accepted 10 September 2009 Available online 19 September 2009 We investigate tail risk in emerging stock markets at the country, regional and world levels, by comparing the investable and noninvestable segments in terms of the expected shortfall of standardized returns and tail dependence on the world market. Emp...

The purpose of this study is to concentrate on the investigation of days-of-week effect on Tehran Stock Exchange and its comparison with other emerging markets. Using Classical Linear Regression (CLR) as well as Autoregressive Conditional Heteroskedasticity (ARCH) models it in indicated has indicated that there is significantly positive total return on Saturdays and significantly negative total...

The goal of agent-based modeling of stock markets is to enrich our understanding of fundamental processes that appear in a market. Artificial stock markets are models of financial markets used to study and understand market dynamics. Agent Based Artificial Stock Markets can be seen as any market model in which prices are formed endogenously as a result of participants’ interaction. There are va...

The interrelationships, interdependencies, integration, and dynamic linkages in between countries, regions including BRIC, country-region, and developing-developed stock markets had been thoroughly researched in the literature. This study aims at investigating above relationships both in short and long-run with special reference to India. It undertakes daily closing values of the BRIC indices f...

Financial and capital markets (especially stock markets) are considered high return investment fields, which in the same time are dominated by uncertainty and volatility. Stock market prediction tries to reduce this uncertainty and consequently the risk. As stock markets are influenced by many economical, political and even psychological factors, it is very difficult to forecast the movement of...

Stock market forecasting is important and interesting, because the successful prediction of stock prices may promise attractive benefits. The economy of Taiwan relies on international trade deeply, and the fluctuations of international stock markets will impact Taiwan stock market. For this reason, it is a practical way to use the fluctuations of other stock markets as forecasting factors for f...

In this study, we assess the dynamic evolution of short-term correlation, long-term cointegration and Error Correction Model (hereafter referred to as ECM)-based long-term Granger causality between each pair of US, UK, and Eurozone stock markets from 1980 to 2015 using the rolling-window technique. A comparative analysis of pairwise dynamic integration and causality of stock markets, measured i...

From the perspective of the agent-based model of stock markets, this paper examines the possible explanations for the presence of the causal relation between stock returns and trading volume. The implication of this result is that the presence of the stock price-volume causal relation does not require any explicit assumptions like information asymmetry, reaction asymmetry, noise traders, or tax...