This paper focuses on testing possible linkages among international gold and ASEAN emerging markets based on daily data from July 28, 2000 to March 31, 2009. The Granger causality test and the Johansen cointegration technique were applied to examine possible short-run associations and the...

The study examines the volatility linkages between India and Asian tiger cubs, i.e., the Philippines, Indonesia, Malaysia, and Thailand. It aims to explore the spillover effects of volatility among these countries' stock markets to provide valuable insights to investors and policymakers. To...

Causal relationships in econometrics are typically based on the concept of predictability and are established in terms of tests for Granger causality. These causal relationships are susceptible to change, especially during times of financial turbulence, making the real-time detection of...

This paper analyzes the relationship between stock market capitalization to GDP and real GDP in 10 Central and Eastern European countries (CEECs) that joined the European Union in 2004 and 2007, with the objective of determining whether the financial markets played a role as drivers of economic...

This paper analyses the relationship between stock market capitalization and real GDP in ten Central and Eastern European countries (CEECs) that joined the European Union in 2004 and 2007, with the objective of determining if the financial markets have played a role as a driver of the economic...

We analyze Granger causality testing in a mixed-frequency VAR, where the difference in sampling frequencies of the variables is large. Given a realistic sample size, the number of high-frequency observations per low-frequency period leads to parameter proliferation problems in case we attempt to...

In this paper, we provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage effect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and implied volatility, and find that implied...

In this paper we give a precise definition of long-run causality in a multivariate non-stationary, possibly cointegrated, framework. A variable is said to be causal for another in the long run if knowledge of the past of the former improves long-run predictions of the latter. In a VAR framework,...

We provide a better understanding of the causal structure in a multivariate time series by introducing a novel statistical procedure for testing indirect and spurious causal effects. In practice, detecting these effects is a complicated task, since the auxiliary variables that transmit/induce...

We derive restrictions for Granger noncausality in Markov-switching vector autoregressive models and also show under which conditions a variable does not affect the forecast of the hidden Markov process. Based on Bayesian approach to evaluating the hypotheses, the computational tools for...