This paper focuses on the causality relation between US and the several Asia-pacific markets (Japan, China, Hong Kong, Taiwan, Singapore, Korea, and Indonesia). We check the causality of the co-movement among the markets across Pacific by using Granger-Causality test, VAR, and event studying on unexpected high volatile period. Our tests show that U.S. and Japan have strong influence to other As...

Granger causality analysis is becoming central for the analysis of interactions between neural populations and oscillatory networks. However, it is currently unclear whether single-trial estimates of Granger causality spectra can be used reliably to assess directional influence. We addressed this issue by combining single-trial Granger causality spectra with statistical inference based on gener...

Causality discovery has been one of the core tasks in scientific research since the beginning of human scientific history. In the age of data tsunami, the task could involve millions of variables, which cannot be achieved feasibly by human. However, the causal discovery using artificial intelligence and statistical techniques in non-experimental settings faces several challenges. In this work, ...

This paper investigates the dynamic relationship between volatility, volume and open interest in CSI 300 futures market using asymmetric GARCH model, Granger causality test, variance decomposition and impulse response function based on 1-min data. ARMA-EGARCH model is employed and find that both contemporaneous and lagged volume is positively related to volatility, and current open interest has...

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well established, multiscale analysis of directed interactions has never been formaliz...

Granger causality methods were developed to analyze the flow of information between time series. These methods have become more widely applied in neuroscience. Frequency-domain causality measures, such as those of Geweke, as well as multivariate methods, have particular appeal in neuroscience due to the prevalence of oscillatory phenomena and highly multivariate experimental recordings. Despite...

Adopt co-integration and granger causality test for analyzing the influences of the deviation of three industrial structures on peasants’ income based on the model of industrial structure deviation with time sequences of peasants’ income and the deviation of three industrial structures in China Jiangxi. It’s found that there exists a long-term positive equilibrium relationship between the devia...

A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been con...

the paper investigates the effects of interest rates on stock market performance by using monthly time series data for the economy of bangladesh over the period of 1991 to 2012. a wide range of econometric techniques have been employed to analyze the relationship between the interest rate and stock market return. the study reveals a stable and significant long run relationship between the varia...